Soil erosion and sediment yield estimation integrating RUSLE and SDR models in the Mesima basin (Calabria, southern Italy)

Massimo Conforti¹, Francesco Chiaravalloti¹ & Fabio Ietto^2
1National Research Council of Italy - Research Institute for Geo-Hydrological Protection (CNR-IRPI), Via Cavour 4/6, 87036 Rende, Italy.
²Department of Biology, Ecology and Earth Science, University of Calabria, Via P. Bucci, Cubo 15B, 87036 Arcavacata di Rende, Italy.
Corresponding author e-mail: massimo.conforti@cnr.it

Soil erosion is a major driver of land degradation, threatening environmental and socioeconomic sustainability. The present study aimed to evaluate the average annual soil loss in the Mesima River basin located in the central-southern sector of the Calabria region (southern Italy). In addition, the study computed the average sediment yield and identified the average sources of sediment within the basin. A spatially distributed approach was applied, integrating the Revised Universal Soil Loss Equation (RUSLE) and Sediment Delivery Ratio (SDR) models with GIS and remote sensing techniques. The results showed that annual soil loss within the basin varied from 0 to 258.35 t/ha/yr with a mean of 3.37 t/ha/yr. The computed yearly soil loss was about 271760 tons. Moreover, the estimated sediment yield within the basin ranged from 0 to 95.75 t/ha/yr with a mean of 1.07 t/ha/yr; consequently, the annual sediment yield is anticipated to be 86.637 tons. These results indicate that approximately 32% of eroded soil is transported to streams, whereas 68% is retained and deposited without reaching streams. Our results show that the Mesima basin is highly diverse in erosion and sediment yield owing to variable topographic, geomorphic, and land-use/cover characteristics across sub-basins. Topographic steepness (LS factor) makes the most significant contribution to soil erosion, followed by the crop and management (CP) factors, in most sub-basins. The current investigation effectively identified erosion-prone areas and critical sediment sources, offering valuable support for sustainable land management and soil conservation planning.

land degradation, erosion modelling, sediment yield, GIS, remote sensing.