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Multi-level flexible debris flow barriers: case study in Peru

Profile image of Vjekoslav BudimirVjekoslav Budimir

2019

Abstract

Monitoring is important for assessing the stability of the ground and for confirming the validity of the design during the construction and operation of structures. The ideal monitoring system for projects in Rock and Geotechnical Engineering would be able to monitor the behavior of small to extensive areas continuously and automatically with high accuracy. In addition, the costs would be low and the system would be easy to handle. Satellite technology has the potential to realize the above monitoring system by combining it with conventional geotechnical instruments. In this paper, satellite technology for displacement monitoring, i.e., GPS and SAR, is firstly outlined and then the concept of spatiotemporal continuous displacement monitoring is introduced. The use of both satellite technology and geotechnical instruments is effective for geotechnical monitoring. Practical applications of GPS for landslide monitoring and collaborative researches using DInSAR with Balkan countries are described.

Figures (384)
Figure 1 GPS fully automatic continuous displacement monitoring system (Iwasaki et al. 2003; Masunari et al. 2003; Shimizu and Matsuda 2002, 2003)
Figure 1 GPS fully automatic continuous displacement monitoring system (Iwasaki et al. 2003; Masunari et al. 2003; Shimizu and Matsuda 2002, 2003)
Figure 3 GPS and DInSAR, and their monitored displacements
Figure 3 GPS and DInSAR, and their monitored displacements
sensor at each monitoring point. Therefore, GPS and DInSAR are complementary to each other. Figure 2 DInSAR for measuring the displacement of the Earth’s surface (background : Google Earth)
sensor at each monitoring point. Therefore, GPS and DInSAR are complementary to each other. Figure 2 DInSAR for measuring the displacement of the Earth’s surface (background : Google Earth)
In the case of DInSAR, the interval of the measurements depends on the satellite regression cycle. It is usually several days or a few weeks or more. Although there may be a limitation in the measurement interval for extensive areas at present, temporally continuous monitoring can be done. Therefore, spatio-temporal continuous displacement monitoring can be realized by combining the two types of satellite technology with geotechnical instruments.
In the case of DInSAR, the interval of the measurements depends on the satellite regression cycle. It is usually several days or a few weeks or more. Although there may be a limitation in the measurement interval for extensive areas at present, temporally continuous monitoring can be done. Therefore, spatio-temporal continuous displacement monitoring can be realized by combining the two types of satellite technology with geotechnical instruments.
The GPS displacement monitoring system (see Figure 1) was applied to monitor the displacements of an unstable steep slope along a road. Since local slope failures have occurred several times over the last 20 years, displacement monitoring has been conducted by borehole inclinometers and surface extensometers. Some of the instruments, however, have occasionally not worked well due to large displacements, and it has been difficult to perform the monitoring continuously. In order to overcome such trouble, the GPS monitoring system has been employed for continuous monitoring (Furuyama et al. 2014; Kien 2019). Figure 5 Monitoring site and slope beside road
The GPS displacement monitoring system (see Figure 1) was applied to monitor the displacements of an unstable steep slope along a road. Since local slope failures have occurred several times over the last 20 years, displacement monitoring has been conducted by borehole inclinometers and surface extensometers. Some of the instruments, however, have occasionally not worked well due to large displacements, and it has been difficult to perform the monitoring continuously. In order to overcome such trouble, the GPS monitoring system has been employed for continuous monitoring (Furuyama et al. 2014; Kien 2019). Figure 5 Monitoring site and slope beside road
Monitoring results Three-dimensional displacements were continuously measured every hour. The monitoring results at G-1 are shown in Figure 6 along with the hourly amount of rainfall. Small displacements of less than 2-3 mm/month were generated at G-1 during the low rainfall period from March to early June. Whenever heavy rain fell from July to October, the displacement gradually increased.
Monitoring results Three-dimensional displacements were continuously measured every hour. The monitoring results at G-1 are shown in Figure 6 along with the hourly amount of rainfall. Small displacements of less than 2-3 mm/month were generated at G-1 during the low rainfall period from March to early June. Whenever heavy rain fell from July to October, the displacement gradually increased.
Table 3 Criteria for assessing the stability
Table 3 Criteria for assessing the stability
Table 2 Criteria for assessing the stability Figure 8 Total displacement (red line) and its velocity (black line) at G-1
Table 2 Criteria for assessing the stability Figure 8 Total displacement (red line) and its velocity (black line) at G-1
Figure 9 Landslide dam and unstable colluvial deposit (Sato et al. 2014) A large-scale slope failure occurred in a mountainous area of Western Japan due to a heavy rainfall brought about by a typhoon. The huge volume of colluvial deposit blocked a river channel and created a landslide dam (see Figure 9). Then, a debris flow occurred due to the erosion of part of the deposit. In order to prevent the collapse of the landslide dam and the occurrence of further debris flows, disaster recovery works were carried out. The GPS monitoring system was applied to monitor the behavior of the unstable colluvial deposit (Sato et al. 2014).
Figure 9 Landslide dam and unstable colluvial deposit (Sato et al. 2014) A large-scale slope failure occurred in a mountainous area of Western Japan due to a heavy rainfall brought about by a typhoon. The huge volume of colluvial deposit blocked a river channel and created a landslide dam (see Figure 9). Then, a debris flow occurred due to the erosion of part of the deposit. In order to prevent the collapse of the landslide dam and the occurrence of further debris flows, disaster recovery works were carried out. The GPS monitoring system was applied to monitor the behavior of the unstable colluvial deposit (Sato et al. 2014).
Figure 10 Plan view of monitoring site and location of GPS sensors (Sato et al. 2014) the monitoring system by means of a solar panel, and the measurement data were transmitted via a cellular phone to a computer at the control office. Extensometers, de- noted by S-1 to S-4, were also set in the upper area of the unstable slope (see Figure 10).
Figure 10 Plan view of monitoring site and location of GPS sensors (Sato et al. 2014) the monitoring system by means of a solar panel, and the measurement data were transmitted via a cellular phone to a computer at the control office. Extensometers, de- noted by S-1 to S-4, were also set in the upper area of the unstable slope (see Figure 10).
Figure 12 Displacement velocity at G-5 and criteria (Sato et al. 2014)
Figure 12 Displacement velocity at G-5 and criteria (Sato et al. 2014)
Figure 14 Plan view of landslide area and trace of displacements at monitoring points (Tosa et al. 2014) Figure 15 shows the monitoring results at G-4 by GPS. It is found that the landslide movement became slow after March 20 and had almost converged by March 23. Although the total amount of the movement of the toe of the slope reached about 250 m and the landslide crushed several houses, there were no injuries to the residents themselves due to the evacuation advisory issued by referring to the monitoring results.
Figure 14 Plan view of landslide area and trace of displacements at monitoring points (Tosa et al. 2014) Figure 15 shows the monitoring results at G-4 by GPS. It is found that the landslide movement became slow after March 20 and had almost converged by March 23. Although the total amount of the movement of the toe of the slope reached about 250 m and the landslide crushed several houses, there were no injuries to the residents themselves due to the evacuation advisory issued by referring to the monitoring results.
Figure 15 Displacement monitoring results at G-4
Figure 15 Displacement monitoring results at G-4
Figure 16 Geological condition of Tuzla: (a) Plan view (modified from Mancini et al. (2009a)) and (b) Vertical X-X’ cross section (Parwata et al. 2019) The total amount of subsidence during the period of 1956 to 2003 was up to 12 m, while it was more than 1m in the area of about 2 kmz2 of the city (Mancini et al. 2009a). The official date of termination of the salt deposit exploitation was in May 2007. However, subsidence still continued at a rate of 10-20 cm/year from 2004 to 2007 according to GPS surveys using the static method (Mancini et al. 2009b).
Figure 16 Geological condition of Tuzla: (a) Plan view (modified from Mancini et al. (2009a)) and (b) Vertical X-X’ cross section (Parwata et al. 2019) The total amount of subsidence during the period of 1956 to 2003 was up to 12 m, while it was more than 1m in the area of about 2 kmz2 of the city (Mancini et al. 2009a). The official date of termination of the salt deposit exploitation was in May 2007. However, subsidence still continued at a rate of 10-20 cm/year from 2004 to 2007 according to GPS surveys using the static method (Mancini et al. 2009b).
This study used the 145 SAR data images observed every 6-12 days by Sentinel-1A/B satellites (ESA) from October 2014 to July 2018 in the descending orbit.
This study used the 145 SAR data images observed every 6-12 days by Sentinel-1A/B satellites (ESA) from October 2014 to July 2018 in the descending orbit.
Figure 18 Comparison between DInSAR and GPS results (Parwata et al. 2019) In addition, the DInSAR results show that the “Tuzla” point was very stable. The total amount of LOS displacement was only a few mm for 3.7 years. This result is reasonable, because this is the reference point (fixed point) of the GPS monitoring system.
Figure 18 Comparison between DInSAR and GPS results (Parwata et al. 2019) In addition, the DInSAR results show that the “Tuzla” point was very stable. The total amount of LOS displacement was only a few mm for 3.7 years. This result is reasonable, because this is the reference point (fixed point) of the GPS monitoring system.
Figure 20 Vipava River Valley and study area The Vipava River Valley, located in the southwest part of Slovenia, is well known as a landslide-prone area (see Figure 20). There are four remarkable landslides in this area (Bizjak and Zupan¢cié 2009; Jemec Auflié et al. 2017; VerbovSek et al. 2018), namely, Rebrnice, Stogovce, Slano blato, and Selo. The area extends 40 km in length and several km in width. The landslides are characterized by the various volumes and velocities of their movement. The occurrence of debris flows and landslides sometimes causes damage to residences, infrastructures, farmland, etc.
Figure 20 Vipava River Valley and study area The Vipava River Valley, located in the southwest part of Slovenia, is well known as a landslide-prone area (see Figure 20). There are four remarkable landslides in this area (Bizjak and Zupan¢cié 2009; Jemec Auflié et al. 2017; VerbovSek et al. 2018), namely, Rebrnice, Stogovce, Slano blato, and Selo. The area extends 40 km in length and several km in width. The landslides are characterized by the various volumes and velocities of their movement. The occurrence of debris flows and landslides sometimes causes damage to residences, infrastructures, farmland, etc.
The “Slano blato landslide area” is taken to see t detailed transition of the LOS displacements from Figure 26. Figure 27 shows the LOS displacement distribution maps and the temporal transition at several points in t Slano blato landslide area. The spatial distribution of t surface displacements is clearly visible. Several deep we were constructed in the top of the slope as countermeasure to the landslide. The locations of the we ne ne Is are marked by black circles and labeled as Wi to Wu on the maps.
The “Slano blato landslide area” is taken to see t detailed transition of the LOS displacements from Figure 26. Figure 27 shows the LOS displacement distribution maps and the temporal transition at several points in t Slano blato landslide area. The spatial distribution of t surface displacements is clearly visible. Several deep we were constructed in the top of the slope as countermeasure to the landslide. The locations of the we ne ne Is are marked by black circles and labeled as Wi to Wu on the maps.
In Figures 22(a) and (b), the temporal transition of the LOS displacements at well points W1, W6, Wu, UW1, and WDi are shown. Figure 23 illustrates the geometrical relationship between the actual three-dimensional displacement vector and the LOS (ascending and descending) displacements.
In Figures 22(a) and (b), the temporal transition of the LOS displacements at well points W1, W6, Wu, UW1, and WDi are shown. Figure 23 illustrates the geometrical relationship between the actual three-dimensional displacement vector and the LOS (ascending and descending) displacements.
Figure 23 Geometrical relationship between actual displacement vector and LOS (ascending and descending) displacements.
Figure 23 Geometrical relationship between actual displacement vector and LOS (ascending and descending) displacements.
Figure 1 a) Area affected by debris flows during the Parma province alluvial event of 2014; b) rainfall data recorded by ARPAE raingauge of Marra during the alluvial event; c) comparison between rainfall data recorded by 3 raingauges and some rainfall thresholds triggering debris-flow proposed in scientific literature. The rainfall values recorded by all rain-gauges are above the thresholds presented in scientific literature (Caine, 1980; Ceriani et al., 1992; Cannon & Gartner, 2005; Crosta & Frattini, 2001; Innes, 1983; Marchi et al., 2002; Paronuzzi et al.,1998; Wieczorek, 1987) (Fig.2c).
Figure 1 a) Area affected by debris flows during the Parma province alluvial event of 2014; b) rainfall data recorded by ARPAE raingauge of Marra during the alluvial event; c) comparison between rainfall data recorded by 3 raingauges and some rainfall thresholds triggering debris-flow proposed in scientific literature. The rainfall values recorded by all rain-gauges are above the thresholds presented in scientific literature (Caine, 1980; Ceriani et al., 1992; Cannon & Gartner, 2005; Crosta & Frattini, 2001; Innes, 1983; Marchi et al., 2002; Paronuzzi et al.,1998; Wieczorek, 1987) (Fig.2c).
Figure 2 a) Area affected by debris flows during the Piacenza province alluvial event of 2015; b) rainfall data recorded by ARPAE raingauge of Salsominore during the alluvial event; c) comparison between rainfall data recorded by 3 raingauges and some rainfall thresholds triggering debris-flow proposed in scientific literature.
Figure 2 a) Area affected by debris flows during the Piacenza province alluvial event of 2015; b) rainfall data recorded by ARPAE raingauge of Salsominore during the alluvial event; c) comparison between rainfall data recorded by 3 raingauges and some rainfall thresholds triggering debris-flow proposed in scientific literature.
Figure 3 a) Map of debris flows distribution during the event of September 2014 in Parma province: torrents affected and triggering points; b) example of debris flow triggering zone documented in Parma province; c) debris flow deposit documented along Rio Vestana: levees with inverse gradation of debris flow deposits in Rio Vestana. Along the channels, streambed scouring and debris deposits have been documented. Furthermore, the debris levees shows the typical inverse gradation of debris flow deposits (Fig.3c).
Figure 3 a) Map of debris flows distribution during the event of September 2014 in Parma province: torrents affected and triggering points; b) example of debris flow triggering zone documented in Parma province; c) debris flow deposit documented along Rio Vestana: levees with inverse gradation of debris flow deposits in Rio Vestana. Along the channels, streambed scouring and debris deposits have been documented. Furthermore, the debris levees shows the typical inverse gradation of debris flow deposits (Fig.3c).
Figure 4 a) Map of debris flows distribution during the event of October 2015: torrents affected and triggering points; b) example of debris flow triggering zone documented in Piacenza province; c) debris flow deposit zone documented in Piacenza province along a torrent affected by debris flow: channel overrun by debris. The field surveys and the analysis of post-event satellite and aerial images have concerned an area of around 350 km? comprising various sub-basins of Trebbia River, Nure Torrent and Aveto Torrent. Slope instability phenomena have been surveyed and mapped, including 113 debris flows (Fig.4a), 89 debris slides, 4 mud flows and 29 erosion on the banks. Furthermore, uo debris flows triggering zones have been identified and mapped in form point: 57% of the phenomena surveyed has affected the sub-basins of the Aveto Torrent, 24% the sub-basins of the Nure Torrent and 19% those of the Trebbia River.
Figure 4 a) Map of debris flows distribution during the event of October 2015: torrents affected and triggering points; b) example of debris flow triggering zone documented in Piacenza province; c) debris flow deposit zone documented in Piacenza province along a torrent affected by debris flow: channel overrun by debris. The field surveys and the analysis of post-event satellite and aerial images have concerned an area of around 350 km? comprising various sub-basins of Trebbia River, Nure Torrent and Aveto Torrent. Slope instability phenomena have been surveyed and mapped, including 113 debris flows (Fig.4a), 89 debris slides, 4 mud flows and 29 erosion on the banks. Furthermore, uo debris flows triggering zones have been identified and mapped in form point: 57% of the phenomena surveyed has affected the sub-basins of the Aveto Torrent, 24% the sub-basins of the Nure Torrent and 19% those of the Trebbia River.
Figure 5 Example of effects on infrastructures in Parma province: a) check-dams cut-through by debris flows; b) road overrun by debris; c) erosion and cut-through of the road track.
Figure 5 Example of effects on infrastructures in Parma province: a) check-dams cut-through by debris flows; b) road overrun by debris; c) erosion and cut-through of the road track.
significant results that allow raising the level of attention on this type of phenomena. References
significant results that allow raising the level of attention on this type of phenomena. References
Figure 1 Simplified geological map of the study area (based or Velié and Vlahovi¢ 2009) The study area extends along the northern Adriatic coast of Croatia and includes the north part of the Istrian peninsula, the Rjecina river valley and Vinodol valley regions. The area is composed of Paleogene flysch, Cretaceous and Jurassic limestone, and alluvial deposits (Veli¢ and Vlahovié 2009) and it is shown on Figure 1.
Figure 1 Simplified geological map of the study area (based or Velié and Vlahovi¢ 2009) The study area extends along the northern Adriatic coast of Croatia and includes the north part of the Istrian peninsula, the Rjecina river valley and Vinodol valley regions. The area is composed of Paleogene flysch, Cretaceous and Jurassic limestone, and alluvial deposits (Veli¢ and Vlahovié 2009) and it is shown on Figure 1.
Figure 2 Landslides in the study area a) the translational landslide Brus, b) a debris flow Krbavéi¢i, c) the rotational landslide Marinci, d) erosion at LesiScina in the Istrian peninsula, e) the Grohovo landslide, f) reactivated landslide Valici, g) landslide on the Grohovo road in the Rjecina river valley, h) intense erosion at Slani Potok, i) dormant landslide in the Vinodol Valley MUVidL US ALIN LIVEN 2UUL), Piyotil LUCN Ilidss UCIVItsS LU soft rocks that can have undesirable behaviours, such as low strength, disaggregation, crumbling, high plasticity, slaking, fast weathering, and many other characteristics (Kanji 2014). The focus of this investigation was on siltstones, which are the flysch complex component most susceptible to weathering, and therefore their mechanical behaviour has the greatest influence on the behaviour of the overall flysch complex. Numerous instabilities and erosion processes (Figure 2) occur in the study area, and are most often related to the weathering of the flysch rock mass. Intense erosion is observed in flysch deposits in the Istrian peninsula (Gulam 2012) and Vinodol valley areas (Jurak et al. 2005), whereas no significant signs of erosion are present in the Rjecina river valley. Numerous landslides have occurred in the flysch deposits in the Istrian peninsula, Rjecina river valley and Vinodol valley regions (Dugonji¢ Jovanéevié 2013, Arbanas et al. 2014, Vivoda et al. 2012, Bernat et al. 2014). These geomorphological events are significantly influenced by weathering processes in the flysch deposits, especially in their fine grained, siltstone component. Weathering reduces the residual shear strength in these deposits, resulting in landslide reactivation.
Figure 2 Landslides in the study area a) the translational landslide Brus, b) a debris flow Krbavéi¢i, c) the rotational landslide Marinci, d) erosion at LesiScina in the Istrian peninsula, e) the Grohovo landslide, f) reactivated landslide Valici, g) landslide on the Grohovo road in the Rjecina river valley, h) intense erosion at Slani Potok, i) dormant landslide in the Vinodol Valley MUVidL US ALIN LIVEN 2UUL), Piyotil LUCN Ilidss UCIVItsS LU soft rocks that can have undesirable behaviours, such as low strength, disaggregation, crumbling, high plasticity, slaking, fast weathering, and many other characteristics (Kanji 2014). The focus of this investigation was on siltstones, which are the flysch complex component most susceptible to weathering, and therefore their mechanical behaviour has the greatest influence on the behaviour of the overall flysch complex. Numerous instabilities and erosion processes (Figure 2) occur in the study area, and are most often related to the weathering of the flysch rock mass. Intense erosion is observed in flysch deposits in the Istrian peninsula (Gulam 2012) and Vinodol valley areas (Jurak et al. 2005), whereas no significant signs of erosion are present in the Rjecina river valley. Numerous landslides have occurred in the flysch deposits in the Istrian peninsula, Rjecina river valley and Vinodol valley regions (Dugonji¢ Jovanéevié 2013, Arbanas et al. 2014, Vivoda et al. 2012, Bernat et al. 2014). These geomorphological events are significantly influenced by weathering processes in the flysch deposits, especially in their fine grained, siltstone component. Weathering reduces the residual shear strength in these deposits, resulting in landslide reactivation.
Figure 3 View of a landslide body and lateral scarp from the crown of the landslide in (a) August 2005 and (b) January 2013 (Vivoda Prodan 2016) residual soils, which differ from their parent rocks in mineralogical composition and structure (Eberhardt et al. 2005, Brown 1981). Flysch rock mass can have very diverse physical and mechanical properties, depending on its lithological composition and weathering state (Chandler 1969, ReifBmiiller 1997). Incompetent members such as claystones, shales and siltstones are particularly affected by weathering processes. In contrast, sandstones, limestone and _ breccioconglomerates are competent members and are considerably more resistant to the influence of exogenetic forces (Mihljevié and Prelogovi¢ 1992). Figure 3 shows high degradation of a flysch rock mass due to weathering in flysch pillars that were exposed to atmospheric conditions for seven years. These processes gradually transformed the fresh rock mass to residual soils and caused changes in its mineralogical composition and reductions in its strength.
Figure 3 View of a landslide body and lateral scarp from the crown of the landslide in (a) August 2005 and (b) January 2013 (Vivoda Prodan 2016) residual soils, which differ from their parent rocks in mineralogical composition and structure (Eberhardt et al. 2005, Brown 1981). Flysch rock mass can have very diverse physical and mechanical properties, depending on its lithological composition and weathering state (Chandler 1969, ReifBmiiller 1997). Incompetent members such as claystones, shales and siltstones are particularly affected by weathering processes. In contrast, sandstones, limestone and _ breccioconglomerates are competent members and are considerably more resistant to the influence of exogenetic forces (Mihljevié and Prelogovi¢ 1992). Figure 3 shows high degradation of a flysch rock mass due to weathering in flysch pillars that were exposed to atmospheric conditions for seven years. These processes gradually transformed the fresh rock mass to residual soils and caused changes in its mineralogical composition and reductions in its strength.
Table 1 Point load test and slake durability test results; including the slake durability index (Iq), disintegration ratio (Dr) and modified disintegration ratio (Drp) after the second cycle, for siltstones of different weathering grades from the Istrian peninsula (Vivoda Prodan 2016) Impact of weathering on the residual shear strength of siltstones
Table 1 Point load test and slake durability test results; including the slake durability index (Iq), disintegration ratio (Dr) and modified disintegration ratio (Drp) after the second cycle, for siltstones of different weathering grades from the Istrian peninsula (Vivoda Prodan 2016) Impact of weathering on the residual shear strength of siltstones
Figure 4 Examples of the weathering profile for the flysch rock mass in the Istria peninsula (Vivoda Prodan 2016) different standard grades of siltstone were investigated in a flysch weathering profile (Figure 4 (FR); Slightly Weathered (SW), Mod (MW), Highly Weathered (HW) Weathered (CW) rock masses; and : Fresh rock mass erately Weathered and Completely Residual Soil (RS). Progressive and gradual weakening and decomposition takes place from the ground surface downward to fresh rock, and thus the weathering of the fl lysch rock material decreases from RS to CW, HW, MW, SW and ER.
Figure 4 Examples of the weathering profile for the flysch rock mass in the Istria peninsula (Vivoda Prodan 2016) different standard grades of siltstone were investigated in a flysch weathering profile (Figure 4 (FR); Slightly Weathered (SW), Mod (MW), Highly Weathered (HW) Weathered (CW) rock masses; and : Fresh rock mass erately Weathered and Completely Residual Soil (RS). Progressive and gradual weakening and decomposition takes place from the ground surface downward to fresh rock, and thus the weathering of the fl lysch rock material decreases from RS to CW, HW, MW, SW and ER.
Figure 5 Fragments of FR siltstone sample taken from Istrian peninsula with various sizes retained in the drum after five cycles in the slake durability test (Vivoda Prodan 2016) parameters, such as disintegration ratio (Dr) and modified disintegration ratio (Drp2), are needed to indicate not only the durability but also the manner of disintegration of siltstones of different weathering grades (Erguler and Shakoor 2009, Cano and Tomas 2016).
Figure 5 Fragments of FR siltstone sample taken from Istrian peninsula with various sizes retained in the drum after five cycles in the slake durability test (Vivoda Prodan 2016) parameters, such as disintegration ratio (Dr) and modified disintegration ratio (Drp2), are needed to indicate not only the durability but also the manner of disintegration of siltstones of different weathering grades (Erguler and Shakoor 2009, Cano and Tomas 2016).
Figure 6 Siltstone sample in the ring shear device a) during and b) after testing
Figure 6 Siltstone sample in the ring shear device a) during and b) after testing
direct shear device (only some cm), which influences the final value of shear strength; (2) sample shearing in the ring shear device is developed under constant shear surface, whereas the shear surface changes (decreasing) during shearing in the direct shear device; and (3) the strength envelope in the direct shear device is based on three specific individual results, whereas the ring shear device enables plotting of the full strength envelope. Other identification test indicated that liquid limits and plasticity indexes increased with increasing weathering grade.
direct shear device (only some cm), which influences the final value of shear strength; (2) sample shearing in the ring shear device is developed under constant shear surface, whereas the shear surface changes (decreasing) during shearing in the direct shear device; and (3) the strength envelope in the direct shear device is based on three specific individual results, whereas the ring shear device enables plotting of the full strength envelope. Other identification test indicated that liquid limits and plasticity indexes increased with increasing weathering grade.
Table 2 Identification test results, ring shear and direct shear test results; including plasticity index (PI), residual friction angle (,) and residual cohesion (c;), steady state shear resistance at sliding surface (ts) for siltstones of different weathering grades from the Istrian peninsula, Valici lake in the Rjecina river valley, and Vindol valley (Vivoda Prodan 2016)
Table 2 Identification test results, ring shear and direct shear test results; including plasticity index (PI), residual friction angle (,) and residual cohesion (c;), steady state shear resistance at sliding surface (ts) for siltstones of different weathering grades from the Istrian peninsula, Valici lake in the Rjecina river valley, and Vindol valley (Vivoda Prodan 2016)
Figure 8 Mineralogical content of flysch samples from a) the Krbavéi¢i landslide in northern Istria (Arbanas et al. 2006), b) the Grohovo landslide in the Rjecina river valley (Benac et al. 2014), and c) the Mala Dubradina catchment in Vinodol valley (Jurak 1980), d) mineralogical content and e) content of different clay minerals in siltstone samples with different Numerous authors have investigated the stability of slopes in soft rocks subjected to weathering processes associated with changes in material strength (Eberhardt et al. 2005, Vlastelica 2015), while Sassa et al. (2010), Dugonji¢ et al. (2014), Sassa et al. (2014), Vivoda et al. (2014), Arbanas et al. (2017) performed numerical models of different landslides using LS-Rapid software.
Figure 8 Mineralogical content of flysch samples from a) the Krbavéi¢i landslide in northern Istria (Arbanas et al. 2006), b) the Grohovo landslide in the Rjecina river valley (Benac et al. 2014), and c) the Mala Dubradina catchment in Vinodol valley (Jurak 1980), d) mineralogical content and e) content of different clay minerals in siltstone samples with different Numerous authors have investigated the stability of slopes in soft rocks subjected to weathering processes associated with changes in material strength (Eberhardt et al. 2005, Vlastelica 2015), while Sassa et al. (2010), Dugonji¢ et al. (2014), Sassa et al. (2014), Vivoda et al. (2014), Arbanas et al. (2017) performed numerical models of different landslides using LS-Rapid software.
Figure 9 Top view of the terrain surface a) in the initial condition, at the end of the movement with sliding surface in b) SW/FR and c) HW/CW weathering grade of flysch rock mass (purple line shows the area of deposited landslide mass at the end of the movement) (Vivoda Prodan and Arbanas 2017) The results of the conducted deterministic 3D slope stability analyses using LS-Rapid software (Vivoda Prodan and Arbanas 2017) clearly show the critical areas for possible landslide reactivation in unfavourable
Figure 9 Top view of the terrain surface a) in the initial condition, at the end of the movement with sliding surface in b) SW/FR and c) HW/CW weathering grade of flysch rock mass (purple line shows the area of deposited landslide mass at the end of the movement) (Vivoda Prodan and Arbanas 2017) The results of the conducted deterministic 3D slope stability analyses using LS-Rapid software (Vivoda Prodan and Arbanas 2017) clearly show the critical areas for possible landslide reactivation in unfavourable
Figure 1 The Kostanjek landslide is located in the western part of the City of Zagreb and in residential area at the foot of the southwestern slope of Mt. Medvednica. The Kostanjek landslideis located in the western part of Zagreb City (Figure 1), and approximately 10 kilometres Outline of research area
