Pemetaan Risiko Longsor Berbasis Skenario Iklim melalui Integrasi GIS–AHP dan Pemodelan Stabilitas Lereng
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Abstract
Perubahan iklim global yang ditandai oleh peningkatan intensitas dan variabilitas curah hujan telah meningkatkan frekuensi serta keparahan longsor, sehingga menimbulkan tantangan signifikan dalam analisis stabilitas lereng pada bidang teknik sipil. Meskipun berbagai pendekatan geoteknik dan pemetaan berbasis GIS telah digunakan, model yang ada umumnya belum mengintegrasikan skenario iklim masa depan secara sistematis, sehingga ketidakpastian hidrologi jangka panjang belum terakomodasi secara memadai. Penelitian ini bertujuan untuk menyusun peta risiko longsor berbasis perubahan iklim melalui pendekatan kuantitatif terintegrasi. Penelitian dilakukan pada wilayah lereng perbukitan dengan data topografi, geoteknik, curah hujan, dan penggunaan lahan yang dianalisis menggunakan integrasi GIS, Analytical Hierarchy Process (AHP), serta analisis stabilitas lereng berbasis limit equilibrium. Data yang digunakan meliputi parameter tanah hasil uji laboratorium dan data spasial multi-layer yang diproses melalui teknik Multi-Criteria Evaluation. Hasil menunjukkan bahwa peningkatan curah hujan sebesar 20% menurunkan nilai Factor of Safety rata-rata hingga 34,9%, sementara sekitar 41% wilayah terklasifikasi dalam zona risiko tinggi. Selain itu, sekitar 70% kejadian longsor teridentifikasi pada lereng dengan kemiringan lebih dari 30°, menunjukkan dominasi faktor geometri lereng dalam ketidakstabilan. Temuan ini menegaskan bahwa perubahan iklim secara signifikan memengaruhi stabilitas lereng dan distribusi risiko longsor. Penelitian ini memberikan kontribusi penting dalam pengembangan model GIS-based climate slope risk mapping yang mengintegrasikan teori stabilitas lereng dan adaptasi perubahan iklim, serta menawarkan implikasi praktis untuk perencanaan tata ruang dan mitigasi risiko berbasis data dalam rekayasa teknik sipil.
Abstract
Global climate change, characterized by increasing intensity and variability of rainfall, has significantly amplified the frequency and severity of landslides, posing critical challenges for slope stability analysis in civil engineering. Although geotechnical methods and GIS-based mapping approaches have been widely applied, existing models generally lack systematic integration of future climate scenarios, leaving long-term hydrological uncertainty insufficiently addressed. This study aims to develop a climate-based landslide risk map using an integrated quantitative approach. The research was conducted in a hilly slope region using topographic, geotechnical, rainfall, and land-use data, analyzed through the integration of GIS, Analytical Hierarchy Process (AHP), and limit equilibrium-based slope stability analysis. The dataset included laboratory-tested soil parameters and multi-layer spatial data processed using Multi-Criteria Evaluation techniques. The results showed that a 20% increase in rainfall reduced the average Factor of Safety by up to 34.9%, while approximately 41% of the study area was classified as high-risk zones. Furthermore, about 70% of landslide occurrences were associated with slopes exceeding 30°, indicating the dominant role of slope geometry in instability. These findings demonstrate that climate change significantly alters slope stability and the spatial distribution of landslide risk. This study contributes to the advancement of a GIS-based climate slope risk mapping framework integrating slope stability theory and climate adaptation, and provides practical implications for spatial planning and risk mitigation strategies in civil engineering.
