Determining the response of ecological drought to meteorological and groundwater droughts in Northwest China using a spatio-temporal matching method

Meteorological drought and groundwater drought in ecologically fragile regions may induce ecological drought. Currently, there is no effective method for revealing the response mechanism of ecological drought to meteorological drought and groundwater drought. Taking Northwest China (NWRC) as an example, meteorological drought, groundwater drought and ecological drought were evluated by standardized pricipitation index, standardized groundwater storage anomaly index, and standardized ecological water deficit index, respectively. The spatio-temporal matching method was improved for identifying propagation between three types of drought events. Then, a model of ecological drought characteristics in response to meteorological drought and groundwater drought characteristics was constructed based on the copula function. Finally, the Bayesian model was used to determine the thresholds of meteorological drought and groundwater drought that trigger ecological drought events at different drought levels. The key findings are as follows. (1) A total of 31 pairs of meteorological-groundwater-ecological drought events with a genetic relationship were identified. The ecological drought events with larger severity were caused by the joint effect of meteorological and groundwater drought, and most of them occurred before the 21st century. (2) The optimal response models of the affected area, duration, and intensity of ecological drought events were Gumbel copula driven by the affected area of meteorological drought, the Student t copula driven by the duration of groundwater drought, and the Joe copula driven by the severity of meteorological and ecological drought, respectively. (3) The thresholds and the corresponding curves of meteorological drought and groundwater drought to trigger mild, moderate, severe, and extreme ecological drought events were obtained. Results of this study can provide valuable information for early warning of ecological drought.