Figure 1 The Kostanjek landslide is located in the western part of the City of Zagreb and in residential area at the foot of the southwestern slope of Mt. Medvednica. The Kostanjek landslideis located in the western part of Zagreb City (Figure 1), and approximately 10 kilometres Outline of research area
Figure 2 Sample localities of waters and spatial distribution of respective water types. One sample of spring water, seven samples of stream water, 1 samples from the mining tunnel (entrance of the tunnel and inner part of tunnel) and 74 ground water samples from private wells in the Kostajek area were collected for hydrochemical and isotope analyses during ground water surveys in September 20n and in June 2012. Figure 2 shows the localities of water samples and respective water types that will be described later.
Figure 2 Sample localities of waters and spatial distribution of respective water types. One sample of spring water, seven samples of stream water, 1 samples from the mining tunnel (entrance of the tunnel and inner part of tunnel) and 74 ground water samples from private wells in the Kostajek area were collected for hydrochemical and isotope analyses during ground water surveys in September 20n and in June 2012. Figure 2 shows the localities of water samples and respective water types that will be described later.
Figure 3 Classification of water types based on multivariate statistics (principal component analysis and clustering). water type is also shown in Figure 2. Both type-A and type-B waters are predominately distributed over the research area and are closely related to the shallow aquifer lithology composed of Sarmatian-Panonian marly strata. Type-A waters are derived Ca and HCO; from marl aquifers. Type-B waters are formed by the mixing of Type-A water with dilute subsurface water from soil zones where so chemical weat uble solids were almost removed during hering processes. Type-C waters are limitedly distributed around the eastern margin of the Kostanjek landslide and Type-D waters gush out from fissures in the d olomite outcrop in the inner part of the tunnel. In particular, Type-D waters are more enriched in Mg and depleted in Sr than type-C waters. It means that the dolomite is area as a later m a major source of Mg in waters from this ention.
Figure 3 Classification of water types based on multivariate statistics (principal component analysis and clustering). water type is also shown in Figure 2. Both type-A and type-B waters are predominately distributed over the research area and are closely related to the shallow aquifer lithology composed of Sarmatian-Panonian marly strata. Type-A waters are derived Ca and HCO; from marl aquifers. Type-B waters are formed by the mixing of Type-A water with dilute subsurface water from soil zones where so chemical weat uble solids were almost removed during hering processes. Type-C waters are limitedly distributed around the eastern margin of the Kostanjek landslide and Type-D waters gush out from fissures in the d olomite outcrop in the inner part of the tunnel. In particular, Type-D waters are more enriched in Mg and depleted in Sr than type-C waters. It means that the dolomite is area as a later m a major source of Mg in waters from this ention.
Figure 4 Isotopic composition of respective water types. Isotopic compositions of waters range from -6.64 to -10.1%o0 in 6180 and from -46.2 to -70.0%o0 in 62H, respectively. All waters are meteoric water (rain and snow) in origin even if type-D waters are depleted in 6180 and 62H comparing with others (Figure 4). The depleted type-D waters in isotope compositions suggest that these are recharged in the higher area of the northern mountain, western part of Mt. Medvednica, and migrate through dolomite aquifer to the depths of the landslide mass. Type-C waters from shallow aquifers in the landslide also include Mg to some extent even though there is no dolomite layer in the landslide mass. -10.1%0 in 6180 and from -46.2 to -70.0%0 in 62H,
Figure 4 Isotopic composition of respective water types. Isotopic compositions of waters range from -6.64 to -10.1%o0 in 6180 and from -46.2 to -70.0%o0 in 62H, respectively. All waters are meteoric water (rain and snow) in origin even if type-D waters are depleted in 6180 and 62H comparing with others (Figure 4). The depleted type-D waters in isotope compositions suggest that these are recharged in the higher area of the northern mountain, western part of Mt. Medvednica, and migrate through dolomite aquifer to the depths of the landslide mass. Type-C waters from shallow aquifers in the landslide also include Mg to some extent even though there is no dolomite layer in the landslide mass. -10.1%0 in 6180 and from -46.2 to -70.0%0 in 62H,
Figure 5 Mg-Ca-Sr systematics for rock samples. Graphical plots of Mg/Ca vs. Sr/Mg ratios of rock samples from soil layer, Sarmatian-Panonian marly strata, Badenian limestone and Triassic dolomite are shown in Figure 5. The relationship between Mg/Ca and Sr/Mg from soil layer and Sarmatian-Panonian marly strata shows a systematic trend which means an array of weathering because Ca and Sr are more soluble than Mg during chemical weathering processes. In contrast, Badenian limestone and Triassic dolomite are extrmely different composition from Soil layer and Sarmatian- Panonian marly strata.
Figure 5 Mg-Ca-Sr systematics for rock samples. Graphical plots of Mg/Ca vs. Sr/Mg ratios of rock samples from soil layer, Sarmatian-Panonian marly strata, Badenian limestone and Triassic dolomite are shown in Figure 5. The relationship between Mg/Ca and Sr/Mg from soil layer and Sarmatian-Panonian marly strata shows a systematic trend which means an array of weathering because Ca and Sr are more soluble than Mg during chemical weathering processes. In contrast, Badenian limestone and Triassic dolomite are extrmely different composition from Soil layer and Sarmatian- Panonian marly strata.
Figure 6 Formation of Type-C waters. Mg-rich Type-C waters are influenced by Type-D waters in deep artesian dolomite aquifer. Legends are the same as Figures 2 and 4. isotope hydrology, the alt altitude of ground water rec 58°O in mid latitudes ranges Depleted &°O values of type- itude effect on 5°O of precipitations (meteoric water) is used to estimate the harge areas. This effect on between -0.15 and -0.30%o for each 100 m of altitude gained (Clark and Fritz, 1997). D waters suggest that these are recharged around 650-800 m higher area than the Kostanjek landslide area, assuming that the altitude effect is -0.25%0/100m and average 5°O value of precipitation is likely -8.0%o in this area. Therefore, it is
Figure 6 Formation of Type-C waters. Mg-rich Type-C waters are influenced by Type-D waters in deep artesian dolomite aquifer. Legends are the same as Figures 2 and 4. isotope hydrology, the alt altitude of ground water rec 58°O in mid latitudes ranges Depleted &°O values of type- itude effect on 5°O of precipitations (meteoric water) is used to estimate the harge areas. This effect on between -0.15 and -0.30%o for each 100 m of altitude gained (Clark and Fritz, 1997). D waters suggest that these are recharged around 650-800 m higher area than the Kostanjek landslide area, assuming that the altitude effect is -0.25%0/100m and average 5°O value of precipitation is likely -8.0%o in this area. Therefore, it is
Figure 1 Planar view of the retaining wall and position of the two Vertical Arrays. Additionally, a site-specific displacement threshold was imposed on inclinometers data for the activation of Early Warning procedures. In particular, the alert level was based on the overcoming of a daily displacement value of 1mm/d consecutively for a whole week. According to this choice, an alarm message would have been issued to authorities responsible of the monitoring activity if the daily threshold was reached for 7 days in a row.
Figure 1 Planar view of the retaining wall and position of the two Vertical Arrays. Additionally, a site-specific displacement threshold was imposed on inclinometers data for the activation of Early Warning procedures. In particular, the alert level was based on the overcoming of a daily displacement value of 1mm/d consecutively for a whole week. According to this choice, an alarm message would have been issued to authorities responsible of the monitoring activity if the daily threshold was reached for 7 days in a row.
Figure 2 Local displacement recorded by DToo80 MEMS at the end of the monitoring activity (January 8", 2019). While these data confirmed the critical condition of the retaining wall, the alert threshold was never overcome for 7 days consecutively, hence no alarm message related to these events was issued during the monitoring period. This could depend of the threshold nature, which was focused on a continuous displacement variation, while the event recorded by DToo80 displayed a rapid evolution in the initial phase and continued with several oscillations for the rest of its duration.
Figure 2 Local displacement recorded by DToo80 MEMS at the end of the monitoring activity (January 8", 2019). While these data confirmed the critical condition of the retaining wall, the alert threshold was never overcome for 7 days consecutively, hence no alarm message related to these events was issued during the monitoring period. This could depend of the threshold nature, which was focused on a continuous displacement variation, while the event recorded by DToo80 displayed a rapid evolution in the initial phase and continued with several oscillations for the rest of its duration.
Figure 5 Cumulative displacement trend over time, recorded by DToo80 MEMS. Figure 4 Local displacement trend over time, recorded by DToo80 MEMS.
Figure 5 Cumulative displacement trend over time, recorded by DToo80 MEMS. Figure 4 Local displacement trend over time, recorded by DToo80 MEMS.
Figure 3 Cumulative displacement recorded by DToo80 MEMS at the end of the monitoring activity (January 8*, 2019).
Figure 3 Cumulative displacement recorded by DToo80 MEMS at the end of the monitoring activity (January 8*, 2019).
Figure 6 Water level variation measured by Piezo Link installed on DToo8o, together with local displacements recorded at -5 m and -10 m. The multi-parametric nature of the instrument, together with the high sampling data acquisition, allowed to correlate different physical quantities in order to assess cause-effect relationships. An example can be observed in Fig. 6 representing the water level variation recorded by the piezometer and the local displacement trend at 5 and 10 metres of depth. It is possible to note how the sudden increasing of water level triggered the movements starting from December 2017. The following peaks did not display any further impulsive displacements, a behaviour that could be related to a more stable configuration of the wall due to maintenance works. This representation underlines the importance of an automated tools in the detection of cause-effect relationships and efficacy control of works related to geotechnical field.
Figure 6 Water level variation measured by Piezo Link installed on DToo8o, together with local displacements recorded at -5 m and -10 m. The multi-parametric nature of the instrument, together with the high sampling data acquisition, allowed to correlate different physical quantities in order to assess cause-effect relationships. An example can be observed in Fig. 6 representing the water level variation recorded by the piezometer and the local displacement trend at 5 and 10 metres of depth. It is possible to note how the sudden increasing of water level triggered the movements starting from December 2017. The following peaks did not display any further impulsive displacements, a behaviour that could be related to a more stable configuration of the wall due to maintenance works. This representation underlines the importance of an automated tools in the detection of cause-effect relationships and efficacy control of works related to geotechnical field.
Figure 9 Local displacement trend over time, recorded by DTo081 MEMS.
Figure 9 Local displacement trend over time, recorded by DTo081 MEMS.
Figure 7 Local displacement recorded by DToo81 MEMS at the end of the monitoring activity (January 8th, 2019). depth of 14 metres. Another major event started at the beginning of December 2018 at the same depth, as can be observed in Fig. 9, and continued until the end of monitoring activities on January 2019. During this time interval, the inclinometer experienced a __ local displacement equal to 12.5 mm.
Figure 7 Local displacement recorded by DToo81 MEMS at the end of the monitoring activity (January 8th, 2019). depth of 14 metres. Another major event started at the beginning of December 2018 at the same depth, as can be observed in Fig. 9, and continued until the end of monitoring activities on January 2019. During this time interval, the inclinometer experienced a __ local displacement equal to 12.5 mm.
Figure 8 Cumulative displacement recorded by DT0081 MEMS at the end of the monitoring activity (January 8th, 2019).
Figure 8 Cumulative displacement recorded by DT0081 MEMS at the end of the monitoring activity (January 8th, 2019).
Figure 10 Cumulative displacement over time, recorded by DToo081 MEMS.
Figure 10 Cumulative displacement over time, recorded by DToo081 MEMS.
Figure 12 Temperature variation recorded by Therm Link, together with displacements measured by DToo81 in the upper part of the wall
Figure 12 Temperature variation recorded by Therm Link, together with displacements measured by DToo81 in the upper part of the wall
Figure 1 Water level variation measured by Piezo Link installed on DTo0081, together with local displacements recorded at -5 m, -10 m and -14 m.
Figure 1 Water level variation measured by Piezo Link installed on DTo0081, together with local displacements recorded at -5 m, -10 m and -14 m.
Figure 13 Local displacement trends between 4 and 8 July 2018, recorded by MEMS and electrolytic sensor at -14 m of depth.
Figure 13 Local displacement trends between 4 and 8 July 2018, recorded by MEMS and electrolytic sensor at -14 m of depth.
Figure 1 Map of Slovenia with recorded landslide occurrences. Studied area is marked with red rectangle.
Figure 1 Map of Slovenia with recorded landslide occurrences. Studied area is marked with red rectangle.
Figure 2 Posavsko hills with recorded landslide occurrences during the studied 7 major rainfall events (red dots) and rain gauges (black and white dots). For the purpose of hourly rainfall data analysis, we used three different rain gauges. Due to the small number of automatic gauges and the large distances between them, we used the data from the closest gauges. They collect rainfall data every 5 minutes or every half an hour, which were recalculated into hourly data.
Figure 2 Posavsko hills with recorded landslide occurrences during the studied 7 major rainfall events (red dots) and rain gauges (black and white dots). For the purpose of hourly rainfall data analysis, we used three different rain gauges. Due to the small number of automatic gauges and the large distances between them, we used the data from the closest gauges. They collect rainfall data every 5 minutes or every half an hour, which were recalculated into hourly data.
Table 1 Skill scores used for validation of the MASPREM models (Gariano et al., 2015).
Table 1 Skill scores used for validation of the MASPREM models (Gariano et al., 2015).
Figure 3 Landslide occurrence in 3 different groups, based on cumulative and antecedent rainfall. The different rain gauges are marked with circles of different colors. occurrence by the end of the day. This however represents some uncertainty regarding the amount of rainfall needed for landslide occurrence, i.e. the landslides could have been triggered during the day at lower amounts of rainfall than we considered. The mean intensity of the rainfall events showed, that the landslides were triggered at similar amounts of rainfall regardless the duration of the events (Fig. 4). For the mean intensity we took hourly rainfall data on the day of the landslide occurrence. The duration of the event was determined as a continuous period of rainfall. The 7 events lasted from 7 to 30 hours continuously and the amount of rainfall varies averagely around 35 mm. The event on September 13" 2014 is an exception. It lasted 18 hours and the amount of rain reached 84.5 mm. This amount of rainfall triggered a lot of landslides on different lithological units. While we do not have accurate time frame, when the landslides were triggered (e.g. at what time during the day), we considered the time of s. Jordanova, T. VerbovSek, M. Jemec-Aufli¢ - Case study: validation and proposal of new rainfall thresholds for shallow landslide predicti« Posavsko hills, eastern Slovenia
Figure 3 Landslide occurrence in 3 different groups, based on cumulative and antecedent rainfall. The different rain gauges are marked with circles of different colors. occurrence by the end of the day. This however represents some uncertainty regarding the amount of rainfall needed for landslide occurrence, i.e. the landslides could have been triggered during the day at lower amounts of rainfall than we considered. The mean intensity of the rainfall events showed, that the landslides were triggered at similar amounts of rainfall regardless the duration of the events (Fig. 4). For the mean intensity we took hourly rainfall data on the day of the landslide occurrence. The duration of the event was determined as a continuous period of rainfall. The 7 events lasted from 7 to 30 hours continuously and the amount of rainfall varies averagely around 35 mm. The event on September 13" 2014 is an exception. It lasted 18 hours and the amount of rain reached 84.5 mm. This amount of rainfall triggered a lot of landslides on different lithological units. While we do not have accurate time frame, when the landslides were triggered (e.g. at what time during the day), we considered the time of s. Jordanova, T. VerbovSek, M. Jemec-Aufli¢ - Case study: validation and proposal of new rainfall thresholds for shallow landslide predicti« Posavsko hills, eastern Slovenia
Figure 4 Mean intensity of the rainfall events. The rainfall event on September 1° 2014 is represented by two sets of data due to the different amount of rainfall, that triggered landslides near two different automatic gauges.
Figure 4 Mean intensity of the rainfall events. The rainfall event on September 1° 2014 is represented by two sets of data due to the different amount of rainfall, that triggered landslides near two different automatic gauges.
Figure 5 Rainfall patterns of the events. The event on September ist 2014 is presented by two sets as in Fig. 4.
Figure 5 Rainfall patterns of the events. The event on September ist 2014 is presented by two sets as in Fig. 4.
Figure 1 Location of the Kostanjek landslide and_ the meteorological station Zagreb-Grié.
Figure 1 Location of the Kostanjek landslide and_ the meteorological station Zagreb-Grié.
Figure 2 Locations of multiple sensor networks at the Kostanjek landslide (Krkaé et al, 2017).
Figure 2 Locations of multiple sensor networks at the Kostanjek landslide (Krkaé et al, 2017).
Figure 3 Cumulative and monthly precipitations measured at Zagreb-Grié meteorological station
Figure 3 Cumulative and monthly precipitations measured at Zagreb-Grié meteorological station
Figure 4 Groundwater level depth and pore pressure at the sliding surface measured at central part of Kostanjek landslide.
Figure 4 Groundwater level depth and pore pressure at the sliding surface measured at central part of Kostanjek landslide.
Figure 6 Cumulative 3D displacements (measured with GNSS 08), compared with groundwater level/pore pressure measured at the central part of landslide.
Figure 6 Cumulative 3D displacements (measured with GNSS 08), compared with groundwater level/pore pressure measured at the central part of landslide.
The observed location is located inside the massive of the Lower Triassic (T,’) as indicated in Fig. 2. Figure 2 Position of the landslide on the map (basic geological map of Prozor 1:100.000) Geological data
The observed location is located inside the massive of the Lower Triassic (T,’) as indicated in Fig. 2. Figure 2 Position of the landslide on the map (basic geological map of Prozor 1:100.000) Geological data
Figure 1 Position of the landslide on the map (topographic map Jablanica 1:25.000) The location of the structure is on the bedrock and behind it is a slope with an angle over 40°. A cut slope happened just five meters from the structure. As informed by the local inhabitants the movement of the slope was very fast and manifested in a loud crash that occurred in January 2018. At that time the entire artificial bank and all the threes ended inside of the lake.
Figure 1 Position of the landslide on the map (topographic map Jablanica 1:25.000) The location of the structure is on the bedrock and behind it is a slope with an angle over 40°. A cut slope happened just five meters from the structure. As informed by the local inhabitants the movement of the slope was very fast and manifested in a loud crash that occurred in January 2018. At that time the entire artificial bank and all the threes ended inside of the lake.
Figure 4 Basic rock on the lake of Jablanica coast (photo, Nikolic T. 2018.)
Figure 4 Basic rock on the lake of Jablanica coast (photo, Nikolic T. 2018.)
Figure 3 Gelogical Strength Index (GSI) value diagram
Figure 3 Gelogical Strength Index (GSI) value diagram
Figure 5 The current situation on the field (Nikolic T. 2018)
Figure 5 The current situation on the field (Nikolic T. 2018)
Figure 6 Fracture of the concrete wall below the house (Nikolic T. 2018) The water going over the slope was the main problem that had to be solved. Fig.5 shows the pipe indicated by red arrows from which the water came into the slope.
Figure 6 Fracture of the concrete wall below the house (Nikolic T. 2018) The water going over the slope was the main problem that had to be solved. Fig.5 shows the pipe indicated by red arrows from which the water came into the slope.
Figure 7 Landslide profile on the site
Figure 7 Landslide profile on the site
The first step was to isolate the slope from the atmospheric impact and make a reinforced concrete (RC) wall with a rock cover behind it (Fig. 9). Figure 9 Slope stability check with RC wall and rock cover behind the wall (Fs =2.056)
The first step was to isolate the slope from the atmospheric impact and make a reinforced concrete (RC) wall with a rock cover behind it (Fig. 9). Figure 9 Slope stability check with RC wall and rock cover behind the wall (Fs =2.056)
Figure 8 Local sliding simulation - Fs=0,491 (estimate with low parameter of rock: GSI = 5, mj =2; 6c: = 5 MPa, y = 25 kN/m3, after aggressive impact of the local condition)
Figure 8 Local sliding simulation - Fs=0,491 (estimate with low parameter of rock: GSI = 5, mj =2; 6c: = 5 MPa, y = 25 kN/m3, after aggressive impact of the local condition)
Conclusion Acknowledgments
Conclusion Acknowledgments
Table 1 Check for overturning stability
Table 1 Check for overturning stability
Figure 1 Location of study area (Tomuro landslide) and simplified topographical map of Tomuro landslide, showing the location of Sampling point, Piezometers and Extensometer Figure 3 Groundwater level fluctuation in the boreholes
Figure 1 Location of study area (Tomuro landslide) and simplified topographical map of Tomuro landslide, showing the location of Sampling point, Piezometers and Extensometer Figure 3 Groundwater level fluctuation in the boreholes
Figure 2 Variation of the rainfall and snowfall precipitation
Figure 2 Variation of the rainfall and snowfall precipitation
displacement rate has been also increased and vice versa. The creep displacement of the landslide as directly related to the groundwater condition. Therefore, the fluctuation of groundwater should be considered to better understand the creeping behaviour of a landslide (Bhat et al. 2017). In this study, the groundwater fluctuation is considered for the stability analysis using the various Limit Equilibrium Methods and Finite Element Method, as well as the numerical simulation of the Tomuro landslide.
displacement rate has been also increased and vice versa. The creep displacement of the landslide as directly related to the groundwater condition. Therefore, the fluctuation of groundwater should be considered to better understand the creeping behaviour of a landslide (Bhat et al. 2017). In this study, the groundwater fluctuation is considered for the stability analysis using the various Limit Equilibrium Methods and Finite Element Method, as well as the numerical simulation of the Tomuro landslide.
Figure 4 Finite element model of Tomuro landslide analysis, which is prepared based on the geological cross- section o the slope of such landslide site. The base of the model is assumed to be fully impervious and fixed, and the lateral sid hydraulic on the fie S-1 repres e (left and right) is constrained by hinged. The head is imposed at the lateral boundaries based d monitoring results of groundwater fluctuation. ents the location of point (i.e., node 199), where the maximum displacement of the landslide body was measured in the field during the period of 2014/1/14 to 2015/7/6 Fig. 4).
Figure 4 Finite element model of Tomuro landslide analysis, which is prepared based on the geological cross- section o the slope of such landslide site. The base of the model is assumed to be fully impervious and fixed, and the lateral sid hydraulic on the fie S-1 repres e (left and right) is constrained by hinged. The head is imposed at the lateral boundaries based d monitoring results of groundwater fluctuation. ents the location of point (i.e., node 199), where the maximum displacement of the landslide body was measured in the field during the period of 2014/1/14 to 2015/7/6 Fig. 4).
Table 1 Material parameters for landslide simulation Model results and discussion
Table 1 Material parameters for landslide simulation Model results and discussion
measured time histories of horizontal displacement at S-1 has slightly increased from
measured time histories of horizontal displacement at S-1 has slightly increased from
Figure 6 Results of shear strain pattern Figure 5 Results of deformation pattern
Figure 6 Results of shear strain pattern Figure 5 Results of deformation pattern
References Figure 7 Comparison of predicted and measured time histories of horizontal displacement at S-1
References Figure 7 Comparison of predicted and measured time histories of horizontal displacement at S-1
The Japanese Archipelago is comprised of five main islands arcs extending approximately 3000 km in the northeast to southwest direction (Fig. 1) and encompasses a total area of about 378,000 kmz2. Seventy-five percent of the total area consists of mountainous and hilly terrain. The five main islands arcs are, from northeast to southwest, Kurile Arc, Northeast Honshu Arc, Izu- Mariana Arc, Southwest Honshu Arc and RyuKyu Arc. These approximately represent plate boundaries among
The Japanese Archipelago is comprised of five main islands arcs extending approximately 3000 km in the northeast to southwest direction (Fig. 1) and encompasses a total area of about 378,000 kmz2. Seventy-five percent of the total area consists of mountainous and hilly terrain. The five main islands arcs are, from northeast to southwest, Kurile Arc, Northeast Honshu Arc, Izu- Mariana Arc, Southwest Honshu Arc and RyuKyu Arc. These approximately represent plate boundaries among
Figure 2 Monthly mean precipitation (after Japan Landslide Society, 1996) the North American Plate, Pacific Plate, Euracian Plate and Philippine Sea Plate. Because of interrelationship between arcs and plates, Japan is located in the area under strong crustal movements and belongs to one of the seismically most active regions. There are 86 active volacnoes in apan. It means approximately 10% of the whole active volcanoes in the world. Furthermore, epicenters of deep- seated earthquakes around Japan are distributed along Kurile-Kamchtka Trench, Japan Trench, Izu-Ogasawara Trench, Nankai Trough and Ryukyu Trench. Landslides occur frequently in the following physiographic zones. The nner Northeast Honshu Arc is representative landslide zone. The Northwest Kyushu Island in the Southwest Honshu Arc is a zone of high-density landslide distribution. The Outer Southwest Honshu (Shikoku Mountain) and the Central Western Honshu (Chubu Mountain) are zones represented by landslides of very slow movement and by very large-scale slope failures of rapid movement.
Figure 2 Monthly mean precipitation (after Japan Landslide Society, 1996) the North American Plate, Pacific Plate, Euracian Plate and Philippine Sea Plate. Because of interrelationship between arcs and plates, Japan is located in the area under strong crustal movements and belongs to one of the seismically most active regions. There are 86 active volacnoes in apan. It means approximately 10% of the whole active volcanoes in the world. Furthermore, epicenters of deep- seated earthquakes around Japan are distributed along Kurile-Kamchtka Trench, Japan Trench, Izu-Ogasawara Trench, Nankai Trough and Ryukyu Trench. Landslides occur frequently in the following physiographic zones. The nner Northeast Honshu Arc is representative landslide zone. The Northwest Kyushu Island in the Southwest Honshu Arc is a zone of high-density landslide distribution. The Outer Southwest Honshu (Shikoku Mountain) and the Central Western Honshu (Chubu Mountain) are zones represented by landslides of very slow movement and by very large-scale slope failures of rapid movement.
Table 1 Designated Landslide Threatened Areas The number of the wohle Landslide Threatened Areas amounts to 6,992 and total area of them amounts to 319,011 ha. It means that about 0.8% of the total area of Japanese territory is designated as Landslide Threatened Areas. The total expenditures of landslide mitigation measures implemented by the responsible agencies during the fiscal year of 2000 are shown in in Table 2.
Table 1 Designated Landslide Threatened Areas The number of the wohle Landslide Threatened Areas amounts to 6,992 and total area of them amounts to 319,011 ha. It means that about 0.8% of the total area of Japanese territory is designated as Landslide Threatened Areas. The total expenditures of landslide mitigation measures implemented by the responsible agencies during the fiscal year of 2000 are shown in in Table 2.
Figure 3 Distribution of landslide prone areas and geotectonic structures (Kitamura, 1992) The distribution of landslide prone areas and related geotectonic structures are shown in Figure 3. Landslides are highly concentrated along the major tectonic lines such as in the northern Fossa Magna Region and near to the Median Tectonic Line in Shikoku Island. A typical landscape chracterized by landslides in the northern Fossa Magana Region are shown in Fig. 4. Another typical landscape characterizes by landslides along the Median Tectonic Line are shown in Fig. 5. Further, Fig. 6 shows an example of extremly high concentration of landslide areas in Matsunoyama-District in Niigata Prefecture. This area is geologically characterized by Neogene formations which consist of black mudstone or alternation of sandstone and mudstone. Soils along the sliding surface in these formations show extremely low shear strength. Twenty percent of the total landslide areas in whole Japan are concentrated in Niigata Prefecture and especially in neighbourhood of this district.
Figure 3 Distribution of landslide prone areas and geotectonic structures (Kitamura, 1992) The distribution of landslide prone areas and related geotectonic structures are shown in Figure 3. Landslides are highly concentrated along the major tectonic lines such as in the northern Fossa Magna Region and near to the Median Tectonic Line in Shikoku Island. A typical landscape chracterized by landslides in the northern Fossa Magana Region are shown in Fig. 4. Another typical landscape characterizes by landslides along the Median Tectonic Line are shown in Fig. 5. Further, Fig. 6 shows an example of extremly high concentration of landslide areas in Matsunoyama-District in Niigata Prefecture. This area is geologically characterized by Neogene formations which consist of black mudstone or alternation of sandstone and mudstone. Soils along the sliding surface in these formations show extremely low shear strength. Twenty percent of the total landslide areas in whole Japan are concentrated in Niigata Prefecture and especially in neighbourhood of this district.
Figure 6 Distribution of landslide areas in Matsunoyama-District in Niigata Prefecture (Suzuki, 2005)
Figure 6 Distribution of landslide areas in Matsunoyama-District in Niigata Prefecture (Suzuki, 2005)
Figure 5 Landslides in metamorphic rock formation
Figure 5 Landslides in metamorphic rock formation
Figure 4 Landslides in Neogene formation
Figure 4 Landslides in Neogene formation
