Evaluation of remotely sensed precipitation estimates using PERSIANN-CDR and MSWEP for spatio-temporal drought assessment over Iran

Satellite Rainfall Estimates (SREs) can provide rainfall information at finer spatial and temporal resolutions, however their performance varies with respect to gauged precipitation data in different climatic regions. A limited number of studies investigated the performance of SREs for spatio-temporal (regional) drought analysis, which is a key component for developing tools for regional drought planning and management. In this study, the performance of two recent SREs (data length > 30 years), which includes Artificial Neural Networks Climate Data Record (PERSIANN-CDR) and the Multi-Source Weighted-Ensemble Precipitation (MSWEP) are selected for spatio-temporal drought assessment over different climatic regions located in Iran. Firstly, the accuracy of SREs was evaluated for deriving standardized precipitation index (SPI) at different time scales (1, 3, 6, 9 and 12 months) for four climatic regions during the period of 1983-2012. Secondly, the performance of SREs was evaluated for regional drought assessment based on the concept of the Severity-Areal-Frequency (SAF) curves. It was observed that the performance of SREs can be different with respect to gauge data in terms of quantifying drought characteristics (e.g., severity, duration, and frequency), identification of major historical droughts, and a significant difference can be observed based on the SAF analysis. For example, the number of drought events based on shorter time scales (SPI-1 and 3) found to be greater for SREs in comparison to gauge information for all climatic regions. While investigating the major historical droughts, discrepancies can be observed between these two types of data sets. For example, gauge data suggests wetness (i.e., SPI-3 > 0.5) near southern Iran, whereas, SREs show droughts (SPI < -1.0) in the same spatial domain. The performance of SREs with respect to gauge data varies largely in terms of quantifying the frequency component embedded in the SAF curves for selected climatic regions located in Iran. Our research findings can be useful for drought assessment in ungagged basins, as well as to develop regional drought management plans to improve water security by integrating multivariate nature of drought events.