Comparative assessment of a flash flood susceptibility map based on morphometric analysis and bivariate statistics in the Upper Citarum Watershed, Indonesia
DOI:
https://doi.org/10.12775/bgeo-2024-0012Keywords
bivariate statistics, flash flood susceptibility, morphometric analysis, statistical index, susceptibility map, IndonesiaAbstract
Flash floods are one of the most destructive natural disasters, characterized by rapid occurrence and high casualty rates due to a lack of preparedness. Mapping susceptibility areas to identify flash-flood-prone zones can be an effective tool for mitigation. Despite various flood susceptibility mapping methodologies, research on the most suitable statistical approach for Indonesia’s unique environmental context remains limited. This study aimed to compare the performance of three statistical methods, namely Shannon’s Entropy (SE), Statistical Index (SI) and Frequency Ratio (FR), in assessing flash flood susceptibility. Conducted in the Upper Citarum Watershed, Indonesia, this study used geospatial analysis using elevation, slope, curve number, lithology, soil movement, rainfall and morphometric parameters of the watershed to analyze flash flood susceptibility in the study area, with morphometric characteristics affecting hydrological processes such as surface runoff and soil erosion. The results indicate that the Statistical Index Flash Flood Susceptibility Map (SI FFSM) is the most effective model for representing flash flood susceptibility, achieving the highest AUC values for success rate (0.907) and prediction rate (0.933). According to the SI method, the three most influential parameters driving flash floods in the research area are elevation, landslides or soil movement, and rainfall. The total high and very high flash flood susceptibility area is 102.29 km2 or 46.95% of the study area. The findings of this study will contribute to the development of more-accurate and -practical tools for disaster risk assessment and management, both in Indonesia and other regions with similar environmental conditions.
References
ALEKSOVA B, MILEVSKI I, MIJALOV R, MARKOVIĆ SB, CVETKOVIĆ VM and LUKIĆ T, 2024, Assessing risk-prone areas in the Kratovska Reka catchment (North Macedonia) by integrating advanced geospatial analytics and flash flood potential index. Open Geosciences 16(1): 20220684. DOI: DOI: https://doi.org/10.1515/geo-2022-0684.
ARORA A, PANDEY M, SIDDIQUI MA, HONG H and MISHRA VN, 2021, Spatial flood susceptibility prediction in Middle Ganga Plain: comparison of frequency ratio and Shannon’s entropy models. Geocarto International 36(18): 2085–2116. DOI: https://doi.org/10.1080/10106049.2019.1687594.
AZMERI, HADIHARDAJA IK and VADIYA R, 2016, Identification of flash flood hazard zones in mountainous small watershed of Aceh Besar Regency, Aceh Province, Indonesia. The Egyptian Journal of Remote Sensing and Space Sciences 19(1): 143–160. DOI: https://doi.org/10.1016/j.ejrs.2015.11.001.
BAGWAN WA and GAVALI RS, 2021, An Integrated Approach for the Prioritization of Subwatersheds in the Urmodi River Catchment (India) for Soil Conservation using Morphometric and Land Use Land Cover (LULC) factors. Journal of Sedimentary Environments 6(1): 39–56. DOI: https://doi.org/10.1007/s43217-020-00041-4.
BOURENANE H, BOUHADAD Y, GUETTOUCHE MS and BRAHAM M, 2015, GIS-based landslide susceptibility zonation using bivariate statistical and expert approaches in the city of Constantine (Northeast Algeria). Bulletin of Engineering Geology and the Environment 74(2): 337–355. DOI: https://doi.org/10.1007/s10064-014-0616-6.
BUI DT, LOFMAN O, REVHAUG I and DICK O, 2011, Landslide susceptibility analysis in the Hoa Binh province of Vietnam using statistical index and logistic regression. Natural Hazards 59(3): 1413–1444. DOI: https://doi.org/10.1007/s11069-011-9844-2.
