Luo et al. (2025) Temporal and Spatial Changes in Soil Drought and Identification of Remote Correlation Effects

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Identification

• Journal: Agriculture
• Year: 2025
• Date: 2025-12-16
• Authors: Weiran Luo, Jianzhong Guo, Ziwei Li, Ning Li, Fei Wang, Hexin Lai, Ruyi Men, Rong Li, Mengting Du, Kai Feng, Yanbin Li, Shengzhi Huang, Qingqing Tian
• DOI: 10.3390/agriculture15242603

Research Groups

• Not explicitly specified in the provided text (typically associated with hydrological and agricultural research departments focused on the Yangtze River Basin).

Short Summary

This study analyzes the spatiotemporal evolution of soil drought in the Yangtze River Basin from 2000 to 2022, identifying precipitation as the primary climatic driver and the Interannual Pacific Oscillation (IPO) as the leading atmospheric circulation influence.

Objective

• To characterize the spatiotemporal patterns, identify mutation points, and quantify the relative contributions of climatic and atmospheric circulation factors to soil drought across the Yangtze River Basin (YRB).

Study Configuration

• Spatial Scale: The Yangtze River Basin (YRB) and its constituent sub-basins, China.
• Temporal Scale: 2000 to 2022 (monthly and annual resolutions).

Methodology and Data

• Models and Indices: Standardized Soil Moisture Index (SSMI) for drought assessment; Shapley Additive Explanations (SHAP) for quantifying factor contributions; mutation analysis for trend shifts.
• Data sources: Remote sensing-based soil moisture data and atmospheric circulation indices (IPO, PDO, DMI).

Main Results

• Drought Severity: August 2022 was the most severe drought month recorded (SSMI = –1.69), with extreme drought covering 39.36% of the basin area. The year 2022 also marked the most severe annual drought (SSMI = –0.94).
• Mutation Points: Two major shifts occurred in May 2011 ("decrease to increase") and June 2019 ("increase to decrease"). Most sub-basin mutations occurred after 2010, primarily categorized as "interrupted decrease."
• Climatic Drivers: Precipitation (PC) is the dominant climatic factor, with a Percentage Area of Significant Coherence (PASC) of 15.48%.
• Circulation Factors: Large-scale oscillations significantly influence drought via remote correlation, led by the Interannual Pacific Oscillation (IPO, mean SHAP = 0.138), followed by the Pacific Decadal Oscillation (PDO, SHAP = 0.111) and the Dipole Mode Index (DMI, SHAP = 0.090).

Contributions

• Provides a comprehensive quantification of how specific atmospheric circulation patterns (IPO, PDO, DMI) drive soil moisture variability in the YRB.
• Identifies critical temporal mutation points in soil drought trends, offering a refined understanding of drought evolution under a changing monsoon climate.
• Establishes a scientific framework for improving agricultural risk management and drought monitoring in a major grain-producing region.

Funding

• Not specified in the provided text.

Citation

@article{Luo2025Temporal,
  author = {Luo, Weiran and Guo, Jianzhong and Li, Ziwei and Li, Ning and Wang, Fei and Lai, Hexin and Men, Ruyi and Li, Rong and Du, Mengting and Feng, Kai and Li, Yanbin and Huang, Shengzhi and Tian, Qingqing},
  title = {Temporal and Spatial Changes in Soil Drought and Identification of Remote Correlation Effects},
  journal = {Agriculture},
  year = {2025},
  doi = {10.3390/agriculture15242603},
  url = {https://doi.org/10.3390/agriculture15242603}
}

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