Volume 10, Number 4 (July 2023):4721-4728, doi:10.15243/jdmlm.2023.104.4721 ISSN: 2339-076X (p); 2502-2458 (e), www.jdmlm.ub.ac.id
Open Access 4721 Research Article
Spatial distribution of landslide potentials and landslide vulnerability in Sukawana and Awan Villages, Kintamani District, Bangli Regency, Bali Province
Made Sri Sumarniasih*,I Gusti Ayu Sintya Dewi, I Wayan Diara
Agroecotechnology Study Program, Faculty of Agriculture, Udayana University, Jl. PB. Sudirman, Denpasar 80232, Bali, Indonesia
*corresponding author: [email protected]
Abstract Article history:
Received 11 January 2023 Accepted 8 March 2023 Published 1 July 2023
Landslide is one of the disasters that often occurs in Indonesia. Bangli is one of the areas in Bali with a high potential for landslides, especially in Kintamani. This study aimed to identify the potential and vulnerability of landslides in Sukawana and Awan Villages, Kintamani District, Bangli Regency. This study used survey and scoring methods according to the Natural Disaster Center at Gadjah Mada University for the parameters that cause landslides, namely, landform, rainfall, slope, geological structure, land use, and soil type. The landslide potential in Sukawana Village is low landslide potential with an area of 71.97 ha (1.81%) in Banjar Kubusalya, a medium potential with an area of 2,198.07 ha (55.30%) in Banjar Kubusalya, Banjar Sukawana and Banjar Paketan and high potential with an area of 932.81 ha (23.47%) located in Banjar Kuum and Banjar Sukawana. Awan Village has medium potential with an area of 772.20 ha (19.43%). For areas with high vulnerability, settlements are 110.96 ha (69.97%) in Sukawana Village, and the road network is dominated by local roads along 28.82 km (34.81%), which are in Sukawana Village.
Keywords:
Kintamani District landslide potential landslide vulnerability
To cite this article: Sumarniasih, M.S., Dewi, I.G.A.S. and Diara, I.W. 2023. Spatial distribution of landslide potentials and landslide vulnerability in Sukawana and Awan Village, Kintamani district, Bangli Regency, Bali Province. Journal of Degraded and Mining Lands Management 10(4):4721-4728, doi:10.15243/jdmlm.2023.104.4721.
Introduction
According to the Regulation of the National Disaster Management Agency number 4 of 2008 (BNPB, 2008), the community, as the initial actors of disaster management as well as disaster victims, must be able within certain limits to handle disasters, so it is hoped that disasters will not develop to a larger scale.
Communities need an understanding of efforts to deal with the risk of landslides that can threaten safety. The increased potential for landslides is due to an increase in population and community activities in managing the environment. This means that public awareness of efforts to reduce the risk of landslides is very important. According to Law Number 24 of 2007 (BNPB, 2008), disaster is an event or series of events
that threatens and disrupts people's lives and livelihoods caused by natural factors and or non- natural factors as well as human factors resulting in human casualties, environmental damage, loss of property, and psychological impact. Furthermore, in Government Regulation (PP) No. 21 of 2008 (BNPB, 2008), disaster risk reduction is a series of efforts to reduce disaster risk, both through physical development and awareness and capacity building in dealing with the threat of landslides (Ndah and Odihi, 2017).
Landslide is one of the geological disasters that often occur in Indonesia (Karnawati et al., 2011;Susilo et al., 2020). Landslide is the movement of soil or rock masses, or a mixture of both, down or out of a slope as a result of disturbing the stability of the soil or rock
Open Access 4722 making up the slope (Yalcin, 2007; Handrianto and
Farhan, 2019; Wang et al., 2022). Landslides can be caused by several factors; human factors and natural factors. In principle, landslides occur when the restraining force is less than the driving force. The trigger for this ground movement is high rainfall and slope (BNPB, 2008). Landslide disasters frequently occur in Indonesia, especially during the rainy season, which is also supported by changes in land use which causes landslide disasters to increase. The masses that move in landslides are large masses so that they often cause casualties in the form of damage to the environment, agricultural land, settlements, and infrastructure, as well as property and even loss of human life (Alexander, 2005; Nugroho, 2016;
Hadmoko et al., 2017). In 2017 Bangli Regency was hit by a landslide disaster due to high rainfall coupled with slope conditions with many settlements which resulted in 12 deaths, 2 serious injuries and 2 minor injuries, as well as causing substantial material losses.