CAO C, XU P, WANG Y, CHEN J, ZHENG L and NIU C, 2016, Flash flood hazard susceptibility mapping using frequency ratio and statistical index methods in coalmine subsidence areas. Sustainability (Switzerland): 8(9): 948. DOI: https://doi.org/10.3390/su8090948.
CEA L and COSTABILE P, 2022, Flood Risk in Urban Areas: Modelling, Management and Adaptation to Climate Change: A Review. Hydrology, 9(3): 50. DOI: https://doi.org/10.3390/hydrology9030050.
Central Bureau of Statistics (BPS) of Cianjur Regency, 2022, Cianjur Regency in Figures 2022. In: (E. Sulaeman E and Nugraha BDP (eds), BPS-Statistics of Cianjur Regency.
CHAIDAR AN, SOEKARNO I, WIYONO A and NUGROHO J, 2017, Spatial analysis of erosion and land criticality of the upstream Citarum watershed. International Journal of Geomate 13(37): 133–140. DOI: https://doi.org/10.21660/2017.37.34572.
CHEN J, SHI X, GU L, WU G, SU T, WANG H-M, KIM J-S, ZHANG L and XIONG L, 2023, Impacts of climate warming on global floods and their implication to current flood defense standards. Journal of Hydrology 618: 129236. DOI: https://doi.org/10.1016/j.jhydrol.2023.129236.
COSTACHE R, HONG H and PHAM QB, 2020, Comparative assessment of the flash-flood potential within small mountain catchments using bivariate statistics and their novel hybrid integration with machine learning models. Science of the Total Environment 711: 134514. DOI: https://doi.org/10.1016/j.scitotenv.2019.134514.
COSTACHE R and TIEN BUI D, 2019, Spatial prediction of flood potential using new ensembles of bivariate statistics and artificial intelligence: A case study at the Putna river catchment of Romania. Science of the Total Environment 691: 1098–1118. DOI: https://doi.org/10.1016/j.scitotenv.2019.07.197.
COSTACHE R and ZAHARIA L, 2017, Flash-flood potential assessment and mapping by integrating the weights-of-evidence and frequency ratio statistical methods in GIS environment – Case study: Bâsca chiojdului river catchment (Romania). Journal of Earth System Science 126(4): 59. DOI: https://doi.org/10.1007/s12040-017-0828-9.
CRUDEN DM and VARNES DJ, 1993, Landslide Types and Processes. U.S. National Academy of Sciences.
DASANTO BD, PRAMUDYA B, BOER R and SUHARNOTO Y, 2014, Effects of forest cover change on flood characteristics in the upper citarum watershed. Jurnal Manajemen Hutan Tropika 20(3): 141–149. DOI: https://doi.org/10.7226/jtfm.20.3.141.
Department of Food Crops and Horticulture West Java, 2024, Soil Type Delineation of West Java Province at a 1:250,000 Scale. In: Satu Peta Jabar. Available at: https://satupeta.jabarprov.go.id/maps?search=tanahandopenCatalog=true.
Department of Public Works and Spatial Planning Cianjur, 2022, Land Use/Land Cover Map of Cianjur Regency. Cianjur Regency Government.
DIAKAKIS M, BOUFIDIS N, SALANOVA GRAU JM, ANDREADAKIS E and STAMOS I, 2020, A systematic assessment of the effects of extreme flash floods on transportation infrastructure and circulation: The example of the 2017 Mandra flood. International Journal of Disaster Risk Reduction 47: 101542. DOI: https://doi.org/10.1016/j.ijdrr.2020.101542.
DUTAL H, 2023, Using morphometric analysis for assessment of flash flood susceptibility in the Mediterranean region of Turkey. Environmental Monitoring and Assessment 195(5): 582. DOI: https://doi.org/10.1007/s10661-023-11201-0.
