Harmonizing models and measurements: Assessing soil erosion through RUSLE model

Soil erosion poses significant ecological and socioeconomic challenges, driven by factors such as inappropriate land use, extreme rainfall events, deforestation, farming methods, and climate change. This study focuses on the Kozhikode district in Kerala, South India, which has seen increased vulnerability to soil erosion due to its unique geographical characteristics, increase in extreme events, and recent land use trends. The research employs RUSLE (Revised Universal Soil Loss Equation), considering multiple contributing factors such as rainfall erosivity (R), slope length and steepness (LS), cover management (C), conservation practices (P), and soil erodibility (K). The study is unique and novel, since it integrates extensive field data collected from agricultural plots across Kozhikode with the RUSLE model predictions, providing a more accurate and context-specific understanding of soil erosion processes and also suggesting management strategies based on risk priority. The study found that Kozhikode experiences an average annual soil loss of 28.7 tons per hectare. A spatial analysis revealed varying erosion risk levels across the district. 52.0% of the area experiences very slight erosion, 10.31% has slight erosion, 6.18% undergoes moderate erosion, 3.88% is moderately severe, 7.34% is at severe erosion risk, 5.6% has very severe erosion, and 14.65% faces extremely severe erosion. Field data collected from agricultural plots across Kozhikode were compared with RUSLE-predicted values, revealing a low root mean square error, indicating a strong correlation between observed and simulated data. Based on these findings, the district was categorized into low, medium, and high-priority regions, with tailored recommendations proposed for each. Implementing these measures could mitigate erosion, preserve soil fertility, and support the long-term sustainability of natural and agricultural ecosystems in Kozhikode. Given the practical challenges in estimating RUSLE factors in Southern India, where data scarcity is a common issue, this preliminary study underscores the need for expanded, long-term field observations to enhance understanding of soil erosion processes at the watershed level.