TY - JOUR
T1 - Soil erosion prediction and spatiotemporal heterogeneity in driving effects of precipitation and vegetation on the northern slope of Tianshan Mountain
AU - Zhang, Biao
AU - Fang, Haiyan
AU - Wu, Shufang
AU - Li, Chaoyue
AU - Wang, Yan
AU - Siddique, Kadambot H.M.
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/6/25
Y1 - 2024/6/25
N2 - 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.
AB - 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.
KW - Climate change
KW - GTWR
KW - LULC
KW - Northern slope of tianshan mountain
KW - Soil erosion
KW - Spatiotemporal heterogeneity of driving effects
UR - http://www.scopus.com/inward/record.url?scp=85193260630&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2024.142561
DO - 10.1016/j.jclepro.2024.142561
M3 - Article
AN - SCOPUS:85193260630
SN - 0959-6526
VL - 459
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 142561
ER -