Drought is dynamic across many regions where the system oscillates between periods of drought and wetness. However, traditional methods of drought analysis rely on indices such as the duration and frequency of drought events, which offer a static view of an inherently dynamic phenomenon. The resiliency index focuses on the structure and dynamics of system responses to crises. It can show how quickly and effectively a natural system recovers after a drought. This study aims to improve drought dynamics analysis. Four indices Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI), Standardized Groundwater Index (SGI), and Standardized Runoff–Groundwater Index (SRGI), were calculated using monthly data (1991–2020) for Aleshtar basin in IRAN. Results indicated that the resiliency index effectively measures the potential for return to normal conditions, both within individual drought types and across different drought types. While SPI, SRI, and SRGI showed no significant trends in resiliency, ranging from 43.8% to 36.5%, 45.8% to 49.3%, and 47.2% to 58.6%, respectively, SGI showed a structural shift, declining from 100% to 36.9%. On average, SRI (37.4%) and SGI (34.7%) had lower resiliency than SPI (46.4%). Overall, resiliency proved to be a useful metric for capturing the dynamic behavior of droughts, with SRGI exhibiting the highest resiliency at 52.2%, surpassing that of any individual drought index.
Sharifi et al. (Fri,) studied this question.