Multi-timescale assessment of propagation thresholds from meteorological to hydrological drought

Abstract

Hydrological drought usually lags behind meteorological drought. Obtaining the propagation threshold (PT) from meteorological drought to hydrological drought is important for providing early warnings of hydrological drought. Previous studies have only used single timescales to characterize PT; however, a single timescale cannot accurately describe the propagation attributes from meteorological to hydrological drought because drought has multi-timescale features. In addition, several methods can be used to obtain PT, such as run theory, correlation analysis, and non-linear response methods. However, these methods might produce different estimates of PT. Here, multi-timescale drought indices, namely the Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI), were used to represent meteorological drought and hydrological drought. PT estimates at multiple timescales (e.g., 1-month, 3-month, and 12-month) obtained from run theory, correlation analysis, and non-linear response methods were compared, and the possible reasons for differences in the PT estimates are discussed. We conducted a case study of three sub-basins (Xinfengjiang River, Qiuxiangjiang River, and Andunshui River) with low levels of human activity in the Dongjiang River Basin, which is located in a humid region in southern China. We found that estimates of PT differed at different timescales of drought indices and with different methods at the same timescales. Longer timescales of hydrological drought corresponded to larger PT and vice versa. The major cause of this pattern was the fact that different timescales of drought indices showed different response sensitivities to drought events. The PT obtained from run theory was the shortest; thus, run theory can provide conservative warnings to aid drought prevention and mitigation. Our findings can help drought managers select effective tools to manage the early stages of hydrological drought based on meteorological forecasts and thus minimize the negative impacts of hazards posed by drought.