Soil erosion caused by rain and runoff is a global issue that keeps getting worse over time. Damage caused by this phenomenon includes accelerated silting of dams. Considering that the storage capacity of major hydraulic structures gradually degrades owing to cumulative sedimentation, Tunisia faces severe environmental threats due to the annual decrease in reservoir capacity. Plant cover and land use are the most significant factors influencing the severity of soil erosion. In this vein, this study investigated the effect of soil cover on erosion at two agricultural sites in the El Kbir watershed, north Tunisia, using the cesium-137 (Cs-137) radioisotope tracer method. This radioactive element has been successfully used for investigating rates and patterns of soil erosion. The cesium-137 inventory obtained for the reference site is about 1341 Bq m-2. For study plots cultivated with olive trees and cereal crops, Cs-137 inventories are about 1036.37 Bq m-2 and 426.82 Bq m-2, respectively. The results show that the net erosion rate estimated by the mass balance model 2 (MBM2) was significantly higher in the cereal cultivated plot with 28.95 t ha-1 year-1 than in the olive cultivated plot with 7.16 t ha-1 year-1. The difference in net erosion rates between the two fields reveals the crucial role of the soil cover, as olive trees showed better resistance to erosive effects because of their system of roots. In contrast, culture of cereal crops, which occupy around 50% of the total area in the region, does not effectively protect and maintain the soil against erosion, which in turn induces intensive erosion of soil, resulting in sedimentation in dams. Soil erosion can therefore be reduced by adapting land use and increasing adequate vegetation cover.

Assessing the spatial distribution of the erosion process is considered a critical initial step to provide valuable insights to decision-makers for devising an effective erosion mitigation strategy to reduce erosion damages. This research was conducted based on a revised universal soil loss equation (RUSLE) model integrated with the geographic information environment (GIS) within the Wadi El Ghareg watershed located in the Menzel Bourguiba region in northeastern Tunisia to simulate the spatial distribution of erosion across the basin which has been experiencing adverse effects of climate change, characterized by periods of drought and heavy rainfall. The RUSLE incorporates several variables, including rainfall erosivity (R), soil erodibility (K), cover management (C), slope length (LS), and conservation practices (P), serving as key predisposition parameters in this research. For the validation process of the applied model, 200 points were selected to create an inventory map; the points were selected based on satellite images and field surveys. The obtained thematic maps were normalized by fuzzy logic and overlaid using the model equation in the GIS. The results identified the most severely eroded areas requiring immediate erosion control measures. Hence, the results reveal that about 1.71% of the area is covered under severe erosion risk, 0.13% area under high erosion risk, 0.26% area under moderate erosion risk, 0.27% area under low erosion risk, and 97.63% of the area under very low erosion risk. The accuracy of the model was evaluated based on the receiver operating characteristic curves (ROC) and the areas under the curves (AUC). The result showed that this model had an excellent predictive accuracy for soil erosion susceptibility, with AUC values of 0.967. The final produced map will be used as a basis for suggesting a framework that can help make practical policy recommendations to fight against erosion in the context of sustainable management of the watershed.