Anthropogenic Influences on the Water Cycle Amplify Uncertainty in Drought Assessments

Climate change and anthropogenic disturbances have altered the global freshwater cycle, causing it to deviate from assumptions of stationarity. However, most current drought assessment methods do not consider such impact of nonstationarity. Here, we introduce a theoretical framework that quantifies errors in drought assessment approaches under various nonstationary conditions, using bias-variance decomposition and Monte Carlo simulations. We then apply this framework to evaluate bias and uncertainty in drought estimation based on remote sensing-informed global terrestrial water storage changes. Our analysis confirms that with over half of the world facing water storage declines, assuming stationarity can lead to underestimation of moderate droughts with high uncertainty depending on the chosen climatology reference periods, while overestimations of exceptional droughts remain consistent and highly certain, irrespective of climatology reference periods on average. Our framework offers insights into building appropriate climatology reference periods for drought estimation while emphasizing the need to recognize seasonal and regional differences.