Figure 8 Relationship between peak strength ¢ ' or residual strength , and plasticity index I, in landslides in fractured metamorphic rock formation and in landslides in Neogene formation (Yatabe et.al., 2000)
Figure 8 Relationship between peak strength ¢ ' or residual strength , and plasticity index I, in landslides in fractured metamorphic rock formation and in landslides in Neogene formation (Yatabe et.al., 2000)
Figure 9 Flow chart for landslide investigation and analysis (Japan Landslide Society, 1996)
Figure 9 Flow chart for landslide investigation and analysis (Japan Landslide Society, 1996)
The sliding surface of active landslides can be determined by measuring displacement of casing pipe according to the movement of the sliding soil mass. Depending on the requirements for surveying accuracy and magnitude of movement, appropriate instruments should be selected from the following representative instruments: (1) Pipe strain gauge, (2) Inclinometer, (3) Multi-layer movement meter. Figure 10 Automated monitoring sytem using IT technology (Japan Landslide Society, 2002)
The sliding surface of active landslides can be determined by measuring displacement of casing pipe according to the movement of the sliding soil mass. Depending on the requirements for surveying accuracy and magnitude of movement, appropriate instruments should be selected from the following representative instruments: (1) Pipe strain gauge, (2) Inclinometer, (3) Multi-layer movement meter. Figure 10 Automated monitoring sytem using IT technology (Japan Landslide Society, 2002)
Figure 1 Airborne laser scanning (a): Schematic diagram, (b): An example on landslides in Medvednica mountain in Zagreb Airborne laser scanning is very useful tool for the identification of landslide in a wide area. It can identify also shallow landslides even when they are only several meters. This method is appropriate to detect geomorphological features that provide essential information in formulation of landslide inventry maps and assessng susceptibility to slope movement (Fig. 11).
Figure 1 Airborne laser scanning (a): Schematic diagram, (b): An example on landslides in Medvednica mountain in Zagreb Airborne laser scanning is very useful tool for the identification of landslide in a wide area. It can identify also shallow landslides even when they are only several meters. This method is appropriate to detect geomorphological features that provide essential information in formulation of landslide inventry maps and assessng susceptibility to slope movement (Fig. 11).
Figure 12 Satellite DInSAR analysis (a):Schematic diagram, (b):Detection in 2010, (c): Landslide in 2011 (Mizuno, 2014)
Figure 12 Satellite DInSAR analysis (a):Schematic diagram, (b):Detection in 2010, (c): Landslide in 2011 (Mizuno, 2014)
Figure 13 Schematic representation of , hazard zoning“ for three processes (Ministry of Land, Infrastructure and Transport, 2014) Remarks: Red zone and yellow zone are designated concerning individual landslide area. Individual landslide areas are identified on the basis of the interpretation of aerial photographs. Red zone: Development activities are restricted. Structure of buildings is to be regulated. Yellow zone: Risk awareness and warning and evacuation system must be arranged.
Figure 13 Schematic representation of , hazard zoning“ for three processes (Ministry of Land, Infrastructure and Transport, 2014) Remarks: Red zone and yellow zone are designated concerning individual landslide area. Individual landslide areas are identified on the basis of the interpretation of aerial photographs. Red zone: Development activities are restricted. Structure of buildings is to be regulated. Yellow zone: Risk awareness and warning and evacuation system must be arranged.
Figure 14 Left: Diagram ilustrating method by Saito; Right: Diagram ilustrating method by Fukuzono Hazard zoning system was introduced in Japan in 2oo1after the severe disasters caused by slope failures and debris flows in Hiroshima in 1999. On the basis of the law, the responsible Ministry formulated the basic guidelines (Fig. 13). Each Prefecture carried out necessary investigations based on the guidelines and mapped the areas affected by landslides, namely red and yellow zones were designated. Hazard zoning system is directly connected with warning and evacuation. It is obligatory for the prefectures to inform the public about the results of the specified hazard zoning and to make known the warning information before disastrous movement of landslides to the mayors and inhabitants of the relevant municipalities. Individual landslide areas are identified on the basis of the interpretation of aerial photographs.
Figure 14 Left: Diagram ilustrating method by Saito; Right: Diagram ilustrating method by Fukuzono Hazard zoning system was introduced in Japan in 2oo1after the severe disasters caused by slope failures and debris flows in Hiroshima in 1999. On the basis of the law, the responsible Ministry formulated the basic guidelines (Fig. 13). Each Prefecture carried out necessary investigations based on the guidelines and mapped the areas affected by landslides, namely red and yellow zones were designated. Hazard zoning system is directly connected with warning and evacuation. It is obligatory for the prefectures to inform the public about the results of the specified hazard zoning and to make known the warning information before disastrous movement of landslides to the mayors and inhabitants of the relevant municipalities. Individual landslide areas are identified on the basis of the interpretation of aerial photographs.
Figure 15 Monitoring system for early warning in Takisaka landslide (Agano River District Office, 2016)
Figure 15 Monitoring system for early warning in Takisaka landslide (Agano River District Office, 2016)
Figure 16 Various types of landslide mitigation measures Hard measures are classified into two types; namely ylandslide control measures“, and ,landslide restraint measures". Landslide control measures involve modifications of the natural conditions of landslide areas such as topography, groundwater and other conditions that indirectly control the landslide movement. Landslide restraint measures, on the other hand, rely on preventing the landslide movement by directly adding a resisting force to the sliding movement. Individual measures included in both types of mitigation measures are listed in Fig. 16, and examples shown in Figs. 17 to 19.
Figure 16 Various types of landslide mitigation measures Hard measures are classified into two types; namely ylandslide control measures“, and ,landslide restraint measures". Landslide control measures involve modifications of the natural conditions of landslide areas such as topography, groundwater and other conditions that indirectly control the landslide movement. Landslide restraint measures, on the other hand, rely on preventing the landslide movement by directly adding a resisting force to the sliding movement. Individual measures included in both types of mitigation measures are listed in Fig. 16, and examples shown in Figs. 17 to 19.
Figure 17 Illustration of various types of landslide mitigation measures (Agano River District Office, 2016)
Figure 17 Illustration of various types of landslide mitigation measures (Agano River District Office, 2016)
Figure 19 Illustration of a drainage tunnel installed in Takisaka landslide (Agano River District Office, 2016)
Figure 19 Illustration of a drainage tunnel installed in Takisaka landslide (Agano River District Office, 2016)
Figure 1 Schematic diagram showing geological fault zone Until recently, the damage caused to retaining structures, slope bridges and the pavement construction by creep movements in the slope necessitated major rehabilitation at regular intervals. Despite this, the condition of the road section continued to worsen noticeably: the pavement surfacing and lateral retaining walls exhibited substantial cracking. In places, this even led to the detachment of retaining wall facings or the destruction of rock bolts/anchor heads (see Figure 2). Apart from the risks posed by localized problem areas, even the possibility of large-scale landslips could not be completely ruled out.
Figure 1 Schematic diagram showing geological fault zone Until recently, the damage caused to retaining structures, slope bridges and the pavement construction by creep movements in the slope necessitated major rehabilitation at regular intervals. Despite this, the condition of the road section continued to worsen noticeably: the pavement surfacing and lateral retaining walls exhibited substantial cracking. In places, this even led to the detachment of retaining wall facings or the destruction of rock bolts/anchor heads (see Figure 2). Apart from the risks posed by localized problem areas, even the possibility of large-scale landslips could not be completely ruled out.
Route Mapping
Route Mapping
Figure 4 Measures to stabilize and drain slope cuttings at foundation level
Figure 4 Measures to stabilize and drain slope cuttings at foundation level
Figure 5 Schematic of standard cross-section
Figure 5 Schematic of standard cross-section
Years of experience have shown this design concept to offer a practical, reliable, durable and cost- effective solution. Figure 7 Schematic showing front slope design with wrap-back and vegetation
Years of experience have shown this design concept to offer a practical, reliable, durable and cost- effective solution. Figure 7 Schematic showing front slope design with wrap-back and vegetation
Figure 8 View of some of the described GRS slopes The successful implementation of construction projects of this technical complexity requires in-depth experience and the commitment of all project team members to the pursuit of innovative solutions.
Figure 8 View of some of the described GRS slopes The successful implementation of construction projects of this technical complexity requires in-depth experience and the commitment of all project team members to the pursuit of innovative solutions.
Figure 1 Standalone GIMS unit (Photo: E. Segina). Materials and methods Strozzi et al. 2018). IMU (Inertial Measurement Unit) sensors have mostly been used in laboratory experiments to determine their usability in measuring ground movements (Abdoun et al. 2006, Hanto et al. 20n, Cmielewski et al. 2013, Tran et al. 2015, Kumar & Naidu 2015, Leng Ooi et al. 2016, Lo Iacon et al. 2017). Less frequently they were applied to the field to measure landslide velocity (Wang et al. 2017, Yang et al. 2017, Awaludin & Agni Dhewa 2018). Combination of different sensors has also already been applied for a similar approach (Benedetti et al. 2017, Carla et al. 2019). The GIMS unit measure ground movements by the three complementary methods: GNSS, InSAR and IMU. Such a multidisciplinary approach promises improved accuracy and verifiability of the data. Application of the open access Copernicus and Galileo systems reduced the cost of the landslide monitoring.
Figure 1 Standalone GIMS unit (Photo: E. Segina). Materials and methods Strozzi et al. 2018). IMU (Inertial Measurement Unit) sensors have mostly been used in laboratory experiments to determine their usability in measuring ground movements (Abdoun et al. 2006, Hanto et al. 20n, Cmielewski et al. 2013, Tran et al. 2015, Kumar & Naidu 2015, Leng Ooi et al. 2016, Lo Iacon et al. 2017). Less frequently they were applied to the field to measure landslide velocity (Wang et al. 2017, Yang et al. 2017, Awaludin & Agni Dhewa 2018). Combination of different sensors has also already been applied for a similar approach (Benedetti et al. 2017, Carla et al. 2019). The GIMS unit measure ground movements by the three complementary methods: GNSS, InSAR and IMU. Such a multidisciplinary approach promises improved accuracy and verifiability of the data. Application of the open access Copernicus and Galileo systems reduced the cost of the landslide monitoring.
Complex Pleistocene to recent landslides in the area are related to the Mesozoic carbonates thrust over folded and tectonically fractured Tertiary siliciclastic flysch (Fig. 2). Such overthrusting has caused steep slopes and fracturing of the rocks, producing intensely weathered carbonates and large amounts of scree deposits. The combination of geological conditions and periods of intense short or prolonged rainfall (average precipitation is approximately 1,700 mm to 2,500 mm/year on the karstic plateau) has led to the formation of different types of complex landslides. Recently, carbonates have been breaking down in the form of steep fans of carbonate scree in the upper part of the valley, increasing the thickness of these sediment layers over 10 m. In the lower part, superficial deposits range from large-scale, deep- seated rotational and translational slides to shallow andslides, slumps, and sedimentary gravity flows in the form of debris or mudflows reworking the carbonate scree and flysch material. Figure 2 Geological map of the study site (Popit et al. 2016) with marked locations of GIMS units.
Complex Pleistocene to recent landslides in the area are related to the Mesozoic carbonates thrust over folded and tectonically fractured Tertiary siliciclastic flysch (Fig. 2). Such overthrusting has caused steep slopes and fracturing of the rocks, producing intensely weathered carbonates and large amounts of scree deposits. The combination of geological conditions and periods of intense short or prolonged rainfall (average precipitation is approximately 1,700 mm to 2,500 mm/year on the karstic plateau) has led to the formation of different types of complex landslides. Recently, carbonates have been breaking down in the form of steep fans of carbonate scree in the upper part of the valley, increasing the thickness of these sediment layers over 10 m. In the lower part, superficial deposits range from large-scale, deep- seated rotational and translational slides to shallow andslides, slumps, and sedimentary gravity flows in the form of debris or mudflows reworking the carbonate scree and flysch material. Figure 2 Geological map of the study site (Popit et al. 2016) with marked locations of GIMS units.
Figure 4 Gyroscope’s preliminary measurements. Figure 3 Inclinometer’s preliminary measurements.
Figure 4 Gyroscope’s preliminary measurements. Figure 3 Inclinometer’s preliminary measurements.
Figure 5 Accelerometer’s preliminary measurements.
Figure 5 Accelerometer’s preliminary measurements.
Figures 3-8 show preliminary measurements performed by one of the installed GIMS unit. Note that IMU and inclinometer results still need to be processed to remove the effect of temperature. Here we report the preliminary results of only one station as an example.
Figures 3-8 show preliminary measurements performed by one of the installed GIMS unit. Note that IMU and inclinometer results still need to be processed to remove the effect of temperature. Here we report the preliminary results of only one station as an example.
Figure 6 First compact active SAR transponders measurements. Figure 7 First compact active SAR transponders measurements.
Figure 6 First compact active SAR transponders measurements. Figure 7 First compact active SAR transponders measurements.
Figure 8 Preliminary results: first GNSS positioning measurements in the east, north and up components computed relatively to VIP7 (reference point). Note that so far, only the satellite images of three passages are available for verifying their correct installation and functioning. On the bases of a preliminary check, we expect positive results, but further data are needed to confirm it.
Figure 8 Preliminary results: first GNSS positioning measurements in the east, north and up components computed relatively to VIP7 (reference point). Note that so far, only the satellite images of three passages are available for verifying their correct installation and functioning. On the bases of a preliminary check, we expect positive results, but further data are needed to confirm it.
Figure 1 (a) Geographical position of the Vinodol Valley in Croatia, and the hillshade map of the northwestern part of the Valley, derived from the 1 m LiDAR DTM. (b) A detail from the Engineering geological map of the nort-western part of the Vinodol Valley (Domlija, 2018), with the soil sampling site. Photographs (c, d) were taken during the sampling of eluvial deposits from the landslide body.
Figure 1 (a) Geographical position of the Vinodol Valley in Croatia, and the hillshade map of the northwestern part of the Valley, derived from the 1 m LiDAR DTM. (b) A detail from the Engineering geological map of the nort-western part of the Vinodol Valley (Domlija, 2018), with the soil sampling site. Photographs (c, d) were taken during the sampling of eluvial deposits from the landslide body.
Figure 2. Dynatriax cyclic triaxial system load on the sample. Cell and back pressure are measured with pressure transducers on the pneumatic unit (Fig.Figure 2(g)), also used for its control, while the pore water pressure transducer (Fig.Figure 2(h)) is directly connected to the main unit (Fig. 2(d)). The soil sample is shaped into the soil specimen for cyclic triaxial testing using specially designed cutter. Cutter is pushed in the soil sampled in the field, resulting in the soil sample of 38 mm in diameter and 76 mm in height. During sample preparation, small part of soil is used to determine the initial water content. Sample is placed in triaxial cell and subjected to B -test (Lade 2016) until B value of 0.96 was reached.
Figure 2. Dynatriax cyclic triaxial system load on the sample. Cell and back pressure are measured with pressure transducers on the pneumatic unit (Fig.Figure 2(g)), also used for its control, while the pore water pressure transducer (Fig.Figure 2(h)) is directly connected to the main unit (Fig. 2(d)). The soil sample is shaped into the soil specimen for cyclic triaxial testing using specially designed cutter. Cutter is pushed in the soil sampled in the field, resulting in the soil sample of 38 mm in diameter and 76 mm in height. During sample preparation, small part of soil is used to determine the initial water content. Sample is placed in triaxial cell and subjected to B -test (Lade 2016) until B value of 0.96 was reached.
Table 2 Summary of cyclic tests
Table 2 Summary of cyclic tests
Table 1 Summary of cyclic tests Results of the performed laboratory tests are presented in the following section. Special attention is given to the determination of cyclic stress ratio and the cyclic double amplitudes of relative deformation.
Table 1 Summary of cyclic tests Results of the performed laboratory tests are presented in the following section. Special attention is given to the determination of cyclic stress ratio and the cyclic double amplitudes of relative deformation.
Figure 3 Variation of CSR with number of cycles with respect to double amplitude cyclic strain
Figure 3 Variation of CSR with number of cycles with respect to double amplitude cyclic strain
Table 1 Piezometer monitoring [2]
Table 1 Piezometer monitoring [2]
Figure 2 Landslide view, km 7+500[2] Figure 1 Geological mapping near km 7+500[2]
Figure 2 Landslide view, km 7+500[2] Figure 1 Geological mapping near km 7+500[2]
Figure 3 Landslide view, km 10+600[2]
Figure 3 Landslide view, km 10+600[2]
Figure 4 Open slope near km 7+800[2] Geotechnical investigation On the area of unstable slopes of Orikum-Himare road, Shen Elize area the following works have been carried out:
Figure 4 Open slope near km 7+800[2] Geotechnical investigation On the area of unstable slopes of Orikum-Himare road, Shen Elize area the following works have been carried out:
In the laboratory detailed testing, are performed to obtain the necessary parameters for assessing the stability of the slopes. These testing included grain size distribution, Atterberg limits, bulk density, specific gravity, direct shear test, residual direct shear test, unconfined compressive strength test, etc...
In the laboratory detailed testing, are performed to obtain the necessary parameters for assessing the stability of the slopes. These testing included grain size distribution, Atterberg limits, bulk density, specific gravity, direct shear test, residual direct shear test, unconfined compressive strength test, etc...
Figure 5 Location of Boreholes [2]
Figure 5 Location of Boreholes [2]
Figure 7 Geological section from borehole BH-5 [2]
Figure 7 Geological section from borehole BH-5 [2]
Figure 8 Typical residual direct shear test [2]
Figure 8 Typical residual direct shear test [2]
Figure 6 Geological section from borehole BH-3[2]
Figure 6 Geological section from borehole BH-3[2]
Figure 9 Typical unconfined compressive strength test[2] Figure 10 Grain size distribution test[2]
Figure 9 Typical unconfined compressive strength test[2] Figure 10 Grain size distribution test[2]
Depth of landslide according to the measurement in 16/05/2019 for BH-3 is 26 m depth; for BH-5 is 16.00 m depth. [2-4] Figure u1 Inclinometer results at BH-3 from January 2018 up to May 2019[2]
Depth of landslide according to the measurement in 16/05/2019 for BH-3 is 26 m depth; for BH-5 is 16.00 m depth. [2-4] Figure u1 Inclinometer results at BH-3 from January 2018 up to May 2019[2]
Table 2 Summary of physical-mechanical features[2]
Table 2 Summary of physical-mechanical features[2]
SEER, eeenes RE Ia Moderately strong, white to grey, fractured limestone, containing small karstic caves, the fractures and cavers are filled with silty clay and are rarely empty. Table 5 Summary of physical-mechanical features[2] SSO Up, enn! SERIA ort Weak to moderately weak, grey, mudstone and sandstone with fractures. The fractures are in dip angle 45 degree but have and small fracture in dip angle 5 degree, with undulated and slickensides surfaces.
SEER, eeenes RE Ia Moderately strong, white to grey, fractured limestone, containing small karstic caves, the fractures and cavers are filled with silty clay and are rarely empty. Table 5 Summary of physical-mechanical features[2] SSO Up, enn! SERIA ort Weak to moderately weak, grey, mudstone and sandstone with fractures. The fractures are in dip angle 45 degree but have and small fracture in dip angle 5 degree, with undulated and slickensides surfaces.
Table 3 Summary of physical-mechanical features[2]
Table 3 Summary of physical-mechanical features[2]
Table 4 Summary of physical-mechanical features [2]
Table 4 Summary of physical-mechanical features [2]
Figure 12 Inclinometer results at BH-5 from January 2018 up to May 2019[2]
Figure 12 Inclinometer results at BH-5 from January 2018 up to May 2019[2]
Table 1 Topographic datasets used in this study, with ArcGIS tools used for derivation from the 1m bare-earth LiDAR DTM.
Table 1 Topographic datasets used in this study, with ArcGIS tools used for derivation from the 1m bare-earth LiDAR DTM.
‘igure 1 (a) Geographical location; and (b) relief map of the Vinodol Valley.
‘igure 1 (a) Geographical location; and (b) relief map of the Vinodol Valley.
Table 2 Definitions of landslide types (Hungr et al., 2014) identified along the carbonate cliffs in the Vinodol Valley.
Table 2 Definitions of landslide types (Hungr et al., 2014) identified along the carbonate cliffs in the Vinodol Valley.
Figure 2 Rock falls and rock topples identified along carbonate cliffs in the Vinodol Valley: (a) scars of recent rock falls; (b, c) chut with overhanging blocks, rock fall scars, and associated recent talus deposits; and (d) potentially unstable an detached blocks.
Figure 2 Rock falls and rock topples identified along carbonate cliffs in the Vinodol Valley: (a) scars of recent rock falls; (b, c) chut with overhanging blocks, rock fall scars, and associated recent talus deposits; and (d) potentially unstable an detached blocks.
Figure 3 Examples of the rock fall and rock topple topography presented on (from left to right) the slope map, the hillshade mar without, and with delineated landslide polygons, identified in: (a) the central part; and (b) in the SE part of the Vindol Valley.
Figure 3 Examples of the rock fall and rock topple topography presented on (from left to right) the slope map, the hillshade mar without, and with delineated landslide polygons, identified in: (a) the central part; and (b) in the SE part of the Vindol Valley.
Figure 4 Examples of the: (a) rock irregular slide; and (b) rock slope deformation topography, shown on (from left to right in (a)) the profile curvature map, the hillshade map without, and with delineated landslide polygon, and on (from left to right in (b)) the slope map, the hillshade map without, and with delineate landslide polygons. cliffs, as the unambiguous source area for an assumed avalanche phenomenon. In the presented case, it is possible that the sedimentary body is actually composed of the two smaller, elongated accumulations of rock material, which may originate from a rock irregular slide phenomenon, and a large rock fall (Domlija 2018). 5a), and a flow-like appearance was clearly expressed on the profile curvature map. Surface roughness was identified as the most appropriate method and can be an indispensable tool for geomorphological mapping of fossil landslide (Popit, 2016). However, no topographic signatures could be with certainty identified along the
Figure 4 Examples of the: (a) rock irregular slide; and (b) rock slope deformation topography, shown on (from left to right in (a)) the profile curvature map, the hillshade map without, and with delineated landslide polygon, and on (from left to right in (b)) the slope map, the hillshade map without, and with delineate landslide polygons. cliffs, as the unambiguous source area for an assumed avalanche phenomenon. In the presented case, it is possible that the sedimentary body is actually composed of the two smaller, elongated accumulations of rock material, which may originate from a rock irregular slide phenomenon, and a large rock fall (Domlija 2018). 5a), and a flow-like appearance was clearly expressed on the profile curvature map. Surface roughness was identified as the most appropriate method and can be an indispensable tool for geomorphological mapping of fossil landslide (Popit, 2016). However, no topographic signatures could be with certainty identified along the
Figure 5 Example of the rock avalanche topography presented on (from left to right) the topographic roughness map, the hillshade map without, and with delineated landslide polygons, identified in the SE part of the Vinodol Valley.
Figure 5 Example of the rock avalanche topography presented on (from left to right) the topographic roughness map, the hillshade map without, and with delineated landslide polygons, identified in the SE part of the Vinodol Valley.
Table 1 Optimal set of mean susceptibility values for the definition of the susceptibility classes. Validation
Table 1 Optimal set of mean susceptibility values for the definition of the susceptibility classes. Validation
internet news (Battistini et al., 2013) and admisitrative reports (Rosi et al., 2015). Figure 2 Hazard matrix combining rainfall rates and susceptibility levels into hazard classes Each landslide was associated to the rainfall rate registered by the threshold system during the day of its occurrence and to the susceptibility value of the spatial unit where it is located. After that, it was possible to simulate the hazard classes that would have been associated to each landslide if the dynamic matrix was active at that time.
internet news (Battistini et al., 2013) and admisitrative reports (Rosi et al., 2015). Figure 2 Hazard matrix combining rainfall rates and susceptibility levels into hazard classes Each landslide was associated to the rainfall rate registered by the threshold system during the day of its occurrence and to the susceptibility value of the spatial unit where it is located. After that, it was possible to simulate the hazard classes that would have been associated to each landslide if the dynamic matrix was active at that time.
Figure 3 Classification of the sub-municipality units in Si, S2, and S3 categories, according to their mean susceptibility This static dataset that can be combined with the dynamic information of the rainfall rate registered (or expected, in case of rainfall forecasts) in each alert zone. Depending on the observed combination of susceptibility level and rainfall rate, the spatial units will be associated to distinct hazard levels presented in Tab. 1). The res updated whenever a rainfal one alert zone. For the sak as per the hazard matrix ult is a dynamic map that is rate changes over at least e of simplicity, we call this spatial aggregation of t aggregation”. he outputs “municipality
Figure 3 Classification of the sub-municipality units in Si, S2, and S3 categories, according to their mean susceptibility This static dataset that can be combined with the dynamic information of the rainfall rate registered (or expected, in case of rainfall forecasts) in each alert zone. Depending on the observed combination of susceptibility level and rainfall rate, the spatial units will be associated to distinct hazard levels presented in Tab. 1). The res updated whenever a rainfal one alert zone. For the sak as per the hazard matrix ult is a dynamic map that is rate changes over at least e of simplicity, we call this spatial aggregation of t aggregation”. he outputs “municipality
Figure 4 Representation of different output aggregations of the warning system for the day 28-12-2017 (validation period): a) is the original configuration providing warnings at the alert zone level; b) is the output proposed by Segoni et al. (2018ba), which is based on 100m x 100m pixels; c) sub-municipalities aggregation proposed in this work
Figure 4 Representation of different output aggregations of the warning system for the day 28-12-2017 (validation period): a) is the original configuration providing warnings at the alert zone level; b) is the output proposed by Segoni et al. (2018ba), which is based on 100m x 100m pixels; c) sub-municipalities aggregation proposed in this work
Figure 1 Physical model for static actions: 1-tensiometers, 2-pore pressure transducers, 3-strain gauges, 4-accelerometers, 5-rainfall simulator (sprinkler system), 6-high speed cameras, 7-terrestrial laser scanner, 8-infrared camera Because of differences in main triggering factors as landslide causes, physical model will be designed for two different actions - one model for static actions (Fig. 1) and one for seismic actions (Fig. 2). Methodology of the Project research consist of the following phases: i) design, construction and testing of the platform for a landslide model; ii) installation of the measuring equipment; iii) construction of slope model; iv) testing a model in static and seismic conditions (with and without remediation measures); v) analysis of measured data and comparison with results of numerical simulations; vi) calibration of equipment and improvement of the model; and lastly vii) reiteration of the same_ phases of testing. Although it would possible to use some of developed rainfall simulators (Iserloh et al. 2012; Lora et al. 2013); there is necessity for developing of rainfall simulator that will be adjusted to the rainfall intensities characteristic for precipitation events in Croatia. Construction of rainfall simulator will include ordinary elements usually used for watering plants and will have the ability to control intensity, flow, uniformity of wetting and time of rainfall simulation. Rainf. all simulator will consist of system of sprinklers with different types of nozzles.
Figure 1 Physical model for static actions: 1-tensiometers, 2-pore pressure transducers, 3-strain gauges, 4-accelerometers, 5-rainfall simulator (sprinkler system), 6-high speed cameras, 7-terrestrial laser scanner, 8-infrared camera Because of differences in main triggering factors as landslide causes, physical model will be designed for two different actions - one model for static actions (Fig. 1) and one for seismic actions (Fig. 2). Methodology of the Project research consist of the following phases: i) design, construction and testing of the platform for a landslide model; ii) installation of the measuring equipment; iii) construction of slope model; iv) testing a model in static and seismic conditions (with and without remediation measures); v) analysis of measured data and comparison with results of numerical simulations; vi) calibration of equipment and improvement of the model; and lastly vii) reiteration of the same_ phases of testing. Although it would possible to use some of developed rainfall simulators (Iserloh et al. 2012; Lora et al. 2013); there is necessity for developing of rainfall simulator that will be adjusted to the rainfall intensities characteristic for precipitation events in Croatia. Construction of rainfall simulator will include ordinary elements usually used for watering plants and will have the ability to control intensity, flow, uniformity of wetting and time of rainfall simulation. Rainf. all simulator will consist of system of sprinklers with different types of nozzles.
