Modeling study demonstrates non-stationary drought propagation and lag responses in river basins, highlighting that stationary indices overestimate hydrological thresholds.
Understanding the correlation and propagation between hydrological and meteorological droughts is crucial for drought early warning and water resource management. However, non-stationary behaviors under changing environments complicate accurate characterization. This study develops a non-stationary framework using climatic and anthropogenic factors within GAMLSS to construct non-stationary meteorological (NRDI) and hydrological (NSRI) drought indices. Combined with nonlinear response models, the propagation relationship is analyzed. Results indicate: (1) Non-stationary indices reveal more reliable drought propagation patterns and scale-dependent lag responses; (2) They capture drought events more accurately, particularly under climate change and human activities; (3) Stationary indices overestimate the hydrological response thresholds, underscoring the necessity of non-stationary approaches.
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Gan et al. (2026) studied this question.
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