Cloud-Based Estimation and Validation of Sediment Yield in a Mediterranean Watershed Using GEE and RUSLE: A Case Study from Northern Morocco

Department of Natural Resources and Environment, Hassan II Institute of Agronomy and Veterinary Medicine, Rabat, Morocco

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

Soil erosion is a major driver of land degradation and sediment accumulation in Mediterranean watersheds, posing a threat to both agricultural productivity and water infrastructure. The El Hachef watershed is particularly vulnerable in northern Morocco's Rif region because of its steep slopes, variable rainfall, and unsustainable land use practices. This study employed Google Earth Engine (GEE) to estimate sediment yield across two periods using an automated integration of environmental and satellite data within an erosion modeling framework. The model results indicated a notable decline in sediment yield between 2009 and 2014 and 2014 and 2018, highlighting the influence of changing rainfall patterns and vegetation cover. Importantly, the predicted sediment yields closely aligned with those derived from independent bathymetric surveys, with less than a 4% difference in the first period and 13% in the second. This strong agreement underscores the reliability of the GEE-based approach as a practical and cost-effective alternative to field-intensive methods. Spatial analysis identified erosion hotspots on steep cultivated slopes with limited vegetation, providing critical insights for targeted soil conservation measures. Overall, this study highlights the value of cloud-based geospatial platforms for operational sediment monitoring in data-scarce environments, providing timely, scalable, and actionable tools for watershed management and decision-making.