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Akter, S., Howladar, M. F., Ahmed, Z., Chowdhury, T. R., & Shahnewaz Sayem, S. M. (2022). Assessing the Climatic Influence on River in Bangladesh: In Perspective of Morphology and Discharge of Surma River. American Journal of Environment and Climate, 1(1), 20–27. https://doi.org/10.54536/ajec.v1i1.181
Anugrah, I., & Laksmono, B. (2023). Upaya Mitigasi Kebakaran Hutan dan Lahan Melalui Program CSR Budidaya Madu Hutan Gambut PT Pertamina RU II Sungai Pakning. Jurnal Teknik Industri Terintegrasi, 6(4), 1202–1211. https://doi.org/10.31004/jutin.v6i4.20303
Ardianto, G., Segah, H., Aguswan, Y., Triyadi, A., & Siska, G. (2023). Analysis of Land Cover Change Using Sentinel-2 Images at Natural Laboratory of Peat Swamp Forest Area CIMTROP University of Palangka Raya. Journal of Peat Science and Innovation, 1(1), 32–44. https://doi.org/10.59032/jpsi.v1i1.7541
Ardizzone, F., Gariano, S. L., Volpe, E., Antronico, L., Coscarelli, R., Manunta, M., & Mondini, A. C. (2023). A Procedure for the Quantitative Comparison of Rainfall and DInSAR-Based Surface Displacement Time Series in Slow-Moving Landslides: A Case Study in Southern Italy. Remote Sensing, 15(2), 320. https://doi.org/10.3390/rs15020320
Bozzolan, E., Holcombe, E. A., Pianosi, F., Marchesini, I., Alvioli, M., & Wagener, T. (2023). A mechanistic approach to include climate change and unplanned urban sprawl in landslide susceptibility maps. Science of The Total Environment, 858, 159412. https://doi.org/10.1016/j.scitotenv.2022.159412
Bračko, T., Žlender, B., & Jelušič, P. (2022). Implementation of Climate Change Effects on Slope Stability Analysis. Applied Sciences, 12(16), 8171. https://doi.org/10.3390/app12168171
Chen, Y. (2021). Application of Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) Methods in Mapping Flood-Prone Areas. https://doi.org/10.3233/FAIA210274
D’Andrea, M. L. G., Iribarnegaray, M. A., Tejerina, W. A., Barboza, A. G. J. S., Correa, J. J., Rodriguez-Alvarez, M. S., & Seghezzo, L. (2021). Multi-Criteria Assessment Model to Identify Suitable Areas for Treated Wastewater Reuse in Agriculture. Rica. https://doi.org/10.20937/rica.53749
Del Vecchio, J., Lathrop, E. R., Dann, J. B., Andresen, C. G., Collins, A. D., Fratkin, M. M., Zwieback, S., Glade, R. C., & Rowland, J. C. (2023). Patterns and rates of soil movement and shallow failures across several small watersheds on the Seward Peninsula, Alaska. Earth Surface Dynamics, 11(2), 227–245. https://doi.org/10.5194/esurf-11-227-2023
Deliveris, A. V, Theocharis, A. I., Koukouzas, N. C., & Zevgolis, I. E. (2022). Numerical Slope Stability Analysis of Deep Excavations Under Rainfall Infiltration. Geotechnical and Geological Engineering, 40(8), 4023–4039. https://doi.org/10.1007/s10706-022-02135-4
Dwinagara, B. (2024). Back Analysis of Rainfall-Induced Waste Dump Failure Using Coupled Hydro-Mechanical Analysis – A Case Study in Coal Mine. International Journal of Geomate, 27(123). https://doi.org/10.21660/2024.123.4618
Farokhzadeh, B., Bazrafshan, O., Singh, V. P., Choobeh, S., & Saravi, M. M. (2022). Future Rainfall Erosivity Over Iran Based on CMIP5 Climate Models. Water, 14(23), 3861. https://doi.org/10.3390/w14233861
Ferrer, J., Guo, Z., Medina, V., Puig-Polo, C., & Hürlimann, M. (2022). A Framework to Project Future Rainfall Scenarios: An Application to Shallow Landslide-Triggering Summer Rainfall in Wanzhou County China. Water, 14(6), 873. https://doi.org/10.3390/w14060873