Table 1 List of the most significant historical earthquakes in the Rijeka Region (modified according to Herak et al. 2017, 2018). The intensity and damage are described according to Medvedev-Sponheuer-Karnikov (MSK) scale. The most of existing researches, that studied landslide initiation and motion caused by an earthquake, used shaking tables that induce vibration corresponding with natural or artificial earthquake seismograms and accelerograms. The main goal of these studies was determination of seismic slope behavior or seismic response and failure of slope material (e.g. Wang and Lin, 2011; Fan et al. 2016).
Table 1 List of the most significant historical earthquakes in the Rijeka Region (modified according to Herak et al. 2017, 2018). The intensity and damage are described according to Medvedev-Sponheuer-Karnikov (MSK) scale. The most of existing researches, that studied landslide initiation and motion caused by an earthquake, used shaking tables that induce vibration corresponding with natural or artificial earthquake seismograms and accelerograms. The main goal of these studies was determination of seismic slope behavior or seismic response and failure of slope material (e.g. Wang and Lin, 2011; Fan et al. 2016).
Figure 2 Physical model for seismic actions: 1-tensiometers, 2-pore pressure transducers, 3-strain gauges, 4-accelerometers, 5-rainfall simulator (sprinkler system), 6-high speed cameras, 7-biaxial shaking tables Seismic impulses will be induced by a pair of shaking platforms (Quanser STI-II biaxial shaking platforms) commonly used for structures testing under cyclic loading in the Laboratory of structures at the Faculty of Civil Engineering University of Rijeka. The dynamic model platform is designed according to the limitations that arise from shaking tables’ characteristics (dimensions and mass of testing object). During the testing, the pair of shaking platforms will be synchronized for joint dynamic action (shaking) in direction of the model slope.
Figure 2 Physical model for seismic actions: 1-tensiometers, 2-pore pressure transducers, 3-strain gauges, 4-accelerometers, 5-rainfall simulator (sprinkler system), 6-high speed cameras, 7-biaxial shaking tables Seismic impulses will be induced by a pair of shaking platforms (Quanser STI-II biaxial shaking platforms) commonly used for structures testing under cyclic loading in the Laboratory of structures at the Faculty of Civil Engineering University of Rijeka. The dynamic model platform is designed according to the limitations that arise from shaking tables’ characteristics (dimensions and mass of testing object). During the testing, the pair of shaking platforms will be synchronized for joint dynamic action (shaking) in direction of the model slope.
Materials and remediation Table 2 Measuring equipment in the model. It was planned to include three main landslide models and their testing in static and dynamic conditions without and with applied remediation measures. The first model will be the simplest one and the model complexity will rise through the upcoming phases and steps of research. The basic model will use sandy soil because o relatively simple behavior of infiltration process and failure triggering and it will be fast and easy to reach the critical stability state. During the establishment of the slope model the scaling procedure will be tested and defined. Model will serve its main purpose to test the functionality of the designed platform models, embedded equipment and planned testing procedures. In the next phases of the Project, more complex soil materials will be built in the models, ranging from silty to clayey soil. These soil materials will have an increase in shear strength in unsaturated conditions while through infiltration they will lose shear strength due to reduction in suction and rise of pore pressures until the slope failure. The soil materials used for slope models will be
Materials and remediation Table 2 Measuring equipment in the model. It was planned to include three main landslide models and their testing in static and dynamic conditions without and with applied remediation measures. The first model will be the simplest one and the model complexity will rise through the upcoming phases and steps of research. The basic model will use sandy soil because o relatively simple behavior of infiltration process and failure triggering and it will be fast and easy to reach the critical stability state. During the establishment of the slope model the scaling procedure will be tested and defined. Model will serve its main purpose to test the functionality of the designed platform models, embedded equipment and planned testing procedures. In the next phases of the Project, more complex soil materials will be built in the models, ranging from silty to clayey soil. These soil materials will have an increase in shear strength in unsaturated conditions while through infiltration they will lose shear strength due to reduction in suction and rise of pore pressures until the slope failure. The soil materials used for slope models will be
Figure 3 Physical model with different remediation constructions — a) retaining wall; b) pile wall; c) buttressing with drainage systems.
Figure 3 Physical model with different remediation constructions — a) retaining wall; b) pile wall; c) buttressing with drainage systems.
Figure 1 (a) Geographical position of the Vinodol Valley in Croatia, and the hillshade map of the northwestern part of the Valley, derived from the 1 m LiDAR DTM. (b) A detail from the Engineering geological map of the nort-western part of the Vinodol Valley (Domlija, 2018), with the soil sampling site. Photo (c) was taken during the sampling of eluvial deposits from the landslide body. bedrock, and their composition varies along the entire study area, depending on lithological composition of a local bedrock. Previous studies showed that eluvial deposits in the Vinodol Valley are mainly composed of the low plasticity clays, high plasticity clays, low plasticity silts to clayey gravels (Pajalié et al. 2017; Domlija 2018). Based on the visual interpretation of 1x1m LiDAR imagery, there are 54 small debris slides identified in the NW part of the Vinodol Valley, with an average landslide area of 750 m? (Domlija 2018). However, the debris slide from which the soil samples were taken in this study (Fig. 1c) occurred after the airborne laser scanning was performed in March 2012, and the landslide phenomenon was identified in the field. The landslide is very small, with the total length of approx. 12 m, and the maximum width of approx. 5 meters. The eluvial deposits (Fig. 1b) cover an area of 2.26 km? in the NW part of the Vinodol Valley (Domlija, 2018). These deposits originate from weathering of soft flysch
Figure 1 (a) Geographical position of the Vinodol Valley in Croatia, and the hillshade map of the northwestern part of the Valley, derived from the 1 m LiDAR DTM. (b) A detail from the Engineering geological map of the nort-western part of the Vinodol Valley (Domlija, 2018), with the soil sampling site. Photo (c) was taken during the sampling of eluvial deposits from the landslide body. bedrock, and their composition varies along the entire study area, depending on lithological composition of a local bedrock. Previous studies showed that eluvial deposits in the Vinodol Valley are mainly composed of the low plasticity clays, high plasticity clays, low plasticity silts to clayey gravels (Pajalié et al. 2017; Domlija 2018). Based on the visual interpretation of 1x1m LiDAR imagery, there are 54 small debris slides identified in the NW part of the Vinodol Valley, with an average landslide area of 750 m? (Domlija 2018). However, the debris slide from which the soil samples were taken in this study (Fig. 1c) occurred after the airborne laser scanning was performed in March 2012, and the landslide phenomenon was identified in the field. The landslide is very small, with the total length of approx. 12 m, and the maximum width of approx. 5 meters. The eluvial deposits (Fig. 1b) cover an area of 2.26 km? in the NW part of the Vinodol Valley (Domlija, 2018). These deposits originate from weathering of soft flysch
where wg represents the area of cyclic curve, and the w, represents the area of the triangle (Fig. Figure 2). The resonant column/torsional shear system consists of several main components. The system is computer operated through the Dynator computer software and main control unit (Fig.2a). Maximal capacity of the cell pressure and pressure transducers (pore water and back pressure) is 1000 kPa. A sample is placed in triaxial cell
where wg represents the area of cyclic curve, and the w, represents the area of the triangle (Fig. Figure 2). The resonant column/torsional shear system consists of several main components. The system is computer operated through the Dynator computer software and main control unit (Fig.2a). Maximal capacity of the cell pressure and pressure transducers (pore water and back pressure) is 1000 kPa. A sample is placed in triaxial cell
Table 2 Summary of soil classification tests Stress reduction curve and damping
Table 2 Summary of soil classification tests Stress reduction curve and damping
Table 1 Summary of small strain cyclic tests Results
Table 1 Summary of small strain cyclic tests Results
Figure 3 Resonant column/Torsional shear system: (a) main control unit, (b) triaxial cell, (c) coils with electromagnet, (d) LVDT’s, (e) sample pedestal, (f) loading cap, (g) back-pressure transducer and (h)volume control.
Figure 3 Resonant column/Torsional shear system: (a) main control unit, (b) triaxial cell, (c) coils with electromagnet, (d) LVDT’s, (e) sample pedestal, (f) loading cap, (g) back-pressure transducer and (h)volume control.
Figure 5 Damping of soil from eluvial deposit in the Vinodol Valley
Figure 5 Damping of soil from eluvial deposit in the Vinodol Valley
Figure 4 G/Gmax reduction curve of soil from eluvial deposit in the Vinodol Valley of shear module very close to the value of Gnq,. For the purpose of these tests the first value of the shear modulus obtained form RC Chirp tests was used as the Gq, value value obtained for the excitation value of 0.001 V). The atter obtained shear modulus from both resonant column and torsional shear test were referenced to the initia value. The result of these two tests are presented in Fig Figure 4. The dashed lines represent the values of shear strength reduction curves for plasticity index of 15% and 30%, respectively, commonly used in geotechnica earthquake engineering (e.g. Vucetic and Dobry 1991; Kramer 1996). The results of strength reduction obtained from resonant column test are plotted with circular markers while the torsional stress results are presented with triangles.
Figure 4 G/Gmax reduction curve of soil from eluvial deposit in the Vinodol Valley of shear module very close to the value of Gnq,. For the purpose of these tests the first value of the shear modulus obtained form RC Chirp tests was used as the Gq, value value obtained for the excitation value of 0.001 V). The atter obtained shear modulus from both resonant column and torsional shear test were referenced to the initia value. The result of these two tests are presented in Fig Figure 4. The dashed lines represent the values of shear strength reduction curves for plasticity index of 15% and 30%, respectively, commonly used in geotechnica earthquake engineering (e.g. Vucetic and Dobry 1991; Kramer 1996). The results of strength reduction obtained from resonant column test are plotted with circular markers while the torsional stress results are presented with triangles.
Blue lines on Fig. 4 and Fig. 5 represents the proposed approximation curves for G/Gmq, reduction and soil damping, respectively. Those two proposed curves are plotted on Fig. 6 and can be used for geotechnical calculations. Figure 6 Proposed G/Gimaqx and damping curve for soil from eluvial deposit in the Vinodol Valley
Blue lines on Fig. 4 and Fig. 5 represents the proposed approximation curves for G/Gmq, reduction and soil damping, respectively. Those two proposed curves are plotted on Fig. 6 and can be used for geotechnical calculations. Figure 6 Proposed G/Gimaqx and damping curve for soil from eluvial deposit in the Vinodol Valley
Table 1 Forecast costs of geotechnical works, documentation making and remediation works on the processed terrain. Total remediation costs are given in kuna.
Table 1 Forecast costs of geotechnical works, documentation making and remediation works on the processed terrain. Total remediation costs are given in kuna.
Category IV - Unstable slopes are the landslide areas with the existence of failure planes or zones along which the shear strength parameters are on residual values (active and old sliding or registered failure zones in slopes of the tectonic origin). The detailed geotechnical investigations will determine the conditions for previous remediation of the terrain which can comprise complex remediation measures (drainage, filling, retaining structures and similar). The terrain remediation can be performed so that the planned buildings make the part of the remediation measures so that the conditions of the terrain remediation contain special geotechnical conditions for building. With the geological structure and categorization of the terrain the landslides and erosions in the field have been described. Conclusions
Category IV - Unstable slopes are the landslide areas with the existence of failure planes or zones along which the shear strength parameters are on residual values (active and old sliding or registered failure zones in slopes of the tectonic origin). The detailed geotechnical investigations will determine the conditions for previous remediation of the terrain which can comprise complex remediation measures (drainage, filling, retaining structures and similar). The terrain remediation can be performed so that the planned buildings make the part of the remediation measures so that the conditions of the terrain remediation contain special geotechnical conditions for building. With the geological structure and categorization of the terrain the landslides and erosions in the field have been described. Conclusions
igure 1 (a) The geographical location of the Vinodol Valley; (b) a detail from the Engineering geological map of the central part of the ‘inodol Valley (Domlija, 2018). Locations of individual soil sampling sites are also presented. Photographs of debris slides located in he nortwestern part (c), and in the central part (from (d) to (1)) of the Vinodol Valley. Investigated debris slides are labelled, ccording to the soil samples labels. Croatia (Fig. 1a). The Valley (64.57 km?) has complex geological and morphological conditions (Bla3kovi¢ 1999), and an elongated shape, with a length of approx. 22 km. Due to the specific topography, the Vinodol Valley can be divided into three main parts (Domlija 2018): the north-western (NW), the central, and the south-eastern (SE) part. The NW and the central parts of the Vinodol Valley belong to the Dubra¢ina River Basin (43.22 km”), while the SE part belongs to the Suha Ri¢ina River Basin (21,35 km?). The area is predominantly rural, with more The prevailing elevations range from 100 to 200 m a.s.l., and the prevailing slope angles range between 5° and 20°. The Valley flanks are composed of Cretaceous and Paleogene carbonate rocks (limestone, and dolomites), while the lower parts and the bottom of the Valley are composed of flysch bedrock (marls, siltstones and sandstones in alternation), in a synclinal position (BlaSkovic 1999).
igure 1 (a) The geographical location of the Vinodol Valley; (b) a detail from the Engineering geological map of the central part of the ‘inodol Valley (Domlija, 2018). Locations of individual soil sampling sites are also presented. Photographs of debris slides located in he nortwestern part (c), and in the central part (from (d) to (1)) of the Vinodol Valley. Investigated debris slides are labelled, ccording to the soil samples labels. Croatia (Fig. 1a). The Valley (64.57 km?) has complex geological and morphological conditions (Bla3kovi¢ 1999), and an elongated shape, with a length of approx. 22 km. Due to the specific topography, the Vinodol Valley can be divided into three main parts (Domlija 2018): the north-western (NW), the central, and the south-eastern (SE) part. The NW and the central parts of the Vinodol Valley belong to the Dubra¢ina River Basin (43.22 km”), while the SE part belongs to the Suha Ri¢ina River Basin (21,35 km?). The area is predominantly rural, with more The prevailing elevations range from 100 to 200 m a.s.l., and the prevailing slope angles range between 5° and 20°. The Valley flanks are composed of Cretaceous and Paleogene carbonate rocks (limestone, and dolomites), while the lower parts and the bottom of the Valley are composed of flysch bedrock (marls, siltstones and sandstones in alternation), in a synclinal position (BlaSkovic 1999).
Figure 3 Particle size distribution in soil samples from landslide deposits in the Dubra¢ina River Basin. The percentage of the coarse-grained soil sample component is the highest for the sample S7 (Fig. 3). This sample contains almost the equal amount of gravel (19.78 %) and sand (18.62 %) size particles (Pr8a 2018). Sample S8 contains 15.18 % of coarse-grained particles, with the 13.33 % of sand, and 1.85 % of gravel size particles. Other tested soil samples contain less than 10 % of coarse- grained component (Fig.3), with the sand size particles prevailing in samples Si, S3, S4, S5, S6, and Sg (Pra 2018).
Figure 3 Particle size distribution in soil samples from landslide deposits in the Dubra¢ina River Basin. The percentage of the coarse-grained soil sample component is the highest for the sample S7 (Fig. 3). This sample contains almost the equal amount of gravel (19.78 %) and sand (18.62 %) size particles (Pr8a 2018). Sample S8 contains 15.18 % of coarse-grained particles, with the 13.33 % of sand, and 1.85 % of gravel size particles. Other tested soil samples contain less than 10 % of coarse- grained component (Fig.3), with the sand size particles prevailing in samples Si, S3, S4, S5, S6, and Sg (Pra 2018).
Figure 2 Soil samples during the laboratory testing methods: (a) the wet sample prepared for the wet sieve analysis; (b) the fine- grained soil sample components during the hydrometer analysis; (c) the sample prepared for the liquid-limit test; and (d) the samples after the plastic-limit test.
Figure 2 Soil samples during the laboratory testing methods: (a) the wet sample prepared for the wet sieve analysis; (b) the fine- grained soil sample components during the hydrometer analysis; (c) the sample prepared for the liquid-limit test; and (d) the samples after the plastic-limit test.
Figure 4 Plasticity chart of soil samples from landslide deposits in the Dubra¢ina River Basin. All tested soil samples are displayed above the A-line in the plasticity chart (Fig. 4). Six samples (Si, $3, S4, S5, S7, and Sg) are displayed in a domain of intermediate plasticity clay (CII according to the ESCS Scheme), with samples S4 and S5 having the same LL and PI values. Two samples (S2, and S8) are high plasticity clays (CIH), and one sample (S6) is low plasticity clay (CIL).
Figure 4 Plasticity chart of soil samples from landslide deposits in the Dubra¢ina River Basin. All tested soil samples are displayed above the A-line in the plasticity chart (Fig. 4). Six samples (Si, $3, S4, S5, S7, and Sg) are displayed in a domain of intermediate plasticity clay (CII according to the ESCS Scheme), with samples S4 and S5 having the same LL and PI values. Two samples (S2, and S8) are high plasticity clays (CIH), and one sample (S6) is low plasticity clay (CIL).
Figure 5 Activity of clay minerals in soil samples from landslide deposits in the Dubra¢ina River Basin.
Figure 5 Activity of clay minerals in soil samples from landslide deposits in the Dubra¢ina River Basin.
Photo 1 a) Satellite image of the landslide. b) Displacement of the road. c) Local stabilization of the road. d) Slide after the execution of the primary stabilization. determining the bearing capacity of anchors in seismic conditions.
Photo 1 a) Satellite image of the landslide. b) Displacement of the road. c) Local stabilization of the road. d) Slide after the execution of the primary stabilization. determining the bearing capacity of anchors in seismic conditions.
Table 1 Values of the calculation parameters according to Regulation 12
Table 1 Values of the calculation parameters according to Regulation 12
Table 2 Values of the calculation parameters according to Eurocode 7 Underground water in the area of the investigated site has been identified at different levels in all test pits. Underground water is accumulated by rainwater infiltration, by the surrounding slopes and in some places the water is supplied by leakages from the water supply network. The seasonal fluctuation of the water level for this area varies. For the purpose of calculation, it is
Table 2 Values of the calculation parameters according to Eurocode 7 Underground water in the area of the investigated site has been identified at different levels in all test pits. Underground water is accumulated by rainwater infiltration, by the surrounding slopes and in some places the water is supplied by leakages from the water supply network. The seasonal fluctuation of the water level for this area varies. For the purpose of calculation, it is
Table 3 Minimum acceptable factors of safety Typically, the designers in Bulgaria together with the slope stability analysis use also the subgrade reaction method (SRM) for determining the shear strength of a structure (pile caps, piles and anchors). In the table 4 are shown the partial coefficients according to Riz and DA2 at STR ultimate limit states: Table 4 Partial factors on actions or the effects of actions
Table 3 Minimum acceptable factors of safety Typically, the designers in Bulgaria together with the slope stability analysis use also the subgrade reaction method (SRM) for determining the shear strength of a structure (pile caps, piles and anchors). In the table 4 are shown the partial coefficients according to Riz and DA2 at STR ultimate limit states: Table 4 Partial factors on actions or the effects of actions
Seismic forces
Seismic forces
The reinforcement has anchors and bored (Figure 1 concrete wall, taking up the load landslide anchors, is also a retaining support wall t in the anchors and Piles are at the body and has been piles with pi foot of the transmitting executed with a t hat transmits the pressure e ca the the pile caps for t been executed with an ps with framed action andslide. The reinforced from a certain area of the forces on the piles and hickness of 0.80 m. It he pile reinforcement. bored cast-in-place concrete piles, with a round cross-section D6oo, with a distance between axes of 1.50 m. The piles are installed in two parallel rows, joined with a pile cap. The layout is of quincunx double-row piles. The length of the piles is 9.00 m. There are passive single bar anchors. The designers have preferred to execute IBO
The reinforcement has anchors and bored (Figure 1 concrete wall, taking up the load landslide anchors, is also a retaining support wall t in the anchors and Piles are at the body and has been piles with pi foot of the transmitting executed with a t hat transmits the pressure e ca the the pile caps for t been executed with an ps with framed action andslide. The reinforced from a certain area of the forces on the piles and hickness of 0.80 m. It he pile reinforcement. bored cast-in-place concrete piles, with a round cross-section D6oo, with a distance between axes of 1.50 m. The piles are installed in two parallel rows, joined with a pile cap. The layout is of quincunx double-row piles. The length of the piles is 9.00 m. There are passive single bar anchors. The designers have preferred to execute IBO
Table 6. Coefficients of stability using retaining structures acc. Eurocode 7 (Fs = 1). Additionally, the terrain was modeled and investigated using the circular-cylindrical slip surface method in accordance with the Eurocode 7 DA 3 method. The safety factor for the most unfavourable sliding surface (the minimum value) Fs should fulfill the condition Fs > 1. Summarized results for the obtained coefficients are given in table 5 (according to Regulation 12) and in table 6 (according to Eurocode 7). Sample solutions are shown in Fig. 2 and Fig. 3.
Table 6. Coefficients of stability using retaining structures acc. Eurocode 7 (Fs = 1). Additionally, the terrain was modeled and investigated using the circular-cylindrical slip surface method in accordance with the Eurocode 7 DA 3 method. The safety factor for the most unfavourable sliding surface (the minimum value) Fs should fulfill the condition Fs > 1. Summarized results for the obtained coefficients are given in table 5 (according to Regulation 12) and in table 6 (according to Eurocode 7). Sample solutions are shown in Fig. 2 and Fig. 3.
Table 5 Coefficients of stability using retaining structures acc. Regulation 12.
Table 5 Coefficients of stability using retaining structures acc. Regulation 12.
Figure 2 Analisys as per the circular-cylindrical slip surface method of Bishop for local and global stability
Figure 2 Analisys as per the circular-cylindrical slip surface method of Bishop for local and global stability
Figure 3 Analisys as per the specific slip surface method of Jambu
Figure 3 Analisys as per the specific slip surface method of Jambu
In order to ensure stability during exploitation a stabilization reinforcement has been implemented. According to Regulation 12, considering the accepted values of the soil parameters, the force of the landslide pressure can be determined by the formula: Figure 4 Calculations scheme for: a. basic combination of loads; 6. particular combination of loads
In order to ensure stability during exploitation a stabilization reinforcement has been implemented. According to Regulation 12, considering the accepted values of the soil parameters, the force of the landslide pressure can be determined by the formula: Figure 4 Calculations scheme for: a. basic combination of loads; 6. particular combination of loads
Figure 5 Solution as per 3PM of Tower (basic combination of loads): a. model; b. Reactions in the springs; c. Deformation scheme Smax=5,05 cm < xrp = 10 cm according to Regulation 12.
Figure 5 Solution as per 3PM of Tower (basic combination of loads): a. model; b. Reactions in the springs; c. Deformation scheme Smax=5,05 cm < xrp = 10 cm according to Regulation 12.
Figure 6 Model for testing anchors Table 5 Correction coefficients yeq2 for reducing the friction in determining the bearing capacity of piles in seismic conditions [34]. After analyzing results from the models, the following conclusions were made, about sand with different water content: Conclusion exerted by loading systems. The device is isolated from the building by vibration isolators. The device is designed to test the anchors in terms of static and dynamic conditions and the scope of testing is: ground acceleration — (0+0.4)g; displacement of the device - (2+3) cm; frequency - (2+12) Hz; overburden pressure - up to 4m soil layers; anchor force up to 10 KN.
Figure 6 Model for testing anchors Table 5 Correction coefficients yeq2 for reducing the friction in determining the bearing capacity of piles in seismic conditions [34]. After analyzing results from the models, the following conclusions were made, about sand with different water content: Conclusion exerted by loading systems. The device is isolated from the building by vibration isolators. The device is designed to test the anchors in terms of static and dynamic conditions and the scope of testing is: ground acceleration — (0+0.4)g; displacement of the device - (2+3) cm; frequency - (2+12) Hz; overburden pressure - up to 4m soil layers; anchor force up to 10 KN.
Photo 5 The landslide, the retaining wall and the aquapark The article has been aimed to present a practical solution for stabilization of a landslide in Bulgaria, in compliance with the current norms. The presented dependence on the anchor strength reduction is one possible, though simple solution to the problem. An importance of the exact position of the strengthening structure was shown. References
Photo 5 The landslide, the retaining wall and the aquapark The article has been aimed to present a practical solution for stabilization of a landslide in Bulgaria, in compliance with the current norms. The presented dependence on the anchor strength reduction is one possible, though simple solution to the problem. An importance of the exact position of the strengthening structure was shown. References
Figure 1 Landslide susceptibility map of the municipality of Zepée (blue color-Water surfaces, green-low susceptibility to landslides yellow-medium susceptibility to landslides, orange- high susceptibility to landslides, red- very high susceptibility to landslides) 3. Creation of a reclassified map of the land cover - it is based on the map of the land cover that is based on the European database on bio-physical land use CORINE Land Cover (CLC), made according to CORINE standards that define the output scale of 1: 100000, a minimum mapping area of 25 ha and the minimum polygon width
Figure 1 Landslide susceptibility map of the municipality of Zepée (blue color-Water surfaces, green-low susceptibility to landslides yellow-medium susceptibility to landslides, orange- high susceptibility to landslides, red- very high susceptibility to landslides) 3. Creation of a reclassified map of the land cover - it is based on the map of the land cover that is based on the European database on bio-physical land use CORINE Land Cover (CLC), made according to CORINE standards that define the output scale of 1: 100000, a minimum mapping area of 25 ha and the minimum polygon width
Figure 2 Reclassified maps for derivation of final map (from the left - reclassified map of terrain slope, reclassified map of engineering geological units, reclassified map of terrain cover)
Figure 2 Reclassified maps for derivation of final map (from the left - reclassified map of terrain slope, reclassified map of engineering geological units, reclassified map of terrain cover)
a a Figure 1.Situation of landslide-topographic map Stari Teotak scale 1:25000 The slope of the surrounding area of the subject location has an exposition towards the east, and the inclination of the slope is 10° (Fig.1) The site is located in the part of the terrain that builds up the upper Miocene sediments (M;') represented by clay, sandstones, marls and subordinate limestones (Fig.2). The dip of sediments is towards the northeast at an angle from 20 to 35 degrees.
a a Figure 1.Situation of landslide-topographic map Stari Teotak scale 1:25000 The slope of the surrounding area of the subject location has an exposition towards the east, and the inclination of the slope is 10° (Fig.1) The site is located in the part of the terrain that builds up the upper Miocene sediments (M;') represented by clay, sandstones, marls and subordinate limestones (Fig.2). The dip of sediments is towards the northeast at an angle from 20 to 35 degrees.
Figure 2 Basic geological map of the list Zvornik scale 1100000 To remedy the landslide, detailed engineering- geological and geomechanical tests were carried out.
Figure 2 Basic geological map of the list Zvornik scale 1100000 To remedy the landslide, detailed engineering- geological and geomechanical tests were carried out.
Based on the results, a landslide remediation project was done. In total, four exploratory boreholes marked B-1 to B- 4 were drilled with taking samples that were processed aboratory to obtain the necessary parameters for the calculation. Along with the drilling, the standard penetration test was carried out. At the indicated location the level of the underground water wasn't registered, while the groundwater level was registered only in the borehole B-4 at a depth of 3.0 m and after 24 hours and the groundwater level at a depth of 3.30 m. On the treated site the geological substrate is made of gray layered marls with dip to the northeast with an angle of 20-35°. In geomechanical boreholes, gray marls were drilled in a well B-2 at a depth of 4.2 m and B-4 at a depth of 4.4 m. On this location, two different types of genetic covers are separated in eluvial-diluvial (ed) and colluvial covers, which are represented by sandy-dusty to marl clay. The thickness of the covers is up to 4.5 meters. Figure 3 The landslide scar
