Geospatial Modeling Based-Multi-Criteria Decision-Making for Flash Flood Susceptibility Zonation in an Arid Area

نویسندگان

چکیده

Identifying areas susceptible to flash flood hazards is essential mitigating their negative impacts, particularly in arid regions. For example, southeastern Sinai, the Egyptian government seeks develop its coastal along Gulf of Aqaba maximize national economy while preserving sustainable development standards. The current study aims map and predict prone utilizing a spatial analytic hierarchy process (AHP) that integrates GIS capabilities, remote sensing datasets, NASA Giovanni web tool application, principal component analysis (PCA). Nineteen triggering parameters were initially considered for developing susceptibility model by conducting detailed literature review using our experiences food studies. Next, PCA algorithm was utilized reduce subjective nature researchers’ judgments selecting factors. By reducing dimensionality data, we eliminated ten explanatory variables, only nine relatively less correlated factors retained, which prevented creation an ill-structured model. Finally, AHP method determine relative weights based on significance floods. resulting as follows: rainfall (RF = 0.310), slope (S 0.221), drainage density (DD 0.158), geology (G 0.107), height above nearest network (HAND 0.074), landforms (LF 0.051), Melton ruggedness number (MRN 0.035), plan curvature (PnC 0.022), stream power index (SPI 0.022). research proved AHP, among most dependable methods multi-criteria decision-making (MCDM), can effectively classify degree risk ungauged areas. found 59.2% area assessed at very low flood, 21% high risk, 19.8% moderate risk. Using under receiver operating characteristic curve (AUC ROC) statistical evaluation metric, GIS-based developed demonstrated excellent predictive accuracy, achieving score 91.6%.

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ژورنال

عنوان ژورنال: Remote Sensing

سال: 2023

ISSN: ['2315-4632', '2315-4675']

DOI: https://doi.org/10.3390/rs15102561