A comparison of the analytical hierarchy process and the fuzzy logic approach for flood susceptibility mapping in a semi-arid ungauged basin (Biskra basin: Algeria). Issue 2 (3rd April 2022)

• Record Type: Journal Article
• Authors: Bouamrane, Ali; Derdous, Oussama; Dahri, Noura; Tachi, Salah-Eddine; Boutebba, Khereddine; Bouziane, Mohamed T.
• Is Part Of: International journal of river basin management. Volume 20:Issue 2(2022)
• Page Start: 203
• Page End: 213
• Publication Date: 2022-04-03
• Subjects: AHP -- Biskra river basin -- FAHP -- flood susceptibility areas -- GIS -- RS; Watershed management -- Periodicals; Water resources development -- Periodicals; Hydraulic engineering -- Periodicals; Watershed hydrology -- Periodicals; Water resources development; Watershed management; Watersheds; Periodicals; 551.483
• DOI: 10.1080/15715124.2020.1830786
• Languages: English
• ISSNs: 1814-2060

Abstract

ABSTRACT: The study presented herein proposes a multi-criteria decision-making tool to identify flood susceptibility areas on a regional scale. The adopted approach is based on the integration of multi-criteria analysis, geographical information systems (GIS) and remote sensing (RS) techniques. Accordingly, flood susceptibility maps were prepared depending on information from six flood-conditioning factors namely Rainfall, Elevation, Slope, Land use/cover, Soil type, and Distance from the river. The relative importance of each factor on the flood susceptibility was assigned based on experts' judgements and then connected to weight values. Two techniques were employed for weight calculation; the analytical hierarchy process (AHP) and the Fuzzy analytic hierarchy process (FAHP). The presented approach was applied to the Biskra basin, located north-eastern Algeria at the Sahara limits. The obtained maps indicate flood susceptibility areas, with high and very high flood susceptibility, mainly occurring at the northern areas of the basin which receive more rainfall, and also in urban areas all over the basin close to drainage networks. The performances of the two models were evaluated using the receiver operating characteristic (ROC) curve and the area under the curve (AUC) by comparing the obtained maps to an inventory map of past flood events. The evaluation results indicated that both the AHP and the FAHP models were found to be suited in predicting flood prone areas in the Biskra basin with AUC values of 93, 61% and 96, 61% respectively. Nevertheless, the FAHP model is preferred due to its ability to minimize vagueness and uncertainty associated with human judgements.