Based on the results, a landslide remediation project was done. In total, four exploratory boreholes marked B-1 to B- 4 were drilled with taking samples that were processed aboratory to obtain the necessary parameters for the calculation. Along with the drilling, the standard penetration test was carried out. At the indicated location the level of the underground water wasn't registered, while the groundwater level was registered only in the borehole B-4 at a depth of 3.0 m and after 24 hours and the groundwater level at a depth of 3.30 m. On the treated site the geological substrate is made of gray layered marls with dip to the northeast with an angle of 20-35°. In geomechanical boreholes, gray marls were drilled in a well B-2 at a depth of 4.2 m and B-4 at a depth of 4.4 m. On this location, two different types of genetic covers are separated in eluvial-diluvial (ed) and colluvial covers, which are represented by sandy-dusty to marl clay. The thickness of the covers is up to 4.5 meters. Figure 3 The landslide scar
Figure 4 Damaged local road
Figure 4 Damaged local road
Figure 5 Dumped the retaining wall next to the house
Figure 5 Dumped the retaining wall next to the house
Figure 7 New plastic pipes instead of crumpled
Figure 7 New plastic pipes instead of crumpled
Figure 9 Map with the borders of landslide In engineering and geological view, the slope with the landslide is unstable since close to this landslide has emerged several new landslides that threaten to endanger several residential buildings. For these reasons, it was necessary to approach as soon as possible the repair of landslides to prevent its further spread and thus the vulnerability of other structures down the slope. In the investigated site there was developed a shallow landslide with a sliding surface at a depth of 2.2 m Fig 9-Fig 10).
Figure 9 Map with the borders of landslide In engineering and geological view, the slope with the landslide is unstable since close to this landslide has emerged several new landslides that threaten to endanger several residential buildings. For these reasons, it was necessary to approach as soon as possible the repair of landslides to prevent its further spread and thus the vulnerability of other structures down the slope. In the investigated site there was developed a shallow landslide with a sliding surface at a depth of 2.2 m Fig 9-Fig 10).
Figure 8 Temporary road repair
Figure 8 Temporary road repair
Morphometric characteristics of the complete ndslide:
Morphometric characteristics of the complete ndslide:
volume, type of landslide), causes and mechanism of moving of earth masses from the engineering and geological aspect, proposed sanitary measures are consisted of: making two retaining structures and drainage systems above retaining structures and a drainage system in the form of fish bones to collect and take off surface and groundwater.
volume, type of landslide), causes and mechanism of moving of earth masses from the engineering and geological aspect, proposed sanitary measures are consisted of: making two retaining structures and drainage systems above retaining structures and a drainage system in the form of fish bones to collect and take off surface and groundwater.
Figure 12 Retaining wall on counterforts References
Figure 12 Retaining wall on counterforts References
Figure 1 Marls and sandstones in alternation | sediments (M31) - represented by ceratites limestones, marl clays, marls, and sandstones less frequently conglomerates. There is the frequent alteration of marls and sandstones in the field (Fig.1.) The orientation of the sediments is north-northeast, which is favorable from the aspect of stability because they are opposite of the slope inclination. The measured elements of dip and strike of the layer are Eds = 10/60 and Eds = 20/50. At this location during exploratory drilling, groundwater levels were measured and monitored in exploration boreholes. On the slope during the rainfall, surface currents form ditches.
Figure 1 Marls and sandstones in alternation | sediments (M31) - represented by ceratites limestones, marl clays, marls, and sandstones less frequently conglomerates. There is the frequent alteration of marls and sandstones in the field (Fig.1.) The orientation of the sediments is north-northeast, which is favorable from the aspect of stability because they are opposite of the slope inclination. The measured elements of dip and strike of the layer are Eds = 10/60 and Eds = 20/50. At this location during exploratory drilling, groundwater levels were measured and monitored in exploration boreholes. On the slope during the rainfall, surface currents form ditches.
Figure 2 Sediment erosion on the slope
Figure 2 Sediment erosion on the slope
Figure 4 Rock embankment Methods to 3.3 m B-10 to 2, 30 m. Based on exploratory drilling it was found that the terrain was made of humus, sandy-dusty clays, mar! clays of different colors (yellow- brown, gray, light brown). These sediments form eluvial- diluvial and colluvial deposits while marls, sandstones, and conglomerates represent the substrate. The sediments of the substrate present the marls that dip at depths of 2.40 to 4.0 meters and the sandstones at a depth of 3.80 m. Also, it was analyzed by the depth and groundwater levels in 22 dug wells in the field (Fig.5). To determine the geomechanical properties of the soil from the exploratory wells, samples of the material for the The exploration of the landslide was carried out by engineering-geological exploratory works, geological mapping, and laboratory sample testing. On the basis of the investigations carried out, an opinion was given on the soil properties and the method of slope drainage. To define the geological, engineering-geological, and geomechanical characteristics of the terrain, ten exploratory boreholes were drilled. The B-1 well was drilled to 3.30 m, B-2 to 6.0 m; B-3 to 4.3 m; B-4 to 4.0 m; B-5 to 3.5 m, B-6 to 3.3 m, B-7 to 3.6 m, B-8 to 4.0 m, B-9 abundant, unresolved drainage of surface water from the roads and heavy rainfall. Numerous landslide scars have been registered below the road at the top of the slope (Fig. 3.). In the upper part of the slope as a temporary remediation measure, a rock embankment has been used to stabilize road communication which on the other hand, serves as surface drainage (Fig. 4.).
Figure 4 Rock embankment Methods to 3.3 m B-10 to 2, 30 m. Based on exploratory drilling it was found that the terrain was made of humus, sandy-dusty clays, mar! clays of different colors (yellow- brown, gray, light brown). These sediments form eluvial- diluvial and colluvial deposits while marls, sandstones, and conglomerates represent the substrate. The sediments of the substrate present the marls that dip at depths of 2.40 to 4.0 meters and the sandstones at a depth of 3.80 m. Also, it was analyzed by the depth and groundwater levels in 22 dug wells in the field (Fig.5). To determine the geomechanical properties of the soil from the exploratory wells, samples of the material for the The exploration of the landslide was carried out by engineering-geological exploratory works, geological mapping, and laboratory sample testing. On the basis of the investigations carried out, an opinion was given on the soil properties and the method of slope drainage. To define the geological, engineering-geological, and geomechanical characteristics of the terrain, ten exploratory boreholes were drilled. The B-1 well was drilled to 3.30 m, B-2 to 6.0 m; B-3 to 4.3 m; B-4 to 4.0 m; B-5 to 3.5 m, B-6 to 3.3 m, B-7 to 3.6 m, B-8 to 4.0 m, B-9 abundant, unresolved drainage of surface water from the roads and heavy rainfall. Numerous landslide scars have been registered below the road at the top of the slope (Fig. 3.). In the upper part of the slope as a temporary remediation measure, a rock embankment has been used to stabilize road communication which on the other hand, serves as surface drainage (Fig. 4.).
Figure 5 Registered dug wells on the landslide
Figure 5 Registered dug wells on the landslide
Figure 6 Layered marls and sandstones
Figure 6 Layered marls and sandstones
Figure 7 Conglomerates on the top of the ridge Based on their characteristics, marls, sandstones, and conglomerates belong to well-petrified rocks. The characteristic feature of these rocks is physical and mechanical decomposition building on thick eluvial- diluvial and slip surface covers. From the hydrogeological point of view, they are hydrogeological isolators that they have the function of water-impermeable rocks while decomposed sandstones have the role of hydrogeological collectors. According to the rock category (GN 200), these rocks are classified in category V.
Figure 7 Conglomerates on the top of the ridge Based on their characteristics, marls, sandstones, and conglomerates belong to well-petrified rocks. The characteristic feature of these rocks is physical and mechanical decomposition building on thick eluvial- diluvial and slip surface covers. From the hydrogeological point of view, they are hydrogeological isolators that they have the function of water-impermeable rocks while decomposed sandstones have the role of hydrogeological collectors. According to the rock category (GN 200), these rocks are classified in category V.
Figure 8 Engineering geological map of landslide Lisovici
Figure 8 Engineering geological map of landslide Lisovici
Table 1 Phases of remediation measures Conclusions
Table 1 Phases of remediation measures Conclusions
Figure 9 Remediation measures
Figure 9 Remediation measures
Table 1 Outline of the landslide
Table 1 Outline of the landslide
Figure1 Flow chart of Genetic Algorithm Analysis
Figure1 Flow chart of Genetic Algorithm Analysis
Figure 2 Location of borehole for groundwater observation Fig.3 shows the schematic view of the observation hole. The pipes used in groundwater level observation holes are non perforated from surface upto GL-1m depth and are perforated below GL-1m. The observation frequency was once a day.
Figure 2 Location of borehole for groundwater observation Fig.3 shows the schematic view of the observation hole. The pipes used in groundwater level observation holes are non perforated from surface upto GL-1m depth and are perforated below GL-1m. The observation frequency was once a day.
Figure 3 Schematic view of the observation hole Regarding the meteorological data, daily rainfall amount, temperature, snow depth were taken from the meteorological station located about 500 m far from landslide site.
Figure 3 Schematic view of the observation hole Regarding the meteorological data, daily rainfall amount, temperature, snow depth were taken from the meteorological station located about 500 m far from landslide site.
Table 2 Parameters obtained using Genetic Algorithm Using the parameters as mentioned in the Tab.z, the calculated value of groundwater level is shown in the Fig.5. The authors performed learning analysis using genetic algorithm and built the prediction model of groundwater level fluctuation. At that time , the authors analyzed the first month exclusively in observation data with consideration of the influence of antecedent rainfall. Tab.2 shows the values of parameters in Obs.-1.
Table 2 Parameters obtained using Genetic Algorithm Using the parameters as mentioned in the Tab.z, the calculated value of groundwater level is shown in the Fig.5. The authors performed learning analysis using genetic algorithm and built the prediction model of groundwater level fluctuation. At that time , the authors analyzed the first month exclusively in observation data with consideration of the influence of antecedent rainfall. Tab.2 shows the values of parameters in Obs.-1.
Figure 4 Observation data of groundwater level (Obs.-1), rainfall amount and snow depth
Figure 4 Observation data of groundwater level (Obs.-1), rainfall amount and snow depth
Figure 5 Calculated result Fig.5 shows the fluctuation curve of calculation data which is attributed by the rainfall and snowmelt. This reflects the response of the real situation of groundwater level in the observation hole. It is obtained that the coefficient of correlation is 0.90 between the observation data and the calculation data.
Figure 5 Calculated result Fig.5 shows the fluctuation curve of calculation data which is attributed by the rainfall and snowmelt. This reflects the response of the real situation of groundwater level in the observation hole. It is obtained that the coefficient of correlation is 0.90 between the observation data and the calculation data.
Figure 6 The observed groundwater level fluctuation and the calculated groundwater level fluctuation during snowmelt period in 2013
Figure 6 The observed groundwater level fluctuation and the calculated groundwater level fluctuation during snowmelt period in 2013
Figure 7 The observed groundwater level fluctuation and the calculated groundwater level fluctuation during snowmelt period in 2014
Figure 7 The observed groundwater level fluctuation and the calculated groundwater level fluctuation during snowmelt period in 2014
Candir Formation (TRag) includes radiolarite, intercalated claystone - limestone, claystone/siltstone, and claystone units. In general, the radiolarite unit is reddish-brown, yellowish-brown, brown, slightly hard - hard, brittle, moderate weak and weathered in places. Discontinuities in radiolarite unit have two dips: 10°-go0° which are open, matte, rough and closed; 45°-90° which are irregular and closed, 1-10 mm calcite filled and sometimes filled with clay. Claystone unit of intercalated claystone - limestone is dark gray - greenish gray-reddish brown, slightly hard - moderately hard, brittle, very weak - moderately weak strength sometimes, moderately - completely weathered in places. Limestone unit intercalated claystone — limestone is generally light gray- beige-white color, hard-mediumhard, medium strength, occasionally moderately weak strength, - slightly- occasionally moderately weathered. The intercalation of these units is observed generally as 5-40 cm limestone and 5-30 cm claystone. Discontinuities in this unit are bright, lubricous, rough, clay-filled with 10°-go°dips; the ones have1o°-45°dips are closed and 1-20 mm calcite filled. The claystone/siltstone unit is gray, greenish gray, reddish-brown, slightly hard to brittle, weak-very weak strength and partly very weathered. Sandy limestone blocks around 5-30 cm thick and hard sandstone blocks up to 10-50 cm thick are observed within the unit. Discontinuities with 20°-80° dips are bright, lubricous, rough, clay-filled and closed; discontinuities with 20°-80‘ dips are generally closed but 1-5 mm calcite and clay - silt filled in places. The claystone unit is generally gray- colored, brittle, very weak strength and completely weathered. There are hard limestone blocks up to 10 cm in size in places, in the unit. The unit is extremely folded, kneaded and sometimes brecciated; it is shale-looking. Observable discontinuities are bright, lubricous, clay- filled and have 20°-45°dips.Total Core Recovery (TCR), Rock QualityDesignation (RQD),Point Load Strength ndex (Is50), Uniaxial Compressive Strength (qu) and Unit Volume Weight (y) values of Candir formation TRac) are given in Table 2. Table 1 SPT and laboratory test results of weathered levels of Candir formation (TRa¢-Ws).
Candir Formation (TRag) includes radiolarite, intercalated claystone - limestone, claystone/siltstone, and claystone units. In general, the radiolarite unit is reddish-brown, yellowish-brown, brown, slightly hard - hard, brittle, moderate weak and weathered in places. Discontinuities in radiolarite unit have two dips: 10°-go0° which are open, matte, rough and closed; 45°-90° which are irregular and closed, 1-10 mm calcite filled and sometimes filled with clay. Claystone unit of intercalated claystone - limestone is dark gray - greenish gray-reddish brown, slightly hard - moderately hard, brittle, very weak - moderately weak strength sometimes, moderately - completely weathered in places. Limestone unit intercalated claystone — limestone is generally light gray- beige-white color, hard-mediumhard, medium strength, occasionally moderately weak strength, - slightly- occasionally moderately weathered. The intercalation of these units is observed generally as 5-40 cm limestone and 5-30 cm claystone. Discontinuities in this unit are bright, lubricous, rough, clay-filled with 10°-go°dips; the ones have1o°-45°dips are closed and 1-20 mm calcite filled. The claystone/siltstone unit is gray, greenish gray, reddish-brown, slightly hard to brittle, weak-very weak strength and partly very weathered. Sandy limestone blocks around 5-30 cm thick and hard sandstone blocks up to 10-50 cm thick are observed within the unit. Discontinuities with 20°-80° dips are bright, lubricous, rough, clay-filled and closed; discontinuities with 20°-80‘ dips are generally closed but 1-5 mm calcite and clay - silt filled in places. The claystone unit is generally gray- colored, brittle, very weak strength and completely weathered. There are hard limestone blocks up to 10 cm in size in places, in the unit. The unit is extremely folded, kneaded and sometimes brecciated; it is shale-looking. Observable discontinuities are bright, lubricous, clay- filled and have 20°-45°dips.Total Core Recovery (TCR), Rock QualityDesignation (RQD),Point Load Strength ndex (Is50), Uniaxial Compressive Strength (qu) and Unit Volume Weight (y) values of Candir formation TRac) are given in Table 2. Table 1 SPT and laboratory test results of weathered levels of Candir formation (TRa¢-Ws).
Figure 2 Triassic aged Candir formation (TRac) including claystone and siltstone. Figure 1 The location map of the landslide (Google Earth view).
Figure 2 Triassic aged Candir formation (TRac) including claystone and siltstone. Figure 1 The location map of the landslide (Google Earth view).
Table 2 The results of laboratory experiments for Candir formation (TRac).
Table 2 The results of laboratory experiments for Candir formation (TRac).
Table 3 Geotechnical parameters of the geological formations (Yuksel Project, 2018).
Table 3 Geotechnical parameters of the geological formations (Yuksel Project, 2018).
a [hen, the strength parameters obtained through the RocLab (Rocscience, 2009) software program are given in Table 3; the obtained normal stress-shear strength graphs are also given in Figure 4. Figure 4 Normal stress-Shear strength graphics ) for TRacfrm; b) for TRag-W5 frm(Sonmez and Ulusay, 2002
a [hen, the strength parameters obtained through the RocLab (Rocscience, 2009) software program are given in Table 3; the obtained normal stress-shear strength graphs are also given in Figure 4. Figure 4 Normal stress-Shear strength graphics ) for TRacfrm; b) for TRag-W5 frm(Sonmez and Ulusay, 2002
Figure 3 GSI chart for Candir formation’s weathered (TRac-W5)and unweathered(TRac) levels,(S6nmez and Ulusay 2002; Yuksel Project 2018). The geological strength index (GSI) has been calculated for rock units using discontinuity Surface Condition Rating (SCR) and Structure Rating (SR) scores were determined from the field studies. In these evaluations, the number of volumetric joints was calculated using Jv = discontinuity set number / discontinuity interval (in meters) equation. It was calculated as 2 / (1/10) = 20 for the very-completely weathered (TRac-W5) and unweathered levels (TRac) of the Candir formation. After that, the Structure Rating (SR) value has been determined as 28 from the graph (Figure 3). In this case, the GSI value was determined as 24 and 34, respectively.
Figure 3 GSI chart for Candir formation’s weathered (TRac-W5)and unweathered(TRac) levels,(S6nmez and Ulusay 2002; Yuksel Project 2018). The geological strength index (GSI) has been calculated for rock units using discontinuity Surface Condition Rating (SCR) and Structure Rating (SR) scores were determined from the field studies. In these evaluations, the number of volumetric joints was calculated using Jv = discontinuity set number / discontinuity interval (in meters) equation. It was calculated as 2 / (1/10) = 20 for the very-completely weathered (TRac-W5) and unweathered levels (TRac) of the Candir formation. After that, the Structure Rating (SR) value has been determined as 28 from the graph (Figure 3). In this case, the GSI value was determined as 24 and 34, respectively.
Figure 1 The topography Z(X, Y) is given in the Cartesian framework, X and Y being the horizontal coordinates. The surface induces a local coordinate system x, y, z (Christen et al., 20104) . It is discretized such that its projection onto the X, Y plane results in a structured mesh (from Christen et al., 2010a)(Fig. 1).
Figure 1 The topography Z(X, Y) is given in the Cartesian framework, X and Y being the horizontal coordinates. The surface induces a local coordinate system x, y, z (Christen et al., 20104) . It is discretized such that its projection onto the X, Y plane results in a structured mesh (from Christen et al., 2010a)(Fig. 1).
Figure 2 Geographical position of the Selanac case study Geological settings are very complex ;initiation zone belongs to Jurassic ophiolites, while transportation and deposition area belongs to tectonic contact of Triassic limestones and magmatic rocks with Palaeozoic metamorphic rocks. Debris flow material is highly heterogeneous in lithological composition, as well as grain size distribution (up to m2boulders) (Fig. 3).
Figure 2 Geographical position of the Selanac case study Geological settings are very complex ;initiation zone belongs to Jurassic ophiolites, while transportation and deposition area belongs to tectonic contact of Triassic limestones and magmatic rocks with Palaeozoic metamorphic rocks. Debris flow material is highly heterogeneous in lithological composition, as well as grain size distribution (up to m2boulders) (Fig. 3).
Figure 3 UAV images of a) soure area b) transportation zone (April 2017)
Figure 3 UAV images of a) soure area b) transportation zone (April 2017)
Even the estimated erosion is very high in some parts (in average 12m), here will be shown results according to transported initiated mass, since first results was made without erosion calculation. Precision of topology finally Figure 4 a) Calculation of deference in topography before and after the activation of the debris flow, b) Pleiades image after the event and position of defined release area RAMMS uses DEM (Digital Elevation Model) as a basic data for defining simple geometry of model. Some researchers suggested 5x5m resolution as an optimal, explaining that even using smaller resolution gave quite similar results. New updated version of RAMMS gives opportunity to use friendly models of the terrain with better resolution, as a standard model. More precision in defining source area, erosion depth and deposition (Fig. 4) were provided after scanning of surface topology with resolution 5x5min April 2017.Those input data were used for testing numerical model and results were compared with previously obtained 30x30mresolution topology input data and results (Kru8ic et al, 2018). The influence of topology resolution data on erosion/deposition model was also tested.
Even the estimated erosion is very high in some parts (in average 12m), here will be shown results according to transported initiated mass, since first results was made without erosion calculation. Precision of topology finally Figure 4 a) Calculation of deference in topography before and after the activation of the debris flow, b) Pleiades image after the event and position of defined release area RAMMS uses DEM (Digital Elevation Model) as a basic data for defining simple geometry of model. Some researchers suggested 5x5m resolution as an optimal, explaining that even using smaller resolution gave quite similar results. New updated version of RAMMS gives opportunity to use friendly models of the terrain with better resolution, as a standard model. More precision in defining source area, erosion depth and deposition (Fig. 4) were provided after scanning of surface topology with resolution 5x5min April 2017.Those input data were used for testing numerical model and results were compared with previously obtained 30x30mresolution topology input data and results (Kru8ic et al, 2018). The influence of topology resolution data on erosion/deposition model was also tested.
Figure 5 Final model with 30x30m DEM as input a) § =500 m/s?,u=0.05 b) deposited material depth=5m
Figure 5 Final model with 30x30m DEM as input a) § =500 m/s?,u=0.05 b) deposited material depth=5m
Results show fewer amounts of deposited volume then volume that flow out of calculation domain. Figure 6 Final model with 5x5m DEM as input a) § =500 m/s?,1=0.11_b) deposited material depth=14m
Results show fewer amounts of deposited volume then volume that flow out of calculation domain. Figure 6 Final model with 5x5m DEM as input a) § =500 m/s?,1=0.11_b) deposited material depth=14m
Figure 1 Aerial view of the Spi¢unak Landslide. The deformations on the state road D3 pavement construction were continuously re-established, while the cracks and deformations of the stone lining at the embankment among the state road, as well as subsidence of the local road in the middle part of the landslide were observed (Fig 2).
Figure 1 Aerial view of the Spi¢unak Landslide. The deformations on the state road D3 pavement construction were continuously re-established, while the cracks and deformations of the stone lining at the embankment among the state road, as well as subsidence of the local road in the middle part of the landslide were observed (Fig 2).
Figure 2 Evidences of the landslide movements: a) main tension crack on the state road D3, b) subsidence of the local road towards the Lokve Lake.
Figure 2 Evidences of the landslide movements: a) main tension crack on the state road D3, b) subsidence of the local road towards the Lokve Lake.
Figure 3 Engineering-geological map of the Spi¢unak Landslide The Spiéunak Landslide is located in Gorski Kotar, a hilly area of the NW _ Dinarides. Two main lithostratigraphic units in the study area are Permian clastic and Jurassic carbonate rocks. The tectonic setting of the area is characterised by numerous faults, frequent Geotechnical investigations (Fig. 3) conducted to determine engineering geological units, the landslide model, included a detailed engineering geological mapping, borehole drilling, laboratory testing of disturbed soil and rock mass samples, inclinometer and piezometer measurements as well as_ geophysical surveying. Nine investigation boreholes, B-1 to B-9, of depth from 13 to 25 m were drilled, 182 m of length in total. In three boreholes, B-5, B-8 and B-10, inclinometer casings were installed immediately after drilling to measure displacements and indicate sliding surface position. Measured displacements indicated sliding surface position that coincides with the contact of moderately weathered layer of shales and sandstones, as it is shown in Figure 4. Piezometer casings in borehole B 2, B-4, B-7 and B-9, were installed to enable measuring o ground water level. Representative soil and rock samples were taken and tested in the Geotechnical laboratory. Geophysical survey using geoelectric tomography and seismic refraction techniques was conducted to determine depth of deposits and assess the dynamic parameters of materials.
Figure 3 Engineering-geological map of the Spi¢unak Landslide The Spiéunak Landslide is located in Gorski Kotar, a hilly area of the NW _ Dinarides. Two main lithostratigraphic units in the study area are Permian clastic and Jurassic carbonate rocks. The tectonic setting of the area is characterised by numerous faults, frequent Geotechnical investigations (Fig. 3) conducted to determine engineering geological units, the landslide model, included a detailed engineering geological mapping, borehole drilling, laboratory testing of disturbed soil and rock mass samples, inclinometer and piezometer measurements as well as_ geophysical surveying. Nine investigation boreholes, B-1 to B-9, of depth from 13 to 25 m were drilled, 182 m of length in total. In three boreholes, B-5, B-8 and B-10, inclinometer casings were installed immediately after drilling to measure displacements and indicate sliding surface position. Measured displacements indicated sliding surface position that coincides with the contact of moderately weathered layer of shales and sandstones, as it is shown in Figure 4. Piezometer casings in borehole B 2, B-4, B-7 and B-9, were installed to enable measuring o ground water level. Representative soil and rock samples were taken and tested in the Geotechnical laboratory. Geophysical survey using geoelectric tomography and seismic refraction techniques was conducted to determine depth of deposits and assess the dynamic parameters of materials.
Figure 4 Borehole B-5 a) measured displacements in inclinometer, b) photography of the borehole core. landslide is 70 m, the width is 85 m and the depth of sliding surface is approximately 20 m. Activity state, according to Cruden and Varnes (1996), can be considered as active, while the style is single, very slow moving. The estimated landslide volume is 0.1 x 10° m3. According to Hungr et al. (2014), landslide is classified as rock rotational slide.
Figure 4 Borehole B-5 a) measured displacements in inclinometer, b) photography of the borehole core. landslide is 70 m, the width is 85 m and the depth of sliding surface is approximately 20 m. Activity state, according to Cruden and Varnes (1996), can be considered as active, while the style is single, very slow moving. The estimated landslide volume is 0.1 x 10° m3. According to Hungr et al. (2014), landslide is classified as rock rotational slide.
Figure 5 Engineering-geological cross-section 2-2’. Permian clastic and Jurassic carbonate rocks are covered with superficial deposits, composed of delluvia deposits and artificial fill. Delluvial deposits are composed of coarse grained and fine grained mixtures. Coarse grained material consists of limestone and dolomite cobbles, angular to subangular, up to 20 cm in size. Fines are composed of low to medium plasticity yellowish brown soil. Artificial fill is a mixture o limestone and dolomite grains, angular to subangular originating form Jurassic carbonate outcrops excavated during road construction.
Figure 5 Engineering-geological cross-section 2-2’. Permian clastic and Jurassic carbonate rocks are covered with superficial deposits, composed of delluvia deposits and artificial fill. Delluvial deposits are composed of coarse grained and fine grained mixtures. Coarse grained material consists of limestone and dolomite cobbles, angular to subangular, up to 20 cm in size. Fines are composed of low to medium plasticity yellowish brown soil. Artificial fill is a mixture o limestone and dolomite grains, angular to subangular originating form Jurassic carbonate outcrops excavated during road construction.
Figure 6 Representative cross section with remedial measures and monitoring equipment.
Figure 6 Representative cross section with remedial measures and monitoring equipment.
Table 1 Mohr-Coulomb geotechnical parameters of geotechnical units obtained from back analysis.
Table 1 Mohr-Coulomb geotechnical parameters of geotechnical units obtained from back analysis.
Figure 7 Slope stability back analysis on representative engineering geological cross section. Mohr-Coulomb strength parameters obtained in back analysis are presented in Table 1. Layer above shale and sandstone bedrock was modelled as a weak layer with low residual shear strength properties that correspond to highly weathered bedrock.
Figure 7 Slope stability back analysis on representative engineering geological cross section. Mohr-Coulomb strength parameters obtained in back analysis are presented in Table 1. Layer above shale and sandstone bedrock was modelled as a weak layer with low residual shear strength properties that correspond to highly weathered bedrock.
Figure 8 Results of slope stability analysis with factor of safety after remedial measures in phases: a) drains instalation, b) rock fill embankment construction, c) pile wall and geotechnical anchor instalation, on representative engineering geological cross section. Slope stability analysis of the landslide with applied remedial measures (Fig 8) used average material shear strength parameters. They were performed according to the designed phases of remedial measure applications: (i) lowering of ground water level with bored and trench drains below the road construction towards the Lokve Lake, (ii) stabilizing rock fill embankment construction along the lower part of the landslide, and (iii) pile wall anchored in the head with pre-stressed geotechnical anchors positioned in the toe of the state road D3 embankment.
Figure 8 Results of slope stability analysis with factor of safety after remedial measures in phases: a) drains instalation, b) rock fill embankment construction, c) pile wall and geotechnical anchor instalation, on representative engineering geological cross section. Slope stability analysis of the landslide with applied remedial measures (Fig 8) used average material shear strength parameters. They were performed according to the designed phases of remedial measure applications: (i) lowering of ground water level with bored and trench drains below the road construction towards the Lokve Lake, (ii) stabilizing rock fill embankment construction along the lower part of the landslide, and (iii) pile wall anchored in the head with pre-stressed geotechnical anchors positioned in the toe of the state road D3 embankment.
