article · Geosystems and Geoenvironment
• An integrated multicriteria analysis method to assess water erosion susceptibility. • The factors of precipitation, slope, and lithology are primary factors. • Five risk levels, highlighting significant erosion prevalence in the region. • The method is validated through comparison with field data. Identifying areas vulnerable to soil erosion is essential for the sustainable management of natural resources and the implementation of effective prevention strategies. This study proposes a robust multi-criteria decision analysis (MCDA)framework integrated with geographic information system (GIS) technology to evaluate susceptibility to water erosion in the upstream watershed of Tassaoute (Central High Atlas, Morocco). Elevation, slope, SPI, TWI, NDVI, LULC, lithology, rainfall, distance from river, and drainage density were the ten factors we employed to establish the soil erosion vulnerability map. Criteria weights were measured using the AHP method based on suggestions from different studies and research that ensured an effective way of soil erosion control. The final susceptibility map, created from GIS data and a classification of natural phenomena, identified five distinct levels: very low, low, moderate, high and very high. It reveals a significant erosion threat, with around 60 % of the study area showing moderate to very high levels of erosion. On the other hand, 40 % of the area studied is considered to be at low risk of erosion. Areas at high risk of erosion are more common on steep slopes, with high rainfall and rocks of the marl and clay formation. The accuracy of the results is assessed using the ROC (receiver operating characteristic) curve. The area under the curve (AUC) is 0.782, equivalent to a prediction accuracy of 78.2 %. In conclusion, this model is proving to be a valuable tool for effectively guiding future planning with regard to sustainable soil and water management, in particular by addressing the problem of soil erosion.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1016/j.geogeo.2025.100389
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.