Gatto, M. P. A. (2023). Incorporating Rainfall Forecast Data in X-Slip Platform to Predict the Triggering of Rainfall-Induced Shallow Landslides in Real Time. Geosciences, 13(7), 215. https://doi.org/10.3390/geosciences13070215
Ghosh, D., Banerjee, A., Puppala, A. J., & Kumar, P. (2024). Exploring the Influence of Climate Change on Earthen Embankments with Expansive Soil. Geosciences, 14(2), 37. https://doi.org/10.3390/geosciences14020037
He, Y., YU, Z., Zhang, Z., Chen, B., & Zhang, K. (2022). Effects of Rainfall on Mechanical Behaviors of Residual-Soil Landslide. Frontiers in Earth Science, 10. https://doi.org/10.3389/feart.2022.925636
Hossain, I., Imteaz, M. A., Gato-Trinidad, S., & Yilmaz, A. G. (2024). Comparison of Future Design Rainfall With Current Design Rainfall: A Case Study in New South Wales, Australia. Atmosphere, 15(7), 739. https://doi.org/10.3390/atmos15070739
Hou, J., Zhang, Y., Xia, J., Wang, Y., Zhang, S., Pan, X., Yang, M., Leng, G., & Dou, M. (2022). Simulation and Assessment of Projected Climate Change Impacts on Urban Flood Events: Insights From Flooding Characteristic Metrics. Journal of Geophysical Research: Atmospheres, 127(3). https://doi.org/10.1029/2021JD035360
JEMEC AUFLIČ, M., BOKAL, G., KUMELJ, Š., MEDVED, A., DOLINAR, M., & JEŽ, J. (2021). Impact of climate change on landslides in Slovenia in the mid-21st century. Geologija, 64(2), 159–171. https://doi.org/10.5474/geologija.2021.009
Jiang, H., Chen, X., Xu, G., Chen, J., Song, D., Lu, M., Guo, H., & Chen, J. (2025). Plant Adaptation and Soil Shear Strength: Unraveling the Drought Legacy in Amorpha Fruticosa. Plants, 14(2), 179. https://doi.org/10.3390/plants14020179
Jiang, X., Qiu, X.-O., Li, Z., Pan, J., Peng, C., Zuo, X., Liao, Z., & Li, Z. (2022). Small-Sized Versus Standard Magnetic Capsule Endoscopy in Adults: A Two-Center, Double-Blinded Randomized Controlled Trial. Endoscopy, 55(01), 52–57. https://doi.org/10.1055/a-1881-4369
Jug, J., Grabar, K., Bek, A., & Strelec, S. (2024). Stabilization of Shallow Landslides Induced by Rainwater Infiltration—A Case Study From Northern Croatia. Geotechnics, 4(1), 242–263. https://doi.org/10.3390/geotechnics4010013
Jumintono, Wiyatiningsih, S., Relawati, R., Yanita, M., & Santi, I. S. (2022). Palm oil plantation transportation management improving using economic information systems and Qm-Windows. Economic Annals-ХХI, 198(7–8), 18–23. https://doi.org/10.21003/ea.V198-02
Júnior, S. M., Casiraghi, Y., Berres, G. W., Leite Frandoloso, M. A., & Rosa, F. D. (2021). Characterization of an area susceptible to floods and inundations in a medium size city in Southern Brazil. International Journal of Hydrology, 5(5), 222–229. https://doi.org/10.15406/ijh.2021.05.00284
Karim, A. A. A., Wilopo, W., Indrawan, I. G. B., & Adriansyah, Y. (2021). Estimating of Maximum Groundwater Level to Trigger Landslide in Batu Hijau Open Pit Mine, West Nusa Tenggara, Indonesia. Journal of Applied Geology, 5(2), 113. https://doi.org/10.22146/jag.58135
Khan, M. A., Ahmad, R., & Khan, H. H. (2022). Multi-Criteria Land Suitability Analysis for Agriculture Using AHP and Remote Sensing Data of Northern Region India. https://doi.org/10.5772/intechopen.102432
Kumar, P., Priyanka, P., Uday, K. V., & Dutt, V. (2024). Addressing class imbalance in soil movement predictions. Natural Hazards and Earth System Sciences, 24(6), 1913–1928. https://doi.org/10.5194/nhess-24-1913-2024