VE) See ee ee Swe: ew aes. Se Figure 1 Framework for landslide risk assessment and management developed by Fell et al. (2008a,b) and scope of research described in this study. The first landslide risk analysis in national scale was done in the frame of Disaster Risk Assessment for the Republic of Croatia during 2018 and the coordinator was Croatian National Platform for Disaster Risk Reduction, CNPDRR. Landslide risk calculation was carried out by the scientists from Croatian Landslide Group, which members are scientists from University of Rijeka, Faculty of Civil Engineering and University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering.
VE) See ee ee Swe: ew aes. Se Figure 1 Framework for landslide risk assessment and management developed by Fell et al. (2008a,b) and scope of research described in this study. The first landslide risk analysis in national scale was done in the frame of Disaster Risk Assessment for the Republic of Croatia during 2018 and the coordinator was Croatian National Platform for Disaster Risk Reduction, CNPDRR. Landslide risk calculation was carried out by the scientists from Croatian Landslide Group, which members are scientists from University of Rijeka, Faculty of Civil Engineering and University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering.
Table 1 Geomorphological classification of slopes (IGU, 1968). Based on two predominating casual factors, lithological units where sliding can be occur and slopes inclination of 5-55°, resulting preliminary landslide susceptibility map of the Republic of Croatia was derived (Fig. 2). The spatial distribution of landslide-prone areas shows that the highest frequency of geomorphological and geological conditions for landslide occurrence is present in the continental part of the Croatia, i.e, in the Pannonian Basin. Given the relative proportion of landslide-prone areas in relation to the area of the county, the largest proportion is in the Krapina-Zagorje County, where 57.8% of the area is susceptible to sliding. Landslide assessment for all Croatian counties is given in (Fig. 2), presented from arger proportions of slide-prone areas to smaller ones. In addition to the relative proportions, the size of the andslide-prone area is relevant for the assessment of the total landslide susceptibility by county. The largest area where landslides can occur is in the Sisak-Moslavina County, which is 806.4 km?. For comparison, county with
Table 1 Geomorphological classification of slopes (IGU, 1968). Based on two predominating casual factors, lithological units where sliding can be occur and slopes inclination of 5-55°, resulting preliminary landslide susceptibility map of the Republic of Croatia was derived (Fig. 2). The spatial distribution of landslide-prone areas shows that the highest frequency of geomorphological and geological conditions for landslide occurrence is present in the continental part of the Croatia, i.e, in the Pannonian Basin. Given the relative proportion of landslide-prone areas in relation to the area of the county, the largest proportion is in the Krapina-Zagorje County, where 57.8% of the area is susceptible to sliding. Landslide assessment for all Croatian counties is given in (Fig. 2), presented from arger proportions of slide-prone areas to smaller ones. In addition to the relative proportions, the size of the andslide-prone area is relevant for the assessment of the total landslide susceptibility by county. The largest area where landslides can occur is in the Sisak-Moslavina County, which is 806.4 km?. For comparison, county with
Figure 2 Preliminary landslide susceptibility map of the Republic of Croatia with proportions of landslide-prone areas and expected number of landslides based on Scenario 1 - the worst possible MORLE scenario and Scenario 2 - the most probable MORLE scenario.
Figure 2 Preliminary landslide susceptibility map of the Republic of Croatia with proportions of landslide-prone areas and expected number of landslides based on Scenario 1 - the worst possible MORLE scenario and Scenario 2 - the most probable MORLE scenario.
Figure 3 Cumulative daily precipitation (mm) on Varazdin meteorological station for March 2018 and the series of theoretical percentile curves (2., 10., 25., 50., 75., 90. i 98.) for period 1961 - 2000 (www.meteo.hr). County. Therefore, climatological analysis of the 20-, 4o- and 100- cumulative day precipitation before landslide activation was conducted based on data from the Sisak meteorological station. The preliminary analysis selected 20-, 40- and 100-day cumulative precipitation as critical, because for those SPI values a certain threshold indicates a potentially damaging landslide occurring. Results of the 20-days cumulative precipitation prior to landslide activation indicates wet weather conditions and for the 40- and 100- days cumulative precipitation a prior activation indicates extremely wet weather conditions. Additionally, cumulative precipitations for 40- and 100- days prior to landslide activation (177.2 and 362.6 mm) represents the second largest measured value for the first half of March since 1961, while the 20- day cumulative precipitation (69.7 mm) is the 5th cumulative precipitation value after the maximum measured in 2016 (107.4 mm). Frequency analysis of triggering the most probable MORLE shows that the 100-day cumulative precipitation prior to the landslide activation on 13 March 2018 can be expected once every 15 years in Zagreb and once every 22 years in VaraZzdin.
Figure 3 Cumulative daily precipitation (mm) on Varazdin meteorological station for March 2018 and the series of theoretical percentile curves (2., 10., 25., 50., 75., 90. i 98.) for period 1961 - 2000 (www.meteo.hr). County. Therefore, climatological analysis of the 20-, 4o- and 100- cumulative day precipitation before landslide activation was conducted based on data from the Sisak meteorological station. The preliminary analysis selected 20-, 40- and 100-day cumulative precipitation as critical, because for those SPI values a certain threshold indicates a potentially damaging landslide occurring. Results of the 20-days cumulative precipitation prior to landslide activation indicates wet weather conditions and for the 40- and 100- days cumulative precipitation a prior activation indicates extremely wet weather conditions. Additionally, cumulative precipitations for 40- and 100- days prior to landslide activation (177.2 and 362.6 mm) represents the second largest measured value for the first half of March since 1961, while the 20- day cumulative precipitation (69.7 mm) is the 5th cumulative precipitation value after the maximum measured in 2016 (107.4 mm). Frequency analysis of triggering the most probable MORLE shows that the 100-day cumulative precipitation prior to the landslide activation on 13 March 2018 can be expected once every 15 years in Zagreb and once every 22 years in VaraZzdin.
prior to landslide activation indicates wet weather conditions (76.8 - 87.1 mm), 4o0- days cumulative precipitation indicates very wet weather conditions (151.3- 152.4 mm) while the 100- days cumulative precipitation extremely wet weather conditions (344.4-365.4 mm). Additionally, cumulative precipitations for 100- days prior to landslide activation represents the largest measured amount on Zagreb-Gri¢ and VaraZzdin meteorological station since 1961. Cumulative precipitations for 40- days prior to landslide activation represents the largest measured value on Zagreb-Grié meteorological station and the second largest measured value on VaraZdin meteorological station, while the 20- day cumulative precipitation is the second largest measured value on Varazdin meteorological station and third on Zagreb-Grié meteorological station. Frequency analysis of triggering the worst possible MORLE shows that the extremely high 100-day cumulative precipitation with wet and very wet 20- and 4o- day cumulative precipitation prior to the landslide activation on 30 March 2013 can be expected once every 98 years in VaraZdin and once every 130 years in Zagreb.
prior to landslide activation indicates wet weather conditions (76.8 - 87.1 mm), 4o0- days cumulative precipitation indicates very wet weather conditions (151.3- 152.4 mm) while the 100- days cumulative precipitation extremely wet weather conditions (344.4-365.4 mm). Additionally, cumulative precipitations for 100- days prior to landslide activation represents the largest measured amount on Zagreb-Gri¢ and VaraZzdin meteorological station since 1961. Cumulative precipitations for 40- days prior to landslide activation represents the largest measured value on Zagreb-Grié meteorological station and the second largest measured value on VaraZdin meteorological station, while the 20- day cumulative precipitation is the second largest measured value on Varazdin meteorological station and third on Zagreb-Grié meteorological station. Frequency analysis of triggering the worst possible MORLE shows that the extremely high 100-day cumulative precipitation with wet and very wet 20- and 4o- day cumulative precipitation prior to the landslide activation on 30 March 2013 can be expected once every 98 years in VaraZdin and once every 130 years in Zagreb.
Figure 1 Flexible ring net barrier withstanding overflow in the Illgraben.
Figure 1 Flexible ring net barrier withstanding overflow in the Illgraben.
Figure 4 Case study overview in Cuenca del Rio Rimac Distrito de Lurigancho, Chosica, Peru with 22 installed flexible debris flow barriers (red dots). Figure 3 Steep, ‘incised slopes overlooking Chosica’s urban area and the unconsolidated material covering these slopes illustrate the debris flow potential.
Figure 4 Case study overview in Cuenca del Rio Rimac Distrito de Lurigancho, Chosica, Peru with 22 installed flexible debris flow barriers (red dots). Figure 3 Steep, ‘incised slopes overlooking Chosica’s urban area and the unconsolidated material covering these slopes illustrate the debris flow potential.
Figure 8 and VX barrier in a narrower channel
Figure 8 and VX barrier in a narrower channel
Figure 5 Scour protection around the posts for UX-barriers designed abrasion protection for the top support rope (see Figures 5 and 6). Depending on the hydraulic conditions and the geometry of the different streams, UX or VX barriers were installed (Figure 7 and 8), as single barrier or in a multi-level combination. The largest barrier was set up in a multi-level setting (Figure 9).
Figure 5 Scour protection around the posts for UX-barriers designed abrasion protection for the top support rope (see Figures 5 and 6). Depending on the hydraulic conditions and the geometry of the different streams, UX or VX barriers were installed (Figure 7 and 8), as single barrier or in a multi-level combination. The largest barrier was set up in a multi-level setting (Figure 9).
Figure 6 Abrasion | protection for the top support rope.
Figure 6 Abrasion | protection for the top support rope.
Figure 7 UX- barriers with two posts in the channel bed
Figure 7 UX- barriers with two posts in the channel bed
Figure 10 Before (2016) and after the debris flow event (2017) and subsequent maintenance (2018) for the stream San Pedregal (above) and Carrosio (below). The first debris flows after installation happened a year later, in January 2017. Up to then, all barriers have retained debris in variable amounts. On average, their retention level has been around 4’600 m3. Subsequently, in February 2017, Peru was hit by great storms which caused even further, large, debris flow events. The flexible debris flow barriers kept fulfilling their function of retaining debris. The multi-level system was efficient since the barriers further downstream were not completely filled and still offer good retention capacity, for potentia following debris flows. During the debris flow events post supports and cable supports got partially eroded. Hence, maintenance work on these elements was done. Eroded parts were rebuilt with new foundations, brakes and cables were replaced. Further, the barriers need emptying when the material is dry and stable. It can be cleaned with an excavator from behind or in certain conditions, when all safety requirements are met, from the front. Figure 10 illustrates the overall process for the barriers, from installation to filling to maintenance, ready for the next debris flow events. Conclusion
Figure 10 Before (2016) and after the debris flow event (2017) and subsequent maintenance (2018) for the stream San Pedregal (above) and Carrosio (below). The first debris flows after installation happened a year later, in January 2017. Up to then, all barriers have retained debris in variable amounts. On average, their retention level has been around 4’600 m3. Subsequently, in February 2017, Peru was hit by great storms which caused even further, large, debris flow events. The flexible debris flow barriers kept fulfilling their function of retaining debris. The multi-level system was efficient since the barriers further downstream were not completely filled and still offer good retention capacity, for potentia following debris flows. During the debris flow events post supports and cable supports got partially eroded. Hence, maintenance work on these elements was done. Eroded parts were rebuilt with new foundations, brakes and cables were replaced. Further, the barriers need emptying when the material is dry and stable. It can be cleaned with an excavator from behind or in certain conditions, when all safety requirements are met, from the front. Figure 10 illustrates the overall process for the barriers, from installation to filling to maintenance, ready for the next debris flow events. Conclusion
Figure 9 The highest barrier is the largest in South America. Debris flow events
Figure 9 The highest barrier is the largest in South America. Debris flow events
Figure 1 Squeezing-out phenomenon at the Takarazuka Golf Course landslide Added to photo taken by The Sankei Shimbun, referring to Yokoyama et al. 1995 The schematic diagram of landslide structure by Varnes (1978) is well known in the description of landslide movement. Oyagi (2004) examined the components of the moving block and the deformation structure based on this schematic diagram, and pointed out the existence of a quasi-fluctuation area on the ground of the accumulation zone at the toe of landslide mass for some landslides. This suggests that the existence of an expansion (generation) of new slope or/and ground failure phenomenon associated with the loading of landslide mass. One example of such expansion is the landslide at Takarazuka Golf Course that was triggered by the 1995 Southern Hyogo Prefecture Earthquake (Figure 1), and the expansion was thought to be the result of squeezing (or squeezing-out) phenomenon (Yokoyama et al. 1995). A recent example is the slope failures (small andslides shown in Figure 2) in Atsuma Town caused by the 2018 Hokkaido Iburi Eastern Earthquake. To clarify this kind of squeezing phenomenon, we have been performing model flume tests in recent years. In this paper, we present the results of tests conducted on the model consisting of two soil layers with different permeability. Keywords Propagation of failure, Pore water pressure, sand, Particle size, permeability, Flume test
Figure 1 Squeezing-out phenomenon at the Takarazuka Golf Course landslide Added to photo taken by The Sankei Shimbun, referring to Yokoyama et al. 1995 The schematic diagram of landslide structure by Varnes (1978) is well known in the description of landslide movement. Oyagi (2004) examined the components of the moving block and the deformation structure based on this schematic diagram, and pointed out the existence of a quasi-fluctuation area on the ground of the accumulation zone at the toe of landslide mass for some landslides. This suggests that the existence of an expansion (generation) of new slope or/and ground failure phenomenon associated with the loading of landslide mass. One example of such expansion is the landslide at Takarazuka Golf Course that was triggered by the 1995 Southern Hyogo Prefecture Earthquake (Figure 1), and the expansion was thought to be the result of squeezing (or squeezing-out) phenomenon (Yokoyama et al. 1995). A recent example is the slope failures (small andslides shown in Figure 2) in Atsuma Town caused by the 2018 Hokkaido Iburi Eastern Earthquake. To clarify this kind of squeezing phenomenon, we have been performing model flume tests in recent years. In this paper, we present the results of tests conducted on the model consisting of two soil layers with different permeability. Keywords Propagation of failure, Pore water pressure, sand, Particle size, permeability, Flume test
Figure 2 Squeezing-out phenomenon at Yoshino, Atsuma, Hokkaido
Figure 2 Squeezing-out phenomenon at Yoshino, Atsuma, Hokkaido
Figure 3 Schematic diagram of flume test apparatus After the soil layer was prepared, strain gauge probes for detecting the location of sliding surface were inserted vertically into the soil layer at three locations of A to C as shown in Figure 3. It is noted that in each probe (made by polypropylene sheet), strain gauges were
Figure 3 Schematic diagram of flume test apparatus After the soil layer was prepared, strain gauge probes for detecting the location of sliding surface were inserted vertically into the soil layer at three locations of A to C as shown in Figure 3. It is noted that in each probe (made by polypropylene sheet), strain gauges were
Figure 4 Result of Test No. 2-2 ((a): Photo and sketch; (b) Time serise change between starin and pore water pressure) 189
Figure 4 Result of Test No. 2-2 ((a): Photo and sketch; (b) Time serise change between starin and pore water pressure) 189
Figure 5 Result of Test No. 2-4 ((a): Photo and sketch; (b) Time serise change between starin and pore water pressure) Figure 6 shows the relationship between the maximum depth of sliding surface and the length of deformation zone (deformation distance) measured by movie from the side of the water tank. In this figure, A is the result of the
Figure 5 Result of Test No. 2-4 ((a): Photo and sketch; (b) Time serise change between starin and pore water pressure) Figure 6 shows the relationship between the maximum depth of sliding surface and the length of deformation zone (deformation distance) measured by movie from the side of the water tank. In this figure, A is the result of the
Figure 6 Relationship between Maximum depth of slideing surface amd Length of deformation zone
Figure 6 Relationship between Maximum depth of slideing surface amd Length of deformation zone
Figure 1 Study area along the coastal area of large Adriatic flysch basin in a few months period. Landslides are thus occurring mostly in the late winter and spring period (from November to May), when the number of rainy days in the three-month period is high and evapotranspiration is low. Due to relatively low permeability of the cover, the infiltration is generally slow and the runout coefficient is high (Perani¢ 2019, Perani¢ et al. 2019). The analyses of the daily, monthly and annual precipitation data have shown that the cumulative precipitation in three months (70-100 days), prior sliding, may have a great influence on water infiltration and groundwater levels rising (Dugonji¢ Jovanéevié and Arbanas 2012, 2017; Dugonji¢ Jovanéevic 2013). Material characteristics relevant for instability occurrence, investigated trough landslide remediation works, scientific research projects, student terrain investigations, doctoral thesis, etc. are presented in this paper. Laboratory testing was mostly performed in the Geotechnical laboratory, at the Civil Engineering Faculty, University of Rijeka. The aim of this research is to define some of the basic geotechnical aspect of materials involved in slope instabilities.
Figure 1 Study area along the coastal area of large Adriatic flysch basin in a few months period. Landslides are thus occurring mostly in the late winter and spring period (from November to May), when the number of rainy days in the three-month period is high and evapotranspiration is low. Due to relatively low permeability of the cover, the infiltration is generally slow and the runout coefficient is high (Perani¢ 2019, Perani¢ et al. 2019). The analyses of the daily, monthly and annual precipitation data have shown that the cumulative precipitation in three months (70-100 days), prior sliding, may have a great influence on water infiltration and groundwater levels rising (Dugonji¢ Jovanéevié and Arbanas 2012, 2017; Dugonji¢ Jovanéevic 2013). Material characteristics relevant for instability occurrence, investigated trough landslide remediation works, scientific research projects, student terrain investigations, doctoral thesis, etc. are presented in this paper. Laboratory testing was mostly performed in the Geotechnical laboratory, at the Civil Engineering Faculty, University of Rijeka. The aim of this research is to define some of the basic geotechnical aspect of materials involved in slope instabilities.
Table 1 Range of shear strength parameters of flysch samples obtained from different studies. DS/RS — direct shear/ring shear apparatus; *- peak values **- residual values; 1_ Vivoda Prodan (2016); *— Maéek et al. (2017); ?- Benac et al. (2014); *- Perani¢ (2019).
Table 1 Range of shear strength parameters of flysch samples obtained from different studies. DS/RS — direct shear/ring shear apparatus; *- peak values **- residual values; 1_ Vivoda Prodan (2016); *— Maéek et al. (2017); ?- Benac et al. (2014); *- Perani¢ (2019).
Figure 2 Plasticity chart of the colluvial cover and residual soil (product of flysch rock mass weathering).
Figure 2 Plasticity chart of the colluvial cover and residual soil (product of flysch rock mass weathering).
Table 2 Results of the slake durability tests, including the slake durability index, disintegration ratio and modified disintegration ratio after second cycle, for siltstones of different weathering grades in the study area.
Table 2 Results of the slake durability tests, including the slake durability index, disintegration ratio and modified disintegration ratio after second cycle, for siltstones of different weathering grades in the study area.
Table 1. Best fit parameters of the van Genuchten (VG) and Fredlund and Xing (F&X) models (Peranic¢ et al. 2018).
Table 1. Best fit parameters of the van Genuchten (VG) and Fredlund and Xing (F&X) models (Peranic¢ et al. 2018).
tested siltstone samples of different weathering grades, and the modified disintegration ratio (Drp) was used to determine potential long term degradation of the tested samples. Highly degraded and fragmented fresh sample after each of five cycles, despite of high Ia: value, is visible on Fig. 3. Figure 3 Highly degraded fresh siltstone from Pazin after each of five cycles of the slake durability test with Ig.=86.12 % and Drp2=0.68.
tested siltstone samples of different weathering grades, and the modified disintegration ratio (Drp) was used to determine potential long term degradation of the tested samples. Highly degraded and fragmented fresh sample after each of five cycles, despite of high Ia: value, is visible on Fig. 3. Figure 3 Highly degraded fresh siltstone from Pazin after each of five cycles of the slake durability test with Ig.=86.12 % and Drp2=0.68.
Figure 4 Measurement results and SWRC of residual soil from a flysch rock mass from the Valici Landslide (Perani¢ et al. 2018).
Figure 4 Measurement results and SWRC of residual soil from a flysch rock mass from the Valici Landslide (Perani¢ et al. 2018).
Figure 1 Analysed section of the route in the length of 150 m Crucial question during the infrastructure facilities designing is gathering existing data at the area of the section in question. During the process of collecting and analysing available data, relevant information will be provided about the benefits as well as problems we may encounter during the implementation of a future project. The lithological type of rock mass, geological age, tectonic damage, extent of decomposition, physical - mechanical characteristics and a number of other factors need to be determined on the basis of the collection of existing documentation. The information from the previous analysis will usable in the planning of both optimal (qualitative and quantitative) exploratory works in order to provide reliable bases for the next phases of designing the project documentation of the road in question.
Figure 1 Analysed section of the route in the length of 150 m Crucial question during the infrastructure facilities designing is gathering existing data at the area of the section in question. During the process of collecting and analysing available data, relevant information will be provided about the benefits as well as problems we may encounter during the implementation of a future project. The lithological type of rock mass, geological age, tectonic damage, extent of decomposition, physical - mechanical characteristics and a number of other factors need to be determined on the basis of the collection of existing documentation. The information from the previous analysis will usable in the planning of both optimal (qualitative and quantitative) exploratory works in order to provide reliable bases for the next phases of designing the project documentation of the road in question.
Table 1 The values of the parameters defined in the 2010 study are reduced by partial safety coefficients
Table 1 The values of the parameters defined in the 2010 study are reduced by partial safety coefficients
Table 3 Values of physic-mechanical parameters defined by Hoek & Brown classification
Table 3 Values of physic-mechanical parameters defined by Hoek & Brown classification
Table 2 Average values of parameters obtained by laboratory testing of samples (parameters marked with * - defined by back analysis, due to the impossibility of testing samples obtained by exploratory drilling). As the geo - exploratory drilling core provided the opportunity to test the uniaxial strength on the samples from layer 3 and layer 4, the mentioned test was performed and, in accordance with the literature recommendations, the parameters of shear strength were determined using the Hoek & Brown classification. The parameter values are showed in Table 3. Ww EA 2 oe Oe) Se CMY Pe, ee Le ete eee a ee! 6 a: a Se
Table 2 Average values of parameters obtained by laboratory testing of samples (parameters marked with * - defined by back analysis, due to the impossibility of testing samples obtained by exploratory drilling). As the geo - exploratory drilling core provided the opportunity to test the uniaxial strength on the samples from layer 3 and layer 4, the mentioned test was performed and, in accordance with the literature recommendations, the parameters of shear strength were determined using the Hoek & Brown classification. The parameter values are showed in Table 3. Ww EA 2 oe Oe) Se CMY Pe, ee Le ete eee a ee! 6 a: a Se
Figure 3 Transverse profile design solution 1 It is noted that the design solution in phase 1, defined on the basis of previous research, was accompanied by certain Figure 2 Cross section 1 with geological layers used in the stability calculation
Figure 3 Transverse profile design solution 1 It is noted that the design solution in phase 1, defined on the basis of previous research, was accompanied by certain Figure 2 Cross section 1 with geological layers used in the stability calculation
Figure 2 shows cross section 1 with the thicknesses of the layers used in the stability calculation, while Figure 3 shows the same section with the solution defined by the phase 1 project.
Figure 2 shows cross section 1 with the thicknesses of the layers used in the stability calculation, while Figure 3 shows the same section with the solution defined by the phase 1 project.
Table 5 Values of physic-mechanical parameters used in the 2017 project
Table 5 Values of physic-mechanical parameters used in the 2017 project
Figure 4 Transversal profile 1 with the adopted 2016 design solution Table 4 Values of physic-mechanical parameters used in the 2016 project
Figure 4 Transversal profile 1 with the adopted 2016 design solution Table 4 Values of physic-mechanical parameters used in the 2016 project
Figure 5 Cross section 1 with the adopted decision from 2017 The solution defined by the 2017 project was implemented in the terrain (Fig. 5). During 2018, the constructed structure was demolished on the observed section of the route. A worrying fact is that all the calculations of stability, stress and deformation were made exactly in the zone where the structural failure occurred. The realistic model proved the inaccuracy of the data used in the calculations and the inadequacy of the project approach in finding solutions.
Figure 5 Cross section 1 with the adopted decision from 2017 The solution defined by the 2017 project was implemented in the terrain (Fig. 5). During 2018, the constructed structure was demolished on the observed section of the route. A worrying fact is that all the calculations of stability, stress and deformation were made exactly in the zone where the structural failure occurred. The realistic model proved the inaccuracy of the data used in the calculations and the inadequacy of the project approach in finding solutions.
Table 7 Natural slope safety factor values by phases The data in Table 7 indicate an inadequate critical review of the results of the investigative work. Simply obtained results of exploratory works should be reviewed on a natural slope. Too high values of the factor of safety, for a given slope geometry, seem unrealistic without further testing. Likewise, the safety factor values of less than one raise the question of possible slope maintenance at a relative standstill.
Table 7 Natural slope safety factor values by phases The data in Table 7 indicate an inadequate critical review of the results of the investigative work. Simply obtained results of exploratory works should be reviewed on a natural slope. Too high values of the factor of safety, for a given slope geometry, seem unrealistic without further testing. Likewise, the safety factor values of less than one raise the question of possible slope maintenance at a relative standstill.
Figure 6 Transversal profile 1 with the adopted 2019 design solution. Table 6 - Values of physic-mechanical parameters used in the 2018 and 2019 project
Figure 6 Transversal profile 1 with the adopted 2019 design solution. Table 6 - Values of physic-mechanical parameters used in the 2018 and 2019 project
Figure 1 Prospective basic geological map of Srebrenik municipality
Figure 1 Prospective basic geological map of Srebrenik municipality
Sliding velocity is very small with cyclic reactivation and calming. The sliding surface is in contact between he eluvial-deluvial soil and the substrate.
Sliding velocity is very small with cyclic reactivation and calming. The sliding surface is in contact between he eluvial-deluvial soil and the substrate.
Figure 3 Stability map of Srebrenik municipality
Figure 3 Stability map of Srebrenik municipality
Figure 4 Sub-location of Tinja as an example of mapping mistake
Figure 4 Sub-location of Tinja as an example of mapping mistake
number of landslides are located in the building areas. It can be concluded that landslide occurrence is closely related to the construction of structures. As an example, on the Figure 5, Gornji Srebrenik sub-location and the micro-location of the K-12 landslide are shown. Figure 5 Sub-location Gornji Srebrenik (a - detail mapping of stability, b - except of stability map of the Srebrenik municipality)
number of landslides are located in the building areas. It can be concluded that landslide occurrence is closely related to the construction of structures. As an example, on the Figure 5, Gornji Srebrenik sub-location and the micro-location of the K-12 landslide are shown. Figure 5 Sub-location Gornji Srebrenik (a - detail mapping of stability, b - except of stability map of the Srebrenik municipality)
Figure 6 Concrete lamellas at K-12 landslide as a substitution for retaining wall the uncertainty in the research, the safety factor can be overestimated or underestimated. This means that the engineering calculation with the numerical safety factor is not always accurate. Due to uncertainty in the budget, either too much or too little money can be spent to stabilize the landslide.
Figure 6 Concrete lamellas at K-12 landslide as a substitution for retaining wall the uncertainty in the research, the safety factor can be overestimated or underestimated. This means that the engineering calculation with the numerical safety factor is not always accurate. Due to uncertainty in the budget, either too much or too little money can be spent to stabilize the landslide.
