Affiliation:
1. Department of Civil Engineering and Architecture, University of Catania, 95123 Catania, Italy
2. Department of Engineering, University of Messina, 98158 Messina, Italy
Abstract
Assessing and monitoring the spatial extent of drought is of key importance to forecasting the future evolution of drought conditions and taking timely preventive and mitigation measures. A commonly used approach in regional drought analysis involves spatially interpolating meteorological variables (e.g., rainfall depth during specific time intervals, deviation from long-term average rainfall) or drought indices (e.g., Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index) computed at specific locations. While plotting a drought descriptor against the corresponding percentage of affected areas helps visualize the historical extent of a drought, this approach falls short of providing a probabilistic characterization of the severity of spatial drought conditions. That can be overcome by identifying drought Severity-Area-Frequency (SAF) curves over a region, which establishes a link between drought features with a chosen probability of recurrence (or return period) and the corresponding proportion of the area experiencing those drought conditions. While inferential analyses can be used to estimate these curves, analytical approaches offer a better understanding of the main statistical features that drive the spatial evolution of droughts. In this research, a technique is introduced to mathematically describe the Severity-Area-Frequency (SAF) curves, aiming to probabilistically understand the correlation between drought severity, measured through the SPEI index, and the proportion of the affected region. This approach enables the determination of the area’s extent where SPEI values fall below a specific threshold, thus calculating the likelihood of observing SAF curves that exceed the observed one. The methodology is tested using data from the ERA5-Land reanalysis project, specifically studying the drought occurrences on Sicily Island, Italy, from 1950 to the present. Overall, findings highlight the improvements of incorporating the spatial interdependence of the assessed drought severity variable, offering a significant enhancement compared to the traditional approach for SAF curve derivation. Moreover, they validate the suitability of reanalysis data for regional drought analysis.
Funder
Autorità di Bacino del Distretto Idrografico della Sicilia—Interventi per il miglioramento dei corpi idrici
the Piano di incentivi per la ricerca di Ateneo (Pia.ce.ri.) of University of Catania
Subject
Water Science and Technology,Aquatic Science,Geography, Planning and Development,Biochemistry
Reference44 articles.
1. Orimoloye, I.R., Belle, J.A., Orimoloye, Y.M., Olusola, A.O., and Ololade, O.O. (2022). Drought: A Common Environmental Disaster. Atmosphere, 13.
2. Drought mitigation: Critical analysis and proposal for a new drought policy with special reference to Gujarat (India);Bandyopadhyay;Prog. Disaster Sci.,2020
3. Spatial patterns and temporal variability of drought in Western Iran;Raziei;Water Resour. Manag.,2009
4. Spatial and temporal variability of precipitation and drought in Portugal;Martins;Nat. Hazards Earth Syst. Sci.,2012
5. Spatial and temporal variability of drought in the arid region of China and its relationships to teleconnection indices;Wang;J. Hydrol.,2015