ELSADEK WM and ALMALIKI AH, 2024, Integrated hydrological study for flash flood assessment using morphometric analysis and MCDA based on hydrological indices—Al-Sail Al-Kabir, KSA. Natural Hazards 120(7): 6853–6880. DOI: https://doi.org/10.1007/s11069-024-06450-2.
FAO, 2015, World reference base for soil resources 2014 International soil classification system for naming soils and creating legends for soil maps. In: Springer Water (3rd ed.). Food and Agriculture Organization of the United Nations. DOI: https://doi.org/10.1007/978-3-319-24409-9_25.
HANG HT, HOA PD, TRU VN and PHUONG NV, 2021, Application of Shannon’S Entropy Model and Gis in Flash Flood Forecasting Along National Highway-6, Hoa Binh Province, Vietnam. International Journal of Geomate 21(87): 50–57. DOI: https://doi.org/10.21660/2021.87.j2316.
HONG H, TSANGARATOS P, ILIA I, LIU J, ZHU AX and CHEN W, 2018, Application of fuzzy weight of evidence and data mining techniques in construction of flood susceptibility map of Poyang County, China. Science of the Total Environment 625: 575–588. DOI: https://doi.org/10.1016/j.scitotenv.2017.12.256.
HORTON RE, 1945, Erosional development of streams and their drainage basins, hydrophysical approach to quantitative morphology. Bulletin of The Geological Society of America 56(3): 275–370. DOI: https://doi.org/10.1130/0016-7606(1945)56.
ISLAM S, TAHIR M and PARVEEN S, 2022, GIS-based flood susceptibility mapping of the lower Bagmati basin in Bihar, using Shannon’s entropy model. Modeling Earth Systems and Environment 8(3): 3005–3019. DOI: https://doi.org/10.1007/s40808-021-01283-5.
JAIN SK, BEEVERS L, ANANDHI A and KUMAR DN, 2022, Multi-Disciplinary Approaches for Data Observation, Analysis, Forecasting, and Management. Frontiers in Environmental Science 10: 888906. DOI: https://doi.org/10.3389/fenvs.2022.888906.
JAVED A, KHANDAY MY and RAIS S, 2011, Watershed prioritization using morphometric and land use/land cover parameters: A remote sensing and GIS based approach. Journal of the Geological Society of India 78(1): 63–75. DOI: https://doi.org/10.1007/s12594-011-0068-6.
JEBUR MN, PRADHAN B and TEHRANY MS, 2014, Optimization of landslide conditioning factors using very high-resolution airborne laser scanning (LiDAR) data at catchment scale. Remote Sensing of Environment 152: 150–165. DOI: https://doi.org/10.1016/j.rse.2014.05.013.
JEHANZAIB M, AJMAL M, ACHITE M and KIM TW, 2022, Comprehensive Review: Advancements in Rainfall-Runoff Modelling for Flood Mitigation. Climate 10(10): 1–17. DOI: https://doi.org/10.3390/cli10100147.
KHOSRAVI K, POURGHASEMI HR, CHAPI K and BAHRI M, 2016, Flash flood susceptibility analysis and its mapping using different bivariate models in Iran: a comparison between Shannon’s entropy, statistical index, and weighting factor models. Environmental Monitoring and Assessment 188(12): 656. DOI: https://doi.org/10.1007/s10661-016-5665-9.
KIA MB, PIRASTEH S, PRADHAN B, MAHMUD AR, SULAIMAN WNA and MORADI A, 2012, An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia. Environmental Earth Sciences 67(1): 251–264. DOI: https://doi.org/10.1007/s12665-011-1504-z.
KURNIADI A, WELLER E, SALMOND J and ALDRIAN E, 2024, Future projections of extreme rainfall events in Indonesia. International Journal of Climatology 44(1): 160–182. DOI: https://doi.org/10.1002/joc.8321.
LI L, LAN H, GUO C, ZHANG Y, LI Q and WU Y, 2017, A modified frequency ratio method for landslide susceptibility assessment. Landslides 14(2): 727–741. DOI: https://doi.org/10.1007/s10346-016-0771-x.
