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Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management
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Harmonizing models and measurements: Assessing soil erosion through RUSLE model
Jasin Sidharthan1, Surendran Udayar Pillai1,2, Marimuthu Subbaiyan3
1KSCSTE-Centre for Water Resources Development and Management (CWRDM), Kozhikode, Kerala, India.
Environmental Science and Pollution Research International
|September 19, 2024
Summary
Soil erosion in Kozhikode, India, averages 28.7 tons/hectare annually. This study integrates field data with the Revised Universal Soil Loss Equation (RUSLE) to map erosion risks and propose targeted conservation strategies.
Area of Science:
- Environmental Science
- Soil Science
- Geospatial Analysis
Background:
- Soil erosion presents significant ecological and socioeconomic challenges globally.
- Factors like land use, extreme weather, deforestation, and farming practices exacerbate erosion.
- Kozhikode district, Kerala, exhibits heightened soil erosion vulnerability due to its geography and land-use trends.
Purpose of the Study:
- To assess and map soil erosion risk in Kozhikode district, Kerala, India.
- To integrate field data with the Revised Universal Soil Loss Equation (RUSLE) for accurate erosion prediction.
- To propose context-specific soil conservation and management strategies based on erosion risk.
Main Methods:
- Application of the Revised Universal Soil Loss Equation (RUSLE) model.
- Integration of RUSLE factors: Rainfall erosivity (R), Slope length and steepness (LS), Cover management (C), Conservation practices (P), and Soil erodibility (K).
- Validation of model predictions using extensive field data from agricultural plots in Kozhikode.
Main Results:
- Kozhikode district experiences an average annual soil loss of 28.7 tons per hectare.
- Spatial analysis revealed significant variations in erosion risk, with 14.65% of the area facing extremely severe erosion.
- High correlation between RUSLE-predicted and observed soil loss values, indicated by a low root mean square error.
Conclusions:
- The study successfully mapped soil erosion hotspots in Kozhikode, identifying areas requiring urgent intervention.
- Tailored management strategies for low, medium, and high-priority erosion risk regions were proposed.
- Emphasized the need for long-term field observations to improve watershed-level soil erosion understanding in data-scarce regions.
