SOIL EROSION MODELLING UNDER CLIMATE CHANGE USING RUSLE MODEL- A CASE STUDY OF MABAYANI DAM CATCHMENT IN TANZANIA

Abstract

In Tanzania, as in many other tropical nations, soil erosion and conservation are significant problems. Since the 1920s, policymakers have seen soil erosion as a serious issue. If proper measures are not taken to address the problems, sedimentation will negatively impact the dam's safety in the initial years of operation. Growing rates of soil erosion upstream and sediment transport downstream are the causes of this phenomenon. The altered precipitation trend brought by climate change is one of the main risks associated with soil erosion. This paper aims to determine the future impact of soil erosion caused by climate change in the Mabayani Dam Catchment, Tanga, Tanzania, by downscaling Global Circulation Model (GCM). This study evaluates the CMIP6 Models' ability to forecast future changes under near-term (2024–2050) SSP2-4.5 and SSP5-8.5 scenarios. The RUSLE model is widely used and accepted as the most accurate model for calculating the average annually soil erosion as it is very simple to integrate with GIS and remote sensing. Annual soil loss estimation trends increased from year to year in Mabayani Dam Catchment, the Spatial Analyst tool in ArcGIS computes the minimum values for each year from 2000 to 2050. Average Soil loss rate for the current and future prediction years i.e. from 2000 to 2023 and from 2024 to 2050 estimated by RUSLE Model is 19.13 and 24.93 tons/ha/year respectively. The catchment is divided into nine sub watersheds with the purpose of identifying high-risk areas for soil erosion within each sub watershed and subsequently developing a Catchment Area Treatment Plan (CAT). The sub Watershed near Mabayani dam (SWS6), at a lower elevation, had the highest mean value of sediment yield; as a result, it has been classified as very high risk (> 1300).