Enhancing monitoring ability for extreme disasters in North China using a novel hydrometeorology-combined drought–flood severity index

Abstract

The heterogeneous triggering conditions of droughts and floods make it difficult for existing monitoring indices to balance the detection of extreme drought and flood events. To overcome this limitation, a hydrometeorology-combined drought-flood severity index (HDSI) is developed by integrating GRACE-based terrestrial water storage (TWS) and precipitation, and the time lag effect between two elements is reasonably handled using a weighting potential water storage model. The performance of the HDSI is evaluated in a typical ecologically fragile region: North China. The results show that the HDSI exhibits favorable spatial and temporal consistency compared with four commonly used indices, implying the effectiveness of the HDSI. With real-documented extreme events as benchmarks, the HDSI demonstrates significant accuracy superiority over the TWS-based monitoring index in capturing flood peak periods and outperforms indices based solely on meteorological elements in identifying drought intensity, which contributes to more profound understanding of extreme disasters under the combined impacts of turbulent climate change and intensive anthropogenic interference. Moreover, detailed investigations on two representative drought and flood events confirm that the HDSI can not only accurately identify the intensifying drought severity induced by water storage deficits in the context of reduced precipitation and growing water use, but also provide timely feedback in the case of emergency flooding due to increased precipitation; thus, it is an important complement to extreme disaster monitoring and early warning systems and can aid in facilitating rational disaster preparedness and decision-making.