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

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Uncertainty assessment of drought characteristics projections in humid subtropical basins in China based on multiple CMIP5 models and different index definitions. / Xu, Kai; Wu, Chuanhao; Zhang, Ce; Hu, Bill.

In: Journal of Hydrology, Vol. 600, 126502, 01.09.2021, p. 1-17.

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@article{213f756e6a154745ade634ec96f7c0b5,
title = "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.",
keywords = "Drought projection, Drought indices, uncertainty quantification, CMIP5, RCPs",
author = "Kai Xu and Chuanhao Wu and Ce Zhang and Bill Hu",
note = "This is the author{\textquoteright}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",
year = "2021",
month = sep,
day = "1",
doi = "10.1016/j.jhydrol.2021.126502",
language = "English",
volume = "600",
pages = "1--17",
journal = "Journal of Hydrology",
issn = "0022-1694",
publisher = "Elsevier Science B.V.",

}

RIS

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 -