Evaluation of drought indices via remotely sensed data with hydrological variables

Abstract

An intercomparison among standard and remotely sensed drought indices was conducted using streamflow and soil moisture measurements collected in the Little River Experimental Watershed, Georgia, US, during the period from 2000 to 2008. All drought indices exhibited a linear, monotonic association with soil moisture, but there was a non-linear monotonic association between the drought indices and streamflow. Of the indices examined, the Evaporative Stress Index (ESI) showed reasonable performance with about 90% accuracy capturing moderate drought conditions and 80% accuracy capturing severe drought conditions in comparison to observed soil moisture and streamflow. While the ability of the ESI to capture shorter term droughts is equal or superior to the Palmer Drought Severity Index (PDSI) when characterizing droughts based on soil moisture and streamflow thresholds, the accuracy of the ESI was less efficient in the case of severe droughts. A drought index developed from the Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture product showed reasonable correlations with the observed soil moisture and streamflow. However the ESI, Vegetation Health Index (VHI), and PDSI demonstrated greater skill in detecting drought in this study region. Multi-variable linear regression models revealed that the joint use of PDSI and appropriate remote sensing products improved predictions of observed hydrologic variables. Overall, the ESI was identified as a promising drought index for characterizing streamflow and soil moisture anomalies, particularly in regions where precipitation observations are unavailable, sparsely distributed, or biased with respect to regional averages.