Latue, T., Latue, P. C., Rakuasa, H., Somae, G., & Muin, A. (2023). Mapping of Landslide Prone Areas in Huamual Sub-District, Seram Bangian Barat Regency, Indonesia. Jurnal Riset Multidisiplin Dan Inovasi Teknologi, 1(02), 84–93. https://doi.org/10.59653/jimat.v1i02.239
Li, X. (2022). Study on Stability and Ecological Restoration of Soil-Covered Rocky Slope of an Abandoned Mine on an Island in Rainy Regions. Sustainability (Switzerland), 14(20). https://doi.org/10.3390/su142012959
Lin, Z., Ji, Y., & Sun, X. (2023). Advance Landslide Prediction and Warning Model Based on Stacking Fusion Algorithm. Mathematics, 11(13), 2833. https://doi.org/10.3390/math11132833
Liu, J., Wu, Y., & Gao, X. (2021). Increase in occurrence of large glacier-related landslides in the high mountains of Asia. Scientific Reports, 11(1), 1635. https://doi.org/10.1038/s41598-021-81212-9
Liu, J., & Xu, C. (2024). Construction and Preliminary Analysis of Landslide Database Triggered by Heavy Storm in the Parallel Range-Valley Area of Western Chongqing, China, on 8 June 2017. Frontiers in Earth Science, 12. https://doi.org/10.3389/feart.2024.1420425
Ma, X., Peng, J., Su, Y., Shi, M., Zheng, Y., Li, X., & Jiang, X. (2024). Deformation Characteristics and Activation Dynamics of the Xiaomojiu Landslide in the Upper Jinsha River Basin Revealed by Multi-Track InSAR Analysis. Remote Sensing, 16(11), 1940. https://doi.org/10.3390/rs16111940
Malemnganbi, R., & Shimray, B. A. (2022). An integrated multiple layer perceptron-genetic algorithm decision support system for photovoltaic power plant site selection. International Journal of Electrical and Computer Engineering (IJECE), 12(2), 1965. https://doi.org/10.11591/ijece.v12i2.pp1965-1972
Mohammadzadeh, S., Scholz, T., & Symmank, L. (2025). Bridging Ecology and Infrastructure: Evaluating the Integrated Benefits of Nature‐based Solutions. Ce/Papers, 8(5), 134–141. https://doi.org/10.1002/cepa.3390
Morales, F. F., & de Vries, W. T. (2021). Establishment of Natural Hazards Mapping Criteria Using Analytic Hierarchy Process (AHP). Frontiers in Sustainability, 2. https://doi.org/10.3389/frsus.2021.667105
Nieto, A., Pica, D. E. A., & Stange, T. (2022). Application of LiDAR-Derived Data Using Multi-Criteria Evaluation (MCE) and Stochastic Modelling; A Flood Risk Analysis of the Mersey River, Nova Scotia. Surg Journal, 14(1). https://doi.org/10.21083/surg.v14i1.6713
Olabode, O. P., Lim, H. S., & Ramli, H. (2022). Geophysical and Geotechnical Evaluation of Landslide Slip Surface in a Residual Soil for Monitoring of Slope Instability. Earth and Space Science, 9(12). https://doi.org/10.1029/2022ea002248
Pallathadka, A. (2023). A Local Snow-Ice Hazard Model Using Weighted Overlay Analysis: Predictive Spatial Decision Support System for Hazard Mitigation. Integrated Journal for Research in Arts and Humanities, 3(2), 60–62. https://doi.org/10.55544/ijrah.3.2.10
Phelps, K., Hiesl, P., Hagan, D., & Hotaling Hagan, A. (2021). The Harvest Operability Index (HOI): A Decision Support Tool for Mechanized Timber Harvesting in Mountainous Terrain. Forests, 12(10), 1307. https://doi.org/10.3390/f12101307
Ravindran, S., & Gratchev, I. (2022). Effect of Water Content on Apparent Cohesion of Soils From Landslide Sites. Geotechnics, 2(2), 385–394. https://doi.org/10.3390/geotechnics2020017
