Abstract:
Soil erosion is a major land degradation process affecting agricultural sustainability,
soil fertility, and long-term productivity. In low-country agricultural systems, erosion
risk is often assumed to be minimal due to gentle slope conditions; however, variations
in land cover and management can still generate spatial differences in soil loss. This
study applied the Revised Universal Soil Loss Equation (RUSLE) model integrated with
Geographic Information System (GIS) techniques to assess spatial soil erosion patterns
in a coconut plantation managed by the National Livestock Development Board (NLDB)
in Dambadeniya, Sri Lanka, within the Low Country Intermediate Zone (IL1). Rainfall
data, soil properties, Digital Soil Map of the World, Digital Elevation Model (DEM), and
satellite imagery were used to derive rainfall erosivity (R), soil erodibility (K), slope
length and steepness (LS), vegetation cover factor (C), and support practice factor
(P) .The P factor was assigned based on existing land-use conditions and published
RUSLE literature, considering the absence of engineered soil conservation measures.
ArcGIS was used to integrate all factors and generate an annual soil loss map. The study
area covers 619 acres, including 495 acres (79.97%) cultivated coconut land and 124
acres (20.03%) uncultivated land. Estimated annual soil loss ranged from 0 to 3.58 t
ha⁻¹ yr⁻¹, which falls within the low erosion category (<5 t ha⁻¹ yr⁻¹). Although overall
erosion is low, spatial variability was observed across the landscape. Higher soil loss
was mainly associated with reduced vegetation cover and weaker land management
practices, while well-vegetated areas showed minimal erosion. The study
demonstrates that in the study area, even gently sloping coconut landscapes exhibit
spatially variable erosion controlled mainly by land cover. GIS-based RUSLE modelling
effectively identifies erosion variability and supports targeted land management
planning.
