Estimating Future Surface Water Availability Through an Integrated Climate‐Hydrology‐Management Modeling Framework at a Basin Scale Under CMIP6 Scenarios
Abstract
Abstract Climate change and increasing water demand due to population growth pose serious threats to surface water availability. The biggest challenge in addressing these threats is the gap between climate science and water management practices. Local water planning often lacks the integration of climate change information, especially with regard to its impacts on surface water storage and evaporation as well as the associated uncertainties. Using Texas as an example, state and regional water planning relies on the use of reservoir “Firm Yield” (FY)—an important metric that quantifies surface water availability. However, this existing planning methodology does not account for the impacts of climate change on future inflows and on reservoir evaporation. To bridge this knowledge gap, an integrated climate‐hydrology‐management (CHM) modeling framework was developed, which is generally applicable to river basins with geographical, hydrological, and water right settings similar to those in Texas. The framework leverages the advantages of two modeling approaches—the Distributed Hydrology Soil Vegetation Model (DHSVM) and Water Availability Modeling (WAM). Additionally, the Double Bias Correction Constructed Analogues method is utilized to downscale and incorporate Coupled Model Intercomparison Project Phase 6 GCMs. Finally, the DHSVM simulated naturalized streamflow and reservoir evaporation rate are input to WAM to simulatemore »
- Authors:
-
[1];
[2];
[3];
[4];
[1];
[1]
- Zachry Department of Civil and Environmental Engineering Texas A&,M University College Station TX USA
- Water Availability Department Surface Water Division Texas Water Development Board Austin TX USA
- Department of Global Ecology Carnegie Institution for Science Stanford CA USA
- Environmental Sciences Division and Climate Change Science Institute Oak Ridge National Laboratory Oak Ridge TN USA
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Water Power Technologies Office; National Science Foundation (NSF); USDOE Office of Science (SC)
- OSTI Identifier:
- 1988175
- Alternate Identifier(s):
- OSTI ID: 1988340; OSTI ID: 1994214
- Grant/Contract Number:
- SECURE Water Act Section 9505; AC05-00OR22725; CBET-1454297
- Resource Type:
- Published Article
- Journal Name:
- Water Resources Research
- Additional Journal Information:
- Journal Name: Water Resources Research Journal Volume: 59 Journal Issue: 7; Journal ID: ISSN 0043-1397
- Publisher:
- American Geophysical Union (AGU)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; water availability; climate change; reservoir firm yield; semi-arid area; open water evaporation; naturalized streamflow
Citation Formats
Shao, Manqing, Fernando, Nelun, Zhu, John, Zhao, Gang, Kao, Shih‐Chieh, Zhao, Bingjie, Roberts, Elizabeth, and Gao, Huilin. Estimating Future Surface Water Availability Through an Integrated Climate‐Hydrology‐Management Modeling Framework at a Basin Scale Under CMIP6 Scenarios. United States: N. p., 2023.
Web. doi:10.1029/2022WR034099.
Shao, Manqing, Fernando, Nelun, Zhu, John, Zhao, Gang, Kao, Shih‐Chieh, Zhao, Bingjie, Roberts, Elizabeth, & Gao, Huilin. Estimating Future Surface Water Availability Through an Integrated Climate‐Hydrology‐Management Modeling Framework at a Basin Scale Under CMIP6 Scenarios. United States. https://doi.org/10.1029/2022WR034099
Shao, Manqing, Fernando, Nelun, Zhu, John, Zhao, Gang, Kao, Shih‐Chieh, Zhao, Bingjie, Roberts, Elizabeth, and Gao, Huilin. Wed .
"Estimating Future Surface Water Availability Through an Integrated Climate‐Hydrology‐Management Modeling Framework at a Basin Scale Under CMIP6 Scenarios". United States. https://doi.org/10.1029/2022WR034099.
@article{osti_1988175,
title = {Estimating Future Surface Water Availability Through an Integrated Climate‐Hydrology‐Management Modeling Framework at a Basin Scale Under CMIP6 Scenarios},
author = {Shao, Manqing and Fernando, Nelun and Zhu, John and Zhao, Gang and Kao, Shih‐Chieh and Zhao, Bingjie and Roberts, Elizabeth and Gao, Huilin},
abstractNote = {Abstract Climate change and increasing water demand due to population growth pose serious threats to surface water availability. The biggest challenge in addressing these threats is the gap between climate science and water management practices. Local water planning often lacks the integration of climate change information, especially with regard to its impacts on surface water storage and evaporation as well as the associated uncertainties. Using Texas as an example, state and regional water planning relies on the use of reservoir “Firm Yield” (FY)—an important metric that quantifies surface water availability. However, this existing planning methodology does not account for the impacts of climate change on future inflows and on reservoir evaporation. To bridge this knowledge gap, an integrated climate‐hydrology‐management (CHM) modeling framework was developed, which is generally applicable to river basins with geographical, hydrological, and water right settings similar to those in Texas. The framework leverages the advantages of two modeling approaches—the Distributed Hydrology Soil Vegetation Model (DHSVM) and Water Availability Modeling (WAM). Additionally, the Double Bias Correction Constructed Analogues method is utilized to downscale and incorporate Coupled Model Intercomparison Project Phase 6 GCMs. Finally, the DHSVM simulated naturalized streamflow and reservoir evaporation rate are input to WAM to simulate reservoir FY. A new term—“Ratio of Firm Yield” (RFY)—is created to compare how much FY changes under different climate scenarios. The results indicate that climate change has a significant impact on surface water availability by increasing reservoir evaporation, altering the seasonal pattern of naturalized streamflow, and reducing FY.},
doi = {10.1029/2022WR034099},
journal = {Water Resources Research},
number = 7,
volume = 59,
place = {United States},
year = {Wed Jul 05 00:00:00 EDT 2023},
month = {Wed Jul 05 00:00:00 EDT 2023}
}
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