Characterizing spatially concurrent hydrological drought and its response to meteorological drought under the impact of human activities
Abstract
The study region is the upper Hanjiang River Basin in China. Understanding how spatially concurrent hydrological droughts ( HD ) respond to meteorological droughts ( MD ) is crucial for early drought warning and mitigation, yet such assessments remain limited under human-altered conditions. This study examines two sub-regions (S1 and S2) in the upper Hanjiang River Basin using monthly precipitation and streamflow data (1961–2020) to characterize the inter-regional MD – HD linkages through elementary and Copula functions. Results indicate that during the natural pre-change period, both S1 and S2 exhibited strong elementary functional relationships between MD and HD magnitudes ( R 2 > 0.8). When the MD magnitude of S1 reached a threshold of 1.16, HD onset occurred, and the HD magnitude of S2 fell within a 70 % probability interval of [0.58, 3.16] with a most likely value of 0.70. In the post-change period, human interventions—particularly reservoir regulation and irrigation—disrupted these elementary linkages, yielding more complex non-linear propagation patterns. The Copula framework successfully quantified the probabilistic linkage of concurrent HD s across regions, enabling estimation of HD severity in one basin based on MD information from another. These findings provide quantitative insight into cross-regional drought propagation and offer practical implications for hydrological drought monitoring and management in data-scarce or regulated basins. • An elementary function links the magnitude relationship between meteorological and hydrological droughts. • The copula function is used to quantify the probability relationship of spatially concurrent hydrological drought. • Human activities would alter these drought relationships in the Upper Hanjiang River basin.
Fields of Study & Subjects
Hydrology and Drought Analysis
Hydrology and Watershed Management Studies
Water resources management and optimization
Publication details
- Journal / source
- Journal of Hydrology Regional Studies
- Volume
- 64
- Pages
- 103129–103129
- Publication date
- 14 January 2026
- Language
- EN