Setyawan, R., Nurtjahjaningtyas, I., & Hidayah, E. (2023). Assessment of Land Erosion Hazard in the Sampean Hulu Sub Watershed, Bondowoso Regency. Jurnal Teknik Pengairan, 14(2), 125–133. https://doi.org/10.21776/ub.pengairan.2023.014.02.3
Shankar Ram, N. R., Sharma, V. K., Mirza, K., Goyal, A., Chowdary, V. M., & Jha, C. S. (2022). Multi-criteria Based Land and Water Resource Development Planning Using Geospatial Technologies (pp. 103–123). https://doi.org/10.1007/978-3-030-90479-1_7
Sulca, J., & Rocha, R. P. d. (2021). Influence of the Coupling South Atlantic Convergence Zone-El Niño-Southern Oscillation (SACZ-ENSO) on the Projected Precipitation Changes Over the Central Andes. Climate, 9(5), 77. https://doi.org/10.3390/cli9050077
Tian, W., Peiffer, H., Malengier, B., Liu, G., & Cheng, L. (2023). Modified Equation of Shear Strength With Respect to Saturation. Applied Sciences, 13(7), 4305. https://doi.org/10.3390/app13074305
Uyan, M., & Dogmus, O. L. (2023). An Integrated GIS-Based ANP Analysis for Selecting Solar Farm Installation Locations: Case Study in Cumra Region, Turkey. Environmental Modeling & Assessment, 28(1), 105–119. https://doi.org/10.1007/s10666-022-09870-1
Vargas-León, L. A., & Giraldo‐Osorio, J. D. (2024). Analysis of Anomalies Due to the ENSO and Long-Term Changes in Extreme Precipitation Indices Using Data From Ground Stations. Hydrology, 11(1), 7. https://doi.org/10.3390/hydrology11010007
Wang, W., Tianyu, N., Huaiyu, Z., Xu, C., & Li, T. (2025). Experimental Study on Accumulation Layer Landslides Based on Thermosensitive Materials. Earth Surface Processes and Landforms, 50(15). https://doi.org/10.1002/esp.70218
Wu, C.-H. (2024). Assessment of Possible Landslide Susceptibility Under Climate Change: A Case in the Chishan River Watershed in Southwestern Taiwan. Water, 16(23), 3420. https://doi.org/10.3390/w16233420
Yang, C., Wu, J., Li, P., Wang, Y., & Yang, N. (2023). Evaluation of Soil-Water Characteristic Curves for Different Textural Soils Using Fractal Analysis. Water, 15(4), 772. https://doi.org/10.3390/w15040772
Zhang, X., Wang, H., Gao, Z., Ke, X., Zhai, Q., Satyanaga, A., & Chua, Y. S. (2023). Evaluation of the Performance of the Horizontal Drain in Drainage of the Infiltrated Water From Slope Soil Under Rainfall Conditions. Sustainability, 15(19), 14163. https://doi.org/10.3390/su151914163
Zhao, L. Q., Dragićević, S., Balram, S., & Pérez, L. (2025). Assessing the Number of Criteria in GIS‐Based Multicriteria Evaluation: A Machine Learning Approach. Geographical Analysis, 57(3), 489–506. https://doi.org/10.1111/gean.70004
Zhou, H., Qiu, J., Li, M., Lü, H. F., & Li, F. (2025). Assessment of Large‐Scale Reservoirs’ Impact on the Local Precipitation. Water Resources Research, 61(5). https://doi.org/10.1029/2025wr039938
Zhu, Y., Ishikawa, T., Yamada, T. J., & Siva Subramanian, S. (2021). Probability assessment of slope instability in seasonally cold regions under climate change. Journal of Infrastructure Preservation and Resilience, 2(1), 20. https://doi.org/10.1186/s43065-021-00034-1
Zhu, Y., Ishikawa, T., Zhang, Y., Nguyen, B. T., & Subramanian, S. S. (2022). A FEM-MPM Hybrid Coupled Framework Based on Local Shear Strength Method for Simulating Rainfall/Runoff-Induced Landslide Runout. Landslides, 19(8), 2021–2032. https://doi.org/10.1007/s10346-022-01849-z
Zhu, Y., Zhuang, J., & Zhao, Y. (2024). Failure Process of High-Loess-Filled-Slopes (HLFSs) During Precipitation Under Different Mitigation Measures. Applied Sciences, 14(1), 419. https://doi.org/10.3390/app14010419