Regional Hydrological Drought Monitoring Using Principal Components Analysis.

Drought quantification is a decision-making approach for water resources planners and managers. There are different statistical methods for regional quantification of droughts, depending on the event being regionally discrete or continuous. Calculating a drought index in the measured grid points of a given region is a prerequisite for the regionalization process of drought by these methods. The aim of this study is the regional analysis of the streamflow drought using the multivariate technique of principal components analysis (PCA). To this end, the streamflow drought index (SDI) was calculated in the seven hydrometric stations of the Sefid-Rud basin in Iran for the period of 1984-2013 in seasonal (winter, spring, summer, and autumn), semiannual (October-March and May-September), and annual (October-September) time scales. Regional monitoring of the SDI was carried out using the PCA technique summarizing the SDI series of all stations into a new series, the so-called the multivariate streamflow drought index (MSDI). The MSDI series at each time scale were analyzed from several statistical aspects. Results showed that there are relatively high correlations between the SDI series of the stations for given time scales. The first principal component (PC₁) explains 58-85% of the regional variations of the SDI series at the mentioned time scales. The MSDI series at multiple time scales follow all stations' SDI fluctuations and appropriately monitor droughts that occurred in the region, especially in long dry periods. The dry and wet severity classes derived from the MSDI series greatly corresponded to those of the SDI time series on different stations. The highest percentage of correspondence between MSDI and SDIs was calculated for the semiannual time scale and the lowest for the spring season. [ABSTRACT FROM AUTHOR]