Guo et al. (2025) Study on the nonlinear propagation mechanism from meteorological drought to hydrological drought in Jialing river basin

Identification

• Journal: Natural Hazards
• Year: 2025
• Date: 2025-10-17
• Authors: Wenxian Guo, Xuefeng Yue, Siyuan Cheng, Chaohui Sun, Zhiqian Yu, Hongxiang Wang
• DOI: 10.1007/s11069-025-07656-8

Research Groups

• School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, 450045, China

Short Summary

This study investigates the nonlinear propagation mechanism from meteorological drought to hydrological drought in the Jialing River basin, quantifying drought propagation thresholds and revealing spatio-temporal drought characteristics. It found that the probability of propagation decreases with increasing hydrological drought class, with specific duration and intensity thresholds identified for triggering different levels of hydrological drought.

Objective

• To investigate the nonlinear propagation mechanism from meteorological drought to hydrological drought and quantify the drought propagation thresholds in the Jialing River basin, providing theoretical guidance for early warning, prevention, and mitigation of drought propagation.

Study Configuration

• Spatial Scale: Jialing River basin, with a total mainstem length of approximately 1120 kilometers and a watershed area of about 160,000 square kilometers.
• Temporal Scale: 1972 to 2017 (46 years).

Methodology and Data

• Models used:
  • Standardized Precipitation Evapotranspiration Index (SPEI) for characterizing meteorological droughts.
  • Standardized Runoff Index (SRI) for characterizing hydrological droughts.
  • Travel theory for identifying drought events.
  • Rotated Empirical Orthogonal Function (REOF) for analyzing spatio-temporal differentiation patterns of meteorological droughts.
  • Center of gravity migration model for reflecting spatio-temporal aggregation and dynamic migration characteristics of drought.
  • Copula function (Clayton-Copula for duration, Frank-Copula for intensity) to construct joint distributions of meteorological and hydrological drought characteristic variables.
  • Bayesian network to analyze the conditional probability of drought propagation and determine thresholds.
  • Kolmogorov–Smirno (K–S) test for selecting optimal marginal distribution functions.
  • AIC, BIC, Kendall rank correlation, Spearman rank correlation, and Squared Euclidean Distance (SED) for evaluating Copula function goodness-of-fit.
• Data sources:
  • Daily runoff data from 1972 to 2017 at Beibei Hydrological Station in Jialing River Basin, obtained from the Hydrological Bulletin of the Yangtze River Water Resources Commission.
  • Daily meteorological data from 1972 to 2017 from 11 national meteorological stations within the Jialing River Basin, obtained from the National Meteorological Data Center website. Data included maximum, minimum, and average temperatures, rainfall, relative humidity, and sunshine hours.
  • Surface meteorological data obtained using the Tyson polygon method.

Main Results

• The Jialing River basin exhibits significant spatial and temporal variability in meteorological drought, categorized into three typical modes. Mode One and Two core areas showed strong persistence with slow dry/wet alternation from 1972 to 1994, transitioning to frequent alternation after 1994. Mode Four core area experienced a significant dry-wet transition around 1995.
• The overall drought center of gravity migrated towards the northern part of the basin, but on an interannual scale, drought events were concentrated in the central-southern part, showing a significant clustering characteristic over time.
• The probability of meteorological drought propagating to hydrological drought decreases significantly with increasing hydrological drought class.
• Drought propagation thresholds:
  • For triggering a moderate hydrological drought (conditional probability > 0.95): Meteorological drought duration ≥ 4.2 months and intensity ≥ 4.1.
  • For triggering a severe hydrological drought (conditional probability > 0.8): Meteorological drought duration ≥ 6.5 months and intensity ≥ 5.2.
  • For triggering an extreme hydrological drought (conditional probability > 0.45): Meteorological drought duration ≥ 7 months and intensity ≥ 5.7.
• Validation with historical drought events (1972, 1978, 1997) showed high consistency between observed propagation patterns and the determined thresholds.

Contributions

• Systematically reveals the spatio-temporal evolution patterns of meteorological drought in the Jialing River Basin.
• Establishes a quantitative research method for drought propagation thresholds by integrating meteorological and hydrological drought indicators using advanced mathematical statistical modeling (Copula function and Bayesian network).
• Provides a comprehensive study on the nonlinear propagation mechanism from meteorological drought to hydrological drought, including the determination of specific duration and intensity thresholds.
• Offers a theoretical basis for improving drought monitoring and early warning systems, optimizing water resource management, and supporting zoning governance in the Jialing River Basin.
• The developed drought propagation threshold research framework provides methodological support for future studies on drought propagation under natural conditions and can be extended to other types of drought research.

Funding

• 2025 Henan Provincial Natural Science Foundation Grant 252300421334
• 2025 Henan Provincial Outstanding Youth Science Foundation 252300421049

Citation

@article{Guo2025Study,
  author = {Guo, Wenxian and Yue, Xuefeng and Cheng, Siyuan and Sun, Chaohui and Yu, Zhiqian and Wang, Hongxiang},
  title = {Study on the nonlinear propagation mechanism from meteorological drought to hydrological drought in Jialing river basin},
  journal = {Natural Hazards},
  year = {2025},
  doi = {10.1007/s11069-025-07656-8},
  url = {https://doi.org/10.1007/s11069-025-07656-8}
}