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Title: Bayesian Hierarchical Model Uncertainty Quantification for Future Hydroclimate Projections in Southern Hills-Gulf Region, USA

Here, this study investigates the hierarchical uncertainty of multi-ensemble hydroclimate projections for the Southern Hills-Gulf region, USA, considering emission pathways and a global climate model (GCM) as two main sources of uncertainty. Forty projections of downscaled daily air temperature and precipitation from 2010 to 2099 under four emission pathways and ten CMIP5 GCMs are adopted for hydroclimate modeling via the HELP3 hydrologic model. This study focuses on evapotranspiration (ET), surface runoff, and groundwater recharge projections in this century. Climate projection uncertainty is characterized by the hierarchical Bayesian model averaging (HBMA) method, which segregates emission pathway uncertainty and climate model uncertainty. HBMA is able to derive ensemble means and standard deviations, arising from individual uncertainty sources, for ET, runoff, and recharge. The model results show that future recharge in the Southern Hills-Gulf region is more sensitive to different climate projections and exhibits higher variability than ET and runoff. Overall, ET is likely to increase and runoff is likely to decrease in this century given the current emission path scenarios. Runoff are predicted to have an 18% to 20% decrease and ET is predicted to have around a 3% increase throughout the century. Groundwater recharge is likely to increase in this centurymore » with a decreasing trend. Recharge would increase about 13% in the early century and will have only a 3% increase in the late century. All hydrological projections have increasing uncertainty towards the end of the century. The HBMA result suggests that the GCM uncertainty dominates the overall hydrological projection uncertainty in the early century and the mid-century. The emission pathway uncertainty becomes important in the late century.« less
Authors:
 [1] ;  [1] ;  [2] ; ORCiD logo [3]
  1. Louisiana State Univ., Baton Rouge, LA (United States)
  2. Texas A & M Univ., College Station, TX (United States)
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Grant/Contract Number:
AC05-00OR22725
Type:
Accepted Manuscript
Journal Name:
Water (Basel)
Additional Journal Information:
Journal Name: Water (Basel); Journal Volume: 11; Journal Issue: 2; Journal ID: ISSN 2073-4441
Publisher:
MDPI
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Bayesian model averaging; uncertainty; climate projection; hydrologic projection; multi-model
OSTI Identifier:
1494023

Beigi, Ehsan, Tsai, Frank T. -C., Singh, Vijay P., and Kao, Shih -Chieh. Bayesian Hierarchical Model Uncertainty Quantification for Future Hydroclimate Projections in Southern Hills-Gulf Region, USA. United States: N. p., Web. doi:10.3390/w11020268.
Beigi, Ehsan, Tsai, Frank T. -C., Singh, Vijay P., & Kao, Shih -Chieh. Bayesian Hierarchical Model Uncertainty Quantification for Future Hydroclimate Projections in Southern Hills-Gulf Region, USA. United States. doi:10.3390/w11020268.
Beigi, Ehsan, Tsai, Frank T. -C., Singh, Vijay P., and Kao, Shih -Chieh. 2019. "Bayesian Hierarchical Model Uncertainty Quantification for Future Hydroclimate Projections in Southern Hills-Gulf Region, USA". United States. doi:10.3390/w11020268. https://www.osti.gov/servlets/purl/1494023.
@article{osti_1494023,
title = {Bayesian Hierarchical Model Uncertainty Quantification for Future Hydroclimate Projections in Southern Hills-Gulf Region, USA},
author = {Beigi, Ehsan and Tsai, Frank T. -C. and Singh, Vijay P. and Kao, Shih -Chieh},
abstractNote = {Here, this study investigates the hierarchical uncertainty of multi-ensemble hydroclimate projections for the Southern Hills-Gulf region, USA, considering emission pathways and a global climate model (GCM) as two main sources of uncertainty. Forty projections of downscaled daily air temperature and precipitation from 2010 to 2099 under four emission pathways and ten CMIP5 GCMs are adopted for hydroclimate modeling via the HELP3 hydrologic model. This study focuses on evapotranspiration (ET), surface runoff, and groundwater recharge projections in this century. Climate projection uncertainty is characterized by the hierarchical Bayesian model averaging (HBMA) method, which segregates emission pathway uncertainty and climate model uncertainty. HBMA is able to derive ensemble means and standard deviations, arising from individual uncertainty sources, for ET, runoff, and recharge. The model results show that future recharge in the Southern Hills-Gulf region is more sensitive to different climate projections and exhibits higher variability than ET and runoff. Overall, ET is likely to increase and runoff is likely to decrease in this century given the current emission path scenarios. Runoff are predicted to have an 18% to 20% decrease and ET is predicted to have around a 3% increase throughout the century. Groundwater recharge is likely to increase in this century with a decreasing trend. Recharge would increase about 13% in the early century and will have only a 3% increase in the late century. All hydrological projections have increasing uncertainty towards the end of the century. The HBMA result suggests that the GCM uncertainty dominates the overall hydrological projection uncertainty in the early century and the mid-century. The emission pathway uncertainty becomes important in the late century.},
doi = {10.3390/w11020268},
journal = {Water (Basel)},
number = 2,
volume = 11,
place = {United States},
year = {2019},
month = {2}
}

Works referenced in this record:

Using Bayesian Model Averaging to Calibrate Forecast Ensembles
journal, May 2005
  • Raftery, Adrian E.; Gneiting, Tilmann; Balabdaoui, Fadoua
  • Monthly Weather Review, Vol. 133, Issue 5, p. 1155-1174
  • DOI: 10.1175/MWR2906.1