A robust ensemble drought index: construction and assessment

Abstract

Drought indices have been commonly used in drought monitoring and assessments, but selecting the most appropriate one under different geographical and climatic conditions is difficult. We constructed a multi-timescale integrated drought index, the Ensemble Drought Index (EDI), for more robust and reliable drought assessments with the widely used Standardized Precipitation Index (SPI), the Palmer Drought Severity Index (PDSI), the selfcalibrated Palmer Drought Severity Index (scPDSI), and the Standardized Precipitation Evapotranspiration Index (SPEI) using the Thornthwaite and the Penman-Monteith methods. The EDI can more accurately describe the major historical drought events, and has high and significant correlation with historical monthly soil moisture and annual runoff data all over China, regardless of regional differences. in region among those indices participating in integration. We also showed that the EDI greatly improved monitoring accuracy in the arid and semi-arid regions of China, where the assessments are always thorny. In the meantime, we revealed how the reference period of fitting statistical parameters affects the accuracy of drought assessments, and concluded that the long-term stationary climate variables series (i.e., without trend) can bring more accurate conclusions.

Multiscale Spatiotemporal Dynamics of Drought within the Yellow River Basin (YRB): An Examination of Regional Variability and Trends

“…Despite its comprehensive approach, the PDSI falls short in capturing the multi-dimensional characteristics of drought phenomena. In an enhancement to the original model, the self-calibrating Palmer Drought Severity Index (scPDSI) has been developed [23,[30][31][32][33][34][35]. This advanced index dynamically adjusts PDSI parameters in response to specific climatic data from individual stations, thus offering a more tailored and effective tool for assessing local climate conditions [36].…”