Abstract:
Soil erosion is a critical issue contributing to global land degradation, impacting
agricultural productivity, ecosystems, and hydroelectric power generation. This
research focuses on the Kalu River catchment in Sri Lanka, addressing soil
erosion exacerbated by land-use changes and human activities. The study aims to
quantitatively and spatially assess soil erosion severity, identify vulnerable areas,
and inform effective land use management and soil conservation practices.
Employing an approach combining severity assessment, land-use change
analysis, and the landslide frequency ratio method, this research sets out to
provide valuable insights for landscape vulnerability assessment. The research
objectives include quantifying and mapping yearly soil loss, investigating the
impact of human intervention on soil erosion, identifying spatial patterns of soil
erosion risk, and categorizing sub-catchments based on erosion severity. Utilizing
the Revised Universal Soil Loss Equation (RUSLE), this study spatially mapped
soil loss and conducted multiple linear regression analysis to reveal variable
influences on soil erosion. The K factor exhibited the highest coefficient,
followed by LS, C, P, and R factors. The comparison of the RUSLE and Artificial
Neural Network (ANN) models showed the RUSLE model's superior
performance in assessing soil erosion susceptibility. Statistical analysis of the
RUSLE model revealed mean soil erosion rates of 0.1215tha-1yr-1 in 2000 and
0.1387tha-1yr-1 in 2020. In contrast, the ANN model accurately predicted soil
erosion with a mean value of 0.9872tha-1yr-1. The research underscores spatial
variations in soil erosion among sub-catchments, emphasizing high-risk areas
requiring targeted soil conservation measures. Recommendations include
implementing machine learning techniques like the ANN model for enhanced
predictions and raising awareness through campaigns and training programs to
foster community engagement in soil conservation efforts. The identification of
high-priority areas in the Kalu River basin emphasizes the importance of
continuous monitoring, appropriate land cover management, and vegetation
practices for sustainable land use.