In Kintamani Regency, there are two villages that have the potential for landslides, namely Sukawana Village and Awan Village (BNPB, 2017).
This study aimed to determine the potential and vulnerability of landslides in Sukawana Village and Awan Village.
Materials and Methods
The study used a survey method by conducting field checks, observing, recording, documenting, and interviewing local residents to find out the location of landslides and the frequency of landslides at each point found and using secondary data. Determination of
landslide hazard potential used a scoring method that referred to the UGM Center for Natural Disaster Studies (PSBA UGM, 2001). The scoring parameters that affect landslides are rainfall, slope, geological structure, landform, soil type, and land use. A map of landslide-prone areas was made by combining a map of potential landslides with a map of settlements and a map of the road network.
Research sites
The research was conducted in Sukawana Village and Awan Village, Kintamani District, Bangli Regency (Figure 1).
Tools and materials
The tools used were a set of laptops for storing and processing data, mobile cameras for documenting activities in the field, GPS (Global Positioning System), QGIS (Quantum Geographic Information System) 3.6.3 software, Microsoft Word 2013 software, and Microsoft Exel 2013 software. The materials used in this study were RBI (Rupabumi Indonesia) maps, DEMNAS (Digital Elevation Model Nasional) 8 m resolution, rainfall data, soil type maps, geological structure maps, and landform maps.
Research stages Creating thematic maps
Thematic maps were prepared to make it easier to analyze landslide potential from data that are not yet in the form of shapefiles. Some thematic maps were made, such as rainfall maps, slope maps, geological structure maps, and landform maps.
Figure 1. Research locations in Sukawana Village and Awan Village.
Open Access 4723 Data analysis
The landslide hazard assessment in this study was parametric, where each parameter was classified into
several classes which describe the magnitude of the contribution to the landslide process. The scores of each class for each parameter are presented in Tables 1, 2, 3, 4, 5 and 6.
Table 1. Landform score value.
No Landform Score
1 Alluvial Plain 1
2 Limestone Hills, Caldera, Vulcan Foot Slopes, Hills, Lower Slopes 2
3 Lower Slopes of Vulkan, Lower Slopes of Hills, Middle Slopes, Plains Between Mountains, Steep Slopes of Mountains
3 4 Middle Slope of the Volkan, Upper Slope of the Hills, Volkan Slope 4
5 Volkan Cone, Volkan Upper Slope, Volkan Lungur, Caldera Valley 5
Source: UGM Center for Natural Disaster Studies (UGM PSBA, 2001).
Table 2. Slope score value.
No Slope (%) Score
1 0-8 Flat 1
2 8-15 Sloping 2
3 15-30 Rather steep 3
4 30-45 Steep 4
5 >45 Very steep 5
Source: UGM Center for Natural Disaster Studies (UGM PSBA, 2001).
Table 3. Rainfall score value.
No Rainfall (mm year-1) Score
1 <1,500 1
2 1,500-1,800 2
3 1,800-2,100 3
4 2,100-2,400 4
5 >2,400 5
Source: UGM Center for Natural Disaster Studies (UGM PSBA, 2001).
Table 4. Land use score value.
No Land Use Score
1 Forests, mangroves, swamps, irrigated rice fields, ponds, salt, sand
1
2 Rainfed fields 2
3 Buildings, settlements 3
4 Shrubs, gardens/plantations 4 5 Grass, vacant land, moor/field 5 Source: UGM Center for Natural Disaster Studies (UGM PSBA, 2001).
Table 5. Geological structure score value.
No Geological Structure Score
1 Horizontal 1
2 Horizontal/Tilt 2
3 Tilt 3
4 Cracks 4
5 Steep oblique 5
Source: UGM Center for Natural Disaster Studies (UGM PSBA, 2001).
Table 6. Soil type score value.
No Soil Type Score
1 Mediterranean Brown, Mediterranean Reddish Brown 1
2 Yellowish Brown Latosol, Reddish Brown Latosol and Litosol 2
3 Brown Latosol and Litosol, Gray Brown Alluvial, Hydromorphic Alluvial 3 4 Brown Regosol, Yellowish Brown Regosol, Gray Brown Regosol, Humus Regosol, Gray
Regosol
4
5 Andosol Gray Brown 5
Source: UGM Center for Natural Disaster Studies (UGM PSBA, 2001).
The landslide potential score was obtained by adding up all the parameters that cause landslides above using the formula below (PSBA UGM, 2001). The landslide
potential score is then classified to obtain a landslide potential class. Classification of potential landslides is presented in Table 7.
