What is it about?
The Geographic Information System (GIS), the Revised Universal Soil Loss Equation (RUSLE), the Analytic Hierarchy Process (AHP), and machine learning algorithms (Random Forest and Reduced Error Pruning (REP) tree) were used in this study to identify the soil erosion risk zones in the Ratlam District.
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Why is it important?
Agriculture employs a sizable age of the population in Ratlam District. Due to a lack of fertility, regions prone to soil erosion are underutilised for agriculture. The remaining agricultural productive fields are in moderate danger of soil erosion. Apart from the subtropical hot summer and general dryness of the study area, which characterise the climatic setting, the effects of soil erosion on fertile land make this study critical for estimating soil erosion and assisting in the preservation of remaining productive lands.
Perspectives
In this study, the soil erosion risk zone of Ratlam District was modelled using geospatial technology, RUSLE, AHP, and machine learning algorithms. The current study could assist the government and non-governmental organisations in appropriately implementing development initiatives and policies.
Prolay Mondal
Raiganj University
Read the Original
This page is a summary of: Assessing and mapping soil erosion risk zone in Ratlam District, central India, Regional Sustainability, December 2022, Elsevier,
DOI: 10.1016/j.regsus.2022.11.005.
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