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Quantifying Sahel Runoff Sensitivity to Climate Variability, Soil Moisture and Vegetation Changes Using Analytical Methods
Quantifying Sahel Runoff Sensitivity to Climate Variability, Soil Moisture and Vegetation Changes Using Analytical Methods
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Quantifying Sahel Runoff Sensitivity to Climate Variability, Soil Moisture and Vegetation Changes Using Analytical Methods
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Quantifying Sahel Runoff Sensitivity to Climate Variability, Soil Moisture and Vegetation Changes Using Analytical Methods
Quantifying Sahel Runoff Sensitivity to Climate Variability, Soil Moisture and Vegetation Changes Using Analytical Methods

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Quantifying Sahel Runoff Sensitivity to Climate Variability, Soil Moisture and Vegetation Changes Using Analytical Methods
Quantifying Sahel Runoff Sensitivity to Climate Variability, Soil Moisture and Vegetation Changes Using Analytical Methods
Journal Article

Quantifying Sahel Runoff Sensitivity to Climate Variability, Soil Moisture and Vegetation Changes Using Analytical Methods

2025
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Overview
Whilst substantial efforts have been deployed to understand the “Sahel hydrological paradox”, most of the studies focused on small experimental watersheds around the central and western Sahel. To our knowledge, there is no study on this issue covering all the watersheds located within the Sahelian belt. The absence of relevant studies may be attributed to a sparsity of in situ data leading to a dearth of knowledge on the Sahel hydrology. To fill this knowledge gap, the present study leverages analytical methods and freely available geospatial datasets to understand the effects of climatic factors, soil moisture and vegetation cover changes on surface runoff in 45 watersheds located within the Sahelian belt over two decades (2000–2021). Analyses show increasing trends in annual precipitation and potential evapotranspiration (PET) in more than 80% of the watersheds. Surface runoff, soil moisture (SM), and vegetation cover measured using the normalised difference vegetation index (NDVI) also show increasing trends in all the watersheds. Multivariable linear regression (MLR) analyses reveal that precipitation, PET, SM, and NDVI contribute about 62% of surface runoff variance. Further analyses using MLR, and the partial least squares regression (PLSR) show that precipitation and NDVI are the main factors influencing surface runoff in the Sahel. Elasticity coefficients reveal that a 10% increase in precipitation, SM and NDVI may lead to about 22%, 26% and 45% increase in surface runoff respectively. In contrast, a 10% increase in PET may lead to a 61% decline in surface runoff in the Sahel. This is the first hydrological study covering all the watersheds located within the Sahelian belt with results showing that surface runoff is influenced by climate, SM and NDVI to varying degrees. Given the unique hydrological characteristics of the Sahel, a better understanding of the different factors influencing surface runoff may be crucial for enhancing climate adaptation and ecological restoration efforts in the region such as the Great Green Wall Initiative.