Yin et al. (2025) A shift in drought propagation trend in the Yellow River Basin during 1980–2020 linked to climate change and vegetation greening

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2025
• Date: 2025-11-29
• Authors: Yunhe Yin, Mijia Yin, Xuezheng Zong, Dongsheng Zhao
• DOI: 10.1016/j.ejrh.2025.102983

Research Groups

• Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
• University of Chinese Academy of Sciences, Beijing, China.

Short Summary

This study investigates the propagation of meteorological drought to soil moisture drought in the Yellow River Basin from 1980 to 2020, identifying a significant shift around the year 2000 where drought propagation time began to prolong and duration extension began to decrease due to vegetation greening.

Objective

• To quantitatively investigate drought propagation time (PT) and the drought duration ratio (DDR) in the Yellow River Basin.
• To explore the spatiotemporal dynamics of drought propagation and identify the dominant driving factors, specifically climate change and vegetation greening.

Study Configuration

• Spatial Scale: Regional (Yellow River Basin, China; approximately 795,000 km²).
• Temporal Scale: 1980–2020 (41 years; monthly resolution).

Methodology and Data

• Models and Indices:
  • Standardized Precipitation Evapotranspiration Index (SPEI) at 1-month and 12-month scales for meteorological drought.
  • Run theory for identifying drought events and calculating PT (lag effect) and DDR (length effect).
  • Principal Component Regression (PCR), Ridge Regression, and Partial Correlation Analysis for attribution.
• Data sources:
  • Eight soil moisture (SM) products: ERA5, ERA-Interim, ERA5 Land, FLDAS Noah, GLDAS Noah (v2.0/v2.1), MERRA2, CFS, and GLEAM.
  • Satellite Data: GIMMS 3g+ Normalized Difference Vegetation Index (NDVI).
  • Land Cover: China’s Land-Use/Cover Datasets (CLCD).
  • Meteorological Data: Daily observations (precipitation, temperature, humidity, etc.) from the Meteorological Information Center, interpolated to 0.1° resolution.

Main Results

• Propagation Characteristics: Average PT was generally 1–2 months, with shorter lags in the middle reaches. DDR values exceeding 2.0 were concentrated in the Loess Plateau, indicating that propagation significantly extends drought duration in this region.
• Temporal Shift: A distinct shift in propagation dynamics occurred around the year 2000. Before 2000, PT showed a shortening trend (-0.038 months/year), and DDR showed an increasing trend. After 2000, PT shifted to a prolonging trend (+0.050 months/year), and DDR shifted to a decreasing trend.
• Driving Factors: The shift was closely linked to vegetation greening. After 2000, the proportion of the basin where PT and DDR were primarily driven by NDVI reached 23.64%–29.30% and 20.80%–23.16%, respectively.
• Seasonality and Severity: PT was shorter and DDR was larger during growing seasons compared to non-growing seasons. Higher meteorological drought severity generally led to shorter PT and higher DDR.

Contributions

• Quantification of the Length Effect: Introduces the Drought Duration Ratio (DDR) to measure how much the propagation process extends the total drought period, a factor often overlooked in individual drought type studies.
• Identification of a Regime Shift: Documents a reversal in drought propagation trends in the Yellow River Basin linked to the timing of large-scale ecological restoration projects (e.g., "Grain to Green").
• Multi-Product Validation: Enhances the reliability of soil moisture drought analysis by comparing and synthesizing results from eight different global soil moisture products.

Funding

• National Natural Science Foundation of China (Reference code: 42377460).

Citation

@article{Yin2025shift,
  author = {Yin, Yunhe and Yin, Mijia and Zong, Xuezheng and Zhao, Dongsheng},
  title = {A shift in drought propagation trend in the Yellow River Basin during 1980–2020 linked to climate change and vegetation greening},
  journal = {Journal of Hydrology Regional Studies},
  year = {2025},
  doi = {10.1016/j.ejrh.2025.102983},
  url = {https://doi.org/10.1016/j.ejrh.2025.102983}
}

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