Figure 1 General view of the study area A slope in the village Velikyi Pereviz, Poltava region, Ukraine is selected for stability assessment (Fig. 1). The site is located on the left bank of the river Psel with absolute elevation of the earth's surface from 125.0 to 155.0 m. Geomorphologically, the territory belongs to the slope of the Poltava loess plateau (Fig. 2). According to the results of engineering-geological surveys, it is established that loamy deposits of Quaternary formation, represented by loess and loess-like (loam) loam, are involved in the slope structure. The slope from the surface is covered with loose and deluvial deposits with a depth of about 5 m. The groundwater level was recorded only in the middle part of the slope. Groundwater was not detected on the plateau and down the slope (Fig. 3). 9 boreholes were drilled (fig. 3), 24 intact samples were taken. Selected samples for each layer were subjected to 6 The nature of the slip surface is often determined not so much by the stress-strain state of the soil mass, but by the natural conditions and geological structure of the soil mass. The method of wedges or sliding block method [Cheng] with polygonal slip surface was used to evaluate slope stability. It is most commonly used in the following cases:
Figure 1 General view of the study area A slope in the village Velikyi Pereviz, Poltava region, Ukraine is selected for stability assessment (Fig. 1). The site is located on the left bank of the river Psel with absolute elevation of the earth's surface from 125.0 to 155.0 m. Geomorphologically, the territory belongs to the slope of the Poltava loess plateau (Fig. 2). According to the results of engineering-geological surveys, it is established that loamy deposits of Quaternary formation, represented by loess and loess-like (loam) loam, are involved in the slope structure. The slope from the surface is covered with loose and deluvial deposits with a depth of about 5 m. The groundwater level was recorded only in the middle part of the slope. Groundwater was not detected on the plateau and down the slope (Fig. 3). 9 boreholes were drilled (fig. 3), 24 intact samples were taken. Selected samples for each layer were subjected to 6 The nature of the slip surface is often determined not so much by the stress-strain state of the soil mass, but by the natural conditions and geological structure of the soil mass. The method of wedges or sliding block method [Cheng] with polygonal slip surface was used to evaluate slope stability. It is most commonly used in the following cases:
Figure 4 Engineering geological profile 1-1
Figure 4 Engineering geological profile 1-1
Table 1 Results of slope calculation by the Wedge method change in a complex stress state, unobstructed deformation in tension; FEM simulation
Table 1 Results of slope calculation by the Wedge method change in a complex stress state, unobstructed deformation in tension; FEM simulation
Figure 5 Scheme for calculating by the Wedge method For a plane problem, these slip surfaces with some approximations can be replaced in the plane of the drawing by one or another number of straight lines - slip lines (Fig. 5). Within the straight lines, blocks of soil are allocated, the weight Q and the angle of inclination a to the horizontal are calculated. The shear force of the block is equal to F = Q - sina, and the resultant holding force is R = Q - cosa - tgp + cst - £, where is £ the block sliding length. The difference between these values will correspond to the shear pressure E. If there is a slope of the filtration flow in the soil, an additional pressure Fy will be acting [Lim et al.].
Figure 5 Scheme for calculating by the Wedge method For a plane problem, these slip surfaces with some approximations can be replaced in the plane of the drawing by one or another number of straight lines - slip lines (Fig. 5). Within the straight lines, blocks of soil are allocated, the weight Q and the angle of inclination a to the horizontal are calculated. The shear force of the block is equal to F = Q - sina, and the resultant holding force is R = Q - cosa - tgp + cst - £, where is £ the block sliding length. The difference between these values will correspond to the shear pressure E. If there is a slope of the filtration flow in the soil, an additional pressure Fy will be acting [Lim et al.].
Figure 6 Distribution of the wedges in studied case The slope safety factor for the case is kst = 1,326. This indicates that the slope is now in a stable condition, and the lowest additional loading, changing of soil properties, additional water saturation of the slope, excavating without a set of anti-landslide measures can lead to loss of slope stability.
Figure 6 Distribution of the wedges in studied case The slope safety factor for the case is kst = 1,326. This indicates that the slope is now in a stable condition, and the lowest additional loading, changing of soil properties, additional water saturation of the slope, excavating without a set of anti-landslide measures can lead to loss of slope stability.
Table 2 Estimated values of physical and mechanical properties of soils
Table 2 Estimated values of physical and mechanical properties of soils
Figure 7 Numerical model with finite elements with layer lebels
Figure 7 Numerical model with finite elements with layer lebels
Figure 9 Deformed model (a) and isopoles of deformation (b) for the second design variant Be a lO a a ek i ek a i ee a Figure 8 Deformed model (a) and isopoles of deformation (b) for the first design variant
Figure 9 Deformed model (a) and isopoles of deformation (b) for the second design variant Be a lO a a ek i ek a i ee a Figure 8 Deformed model (a) and isopoles of deformation (b) for the first design variant
Table 3 Comparison of calculation results by different methods By analysis of the data obtained and its comparing with the real slope state, it can be stated that modeling using residual soil strength characteristics, when assigned to deluvial soils, yields a result that is closer to coincides with real slope processes (formation of landslide slumps, cracking, deformation of buildings and structures, "tilted trees", etc.). Other methods give too high value of slope safety factor or inadequate scheme for the slope failure development and inadequate slip surface. The difference between the analytical method and the finite element method gives a safety factor with a deviation of about 7 - 10%.
Table 3 Comparison of calculation results by different methods By analysis of the data obtained and its comparing with the real slope state, it can be stated that modeling using residual soil strength characteristics, when assigned to deluvial soils, yields a result that is closer to coincides with real slope processes (formation of landslide slumps, cracking, deformation of buildings and structures, "tilted trees", etc.). Other methods give too high value of slope safety factor or inadequate scheme for the slope failure development and inadequate slip surface. The difference between the analytical method and the finite element method gives a safety factor with a deviation of about 7 - 10%.
FF OPP, NO VY UU ONTO UP. OU OP RECON WCU FUP OEE FP URN UO UP UR Oe Uh Se Oey UO ev er ae” Be FUN ee OE OU PR 8, ONE eee Oe eee, ae ee ee Figure 10 Deformed model (a) and d isopoles (b) of deformation for the third calculation variant
FF OPP, NO VY UU ONTO UP. OU OP RECON WCU FUP OEE FP URN UO UP UR Oe Uh Se Oey UO ev er ae” Be FUN ee OE OU PR 8, ONE eee Oe eee, ae ee ee Figure 10 Deformed model (a) and d isopoles (b) of deformation for the third calculation variant
Figure 1 Landslide photo, a sliding mass that has been gravitationally moved along the road.
Figure 1 Landslide photo, a sliding mass that has been gravitationally moved along the road.
Figure 2 Geological structure of the wider area of Makljenovac, Scale 1: 100,000 (Retrieved from: OGK OGK; Doboj_L 34-109)
Figure 2 Geological structure of the wider area of Makljenovac, Scale 1: 100,000 (Retrieved from: OGK OGK; Doboj_L 34-109)
Figure 3 Longitudinal engineeringgeological and geotechnical section 1-1’ Retrieved from: Elaborate, 2014)
Figure 3 Longitudinal engineeringgeological and geotechnical section 1-1’ Retrieved from: Elaborate, 2014)
Figure 4 Engineering geological map (Retrieved from: Elaborate, 2014)
Figure 4 Engineering geological map (Retrieved from: Elaborate, 2014)
Figure 5 Calculation of factor stability in natural state Fs = 1,000. (Retrieved from: Zlatan T., Divel d.o.o. Sarajevo, 2014) To determine the relevant material parameters of the GS 1 cover material in its natural state, a back analysis was carried out in the Plaxis software package, Fig. 5.
Figure 5 Calculation of factor stability in natural state Fs = 1,000. (Retrieved from: Zlatan T., Divel d.o.o. Sarajevo, 2014) To determine the relevant material parameters of the GS 1 cover material in its natural state, a back analysis was carried out in the Plaxis software package, Fig. 5.
Figure 6 Calculation of factor stability after rehabilitation of landslide, Fs = 1,298. (Retrieved from: Zlatan T., Divel d.o.o. Sarajevo, 2014)
Figure 6 Calculation of factor stability after rehabilitation of landslide, Fs = 1,298. (Retrieved from: Zlatan T., Divel d.o.o. Sarajevo, 2014)
On the basis of the presented problems, as well as considering the mentioned possibilities of cheaper solutions, the following works are foreseen for landslide remediation (shown in Fig. 7): Figure 7 Geological structure of the wider area of Makljenovac, Scale 1: 100,000 (Retrieved from: Zlatan T. Divel d.o.o. Sarajevo, 2014)
On the basis of the presented problems, as well as considering the mentioned possibilities of cheaper solutions, the following works are foreseen for landslide remediation (shown in Fig. 7): Figure 7 Geological structure of the wider area of Makljenovac, Scale 1: 100,000 (Retrieved from: Zlatan T. Divel d.o.o. Sarajevo, 2014)
Figure 1 Map of runout distance of previous rockfall events occurred in December 2017
Figure 1 Map of runout distance of previous rockfall events occurred in December 2017
Figure 2 Source area of rockfalls
Figure 2 Source area of rockfalls
Figure 3 Kinetic energy values (95% confidence level) per raster cell for study area
Figure 3 Kinetic energy values (95% confidence level) per raster cell for study area
Figure 4 Increasing of kinetic energy values (95% confidence level) per raster cell along steepest descent (Figure 2) for simulated rockfall with block volume of 15 m3
Figure 4 Increasing of kinetic energy values (95% confidence level) per raster cell along steepest descent (Figure 2) for simulated rockfall with block volume of 15 m3
Figure 5 Variation of kinetic energy values (95% confidence level) per raster cell along railway. Maximum value is 7996 kJ [.Peternel, J.Jez, B.Milanic, A.Markelj, M.Kobal - Determination and studying rockfall hazard using process modelling in the case of rockfalls alon ‘ailway link between Renke - Zagorje (central Slovenia)
Figure 5 Variation of kinetic energy values (95% confidence level) per raster cell along railway. Maximum value is 7996 kJ [.Peternel, J.Jez, B.Milanic, A.Markelj, M.Kobal - Determination and studying rockfall hazard using process modelling in the case of rockfalls alon ‘ailway link between Renke - Zagorje (central Slovenia)
Figure 6 Normal passage heights (95% confidence level) per raster cell for study area Normal passage heights (95% confidence level) per raster cell ranges from 0.9 m to 44.7 m (cliffs above railway). Mean value of normal passage heights equals 5.1 m. Along railway path normal passage heights (95% confidence level) per raster cell ranges from 0.0 m to 22.9 with mean value of 6.6 m (Figure 6 and Figure 7).
Figure 6 Normal passage heights (95% confidence level) per raster cell for study area Normal passage heights (95% confidence level) per raster cell ranges from 0.9 m to 44.7 m (cliffs above railway). Mean value of normal passage heights equals 5.1 m. Along railway path normal passage heights (95% confidence level) per raster cell ranges from 0.0 m to 22.9 with mean value of 6.6 m (Figure 6 and Figure 7).
Figure 7 Variation of normal passage heights (95% confidence level) per raster cell along railway. Maximum value is 22.9 m
Figure 7 Variation of normal passage heights (95% confidence level) per raster cell along railway. Maximum value is 22.9 m
evenly cover the area of operation. The landmarks are set using a Topcon GPS GNSS device with a link to the CROPOS system that provides 2-3cm real-time positioning accuracy in all three dimensions. Figure 1 Digital orthophoto (DOF)
evenly cover the area of operation. The landmarks are set using a Topcon GPS GNSS device with a link to the CROPOS system that provides 2-3cm real-time positioning accuracy in all three dimensions. Figure 1 Digital orthophoto (DOF)
Figure 2 Basic elements of drilling
Figure 2 Basic elements of drilling
Figure 4 Drilling profile of B5 Figure 5 Results of the Proctor test for the sample from SJ-1
Figure 4 Drilling profile of B5 Figure 5 Results of the Proctor test for the sample from SJ-1
Figure 6 Results of the Proctor test for the sample from SJ-2.
Figure 6 Results of the Proctor test for the sample from SJ-2.
The thickness of the loose cover in zone VPo (and VPo +) is similar to that in zones VPi (between 5 and 5.5 m), but it is not significantly smaller in zones VP2 (4.0 m), only in zones VP3 and then in zones VP4 decreases rapidly (1.0 to 1.5 m). However, the VP3 and VP4 zones are too close to the upper edge of the landslide, so we can exclude them from considerations that focus on the route selection of the supporting foot embankment. All in all, it turns out that the route of the future supporting foot embankment (as a vital component of the remedial solution) should be placed in the zone of the height plateau VP1 where the mean depth of the ST is approximately 5.0 m and the mean height of the terrain (from the aspect of exploratory wells) is approx. 160 m n.m. foe oe ee n,n ee. oo rs | The clay slope stability check was performed through a computational model compliant with Slide 6.0 (Rockscience Inc.), which uses the limit equilibrium criterion to calculate slip factors. The Mohr-Coulomb Model (MCM) was used to describe soil behavior. The input parameters used in the program are given in the following tables.
The thickness of the loose cover in zone VPo (and VPo +) is similar to that in zones VPi (between 5 and 5.5 m), but it is not significantly smaller in zones VP2 (4.0 m), only in zones VP3 and then in zones VP4 decreases rapidly (1.0 to 1.5 m). However, the VP3 and VP4 zones are too close to the upper edge of the landslide, so we can exclude them from considerations that focus on the route selection of the supporting foot embankment. All in all, it turns out that the route of the future supporting foot embankment (as a vital component of the remedial solution) should be placed in the zone of the height plateau VP1 where the mean depth of the ST is approximately 5.0 m and the mean height of the terrain (from the aspect of exploratory wells) is approx. 160 m n.m. foe oe ee n,n ee. oo rs | The clay slope stability check was performed through a computational model compliant with Slide 6.0 (Rockscience Inc.), which uses the limit equilibrium criterion to calculate slip factors. The Mohr-Coulomb Model (MCM) was used to describe soil behavior. The input parameters used in the program are given in the following tables.
Table 2 Input parameters for soil As a critical slope profile, the PPII-6 profile was selected for the purpose of computational stability analysis, modeled such that the characteristic geotechnical conditions (soil thinning scheme, soil materials, and their parameters and slope contour geometry) gradually followed successive chronological changes that reflected expected effect of remedial measures. The following table (table 3) can be used to track the changes in question: Table 2 Modeled seotechnical conditions
Table 2 Input parameters for soil As a critical slope profile, the PPII-6 profile was selected for the purpose of computational stability analysis, modeled such that the characteristic geotechnical conditions (soil thinning scheme, soil materials, and their parameters and slope contour geometry) gradually followed successive chronological changes that reflected expected effect of remedial measures. The following table (table 3) can be used to track the changes in question: Table 2 Modeled seotechnical conditions
Figure 7 Current status (model A)
Figure 7 Current status (model A)
Figure 8 Drain installation (model B1)
Figure 8 Drain installation (model B1)
Figure 9 Construction of floor embankments, that is the embankments
Figure 9 Construction of floor embankments, that is the embankments
Figure 1 Successive step-by-step sloping of the slope surface (preparation for finishing the slopes) - schematic diagram
Figure 1 Successive step-by-step sloping of the slope surface (preparation for finishing the slopes) - schematic diagram
Figure 12 Schematic representation of the foot "foundation" of the hillside slope of the embankments
Figure 12 Schematic representation of the foot "foundation" of the hillside slope of the embankments
Figure 13 Construction of an embankment during clay pit remediation. A sandy layer of lime is visible, which is compacted with “hedges” before installing the next layer
Figure 13 Construction of an embankment during clay pit remediation. A sandy layer of lime is visible, which is compacted with “hedges” before installing the next layer
Figure 14 Test results of embedded material in the embankments (excerpt from the complete test table)
Figure 14 Test results of embedded material in the embankments (excerpt from the complete test table)
Figure 15 Comparative view of the northern part of the clay pit (a) Prior to remediation work (b) After the rehabilitation works have been carried out (Phase II) - 31.X.2018. References
Figure 15 Comparative view of the northern part of the clay pit (a) Prior to remediation work (b) After the rehabilitation works have been carried out (Phase II) - 31.X.2018. References
Figure 1 Red dot marks the location of the studied area (map source: www.geopedia.si) landslide body and the proximate hinterland. Absolute displacement rates were interpreted based on geotechnical monitoring using an inclinometer installed in the CK-2/17 borehole (39 m deep), while ground water levels were measured in the Ck-1/17 borehole (40 m deep equipped with a piezometer. Displacement profiles obtained from the inclinometers show magnitude, depth, direction and rate of ground movement. Geophysica measurements were performed behind the landslide crown cracks in the nearest vicinity of the geomechanica boreholes. According to the expected lithology and target depths, the Electrical resistivity tomography (ERT) and Seismic refraction tomography (SRT) profiles in the ENE- WSW direction were selected (Fig. 3).
Figure 1 Red dot marks the location of the studied area (map source: www.geopedia.si) landslide body and the proximate hinterland. Absolute displacement rates were interpreted based on geotechnical monitoring using an inclinometer installed in the CK-2/17 borehole (39 m deep), while ground water levels were measured in the Ck-1/17 borehole (40 m deep equipped with a piezometer. Displacement profiles obtained from the inclinometers show magnitude, depth, direction and rate of ground movement. Geophysica measurements were performed behind the landslide crown cracks in the nearest vicinity of the geomechanica boreholes. According to the expected lithology and target depths, the Electrical resistivity tomography (ERT) and Seismic refraction tomography (SRT) profiles in the ENE- WSW direction were selected (Fig. 3).
Figure 2 Cikla landslide extent and place of meterial accumulation in the Cikla stream.
Figure 2 Cikla landslide extent and place of meterial accumulation in the Cikla stream.
Figure 4 (a) open cracks in the upper part of the Cikla landslide; (b) active movements in the middle part; (c) sediment of the April 2017 debris flow event in the Cikla stream
Figure 4 (a) open cracks in the upper part of the Cikla landslide; (b) active movements in the middle part; (c) sediment of the April 2017 debris flow event in the Cikla stream
Figure 3 Map of applied methods. Inclinometric borehole = CK- 1; piezometric borehole = CK-2.
Figure 3 Map of applied methods. Inclinometric borehole = CK- 1; piezometric borehole = CK-2.
Figure 5 Borehole CK-2/17 log (right) and results of four inclinometer measurements (campaigns from 12/10/2017 to 19/4/2019) (left) Alluvial fans in the valleys due to their morphology usually appear very attractive and suitable for settlement. At the same time, planners and investors often forget or ignore the fact that these sedimentary bodies were formed during extensive torrential and/or mass flow processes in the past. The KoroSka Bela alluvial fan is also just such a case. The sudden movement of large landslide masses and the transformation of the sediment-water mixture into the debris flow could pose serious threat for the settlement. Therefore, the planning of mitigation measures to protect the settlement in the future will pose a significant challenge. For this reason, an active monitoring of the landslide is planned in the future, while effective mitigation measures and_ possible construction works can be based on additional detailed geotechnical studies and stability analyses.
Figure 5 Borehole CK-2/17 log (right) and results of four inclinometer measurements (campaigns from 12/10/2017 to 19/4/2019) (left) Alluvial fans in the valleys due to their morphology usually appear very attractive and suitable for settlement. At the same time, planners and investors often forget or ignore the fact that these sedimentary bodies were formed during extensive torrential and/or mass flow processes in the past. The KoroSka Bela alluvial fan is also just such a case. The sudden movement of large landslide masses and the transformation of the sediment-water mixture into the debris flow could pose serious threat for the settlement. Therefore, the planning of mitigation measures to protect the settlement in the future will pose a significant challenge. For this reason, an active monitoring of the landslide is planned in the future, while effective mitigation measures and_ possible construction works can be based on additional detailed geotechnical studies and stability analyses.
Figure 1 Disaster, risk and crisis management cycle (FAO, 2004) Figure 1 shows risk management cycle that is divided into two parts, before and after disaster occurrence. The main difference between processes before and after the disaster is that first belong to protection and latter to recovery.
Figure 1 Disaster, risk and crisis management cycle (FAO, 2004) Figure 1 shows risk management cycle that is divided into two parts, before and after disaster occurrence. The main difference between processes before and after the disaster is that first belong to protection and latter to recovery.
Figure 2 Results of risk evaluation in the form of risk matrix for: (a) landslide hazard with the worst possible consequences (circle); and (b) landslide hazard with the most probable unfavourable consequences (triangle).
Figure 2 Results of risk evaluation in the form of risk matrix for: (a) landslide hazard with the worst possible consequences (circle); and (b) landslide hazard with the most probable unfavourable consequences (triangle).
Figure 1 A view at the City of Omis and limestone slopes above the town. The City of Omi’, Croatia, was threatened by numerous rockfall occurrences in the past that caused significant damages at residential structures and infrastructure (Arbanas et al., 2019). The old town of Omi8, is situated in the middle part of the Adriatic coast, at the mouth of the Cetina River in the toe of high limestone cliffs (Figure 1) and it is very exposed to high rockfall hazards. The rockfall events along the limestone slopes were caused by unfavorable rock mass characteristics, rock mass weathering in combination with heavy rainfalls and the man-made influences (Arbanas et al., 2012). 1) University of Rijeka, Faculty of Civil Engineering, Rijeka, Radmile Matejci¢ 3, zeljko.arbanas@gradri.uniri.hr
Figure 1 A view at the City of Omis and limestone slopes above the town. The City of Omi’, Croatia, was threatened by numerous rockfall occurrences in the past that caused significant damages at residential structures and infrastructure (Arbanas et al., 2019). The old town of Omi8, is situated in the middle part of the Adriatic coast, at the mouth of the Cetina River in the toe of high limestone cliffs (Figure 1) and it is very exposed to high rockfall hazards. The rockfall events along the limestone slopes were caused by unfavorable rock mass characteristics, rock mass weathering in combination with heavy rainfalls and the man-made influences (Arbanas et al., 2012). 1) University of Rijeka, Faculty of Civil Engineering, Rijeka, Radmile Matejci¢ 3, zeljko.arbanas@gradri.uniri.hr
Figure 2 Fallen rock block came through the roof in the house in January 2012 (www.24sata.hr).
Figure 2 Fallen rock block came through the roof in the house in January 2012 (www.24sata.hr).
Figure 3 3DPC provided by TLS and SfM techniques. A view at the slope (down); a layout over the middle part of the town (left up). Detailed engineering geological mapping was carried out on the limited parts of the rock slopes at the parts where it was possible to physically access to the slopes. Because of very steep to vertical slopes, mapping and determination of rock mass characteristics was carried out by remote sensing on a high resolution 3DPC (Riquelme et al., 2016). Analysis of high resolution 3DPC enable the main characteristics of rock mass in a slope necessary for further analyses of rockfall source and rockfall mechanism such as discontinuity orientation (Lato and Voge, 2012; Riquelme et al., 2014), discontinuity spacing (Riquelme et al., 2015), discontinuity persistence (Riquelme et al., 2018) as well as rock block volumes (Chen et al., 2017). All these data were combined with engineering geological mapping carried out in the field.
Figure 3 3DPC provided by TLS and SfM techniques. A view at the slope (down); a layout over the middle part of the town (left up). Detailed engineering geological mapping was carried out on the limited parts of the rock slopes at the parts where it was possible to physically access to the slopes. Because of very steep to vertical slopes, mapping and determination of rock mass characteristics was carried out by remote sensing on a high resolution 3DPC (Riquelme et al., 2016). Analysis of high resolution 3DPC enable the main characteristics of rock mass in a slope necessary for further analyses of rockfall source and rockfall mechanism such as discontinuity orientation (Lato and Voge, 2012; Riquelme et al., 2014), discontinuity spacing (Riquelme et al., 2015), discontinuity persistence (Riquelme et al., 2018) as well as rock block volumes (Chen et al., 2017). All these data were combined with engineering geological mapping carried out in the field.
simulation was conducted for each of 8 location of rockfall protection barriers, Additional check was carried out using RockFall software and 2D simulations for critical points identified by 3D simulations. Both 2D and 3D simulations enabled precise defining of rockfall protection barrier positions and their heights and energy absorption capacity. Conducted simulations pointed out on the need for installation of additional rockfall protection barrier at position where rock blocks can leap over a barrier. Position of each barrier pole was precisely determined and defined in high resolution DTM and 3DPC that enabled clear positioning of protection structures in construction stage Figures 4 and 5). Stability analyses for potentially unstable rock blocks identified in the main design were conducted that defined necessary support system for each analyzed rock block and precisely determined and defined elements of support system in high resolution DTM and 3DPC. RocPro3D and RockFall software were employed to conduct the rockfall simulation. RocPro3D is a software that enables 3D simulation of rockfall trajectories, using a probabilistic approach that considers a rock block volume and form, soil properties, irregularities of slope surface and restitution coefficient. RocPro3D for simulation uses DTM developed from 3DPC. RocPro3D was used to define and check precise locations, heights and energy absorption capacity of rockfall protection barriers. More than 1.000 Figure 4 An aerial view at the rockfall protection barriers at limestone slopes above the City of Omi8 (left up), a view at the rockfall protection barriers of 2000 kJ capacity at limestone slopes above the center of the City of Omi8 (right up); an aerial view at the rockfall protection barrier of 2000 kJ capacity in the ravine above the City of Omi8 (left down); a view at the rock mass support systems including rock bolts in combination with steel ropes and steel wire meshes at limestone slope below the Peovica Fortress (right down).
simulation was conducted for each of 8 location of rockfall protection barriers, Additional check was carried out using RockFall software and 2D simulations for critical points identified by 3D simulations. Both 2D and 3D simulations enabled precise defining of rockfall protection barrier positions and their heights and energy absorption capacity. Conducted simulations pointed out on the need for installation of additional rockfall protection barrier at position where rock blocks can leap over a barrier. Position of each barrier pole was precisely determined and defined in high resolution DTM and 3DPC that enabled clear positioning of protection structures in construction stage Figures 4 and 5). Stability analyses for potentially unstable rock blocks identified in the main design were conducted that defined necessary support system for each analyzed rock block and precisely determined and defined elements of support system in high resolution DTM and 3DPC. RocPro3D and RockFall software were employed to conduct the rockfall simulation. RocPro3D is a software that enables 3D simulation of rockfall trajectories, using a probabilistic approach that considers a rock block volume and form, soil properties, irregularities of slope surface and restitution coefficient. RocPro3D for simulation uses DTM developed from 3DPC. RocPro3D was used to define and check precise locations, heights and energy absorption capacity of rockfall protection barriers. More than 1.000 Figure 4 An aerial view at the rockfall protection barriers at limestone slopes above the City of Omi8 (left up), a view at the rockfall protection barriers of 2000 kJ capacity at limestone slopes above the center of the City of Omi8 (right up); an aerial view at the rockfall protection barrier of 2000 kJ capacity in the ravine above the City of Omi8 (left down); a view at the rock mass support systems including rock bolts in combination with steel ropes and steel wire meshes at limestone slope below the Peovica Fortress (right down).
GEOINVEST Grupa je vodeéa i najveca kompanija za realizaciju svih vrsta geotehni¢kih projekata u regiji, sa sjedistem u Ljubljani (Republika Slovenija) i tvrtkama u Varazdinu (Republika Hrvatska), Sarajevu (Bosna i Hercegovina) i Sremskoj Mitrovici (Republika Srbija). U sastava GEOINVEST Grupacije je i Geostroj d.o.0. Ljubljana za proizvodnju i odrzavanje geotehni¢ke opreme. Djelatnost firme: piloti, geotehni¢ka sidra, mlazno injektiranje — jet grouting, poboljSanje temeljnog tla, AB dijafragme, torkretiranje, gradevinske jame, geomehanicka istrazivanja.
GEOINVEST Grupa je vodeéa i najveca kompanija za realizaciju svih vrsta geotehni¢kih projekata u regiji, sa sjedistem u Ljubljani (Republika Slovenija) i tvrtkama u Varazdinu (Republika Hrvatska), Sarajevu (Bosna i Hercegovina) i Sremskoj Mitrovici (Republika Srbija). U sastava GEOINVEST Grupacije je i Geostroj d.o.0. Ljubljana za proizvodnju i odrzavanje geotehni¢ke opreme. Djelatnost firme: piloti, geotehni¢ka sidra, mlazno injektiranje — jet grouting, poboljSanje temeljnog tla, AB dijafragme, torkretiranje, gradevinske jame, geomehanicka istrazivanja.
Temelj na kojem gradimo nasu tvrtku je kvaliteta usluge, poStivanje ugovorenih rokova, fleksibilnost prema Investitorima te trziSno prihvatljive cijene.
Temelj na kojem gradimo nasu tvrtku je kvaliteta usluge, poStivanje ugovorenih rokova, fleksibilnost prema Investitorima te trziSno prihvatljive cijene.
www.geoinvest.si, www.geoinvest.ba, www.geoinvest.hr, www.geoinvest.rs
www.geoinvest.si, www.geoinvest.ba, www.geoinvest.hr, www.geoinvest.rs
DRUSTVO ZA PROJEKTOVANJE, SAVJETOVANJE | ISTRAZIVANJE U GRADEVINARSTVU
DRUSTVO ZA PROJEKTOVANJE, SAVJETOVANJE | ISTRAZIVANJE U GRADEVINARSTVU

