Non-parametric time between events and amplitude methods for monitoring regional drought characteristics

Drought is a significant natural phenomenon with profound environmental, economic, and societal impacts. Effective monitoring of drought characteristics—such as frequency, magnitude, and duration—is essential for developing resilience and mitigation strategies. This paper proposes a non-parametric Time Between Events and Amplitude (TBEA) framework for the statistical monitoring of regional drought characteristics. Drought events are identified using an area-weighted regional Standardized Precipitation and Evapotranspiration Index (SPEI), computed at 12- and 24-month accumulation scales to represent hydrological and socio-economic droughts, respectively. Two complementary distribution-free monitoring approaches are considered. An exponentially weighted moving average TBEA control chart is employed to detect gradual and persistent departures from baseline drought dynamics, while a non-parametric change-point control chart based on the Kolmogorov–Smirnov statistic is used to identify abrupt distributional shifts in a composite TBEA statistic. Both methods jointly account for the time between successive drought events and their magnitudes, providing a unified stochastic representation of drought occurrence processes. The proposed methodology is applied to more than a century of monthly SPEI data for the Emilia-Romagna region (Italy). The results provide consistent evidence of a long-term deterioration in regional drought characteristics beginning in the early 2000s, characterized by increasingly frequent and severe drought events. The fully non-parametric nature of the framework makes it well suited for operational drought monitoring and for broader applications in environmental event analysis.