2022
DOI: 10.1007/978-981-16-7373-3_3
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Spatial Prediction of Flood Frequency Analysis in a Semi-Arid Zone: A Case Study from the Seyad Basin (Guelmim Region, Morocco)

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Cited by 16 publications
(11 citation statements)
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“…In this study, we use the AHP model with 14 factors to map the potential groundwater areas (GWPA) in the Ifni basin. This approach has yielded satisfactory results in similar basins [4,5,9,11,19,22]. Our analysis of the factors, such as those used in previous studies [4,5,10,22], revealed that certain relevant factors, such as land use, the intersection between geological lineaments and the hydrographic network, the density of the nodes, and TPI, were not considered in the model.…”
Section: Introductionmentioning
confidence: 79%
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“…In this study, we use the AHP model with 14 factors to map the potential groundwater areas (GWPA) in the Ifni basin. This approach has yielded satisfactory results in similar basins [4,5,9,11,19,22]. Our analysis of the factors, such as those used in previous studies [4,5,10,22], revealed that certain relevant factors, such as land use, the intersection between geological lineaments and the hydrographic network, the density of the nodes, and TPI, were not considered in the model.…”
Section: Introductionmentioning
confidence: 79%
“…This basin lies in the fractured and crystalline formations of the Ifni buttonhole, which is part of the western Anti-Atlas range [6,7]. In hydrological terms, it experiences heavy floods that bring significant volumes of surface water, which could be mobilized [8,9]. However, due to the low permeability of the geological formations, the water is not utilized and is instead lost in the Atlantic Ocean.…”
Section: Introductionmentioning
confidence: 99%
“…In recent decades, the world has been affected by severe flooding, causing thousands of deaths, disruption of economic activities, and infrastructure destruction [2,5,6]. The flooded phenomena have been studied by several researchers, particularly in the development of theories, numerical models, and statistical methodologies, to describe flood behavior and space-time evolution [7][8][9].…”
Section: Introductionmentioning
confidence: 99%
“…In recent years, researchers have developed other techniques to predict the impact of high-intensity and short-duration floods, namely the Weights of evidence Model [20], Frequency Ratio [21], Index of Entropy [22], Random Forest [23], Logistic Regression [24], Artificial Neural Network [25], Index of Entropy [26], Analytical Hierarchy Process [27], and Flood Hazard Index (FHI) [8,28]. The latter, widely applied in several regions of the world, has shown its effectiveness.…”
Section: Introductionmentioning
confidence: 99%
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