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.
| Original language | English |
|---|---|
| Article number | e2022WR034099 |
| Journal | Water Resources Research |
| Volume | 59 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jul 2023 |
Funding
This work was supported by the U.S. National Science Foundation's Non-Academic Research Internship Program, the U.S. National Science Foundation (Grant CBET-1454297), and U.S. Geological Survey (USGS) graduate student research grants through Texas Water Research Institute. It was also partially supported by the U.S. Department of Energy (DOE) Water Power Technologies Office as a part of the SECURE Water Act Section 9505 Assessment. One of the authors is an employee of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the DOE. DHSVM is maintained jointly by the Hydrology Group at Pacific Northwest National Laboratory (PNNL) and the Civil Engineering Department at the University of Washington. We thank Dr. Zhuoran Duan at PNNL for assisting with the DHSVM model. This work has benefitted from the usage of the Texas A&M Supercomputing Facility (http://hprc.tamu.edu). The climate model downscaling was conducted at the Oak Ridge Leadership Computing Facility, which is a Department of Energy Office of Science User Facility. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF. This work was supported by the U.S. National Science Foundation's Non‐Academic Research Internship Program, the U.S. National Science Foundation (Grant CBET‐1454297), and U.S. Geological Survey (USGS) graduate student research grants through Texas Water Research Institute. It was also partially supported by the U.S. Department of Energy (DOE) Water Power Technologies Office as a part of the SECURE Water Act Section 9505 Assessment. One of the authors is an employee of UT‐Battelle, LLC, under contract DE‐AC05‐00OR22725 with the DOE. DHSVM is maintained jointly by the Hydrology Group at Pacific Northwest National Laboratory (PNNL) and the Civil Engineering Department at the University of Washington. We thank Dr. Zhuoran Duan at PNNL for assisting with the DHSVM model. This work has benefitted from the usage of the Texas A&M Supercomputing Facility ( http://hprc.tamu.edu ). The climate model downscaling was conducted at the Oak Ridge Leadership Computing Facility, which is a Department of Energy Office of Science User Facility. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF.
Keywords
- climate change
- naturalized streamflow
- open water evaporation
- reservoir firm yield
- semi-arid area
- water availability