Landslide Potential Score = (6 Score BL) + (5 Score KL) + (5 Score CH) + (4 Score PL) + (3 Score SG) + (2 Score MT)
where BL = land form, KL = slope, CH = rainfall, PL= land use, SG = geological structure, and MT = type.
Open Access 4724 Table 7. Landslide potential classification.
No Landslide potential score
Landslide Potential Classification
1 <40 No Potential
2 40-60 Low Potential
3 60-90 Moderate Potential
4 >100 High Potential
Overlay
The determination of landslide potential was analyzed using QGIS 3.6.3 software. The overlay method analyzes and integrates two or more different spatial data to obtain landslide potential maps using several maps that become landslide parameters.
Mapping landslide-prone areas
Making a map of landslide-prone areas is an overlapping stage between a potential landslide map with a map of settlements and a map of the road network to find out whether the location of the distribution of landslide points is close to residential areas and the road network or not.
Results and Discussion Potential for landslide
Based on the results of the landslide potential analysis, it is known that the high landslide potential class is located in Sukawana Village, with an area of 932.81 ha (23.47%). The moderate landslide potential class is located in two villages, namely Sukawana Village and Awan Village, with an area of 2,198.07 ha (55.30%) respectively in Sukawana Village and 772.20 ha (19.43%) in Awan Village, areas with low-class potential is located in Sukawana Village with an area of 71.97 ha (1.81%).
The vulnerability of landslides in the study area depends on the presence or absence of infrastructure and human settlements. The results of the analysis
showed that the total area of landslide-prone settlements is 158.59 ha, while the total area of landslide-prone roads is 82.79 km long. For high potential landslide-prone settlements are in Sukawana Village, with an area of 18.21 ha (11.48%). The medium potential for landslide-prone settlements is in Sukawana Village and Awan Village (55 %).
For the analysis of landslide-prone roads are divided into three, namely local roads, footpaths and collector roads. In Sukawana Village, there are two local roads, namely local roads with a medium length of 28.82 km (34.81%) and local roads with a high potential of 19.76 km (23.86%). The local road in Awan Village has a moderate potential of 13.88 km (16.77%). There are two potentials for footpaths in Sukawana Village, namely a medium potential of 12.72 km (15.36%) and a high potential of 3.82 km (4.61%). In Desa Awan, the trail has a moderate potential of 0.02 km (0.03%). The collector road has a medium potential of 3.16 meters (3.81%) and a high potential of 0.62 meters (0.74%) in Sukawana Village.
The scores and classes of potential landslides located in Sukawana Village and Awan Village are presented in Table 8. The results of the analysis of population settlements and landslide-prone road networks are presented in Tables 9 and 10. The spatial distribution of landslide potential is shown in Figure 2, while the spatial distribution of landslide vulnerability is shown in Figure 3.
The area with low potential for landslides is Sukawana Village, with an area of 71.97 ha (1.81%) with land use types dominated by dryland forest and Regosol Brown soil types. The landform of this area is on the upper slopes of the volcano with flat slopes (0-8%), with rainfall ranging from 1,800-2,100 mm year-1. This area has a low potential for landslides because it has flat slopes where the velocity of water flow is lower than steep slopes. Supported by land use dominated by forests, tree roots in the forest can hold the soil and can absorb rainwater that falls so as to prevent landslides.
Table 8. Landslide potential class.
No Landslide Potential Village Area (ha) Percentage (%)
1 Low Potential Sukawana 71.97 1.81
2 Moderate Potential Awan 772.20 19.43
Sukawana 2,198.81 55.30
3 High Potential Sukawana 932.81 23.47
Total Area 3,975.05 100.00
Table 9. Landslide prone settlements.
No Village Landslide Category Area (ha) Percentage (%)
1 Awan Low Potential 29.42 18.55
2 Sukawana Moderate Potential 110.96 69.97
3 Sukawana High Potential 18.21 11.48
Total Area 158.59 100.00
Open Access 4725 Table 10. Landslide prone road network.
No Road Type Landslide Category Village Long (km) Percentage Long (%)
1 Local Road Moderate Potential Awan 13.88 16.77
2 Local Road Moderate Potential Sukawana 28.82 34.81
3 Local Road High Potential Sukawana 19.76 23.86
4 Collector Street Moderate Potential Sukawana 3.16 3.81
5 Collector Street High Potential Sukawana 0.62 0.74
6 Footpath Moderate Potential Awan 0.02 0.03
7 Footpath Moderate Potential Sukawana 12.72 15.36
8 Footpath High Potential Sukawana 3.82 4.61
Total Path Length 82.8 100.00
Figure 2. Landslide potential map of Sukawana Village and Awan Village.
