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

被引:5
|
作者
Khaddari, Achraf [1 ]
Jari, Abdessamad [2 ]
Chakiri, Said [1 ]
El Hadi, Hassan [3 ]
Labriki, Allal [3 ]
Hajaj, Soufiane [2 ]
Goumghar, Lahcen [4 ]
El Harti, Abderrazak [2 ]
Abioui, Mohamed [5 ,6 ]
机构
[1] Ibn Tofail Univ, Fac Sci, Dept Geol, Lab Geosci, Kenitra 133, Morocco
[2] Sultan Moulay Slimane Univ, Fac Sci & Tech, Lab Geomat Georesources & Environm, Beni Mellal 23000, Morocco
[3] Hassan II Univ, Fac Sci Ben MSik, Dept Geol, Geodynam Lab Old Chains, Casablanca 7955, Morocco
[4] Ibn Tofail Univ, Fac Sci, Nat Resources & Sustainable Dev Lab, Kenitra 133, Morocco
[5] Ibnou Zohr Univ, Fac Sci, Dept Earth Sci, Geosci Environm & Geomat Lab, Agadir 80000, Morocco
[6] Univ Coimbra, Fac Sci & Technol, Dept Earth Sci, MARE Marine & Environm Sci Ctr,Sedimentary Geol G, P-3030790 Coimbra, Portugal
来源
JOURNAL OF ECOLOGICAL ENGINEERING | 2023年 / 24卷 / 08期
关键词
Assaka watershed; flood susceptibility; GIS; multi-criteria analysis; FLM; AHP; FREQUENCY RATIO; AREAS; DECISION; PREDICTION; REGRESSION; RAINFALL; GUMBEL; TOOLS;
D O I
10.12911/22998993/165958
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 Fuzzifi-cation 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.
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页码:62 / 83
页数:22
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