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Article

Coupling RUSLE with Spatial Econometrics: A 35-Year Assessment of Soil Erosion Dynamics and Driving Factors on the Loess Plateau, China (1990–2024)

1
School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 211800, China
2
Changwang School of Honors, Nanjing University of Information Science and Technology, Nanjing 210044, China
3
School of Earth Science and Engineering, Hohai University, Nanjing 211100, China
4
Geological Data Archives of Jiangsu Province, Nanjing 210012, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2026, 18(12), 2034; https://doi.org/10.3390/rs18122034
Submission received: 6 May 2026 / Revised: 16 June 2026 / Accepted: 17 June 2026 / Published: 18 June 2026

Abstract

Soil erosion poses a severe threat to agricultural productivity and ecological security on the Loess Plateau. However, previous studies have rarely integrated physical modeling, elasticity coefficients, and spillover effects into a unified framework at the county level. To address this gap, this study coupled the Revised Universal Soil Loss Equation (RUSLE) with the Spatial Durbin Model (SDM) to systematically investigate the spatiotemporal dynamics, factor elasticity characteristics, and spatial dependence mechanisms of soil erosion on the Loess Plateau from 1990 to 2024. Results show that the annual average erosion rate decreased by 15.5%, with a highly volatile phase before 2001 and a stabilized, low-erosion phase thereafter. The driving factors exhibited marked heterogeneity in direction and strength. The land cover and management factor (C) was the strongest erosion-reducing factor, whereas annual precipitation (PRE) was the primary natural erosion-enhancing factor. County-level erosion also displayed significant positive spatial dependence. PRE had a stable positive indirect effect, whereas C and the support practice factor (P) mainly contained erosion within local jurisdictions. These findings of a unified RUSLE–SDM framework reveal a joint driving mechanism of localized human interventions and climate-driven cross-regional spillovers, providing quantitative support for differentiated soil and water conservation strategies on the Loess Plateau.
Keywords: Loess Plateau; soil erosion; RUSLE model; Spatial Durbin Model; elasticity coefficients; spillover effects; driving factor effects Loess Plateau; soil erosion; RUSLE model; Spatial Durbin Model; elasticity coefficients; spillover effects; driving factor effects

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MDPI and ACS Style

Liang, Y.; Dai, W.; Xia, Y.; Sun, J.; Lin, Q. Coupling RUSLE with Spatial Econometrics: A 35-Year Assessment of Soil Erosion Dynamics and Driving Factors on the Loess Plateau, China (1990–2024). Remote Sens. 2026, 18, 2034. https://doi.org/10.3390/rs18122034

AMA Style

Liang Y, Dai W, Xia Y, Sun J, Lin Q. Coupling RUSLE with Spatial Econometrics: A 35-Year Assessment of Soil Erosion Dynamics and Driving Factors on the Loess Plateau, China (1990–2024). Remote Sensing. 2026; 18(12):2034. https://doi.org/10.3390/rs18122034

Chicago/Turabian Style

Liang, Yuhanbing, Wen Dai, Yujin Xia, Jiangbing Sun, and Qigen Lin. 2026. "Coupling RUSLE with Spatial Econometrics: A 35-Year Assessment of Soil Erosion Dynamics and Driving Factors on the Loess Plateau, China (1990–2024)" Remote Sensing 18, no. 12: 2034. https://doi.org/10.3390/rs18122034

APA Style

Liang, Y., Dai, W., Xia, Y., Sun, J., & Lin, Q. (2026). Coupling RUSLE with Spatial Econometrics: A 35-Year Assessment of Soil Erosion Dynamics and Driving Factors on the Loess Plateau, China (1990–2024). Remote Sensing, 18(12), 2034. https://doi.org/10.3390/rs18122034

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