Open Access 4726 Figure 3. Landslide vulnerability map of Sukawana Village and Awan Village.
The potential areas for landslides to occur are areas with the largest area compared to other potential classes and are located in two villages, namely in Sukawana Village, with an area of 2,198.07 ha or 55.30% of the total area of the study area and in Awan Village with an area of 772.20 ha or 19.43% of the total research area. The Sukawana Village is on a rather steep slope (15-30%) to steep (30-45%), while Awan Village is on a rather steep slope (15-30%) with volcanic upper slopes, middle slopes, lower slopes and the caldera valley in Sukawana Village, while the landform in Awan Village is a volcanic basin and caldera valley complex. The types of land use in
Sukawana Village are settlements, plantations, fields and forests, while the types of land use in Awan Village are fields, plantations and settlements. This area has a sloping to steep sloping topography.
Rainfall in Sukawana Village is 1,800-2,100 mm year-1, and in Awan Village, it is 1,500-1,800 mm year-1. The types of soil that are scattered in areas with the potential for landslides to occur are Regosol Humus and Regosol Gray. The condition of the slope is a factor that influences landslides and is supported by a geological structure that is sloping to steeply sloping, which makes the constituent rocks not resistant so that processes such as weathering, erosion
Open Access 4727 and landslides occur intensively. Therefore, with a
high score of 4 and 5 on the slope factor and geological structure, this area is included in the medium potential category.
The area with a high potential for landslides in Skewana village has an area of 932.81 ha or 23.47%, is a highland area, and is on a very steep slope (> 45%).
The area has a geological structure dominated by steep slopes and upslope landforms. The soil is dominated by volcanic Regosol Gray, with land use type dominated by forests, fields, plantations, and settlements. Rainfall conditions are relatively moderate, with a range of 1,800-2,100 mm year-1. Land with sloping slopes has the potential to experience soil movement; the steeper the angle of inclination of a slope, the greater the driving force of the mass of soil and rock making up the soil. In areas that have steep slopes, weathered material or rocks can easily slide due to the gravitational force that pulls the material. The slope of the slopes of geological structures and landforms is a factor that contributes more to landslides, with high scores ranging from 4 to 5. According to Sumarniasih (2017) and Diara et al.
(2022), landslides in Kintamani District are due to high rainfall and slope >15%, and land use does not pay attention to the rules of conservation. This situation is supported by Liu et al. (2021) and Oktafiani et al.
(2022) that the slope significantly affects the timing and volume of landslides. Zaika and Syafi'ah (2012) reported that the large slope plays a role in the process of landslide occurrence. The greater the slope angle, the greater the thrust produced by the slope, and the greater the existing shear force so that landslides also occur faster. One form of the driving force that plays a role or dominates the slope when a landslide occurs is the force of gravity. The force of gravity plays a direct role in the process of moving materials (slides) either slowly or quickly (Adhitya et al., 2016; Sukriza et al., 2019).
Landslide hazard
The level of vulnerability to landslides in an area is determined by the potential for landslides, the distribution of settlements and the road network in the area (Galli and Guzzetti, 2007; Erener and Düzgün, 2013). The vulnerability parameter has socio- economic value so that if a landslide occurs in this area, it will cause material losses or not (Subasinghe and Kawasaki, 2021). Based on the results of the analysis of residential areas that are most prone to landslides is Sukawana Village, with an area of 110.96 ha (69.97%) with moderate potential. The high potential prone to landslides is in Sukawana Village, with an area of 18.21 ha (11.48%), and Awan Village has landslide-prone settlements with an area of 29.42 ha (18.55%). These results indicate that the vulnerability to landslides in residential areas is in Sukawana Village. The results of the analysis of landslide-prone roads are divided into three, namely
local roads, footpaths and collector roads. In Sukawana Village, there are two local roads, namely local roads with a medium length of 28.82 km (34.81%) and local roads with a high potential of 19.76 km (23.86%). The local road in Awan Village has a moderate potential of 13.88 km (16.77%). There are two potential footpaths in Sukawana Village: a medium potential of 12.72 km (15.36%) and a high potential of 3.82 km (4.61%). In Awan Village, the trail has a moderate potential of 0.02 km (0.03%). The collector road has a medium potential of 3.16 meters (3.81%) and a high potential of 0.62 meters (0.74%) in Sukawana Village. These results indicate that the road network's landslide susceptibility is dominated by local roads in Sukawana Village.
