Rights statement: This is the author’s version of a work that was accepted for publication in Journal of Hydrology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Hydrology, 600, 2021 DOI: 10.1016/j.jhydrol.2021.126502
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Uncertainty assessment of drought characteristics projections in humid subtropical basins in China based on multiple CMIP5 models and different index definitions
AU - Xu, Kai
AU - Wu, Chuanhao
AU - Zhang, Ce
AU - Hu, Bill
N1 - This is the author’s version of a work that was accepted for publication in Journal of Hydrology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Hydrology, 600, 2021 DOI: 10.1016/j.jhydrol.2021.126502
PY - 2021/9/1
Y1 - 2021/9/1
N2 - 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.
AB - 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.
KW - Drought projection
KW - Drought indices
KW - uncertainty quantification
KW - CMIP5
KW - RCPs
U2 - 10.1016/j.jhydrol.2021.126502
DO - 10.1016/j.jhydrol.2021.126502
M3 - Journal article
VL - 600
SP - 1
EP - 17
JO - Journal of Hydrology
JF - Journal of Hydrology
SN - 0022-1694
M1 - 126502
ER -