Identifying drought propagation by simultaneously considering linear and nonlinear dependence in the Wei River basin of the Loess Plateau, China

Meteorological drought propagating to hydrological drought usually occurs with a noticeable time delay due to the catchment buffering effect. Knowledge gain in the delayed hydrological response is indispensable for developing timely drought monitoring systems. In this study, a two-stage statistical framework is proposed for identifying the response time of hydrological droughts to meteorological droughts at a weekly resolution. Candidate response time is initially selected by exclusively evaluating linear or nonlinear correlations between precipitation and streamflow anomalies. In the second stage, the optimal response time is determined, at which the greatest number of streamflow deficits can be monitored by concurrent precipitation deficits. A case study is conducted for the Wei River basin of the Loess Plateau, China to investigate the spatio-temporal variability in drought response time under a changing environment. Results indicate that hydrological droughts respond to meteorological droughts with time lags of 25–39 weeks, exhibiting noticeable spatial variability. The long-time hydrological response is expected where there are sufficient vegetation and loess deposits. Drought response time identification for each calendar month reveals the long-term and short-term hydrological response in winter and summer, respectively. A time-varying baseflow index is found to be positively related to the drought response time, therefore having control on its marked seasonality. In a changing environment, summer hydrological droughts tend to respond to precipitation variability at longer time scales, while decreasing response time is noticed in winter. A preliminary attribution analysis highlights that changes in meteorological drought severity and catchment water storage in combination exert control on the temporal variability in drought response time over the past half-century. Findings of the study may favor hydrological drought monitoring dependent on precipitation deficit information available at large spatial extent.