LUBIS SW and RESPATI MR, 2021, Impacts of convectively coupled equatorial waves on rainfall extremes in Java, Indonesia. International Journal of Climatology 41(4): 2418–2440. DOI: https://doi.org/10.1002/joc.6967.
LUU C, HA H, BUI QD, LUONG ND, KHUC DT, VU H and NGUYEN DQ, 2023, Flash flood and landslide susceptibility analysis for a mountainous roadway in Vietnam using spatial modeling. Quaternary Science Advances 11: 100083. DOI: https://doi.org/10.1016/j.qsa.2023.100083.
MAHMOOD S and RAHMAN AU, 2019, Flash flood susceptibility modelling using geomorphometric approach in the Ushairy Basin, eastern Hindu Kush. Journal of Earth System Science 128(4): 1–14. DOI: https://doi.org/10.1007/s12040-019-1111-z.
MANSOUR A, MRAD D and DJEBBAR Y, 2024, Advanced modeling for flash flood susceptibility mapping using remote sensing and GIS techniques: a case study in Northeast Algeria. Environmental Earth Sciences 83(2): 1–19. DOI: https://doi.org/10.1007/s12665-023-11324-0.
MELTON MA, 1965, The Geomorphic and Paleoclimatic Significance of Alluvial Deposits in Southern Arizona. The Journal of Geology 73(1): 1–38.
MILLER VC, 1953, A Quantitative Geomorphic Study of Drainage Basin Characteristics in the Clinch Mountain Area, Virginia and Tennessee. Columbia University. Department of Geology Tech. Rept. 3(19). DOI: https://doi.org/10.1086/626413.
National Agency for Disaster Countermeasure, 2023, LAPORAN HARIAN: Selasa, 21 Maret.
OGAREKPE NM, NNAJI CC and EKPENYONG MG, 2022, Flash Flood Risk Assessment of the Great Kwa River Basin Using Analytical Hierarchy Process. Water Conservation Science and Engineering 7(4): 599–611. DOI: https://doi.org/10.1007/s41101-022-00167-8.
PRADHAN B, 2009, Groundwater potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques. Central European Journal of Geosciences 1(1): 120–129. DOI: https://doi.org/10.2478/v10085-009-0008-5.
RAHMAN MT, ALDOSARY AS, NAHIDUZZAMAN KM and REZA I, 2016, Vulnerability of flash flooding in Riyadh, Saudi Arabia. Natural Hazards 84(3): 1807–1830. DOI: https://doi.org/10.1007/s11069-016-2521-8.
RAHMATI O, POURGHASEMI HR and ZEINIVAND H, 2016, Flood susceptibility mapping using frequency ratio and weights-of-evidence models in the Golastan Province, Iran. Geocarto International 31(1): 42–70. DOI: https://doi.org/10.1080/10106049.2015.1041559.
RAHMATI O, ZEINIVAND H and BESHARAT M, 2016, Flood hazard zoning in Yasooj region, Iran, using GIS and multi-criteria decision analysis. Geomatics, Natural Hazards and Risk 7(3): 1000–1017. DOI: https://doi.org/10.1080/19475705.2015.1045043.
SAMANTA RK, BHUNIA GS, SHIT PK and POURGHASEMI HR, 2018, Flood susceptibility mapping using geospatial frequency ratio technique: a case study of Subarnarekha River Basin, India. Modeling Earth Systems and Environment 4(1): 395–408. DOI: https://doi.org/10.1007/s40808-018-0427-z.
SARKAR D and MONDAL P, 2020, Flood vulnerability mapping using frequency ratio (FR) model: a case study on Kulik river basin, Indo-Bangladesh Barind region. Applied Water Science 10(1): 1–13. DOI: https://doi.org/10.1007/s13201-019-1102-x.
