Evaluating Soil Erosion through Geospatial Techniques: Difficulties and Prospects in the Context of the Central Indian Chambal River Basin

Ashwini Suryawanshi

ICAR- Research Complex for NEH Region, Basar, Arunachal Pradesh Centre, India.

Snehil Dubey *

Agriculture and Food Engineering Department, IIT Kharagpur, West Bengal, India.

Mahima Sharma

Tetra Tech ARD Forest Plus 2.0, Lajpat Nagar 3, New Delhi, India.

*Author to whom correspondence should be addressed.


Abstract

Soil erosion is the greatest threat to the ecosystem which gets accelerated due to environmental agents such as water and wind as well as anthropogenic activities. Effective estimation of soil degradation plays an important role in planning preventive measures and conserving the soil. This study was carried out to provide decision-makers with a picture of soil erosion in Madhya Pradesh's Chambal basin and to identify environmentally hot areas to assist in planning effective conservation measures. By using a few input parameters to create raster maps of the Rainfall erosivity factor (R), Soil erodibility factor (K), Topographic factor (LS), Cover and management factor (C), and Support practice factor (P), the Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE) models were applied. The classification of soil erosion and the area portion in each class was then acknowledged. According to the USLE and RUSLE models, the average soil loss for the entire basin is 2.00 t ha-1 yr-1 and 3.04 t ha-1 yr-1, respectively. According to the USLE and RUSLE models, the ranges under severe risk are 0.33% and 0.76%, while the ranges under extremely severe risk are 0.45% and 0.78%, respectively. The land use/land cover (LULC) map for the study area was acquired from satellite data in the USLE, and the Normalized Difference Vegetation Index (NDVI) map was incorporated into the RUSLE model to enhance the comprehension and identification of vegetation. This integration is crucial for capturing detailed information in the RUSLE model. Consequently, RUSLE yields superior results compared to the USLE model, underscoring the significance of incorporating finer details, especially those related to vegetation, for more accurate outcomes.

Keywords: Soil erosion, universal soil loss equation, remote sensing, revised universal soil loss equation, conservation planning


How to Cite

Suryawanshi , Ashwini, Snehil Dubey, and Mahima Sharma. 2023. “Evaluating Soil Erosion through Geospatial Techniques: Difficulties and Prospects in the Context of the Central Indian Chambal River Basin”. International Journal of Environment and Climate Change 13 (11):4518-33. https://doi.org/10.9734/ijecc/2023/v13i113632.

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