These results indicate that the road network's landslide susceptibility is dominated by local roads in Sukawana Village. Several buildings are above and below a very steep slope. High cliffs without support and mechanical treatment to maintain slope stability are very prone to landslides, especially during the rainy season. Access to settlements, plantations or community fields is relatively small and steep, where only two motorbikes and one car or truck can pass several roads to get to the location that has not been asphalted and still use dirt roads. If there is a landslide on a large scale, the road will be covered by the landslide. Landslide events with steep to very steep slopes with hilly landscapes become areas that have a high level of landslide vulnerability. Along this road is a hilly landscape, so it has a high potential for landslides with a risk to the safety of human lives that pass through this area. According to Bachri (2021), the level of landslide risk has different values depending on risk parameters, community vulnerability, and regional capacity, also the most dominant landslides with slopes >45, type of agricultural land use, and the occurrence of rain. In addition, the dominant factors that influence landslides are human activities in land use, soil properties, steep-very steep slopes, soil type, young rocks (Quaternary geological period), rainfall events, and high earthquake magnitudes (Fata et al., 2022)
Conclusion
Based on the study, it can be concluded that Sukawana Village has low, medium, and high potentials for landslides, with the majority of the medium and high potential areas located in Banjar Kubusalya, Banjar Sukawana, Paketan Banjar, Banjar Kuum, and Awan Village. The vulnerability level in Sukawana and Awan Villages can be classified as medium and high, depending on the presence of residential areas and the road network. The landslide potential distribution map in Sukawana Village shows a low landslide potential with an area of 71.97 ha (1.81%) located in Banjar Kubusalya, a medium potential with an area of 2,198.07 ha (55.30%) in Banjar Kubusalya, Banjar
Open Access 4728 Sukawana and Paketan Banjar and high potential with
an area of 932.81 ha (23.47%) is in Banjar Kuum and Banjar Sukawana. Awan Village has medium potential with an area of 772.20 ha (19.43%). For areas with high vulnerability to settlements, 110.96 ha (69.97%) are in Sukawana Village, and the road network is dominated by local roads along 28.82 km (34.81%), which are in Sukawana Village.
Acknowledgements
The authors thank the Agroecotechnology Study Program, Faculty of Agriculture, Udayana University, for the laboratory support in soil analysis, data processing and manuscript preparation.
References
Adhitya, F., Rusdiana, O. and Saleh, M.B. 2016.
Determination of plant species for landslide mitigation efforts and their cultivation techniques in landslide- prone areas at KPH Lawu DS: a case study at RPH Cepoko. Jurnal Silvikultur Tropika 8(1):9-19, doi:10.29244/j-siltrop.8.1.9-19 (in Indonesian).
Alexander, D. 2005. Vulnerability to landslides. In: Glade, T., Anderson, M. and Crozier, M.J. (eds), Landslide Hazard and Risk, John Wiley & Sons Ltd., Chichester, UK, 175-198, doi:10.1002/9780470012659.ch5.
Bachri, S., Sumarmi, S., Utaya, L., Irawan, L.Y., Tyas, L.W.N., Nurdiansyah, F.D., Nurjanah, A.F., Wirawan, R., Adillah, A.A. and. Purnama, D.S. 2021. Landslide Risk Analysis in Kelud Volcano, East Java, Indonesia.
Indonesian Journal of Geography 53(3):408-423, doi:10.22146/ijg.40909.
BNPB (The National Disaster Management Agency). 2008.
Regulation of the Head of the National Disaster Management Agency. National Disaster Management Agency.
BNPB (The National Disaster Management Agency). 2017.
Twelve Buried Landslides in 3 Villages, Kintamani District, Bali. National Board for Disaster Management.
Diara, I.W., Suyarto, R. and Saifulloh, M. 2022. Spatial distribution of landslide susceptibility in new road construction Mengwitani-Singaraja, Bali-Indonesia:
based on geospatial data. International Journal of GEOMATE 23(96):95-103, doi:10.21660/2022.96.3320.
Erener, A. and Düzgün, H.S. 2013. A regional scale quantitative risk assessment for landslides: case of Kumluca watershed in Bartin, Turkey. Landslides 10:55- 73, doi:10.1007/s10346-012-0317-9.