SAYAMA T, YAMADA M, SUGAWARA Y and YAMAZAKI D, 2020, Ensemble flash flood predictions using a high-resolution nationwide distributed rainfall-runoff model: case study of the heavy rain event of July 2018 and Typhoon Hagibis in 2019. Progress in Earth and Planetary Science 7(1): 75. DOI: https://doi.org/10.1186/s40645-020-00391-7.
SCHOENEBERGER P, WYSOCKI D, BUSSKOHL C and LIBOHOVA Z, 2017, Landscapes, Geomorphology, and Site Description. In: The Soil Survey Manual. USDA Agriculture Handbook 18: 21–82.
SCHUMM SA, 1956, Evolution of Drainage Systems and Slopes in Badlands at Perth Amboy, New Jersey. Bulletin of the Geological Society of America 67(5): 597–646. DOI: https://doi.org/10.1130/0016-7606(1956)67.
Strahler A, 1957, Quantitative Analysis of Watershed Geomorphology, Transactions of the American Geophysical Union. Transactions, American Geophysical Union 38(6): 913–920.
Sudjatmiko, 2003, Geological Map of The Cianjur Quadrangle, Jawa Scale 1:100.000. Ministry of Energy and Mineral Resources.
Tabari H, 2020, Climate change impact on flood and extreme precipitation increases with water availability. Scientific Reports 10(1): 13768. DOI: https://doi.org/10.1038/s41598-020-70816-2.
TAHERIZADEH M, NIKNAM A, NGUYEN-HUY T, MEZŐSI G and SARLI R, 2023, Flash flood-risk areas zoning using integration of decision-making trial and evaluation laboratory, GIS-based analytic network process and satellite-derived information. Natural Hazards 118(3): 2309–2335. DOI: https://doi.org/10.1007/s11069-023-06089-5.
Tehrany SM, PRADHAN B and JEBUR MN, 2013, Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS. Journal of Hydrology 504: 69–79. DOI: https://doi.org/10.1016/j.jhydrol.2013.09.034.
TEHRANY SM, KUMAR L, NEAMAH JEBUR M and SHABANI F, 2019, Evaluating the application of the statistical index method in flood susceptibility mapping and its comparison with frequency ratio and logistic regression methods. Geomatics, Natural Hazards and Risk 10(1): 79–101. DOI: https://doi.org/10.1080/19475705.2018.1506509.
UNISDR, 2015, The Human Cost of Weather Related Disasters 1995–2015. UNISDR.
VAN WESTEN CJ, 1997, Statistical landslide hazard analysis. ILWIS 2.1 for Windows application guide. ITC Publication.
WANG X, GOURBESVILLE P and LIU C, 2023, Flash Floods: Forecasting, Monitoring and Mitigation Strategies. Water (Switzerland) 15(9): 1–5. DOI: https://doi.org/10.3390/w15091700.
WANG X and LIU L, 2023, The Impacts of Climate Change on the Hydrological Cycle and Water Resource Management. Water 15(13): 2342. DOI: https://doi.org/10.3390/w15132342.
YALCIN A, 2008, GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations. Catena 72(1): 1–12. DOI: https://doi.org/10.1016/j.catena.2007.01.003.
YULIANTO F, SUWARSONO NUGROHO UC, NUGROHO NP, SUNARMODO W and KHOMARUDIN MR, 2020, Spatial-Temporal Dynamics Land Use/Land Cover Change and Flood Hazard Mapping in the Upstream Citarum Watershed, West Java, Indonesia. Quaestiones Geographicae 39(1): 125–146. DOI: https://doi.org/10.2478/quageo-2020-0010.
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Copyright (c) 2024 Fitriany Amalia Wardhani, Elenora Gita Alamanda Sapan, Nicko Widiatmoko, Muhammad Ravi Yuvhendmindo, Budi Heru Santosa, Wiwiek Dwi Susanti, Andrea Emma Pravitasari, Endra Triwisesa, Iwan Ridwansyah
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