Li et al. (2026) Multiscale Evolution and Climatic Influences on Groundwater Drought in the Huaihe River Basin

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Identification

• Journal: Hydrology
• Year: 2026
• Date: 2026-10-21
• Authors: Dongxiao Li, Fei Wang, Qingqing Tian, Yu Tian
• DOI: 10.3390/hydrology13100281

Research Groups

Not explicitly mentioned in the provided text.

Short Summary

This study developed a Groundwater Drought Index (GDI) for the Huaihe River Basin (HRB) using GRACE/GRACE-FO and GLDAS data to analyze its spatiotemporal evolution and multiscale responses. The research revealed a basin-wide groundwater drought around 2020, characterized by predominantly downward GDI trends and significant influences from local hydroclimatic variables and large-scale teleconnections like the Interdecadal Pacific Oscillation (IPO) and Tropical South Atlantic Index (TSA).

Objective

• To investigate the spatiotemporal evolution and multiscale responses of groundwater drought in the Huaihe River Basin (HRB).

Study Configuration

• Spatial Scale: Huaihe River Basin (HRB), including sub-basins like the Shandong Peninsula and Coastal River systems (SPCR) and Yishu-Si River system (YSR).
• Temporal Scale: Data from 2003 to 2025.

Methodology and Data

• Models used:
  • Groundwater Drought Index (GDI) construction.
  • Bayesian Estimator of Abrupt change, Seasonality, and Trend (BEAST) for trend shifts.
  • Modified Mann–Kendall (MMK)–Hurst analysis for persistence and trends.
  • Wavelet coherence for multiscale hydroclimatic relationships.
  • Extreme Gradient Boosting–Shapley Additive Explanations (XGBoost-SHAP) for teleconnection contributions.
• Data sources:
  • Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GRACE-FO) data.
  • Global Land Data Assimilation System (GLDAS) data.

Main Results

• The Groundwater Drought Index (GDI) showed clear temporal variability and spatial heterogeneity across the Huaihe River Basin (HRB).
• A basin-wide groundwater drought occurred around 2020, with the basin-averaged GDI reaching a minimum of −2.23 in June 2020 and the lowest sub-basin value being −3.25.
• Change points in the Shandong Peninsula and Coastal River systems (SPCR) and Yishu-Si River system (YSR) were identified in April 2018 and August 2019, respectively.
• Modified Mann–Kendall (MMK)–Hurst analysis indicated predominantly downward GDI trends across the basin, with persistent drying characteristics in parts of the central and northern HRB.
• Wavelet analysis revealed clear multiscale relationships between GDI and local hydroclimatic variables, with soil moisture (SM) having the largest proportion of significant coherence area (POSP = 19.47%).
• Shapley Additive Explanations (SHAP) analysis identified the Interdecadal Pacific Oscillation (IPO) and Tropical South Atlantic Index (TSA) as the two most important teleconnection predictors, with Mean |SHAP| values of 0.1621 and 0.1314, respectively.

Contributions

• Developed a comprehensive framework integrating multiple advanced analytical methods (BEAST, MMK–Hurst, wavelet coherence, XGBoost-SHAP) for characterizing groundwater drought evolution and multiscale responses.
• Provided a detailed spatiotemporal analysis of groundwater drought in the Huaihe River Basin, including specific drought events, trend shifts, and persistence.
• Quantified the multiscale relationships between groundwater drought and local hydroclimatic variables, highlighting the significant role of soil moisture.
• Identified and quantified the contributions of key large-scale ocean–atmosphere teleconnections (IPO, TSA) to groundwater drought variability.
• Offered a useful basis for improved groundwater drought monitoring, risk assessment, and basin-scale water-resource management.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{Li2026Multiscale,
  author = {Li, Dongxiao and Wang, Fei and Tian, Qingqing and Tian, Yu},
  title = {Multiscale Evolution and Climatic Influences on Groundwater Drought in the Huaihe River Basin},
  journal = {Hydrology},
  year = {2026},
  doi = {10.3390/hydrology13100281},
  url = {https://doi.org/10.3390/hydrology13100281}
}