Cropland water erosion simulated by RUSLE2 with updated erosivity and, temperature and precipitation normals

Authors: MOMM, HENRIQUE - Middle Tennessee State University; Wells, Robert; ELKADIRI, RACHA - Middle Tennessee State University; SEEVER, T - Middle Tennessee State University; YODER, D - University Of Tennessee; DARNAULT, CJG - Clemson University; Bingner, Ronald

Submitted to: Catena
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/15/2025
Publication Date: N/A
Citation: N/A

Interpretive Summary: Conservationists, in partnership with producers, use soil erosion estimation technology to support the development of plans to protect topsoil and promote crop yield. These tools aid in the selection farming best management practices and implementation of conservation alternatives. One important U.S. Department of Agriculture (USDA) technology is the Revised Universal Soil Loss Equation, Version 2 (RUSLE2) soil erosion model. A complete set of input databases is used to accurately describe local existing conditions, where climate is a key input database when estimating soil erosion. In this study, climate database updates based on historic observations, were used to quantify their impact on soil loss estimation in the contiguous US. Five 30-year climate datasets from 1970 to 2020 and shifted by five years were used. The top two dominant crops in the U.S., corn and soybeans, were selected covering more than half of the farmland and are represented in nearly 1,900 counties across the country. Analysis of changes over time and space suggests an increasing trend in soil loss in the central portion of the eastern continental US. These trends were affected by soil type and farming management. Findings indicate that updates to climate databases could improve soil loss estimates and site-specific conservation cropland field planning designs.

Technical Abstract: Soil loss associated with farming activities has lasting impacts locally and regionally. Mitigating topsoil loss within farming systems can be a complex task given the large scale of operations and the multifaceted controlling factors that range from climate/weather, physical conditions, chemical parameters, and anthropogenic factors. Modelling technology supports soil conservation efforts by integrating knowledge from multiple physical processes to offer timely evaluation of different system alternatives. These systems are sensitive to the input databases that guide soil loss calculations. The current study is designed to assess and quantify the impact of updated input climate databases on soil loss estimates at the contiguous United States (CONUS) scale using the RUSLE2 soil erosion model. Two dominant crops were identified: corn/maize (Zea mays) and soybean (Glycine max), which totaled a combined 55% of the total agricultural area in the CONUS, and a total of 1867 counties/zones were considered. Three analyses were performed by varying the input climate and management databases. First, a comparison of soil loss using the official RUSLE2 climate database and two others that employed updated analytical procedures yielded excellent agreement, and lower residual variance was found when considering all small events. The same procedure was used to generate five 30-year climate databases that shifted by 5 years from 1970 to 2020. Temporal and spatial analysis considered generic and local management. Temporal analysis of soil loss estimates suggests an increasing trend in the central portion of the eastern CONUS. These trends were magnified or reduced by soil type and management schedule and operations. Findings indicate that updates to climate databases could be utilized to improve soil loss estimates and site-specific conservation planning design.