Fata, Y.A., Hendrayanto, H., Kuncahyo, B., Erizal, E. and Tarigan, S.D. 2022. Characteristics and factors affecting surface and shallow landslides in West Java, Indonesia.
Journal of Degraded and Mining Lands Management 10(1):3849-3859, doi:10.15243/jdmlm. 2022.101.3849.
Galli, M. and Guzzetti, F. 2007. Landslide vulnerability criteria: a case study from Umbria, Central Italy.
Environmental Management 40(4):649-665, doi:10.1007/s00267-006-0325-4.
Hadmoko, D.S., Lavigne, F. and Samodra, G. 2017.
Application of a semiquantitative and GIS-based statistical model to landslide susceptibility zonation in Kayangan Catchment, Java, Indonesia. Natural Hazards 87:437-468, doi:10.1007/s11069-017-2772-z.
Handrianto, Y. and Farhan, M. 2019. C. 45 Algorithm for classification of causes of landslides. SinkrOn: Jurnal dan Penelitian Teknik Informatika 4(1):120-127, doi:10.33395/sinkron.v4i1.10154.
Karnawati, D., Fathani, T.F., Ignatius, S., Andayani, B., Legono, D. and Burton, P.W. 2011. Landslide hazard and community-based risk reduction effort in Karanganyar and the surrounding area, Central Java, Indonesia. Journal of Mountain Science 8:149-153, doi:10.1007/s11629-011-2107-6.
Liu, Y., Deng, Z. and Wang, X. 2021. The effects of rainfall, soil type and slope on the processes and mechanisms of rainfall-induced shallow landslides. Applied Sciences 11(24):11652, doi:10.3390/app112411652.
Ndah, A.B. and Odihi, J.O. 2017. A systematic study of disaster risk in Brunei Darussalam and options for vulnerability-based disaster risk reduction. International Journal of Disaster Risk Science 8:208-223, doi:10.1007/s13753-017-0125-x.
Nugroho, S.P. 2016. Disaster Management Evaluation and 2016. Disaster Prediction. Jakarta: BNPB (in Indonesian).
Oktafiani, T.P., Utami, S.R. and Agustina, C. 2022.
Simulation of landslide measurement on different slopes and depths of slip field. Jurnal Tanah dan Sumberdaya Lahan 9(2):329-337, doi:10.21776/ub.jtsl.
2022.009.2.13 (in Indonesian).
PSBA UGM. 2001. Preparation of Landslide Natural Disaster Management Information System in Kulon Progo Regency. Final report. Kulon Progo Regency Government Regional Development Planning.
Subasinghe, C.N. and Kawasaki, A. 2021. Assessment of physical vulnerability of buildings and socio-economic vulnerability of residents to rainfall induced cut slope failures: a case study in central highlands, Sri Lanka.
International Journal of Disaster Risk Reduction 65:102550, doi:10.1016/j.ijdrr.2021.102550.
Sukrizal, E., Fatimah, and Nizamuddin. 2019. Analysis of landslide hazards area using Geographic Information System in Gayo Lues District. International Journal of Multicultural and Multireligious Understanding 6(2):193-203, doi:10.18415/ijmmu.v6i3.807.
Sumarniasih, M.S. 2017. Identification and mapping of prone to landslide in the Sub District of Kintamani. Bali Province, Indonesia. International Journal of Environmental & Agriculture Research 3(9):59-64, doi:10.25125/agriculture-journal-IJOEAR-SEP-2017-7.
Susilo, A., Fitriah, F., Rachmawati, T.A. and Suryo, E.A.
2020. Analysis of landslide area of Tulung subdistrict, Ponorogo, Indonesia in 2017 using resistivity method. Smart and Sustainable Built Environment 9(4):341-360, doi:10.1108/SASBE-06- 2019-0082.
Wang, X., Xiao, Y., Shi, W., Ren, J., Liang, F., Lu, J. and Yu, X. 2022. Forensic analysis and numerical simulation of a catastrophic landslide of dissolved and fractured rock slope subject to underground mining. Landslides 19(5):1045-1067, doi:10.1007/
s10346-021-01842-y.
Yalcin, A. 2007. The effects of clay on landslides: A case study. Applied Clay Science 38(1-2):77-85, doi:10.1016/j.clay.2007.01.007.
Zaika, Y. and Syafi’ah, S. 2012. Effect of dynamic loads and soil moisture content on slope stability in sandy loam soils. Rekayasa Sipil 5(1):35-39 (in Indonesian).
