Uncertainty assessment of drought characteristics projections in humid subtropical basins in China based on multiple CMIP5 models and different index definitions

Abstract

This study presents an assessment of projection and uncertainty of drought characteristics (frequency DF, drought area Da) using three drought indices (Palmer Drought Severity Index, PDSI; Standardized Precipitation Index, SPI; Standardized Precipitation Evapotranspiration Index, SPEI) in the humid subtropical Pearl River basin in southern China during the period 2021–2050. The projection is based on 13 CMIP5 general circulation models (GCMs) under three Representative Concentration Pathway scenarios (RCP2.6, RCP4.5 and RCP8.5). Specifically, the SPI is derived by the precipitation simulations of 13 GCMs, whereas the PDSI and SPEI are computed based on the simulations from the Variable Infiltration Capacity (VIC) model forced by 13 GCMs. The uncertainty of projected drought indices (PDSI, SPI and SPEI) due to various GCMs and RCPs is quantified by the variance-based sensitivity analysis approach. The results indicate that the sign and magnitude of the projected changes in DF and Da are highly dependent on the index definition at the regional scale, and the SPI tends to underestimate the projected changes in DF compared with PDSI and SPEI. There is a large model spread in the projected DF changes (especially for SPEI) under all RCP scenarios, with larger model spread for more extreme drought events. Uncertainty analysis shows that GCM contributes more than 90% of total uncertainty in drought indices projections, while the RCP uncertainty is rather limited (< 10%) compared with GCM. The GCM uncertainty is spatially unevenly distributed and shows large variability at the interannual scale. This study highlights the sensitivity of drought projections to the index definition as well as the large spatial–temporal variability of general sources of uncertainty in drought projections.