Characteristics of seasonal snow cover variations and their effects on soil moisture and vegetation dynamics in Xinjiang
- 1College of Water Conservancy and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China; Xinjiang Key Laboratory of Hydraulic Engineering Security and Water Disasters Prevention, Urumqi 830052, China
- 2College of Water Conservancy and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China; Xinjiang Key Laboratory of Hydraulic Engineering Security and Water Disasters Prevention, Urumqi 830052, China; Corresponding author at: College of Water Conservancy and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China.
Abstract
Snow cover acts as a critical regulator of the hydrological cycle and ecological stability in arid and semi-arid regions. Focusing on Xinjiang, this study integrated multi-source data from 2000 to 2023, including spring snowmelt (SSM), snow depth (SD), climatic factors (spring temperature, ST; spring precipitation, SP), spring soil moisture (SM), and the Normalized Difference Vegetation Index (NDVI). By combining trend analysis, correlation analysis, XGBoost, and structural equation modeling (SEM), we systematically investigated the spatial patterns of spring snow under climate change and their relationships with SM and NDVI. The results indicate that both SSM (−0.44 mm/year) and SD (−2.80 mm/year) in Xinjiang exhibited a declining trend. Increasing spring temperature was identified as a major factor associated with snowpack thinning, and its negative effect weakened the positive replenishment effect of spring precipitation on spring snow conditions. Spring snow exhibited a relatively stable positive linkage with soil moisture (SM), with positive correlations accounting for more than 70% of the study area; however, this moisture linkage was not synchronously reflected in increased vegetation greenness. XGBoost-SHAP analysis showed that spring precipitation had the highest relative importance in predicting SM, whereas NDVI prediction was mainly influenced by climatic factors and SM, with lower relative contributions from SSM and SD. Furthermore, SEM results indicated a strong positive pathway between SSM and SM (path coefficient = 0.43), while the direct pathway between SSM and NDVI was relatively weak (−0.02), suggesting that the relationship between spring snow and vegetation dynamics may be largely associated with SM mediation. Meanwhile, spring temperature exhibited a strong direct positive pathway with NDVI. Over the past 24 years, SM and NDVI in Xinjiang have exhibited a “decreasing water, increasing greenness” divergence, which may be attributed to warming that, on the one hand, promotes earlier vegetation green-up, while on the other hand advances snowmelt and enhances evapotranspiration, thereby reducing SM. This study systematically revealed the associations and asynchronous responses among climate factors, snow variables, SM, and NDVI in Xinjiang. These findings provide a scientific basis for ecological security early-warning and adaptive water resource management in arid regions.
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BibTeX
@article{qiu2026characteristics,
title = {{Characteristics of seasonal snow cover variations and their effects on soil moisture and vegetation dynamics in Xinjiang}},
author = {Xiaoyan Qiu and Zhenxia Mu and Rongqin Yang and Zilong Li and Jing Liu},
journal = {Ecological Indicators},
year = {2026},
month = oct,
doi = {10.1016/j.ecolind.2026.115514},
url = {https://doi.org/10.1016/j.ecolind.2026.115514},
note = {CC BY},
}
RIS
TY - JOUR
TI - Characteristics of seasonal snow cover variations and their effects on soil moisture and vegetation dynamics in Xinjiang
AU - Xiaoyan Qiu
AU - Zhenxia Mu
AU - Rongqin Yang
AU - Zilong Li
AU - Jing Liu
PY - 2026
DA - 2026/10/23
JO - Ecological Indicators
DO - 10.1016/j.ecolind.2026.115514
UR - https://doi.org/10.1016/j.ecolind.2026.115514
AB - Snow cover acts as a critical regulator of the hydrological cycle and ecological stability in arid and semi-arid regions. Focusing on Xinjiang, this study integrated multi-source data from 2000 to 2023, including spring snowmelt (SSM), snow depth (SD), climatic factors (spring temperature, ST; spring precipitation, SP), spring soil moisture (SM), and the Normalized Difference Vegetation Index (NDVI). By combining trend analysis, correlation analysis, XGBoost, and structural equation modeling (SEM), we systematically investigated the spatial patterns of spring snow under climate change and their relationships with SM and NDVI. The results indicate that both SSM (−0.44 mm/year) and SD (−2.80 mm/year) in Xinjiang exhibited a declining trend. Increasing spring temperature was identified as a major factor associated with snowpack thinning, and its negative effect weakened the positive replenishment effect of spring precipitation on spring snow conditions. Spring snow exhibited a relatively stable positive linkage with soil moisture (SM), with positive correlations accounting for more than 70% of the study area; however, this moisture linkage was not synchronously reflected in increased vegetation greenness. XGBoost-SHAP analysis showed that spring precipitation had the highest relative importance in predicting SM, whereas NDVI prediction was mainly influenced by climatic factors and SM, with lower relative contributions from SSM and SD. Furthermore, SEM results indicated a strong positive pathway between SSM and SM (path coefficient = 0.43), while the direct pathway between SSM and NDVI was relatively weak (−0.02), suggesting that the relationship between spring snow and vegetation dynamics may be largely associated with SM mediation. Meanwhile, spring temperature exhibited a strong direct positive pathway with NDVI. Over the past 24 years, SM and NDVI in Xinjiang have exhibited a “decreasing water, increasing greenness” divergence, which may be attributed to warming that, on the one hand, promotes earlier vegetation green-up, while on the other hand advances snowmelt and enhances evapotranspiration, thereby reducing SM. This study systematically revealed the associations and asynchronous responses among climate factors, snow variables, SM, and NDVI in Xinjiang. These findings provide a scientific basis for ecological security early-warning and adaptive water resource management in arid regions.
SN - 1470-160X
SN - 1872-7034
ER -