Mutation Identification and Influencing Factors of Drought in the North China Plain Based on SSMI

The North China Plain (NCP) serves as a core grain production base and one of the most water-scarce regions in China. Under global warming and intensified human activities (irrigation, groundwater exploitation, and returning farmland to forests and grasslands), soil drought has become a critical constraint on regional agricultural sustainability. This study systematically explored temporal trends, spatial disparities, and abrupt changes of soil drought using remote sensing-based soil moisture dataset. Adopting gridded Modified Mann–Kendall test, wavelet coherence analysis and SHapley Additive exPlanations (SHAP), this paper quantitatively revealed multi-scale driving mechanisms and teleconnection responses of soil drought. Drought in 2002 followed a unimodal pattern with continuous expansion from May to October. The drought-affected area peaked at 77.6% in September. Regional soil moisture increased significantly during 1982–2024, accompanied by sustained drought alleviation. Breaks for Additive Seasons and Trend (BFAST) detection verified a regional abrupt change in 2003. Drought deteriorated before 2003 and obviously relieved afterwards. Wavelet analysis indicated that precipitation dominated drought evolution. This study clarifies the evolutionary trend of drought transition from intensification to alleviation across the NCP, providing scientific evidence for the optimal allocation of water resources, regulation of farmland irrigation, and development of agricultural drought resistance.

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Publication Details

Journal
Agriculture
Published
2026-07-01
DOI
https://doi.org/10.3390/agriculture16131439
Primary Topic
Hydrology and Drought Analysis
Type
article
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Mutation Identification and Influencing Factors of Drought in the North China Plain Based on SSMI

Z Li, N Li, Weiran Luo, Baowei Zhang et al.
Agriculture
Hydrology and Drought Analysis
article

Mutation Identification and Influencing Factors of Drought in the North China Plain Based on SSMI

Z Li, N Li, Weiran Luo, Baowei Zhang, Fei Wang, Bingjie Liang, Jianzhong Guo
article en

Abstract

The North China Plain (NCP) serves as a core grain production base and one of the most water-scarce regions in China. Under global warming and intensified human activities (irrigation, groundwater exploitation, and returning farmland to forests and grasslands), soil drought has become a critical constraint on regional agricultural sustainability. This study systematically explored temporal trends, spatial disparities, and abrupt changes of soil drought using remote sensing-based soil moisture dataset. Adopting gridded Modified Mann–Kendall test, wavelet coherence analysis and SHapley Additive exPlanations (SHAP), this paper quantitatively revealed multi-scale driving mechanisms and teleconnection responses of soil drought. Drought in 2002 followed a unimodal pattern with continuous expansion from May to October. The drought-affected area peaked at 77.6% in September. Regional soil moisture increased significantly during 1982–2024, accompanied by sustained drought alleviation. Breaks for Additive Seasons and Trend (BFAST) detection verified a regional abrupt change in 2003. Drought deteriorated before 2003 and obviously relieved afterwards. Wavelet analysis indicated that precipitation dominated drought evolution. This study clarifies the evolutionary trend of drought transition from intensification to alleviation across the NCP, providing scientific evidence for the optimal allocation of water resources, regulation of farmland irrigation, and development of agricultural drought resistance.

AgricultureVol. 16(13)
Henan University (CN), North China University of Water Resources and Electric Power (CN), Zhengzhou University (CN), Henan University of Engineering (CN), Yellow River Institute of Hydraulic Research (CN)
Zero hunger
Openalex Percentile: Top 8%
Hydrology and Drought Analysis
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Mutation Identification and Influencing Factors of Drought in the North China Plain Based on SSMI — Z Li, N Li, et al. · Agriculture (2026) | TGRS Research Map | TGRS