Integrating a GIS and Remote Sensing Approach in the Agricultural Conservation Decision Support Tool for Soil Erosion Estimation

Shrivastav, Manish; Mickelson, Steven; Tim, Udoyara S.; Webber, David F.

Integrating a GIS and Remote Sensing Approach in the Agricultural Conservation Decision Support Tool for Soil Erosion Estimation

File

2025-Mickelson-IntegratingAGIS.pdf (1.65 MB)

Date

2025-04

Authors

Shrivastav, Manish

Mickelson, Steven

Tim, Udoyara S.

Webber, David F.

Publisher

American Society of Agricultural and Biological Engineers (ASABE)

Abstract

Severe soil erosion due to intensified agriculture and other anthropogenic activities is a major contributor to land degradation. Landscape modeling can provide quantitative and consistent estimates of soil erosion under a wide range of conditions for planning best management practices at the field- and watershed-scale. This study incorporated the Universal Soil Loss Equation (USLE) model with a Geographical Information System (GIS) and Remote Sensing (RS) data to develop and demonstrate a component of the Agricultural Conservation Decision Support Tool (AgConDST). This component of the AgConDST was developed to identify sediment source areas and estimate soil erosion from various catchments. The catchments were discretized into hydrologically homogeneous grid cells to capture the catchment heterogeneity. Gross soil erosion in each cell was then calculated using the USLE by carefully determining its various parameters. This USLE- and GIS-based sub-tool component of the AgConDST can effectively identify high and low erosion-prone zones and consequently aid in the implementation of soil conservation practices.

Academic or Administrative Unit

Department of Agricultural and Biosystems Engineering (CALS)

Type

article

Comments

This article is published as Shrivastav, Manish, Steven K. Mickelson, Udoyara S. Tim, and David F. Webber. "Integrating a GIS and Remote Sensing Approach in the Agricultural Conservation Decision Support Tool for Soil Erosion Estimation." Applied Engineering in Agriculture (2025): 0. doi: https://doi.org/10.13031/aea.16070.

Rights Statement

© 2025 American Society of Agricultural and Biological Engineers. The authors have paid for open access for this article. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/).