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    gerardo herrera

    Remote Sensing of Environment, 2013

    In this work it is demonstrated how the combination of multi-sensor and multi-temporal SAR data improves the monitoring capacity of very slow landslides. The study area is the Upper Tena Valley (Central Spanish Pyrenees), where mostly very slow earth flows, have caused direct damage estimated at approximately 15 M€ in the last decade. The advanced DInSAR processing of ascending orbit ALOS PALSAR images (2006)(2007)(2008)(2009)(2010) and descending orbit ERS & Envisat (2001-2007 and TerraSAR-X (2008) datasets, has provided heterogeneous displacement velocity measurements. The projection along the steepest slope of LOS displacements reduces the geometrical differences introduced by each satellite. These results were compared and validated with available D-GPS measurements. In a second step PS displacement data are combined with a landslide inventory, increasing the number of monitored landslides with sufficient PS from 4% to 19%, obtained from C-and X-band data, to 38% of the total (294). Finally, the retrieved multi-sensor landslides velocities are classified with respect to the magnitude of road damages that occurred in the 2008-2010 period. At local scale, the combination of multi-sensor data was useful to differentiate different landslide displacement directions, to measure different velocity patterns within the same moving mass, and to distinguish the slower (natural) and faster (human induced) landslides. The analysis of displacement time series permitted to evaluate the acceleration caused by a destabilising anthropogenic change, and the correlation between displacement variability and seasonal precipitation and melting.

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    Monitoring of remedial works performance on landslide-affected areas through ground- and satellite-based techniques
    Massimo Ramondini

    CATENA

    Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques have been repeatedly proved as an effective tool for monitoring built environments affected by geological hazards. In this paper, it is described how the Coherent Pixel Technique (CPT) approach has been successfully applied to assess the response of an unstable slope to the different phases of remedial works following a landslide event. The CPT technique was performed on 59 COSMO-SkyMed images (May 2011-August 2016) centered on the Quercianella settlement (a small hamlet of Livorno municipality, Tuscany, Italy), where the reactivation of a dormant shallow slide had occurred in March 2011 and, hereafter, a geotechnical intervention, designed with the aim of mitigating the risks, has been conducted from August 2013 lasting thirteen months. The time series of CPT results show a deformation pattern characterized by sudden accelerations (up to 21 mm in few months) in correspondence of the beginning of the interventions, during which the area has been excavated to install a drainage well, followed by mild decelerations and resulting from the stabilization of the area after the conclusion of the works. In particular, the integration of ground-based subsurface monitoring (inclinometers and piezometers) and DInSAR superficial data have provided consistent results for landslide characterization and helped in defining the state of activity and the areal distribution of the sliding surface. Moreover, the performance of remedial works installed in the landslide-affected area has been observed, showing the stabilization in the upper part of the hamlet and the still ongoing movement in the lower part. The combined monitoring system led 2 also the geotechnical company in charge to design further stabilization works as to preserve buildings and roads in the still moving area. Therefore, the integration of remote sensing techniques and in situ instruments represents a timely and cost-efficient solution for monitoring intervention works, opening new perspectives to engineering design for the stabilization of unstable slopes.

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    Down-slope combination of orbital and ground-based DInSAR for the efficient monitoring of slow-moving landslides
    Ruben Iglesias

    This paper seeks to demonstrate that radar-based remote sensing techniques are as effective as conventional geotechnical ones for geo-hazard assessment and mitigation. Concretely, this work encourages the proper combination of differential synthetic aperture radar (SAR) interferometry (DInSAR) results, using high-resolution X-band SAR data coming from orbital and ground-based SAR sensors, for the efficient monitoring of slow-moving landslides.

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    DInSAR techniques for monitoring slow-moving landslides
    Domenico Calcaterra

    Remote sensing is being frequently applied in recent years to monitor slope instability phenomena. Since satellite images cover wide territories with frequent passages, their use seems to be extremely promising in terms of landslide monitoring. Among the different techniques proposed, the Permanent Scatterers (PS) technique is a multi-interferogram approach for processing SAR data that allows to overcome the limitations of the traditional DInSAR. In the present paper, some preliminary considerations are developed, deriving from the use of the PS technique in a small town of Campania region, Italy, where some slow-moving complex landslides affect the urban area. The SAR data have been relieved from the ERS-1 and ERS-2 sensors of the European Space Agency in the 1992-2001 time span. The SAR data are being compared with field evidence of structural damages to urban buildings and infrastructures, in view of further field-based observations, integrated with classical site monitoring data.

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    Spatiotemporal monitoring of surface motions using DInSAR techniques integrated with geological information: a case study of an iron mine in the Amazon region using TerraSAR-X and RADARSAT-2 data
    JosÉ Mura

    Environmental Earth Sciences, 2018

    Instabilities are extremely common in the iron open-pit mines located in the Carajás mineral province, the world´s largest iron reserves located in the Brazilian Amazon. Due to deep excavations in rock products of low geomechanical quality, heavy precipitation, and blasting practices, mining operations in the area present surface displacements that potentially lead to slope instabilities with several risks (personnel, equipment, mining infrastructure, etc.). This paper presents the results related to the N5E mine based on DInSAR Time Series (DTS) and Persistent Scatterer Interferometry (PSI) using a temporal series of 33 StripMap TerraSAR-X (SM TSX) images, and geological information provided from a 3D photointerpretation of an SM TSX and Ultra-Fine RADARSAT-2 (UF RST) stereo-pair, calibrated with field data. Measurement point (DTS, PSI) results were compared with in situ geodetic survey information (total station/prism measurements) and showed good agreement indicating that most of the mine can be considered stable during the period of the TSX coverage. The highest accumulated displacements were spatially related to a thematic unit mapped as a landfill. For other sectors of the mine, lower deformation rates were related to photointerpreted lineaments related to the Carajás fault system suggesting that geological structures can play a key role in controlling some surface displacements. The investigation demonstrated that the strategy based on the use of DTS and PSI techniques integrated with geological data provided a synoptic view of the deformation process that affected the mine. The approach was relevant for ground displacements monitoring of the study area with DInSAR results compared with in situ geodetic measurements showing good statistical correlation.

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    Analysis of Geohazards in Road Construction
    mato uljarevic

    Proceedings of the 4th Regional Symposium on Landslides in the Adriatic - Balkan Region, 2019

    Monitoring is important for assessing the stability of the ground and for confirming the validity of the design during the construction and operation of structures. The ideal monitoring system for projects in Rock and Geotechnical Engineering would be able to monitor the behavior of small to extensive areas continuously and automatically with high accuracy. In addition, the costs would be low and the system would be easy to handle. Satellite technology has the potential to realize the above monitoring system by combining it with conventional geotechnical instruments. In this paper, satellite technology for displacement monitoring, i.e., GPS and SAR, is firstly outlined and then the concept of spatiotemporal continuous displacement monitoring is introduced. The use of both satellite technology and geotechnical instruments is effective for geotechnical monitoring. Practical applications of GPS for landslide monitoring and collaborative researches using DInSAR with Balkan countries are described.

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    Landslide hazard analysis in national-scale for landslide risk assessment in Croatia
    Zeljko Arbanas

    2019

    Monitoring is important for assessing the stability of the ground and for confirming the validity of the design during the construction and operation of structures. The ideal monitoring system for projects in Rock and Geotechnical Engineering would be able to monitor the behavior of small to extensive areas continuously and automatically with high accuracy. In addition, the costs would be low and the system would be easy to handle. Satellite technology has the potential to realize the above monitoring system by combining it with conventional geotechnical instruments. In this paper, satellite technology for displacement monitoring, i.e., GPS and SAR, is firstly outlined and then the concept of spatiotemporal continuous displacement monitoring is introduced. The use of both satellite technology and geotechnical instruments is effective for geotechnical monitoring. Practical applications of GPS for landslide monitoring and collaborative researches using DInSAR with Balkan countries are described.

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    Landslide risk management in Croatia: Current state
    Zeljko Arbanas

    2019

    Monitoring is important for assessing the stability of the ground and for confirming the validity of the design during the construction and operation of structures. The ideal monitoring system for projects in Rock and Geotechnical Engineering would be able to monitor the behavior of small to extensive areas continuously and automatically with high accuracy. In addition, the costs would be low and the system would be easy to handle. Satellite technology has the potential to realize the above monitoring system by combining it with conventional geotechnical instruments. In this paper, satellite technology for displacement monitoring, i.e., GPS and SAR, is firstly outlined and then the concept of spatiotemporal continuous displacement monitoring is introduced. The use of both satellite technology and geotechnical instruments is effective for geotechnical monitoring. Practical applications of GPS for landslide monitoring and collaborative researches using DInSAR with Balkan countries are described.

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