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Analysis of Spatiotemporal Variability and Drivers of Soil Moisture in the Ziwuling Region

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  • Jing Li

    (State Key Laboratory of Water Engineering Ecology and Environment in Arid Area, Xi’an University of Technology, Xi’an 710048, China)

  • Yinxue Luo

    (State Key Laboratory of Water Engineering Ecology and Environment in Arid Area, Xi’an University of Technology, Xi’an 710048, China)

  • Zhanbin Li

    (State Key Laboratory of Water Engineering Ecology and Environment in Arid Area, Xi’an University of Technology, Xi’an 710048, China)

  • Guoce Xu

    (State Key Laboratory of Water Engineering Ecology and Environment in Arid Area, Xi’an University of Technology, Xi’an 710048, China)

  • Mengjing Guo

    (State Key Laboratory of Water Engineering Ecology and Environment in Arid Area, Xi’an University of Technology, Xi’an 710048, China)

  • Fengyou Gu

    (State Key Laboratory of Water Engineering Ecology and Environment in Arid Area, Xi’an University of Technology, Xi’an 710048, China)

Abstract

Understanding soil moisture’s spatiotemporal variations and the factors influencing it is crucial for the restoration and growth of vegetation across the Loess Plateau, particularly in the Ziwuling region. This study employs soil moisture remote sensing data, complemented by information on soil properties, environmental conditions, and topography, to examine soil moisture variability within the Ziwuling region between 2001 and 2020. Using trend analysis, geographic detectors, and multi-scale geographic weighting techniques, this research aims to elucidate the effects of driving factors on soil moisture’s spatiotemporal patterns. The findings indicate the following: (1) Over the study period, the mean soil moisture in the Ziwuling region exhibited a relatively stable declining trend, with an annual decrease of −0.00047 m 3 /(m 3 ·a). Spatially, higher soil moisture levels were observed in the south-central area, while lower levels occurred in the northern, western, and eastern peripheries. (2) Geoprobe analysis illustrated that the normalized difference vegetation index (NDVI) had the most notable effect on the spatial distribution of soil moisture in the region. As a direct indicator of vegetation cover, NDVI strongly affects soil moisture distribution through ecological and hydrological processes. Following NDVI, average annual potential evapotranspiration and annual precipitation were identified as the next most influential factors. The combined effect of these factors on soil moisture surpassed that of individual factors, with the interaction between NDVI and annual precipitation being particularly pronounced, predominantly controlling the spatial variability of soil moisture in the Ziwuling region. (3) Different factors exhibited varying effects on soil moisture levels. Notably, slope and elevation consistently had negative impacts, whereas variables such as soil texture (loam and sand), land use, temperature, precipitation, NDVI, and slope aspect showed bidirectional influences. This study offers a comprehensive analysis of the spatiotemporal variability of soil moisture and its controlling factors in the Ziwuling region, ultimately offering a scientific basis to support ecological restoration and sustainable development initiatives on the Loess Plateau.

Suggested Citation

  • Jing Li & Yinxue Luo & Zhanbin Li & Guoce Xu & Mengjing Guo & Fengyou Gu, 2025. "Analysis of Spatiotemporal Variability and Drivers of Soil Moisture in the Ziwuling Region," Sustainability, MDPI, vol. 17(17), pages 1-24, September.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:17:p:8025-:d:1743430
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    References listed on IDEAS

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    1. Yonghua Zhao & Li Liu & Shuaizhi Kang & Yong Ao & Lei Han & Chaoqun Ma, 2021. "Quantitative Analysis of Factors Influencing Spatial Distribution of Soil Erosion Based on Geo-Detector Model under Diverse Geomorphological Types," Land, MDPI, vol. 10(6), pages 1-17, June.
    2. Huang, Ze & Liu, Yu & Qiu, Kaiyang & López-Vicente, Manuel & Shen, Weibo & Wu, Gao-Lin, 2021. "Soil-water deficit in deep soil layers results from the planted forest in a semi-arid sandy land: Implications for sustainable agroforestry water management," Agricultural Water Management, Elsevier, vol. 254(C).
    3. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
    4. Xue Li & Kunxia Yu & Xiang Zhang & Guojun Zhang & Zhanbin Li & Peng Li & Xiaoming Zhang & Yang Zhao & Wentao Ma, 2023. "Spatial and Temporal Evolutionary Characteristics of Vegetation in Different Geomorphic Zones of Loess Plateau and Its Driving Factor Analysis," Sustainability, MDPI, vol. 15(16), pages 1-19, August.
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