Spatiotemporal Variability and Dominant Driving Factors of Soil Moisture in the Yellow River Basin from 1982 to 2024

Soil moisture (SM) is a pivotal state variable of the terrestrial hydrosphere, modulating energy partitioning, agricultural productivity and extreme-event propagation. This study analyzes 43 years (1982–2024) of data to assess soil moisture (SM) dynamics in the Yellow River Basin (YRB). Results indicate a statistically significant basin-wide SM decline across weekly, monthly, and annual scales, with grid-scale slopes ranging from −2.26 × 10−4 to 8.32 × 10−5 m3 m−3 month−1. Spatially, non-farm areas retain higher SM than cultivated lands, with a distinct upstream-to-downstream variability pattern. While alpine headwaters show moistening, pervasive drying characterizes mid- and lower-catchments. Critically, transitional landscapes are approaching tipping points, risking shifts into persistently wetter or drier stable states where minor perturbations could lock ecosystems into new conditions. This underscores the urgent need for targeted climate-adaptation interventions. Generalized additive modeling identifies surface net solar radiation, soil temperature, and vapor pressure deficit as dominant drivers across multiple temporal scales. Their respective contributions, averaged across the basin, accounted for 29.4%, 25.3%, and 23.0% of the explained variance. Additionally, actual evapotranspiration emerged as a significant driver on the weekly scale, particularly within the center of the basin. These findings enhance process-based understanding of SM variability and provide a scientific foundation for adaptive water-resource management in the YRB.

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Publication Details

Journal
Agronomy
Published
2026-04-12
DOI
https://doi.org/10.3390/agronomy16080791
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.00

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article

Spatiotemporal Variability and Dominant Driving Factors of Soil Moisture in the Yellow River Basin from 1982 to 2024

Honghui Sang, Qingbao Pei, Xinyu Zhao, Qianya Yang et al.
Agronomy
Soil Moisture and Remote Sensing
article

Spatiotemporal Variability and Dominant Driving Factors of Soil Moisture in the Yellow River Basin from 1982 to 2024

Honghui Sang, Qingbao Pei, Xinyu Zhao, Qianya Yang, Xiaoyun Wang
article en

Abstract

Soil moisture (SM) is a pivotal state variable of the terrestrial hydrosphere, modulating energy partitioning, agricultural productivity and extreme-event propagation. This study analyzes 43 years (1982–2024) of data to assess soil moisture (SM) dynamics in the Yellow River Basin (YRB). Results indicate a statistically significant basin-wide SM decline across weekly, monthly, and annual scales, with grid-scale slopes ranging from −2.26 × 10−4 to 8.32 × 10−5 m3 m−3 month−1. Spatially, non-farm areas retain higher SM than cultivated lands, with a distinct upstream-to-downstream variability pattern. While alpine headwaters show moistening, pervasive drying characterizes mid- and lower-catchments. Critically, transitional landscapes are approaching tipping points, risking shifts into persistently wetter or drier stable states where minor perturbations could lock ecosystems into new conditions. This underscores the urgent need for targeted climate-adaptation interventions. Generalized additive modeling identifies surface net solar radiation, soil temperature, and vapor pressure deficit as dominant drivers across multiple temporal scales. Their respective contributions, averaged across the basin, accounted for 29.4%, 25.3%, and 23.0% of the explained variance. Additionally, actual evapotranspiration emerged as a significant driver on the weekly scale, particularly within the center of the basin. These findings enhance process-based understanding of SM variability and provide a scientific foundation for adaptive water-resource management in the YRB.

AgronomyVol. 16(8)
Hebei Agricultural University (CN), North China University of Water Resources and Electric Power (CN), Ministry of Water Resources of the People's Republic of China (CN)
Jiangxi Provincial Department of Science and Technology
Openalex Percentile: Top 25%
Soil Moisture and Remote Sensing
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