Soil erosion prediction and spatiotemporal heterogeneity in driving effects of precipitation and vegetation on the northern slope of Tianshan Mountain.

Soil erosion changes become more unclear in the future due to climate change and increased human activity. However, the spatiotemporal heterogeneity in the driving effects of key factors on soil erosion remains inadequately understood on the northern slope of the Tianshan Mountains (NSTM). In this paper, the spatiotemporal evolution of soil erosion on the NSTM was evaluated in the historical period (2000–2015) by the Revised Universal Soil Loss Equation (RUSLE) model. Subsequently, the FLUS-CMIP6-RUSLE model was employed to predict soil erosion in the future period (2030–2050). Then, the GTWR model was used to dissect the spatiotemporal heterogeneity in the driving effects of precipitation and vegetation. The results indicated that soil erosion on the NSTM fluctuated from 2000 to 2015, increasing by 1.77 t ha −1 yr −1. Soil erosion areas mainly occurred in Changji City, Fukang City, Hutubi County, Mulei County, Qitai County, and Turpan City. The soil erosion modulus in 2030, 2040, and 2050 under different climate scenarios will be 26.56,28.83, and 37.49 t ha −1 yr −1, respectively. The spatial pattern of soil erosion is similar to the historical period. Precipitation was the main factor intensifying soil erosion in the eastern and western counties from 2000 to 2020, while the soil erosion change in central counties was affected by vegetation. In the future, soil erosion change in the counties (i.e., Karamay, Yili, Tacheng, Shihezi, Manas, Qitai, and Mulei) will be driven by precipitation. The vegetation will be the main driver of soil erosion change in central and eastern counties (i.e., Urumqi, Turpan, Fukang City, Jimsar County, and Changji City). This study firstly attempts to explore the spatiotemporal heterogeneity in the driving effects of precipitation and vegetation using Spatial-Temporal Geographically Weighted Regression (GTWR) in urban agglomerations of NSTM. It is meaningful to explore erosion-prone regions and to implement rational soil conservation measures in the study region and similar regions in the world. [Display omitted] • A coupled model was constructed to predict soil erosion for future scenarios on NSTM. • The spatiotemporal heterogeneity in effects of precipitation and vegetation were explored using GTWR. • Precipitation exacerbated soil erosion in eastern and western counties (2000 - 2020); central counties more by vegetation. • Vegetation to be key factor driving soil erosion change in Turpan; Wujiaqv and Mulei by precipitation (2030 - 2050). [ABSTRACT FROM AUTHOR]