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1 Journal of Ecological Engineering

1 2023

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A Comparative Analysis of Analytical Hierarchy Process and Fuzzy Logic Modeling in Flood Susceptibility Mapping in the Assaka Watershed, Morocco

Khaddari Achraf, Jari Abdessamad, Chakiri Saïd, El Hadi Hassan, Labriki Allal, Hajaj Soufiane, Goumghar Lahcen, El Harti Abderrazak, Abioui Mohamed

Journal of Ecological Engineering

2023

Vol. 24, nr 8

62--83

The Assaka watershed is one of the largest watersheds in the Guelmim region in southern Morocco. It is frequently exposed to the many flooding events that can be responsible for many costly human and material damages. This work illustrates a decision-making methodology based on Analytical Hierarchy Process (AHP) and Fuzzy Logic Modelling (FLM), in the order to perform a useful flood susceptibility mapping in the study area. Seven decisive factors were introduced, namely, flow accumulation, distance to the hydrographic network, elevation, slope, LULC, lithology, and rainfall. The susceptibility maps were obtained after normalization and weighting using the AHP, while after Fuzzification as well as the application of fuzzy operators (OR, SUM, PRODUCT, AND, GAMMA 0.9) for the fuzzy logic methods. Thereafter, the flood susceptibility zones were distributed into five flood intensity classes with very high, high, medium, low, and, very low susceptibility. Then validated by field observations, an inventory of flood-prone sites identified by the Draa Oued Noun Hydraulic Watershed Agency (DONHBA) with 71 carefully selected flood-prone sites and GeoEye-1 satellite images. The assessment of the mapping results using the ROC curve shows that the best results are derived from applying the fuzzy SUM (AUC = 0.901) and fuzzy OR (AUC = 0.896) operators. On the other hand, the AHP method (AUC = 0.893) shows considerable mapping results. Then, a comparison of the two methods of SUM fuzzy logic and AHP allowed considering the two techniques as complementary to each other. They can accurately model the flood susceptibility of the Assaka watershed. Specifically, this area is characterized by a high to very high risk of flooding, which was estimated at 67% and 30% of the total study area coverage using the fuzzy logic (SUM operator) and the AHP methods, respectively. Highly susceptible flood areas require immediate action in terms of planning, development, and land use management to avoid any dramatic disaster.