Elizabeth A. Payton

Persistent droughts and anthropogenic warming have brought the southwestern United States—one of the world's most highly managed hydrologic regions—to the brink of a water supply crisis. Here, we examine the changes in hydrologic fluxes due to a shift toward aridity and the extent to which water storage in major reservoirs has offset these changes using a novel, high‐resolution (4 km) configuration of a state‐of‐the‐science land model, the Community Land Model. We leverage an emulation‐based parameter optimization approach to improve model hydrologic performance and reservoir parametrizations (generic and data‐driven) to simulate water storage and release. The hydrologic performance is notably improved across 121 basins in the Southwest, which translates into improved simulation of inflow, storage, and release across 133 reservoirs. The data‐driven approach outperforms the generic one, in simulating reservoir storage but not releases due to biases in inflows. Model simulations show a widespread increase in evapotranspiration (especially its soil evaporation component), driven primarily by increased absorption of solar radiation due to snowpack loss, which suppresses runoff. Increases in snowmelt mitigate runoff deficits during spring, which highlights the sensitivity of runoff response to the seasonal distribution of hydroclimatic supply and demand in the Southwest. Up to 40% of inflow deficits are met by surface water storage in large reservoirs (i.e., Mead and Powell). Simulated estimates of this supply‐demand imbalance are sensitive to biases in simulated inflows and releases. Caution is therefore warranted when using land models with reservoir parametrization for future drought risk and water scarcity assessments.

Crucial to the assessment of future water security is how the land model component of Earth System Models partition precipitation into evapotranspiration and runoff, and the sensitivity of this partitioning to climate. This sensitivity is not explicitly constrained in land models nor the model parameters important for this sensitivity identified. Here, we seek to understand parametric controls on runoff sensitivity to precipitation and temperature in a state‐of‐the‐science land model, the Community Land Model version 5 (CLM5). Process‐parameter interactions underlying these two climate sensitivities are investigated using the sophisticated variance‐based sensitivity analysis. This analysis focuses on three snow‐dominated basins in the Colorado River headwaters region, a prominent exemplar where land models display a wide disparity in runoff sensitivities. Runoff sensitivities are dominated by indirect or interaction effects between a few parameters of subsurface, snow, and plant processes. A focus on only one kind of parameters would therefore limit the ability to constrain the others. Surface runoff exhibits strong sensitivity to parameters of snow and subsurface processes. Constraining snow simulations would require explicit representation of the spatial variability across large elevation gradients. Subsurface runoff and soil evaporation exhibit very similar sensitivities. Model calibration against the subsurface runoff flux would therefore constrain soil evaporation. The push toward a mechanistic treatment of processes in CLM5 have dampened the sensitivity of parameters compared to earlier model versions. A focus on the sensitive parameters and processes identified here can help characterize and reduce uncertainty in water resource sensitivity to climate change.

The impacts of a severe sustained drought on Colorado River system water resources were investigated by simulating the physical and institutional constraints within the Colorado River Basin and testing the response of the system to different hydrologic scenarios. Simulations using Hydrosphere's Colorado River Model compared a 38‐year severe sustained drought derived from 500 years of reconstructed streamflows for the Colorado River basin with a 38‐year streamflow trace extracted from the recent historic record. The impacts of the severe drought on streamflows, water allocation, storage, hydropower generation, and salinity were assessed. Estimated deliveries to consumptive uses in the Upper Basin states of Colorado, Utah, Wyoming, New Mexico, and northern Arizona were heavily affected by the severe drought, while the Lower Basin states of California, Nevada, and Arizona suffered only slight shortages. Upper Basin reservoirs and streamflows were also more heavily affected than those in the Lower Basin by the severe drought. System‐wide, total hydropower generation was 84 percent less in the drought scenario than in the historical stream‐flow scenario. Annual, flow‐weighted salinity below Lake Mead exceeded 1200 ppm for six years during the deepest portion of the severe drought. The salinity levels in the historical hydrology scenario never exceeded 1100 ppm.

The marginal economic value of streamflow leaving forested areas in the Colorado River Basin was estimated by determining the impact on water use of a small change in streamflow and then applying economic value estimates to the water use changes. The effect on water use of a change in streamflow was estimated with a network flow model that simulated salinity levels and the routing of flow to consumptive uses and hydroelectric dams throughout the Basin. The results show that, under current water management institutions, the marginal value of streamflow in the Colorado River Basin is largely determined by nonconsumptive water uses, principally energy production, rather than by consumptive agricultural or municipal uses. The analysis demonstrates the importance of a systems framework in estimating the marginal value of streamflow.

A raw water supply Master Plan has been prepared for the City of Boulder, Colorado. The city's portfolio of water rights includes decrees for native water from Boulder Creek and shares in two large transbasin diversion projects. The supply system is operated to meet municipal and industrial demands, provide minimum streamflows for Boulder Creek, and generate revenues from hydroelectric turbines installed in raw‐ and treated‐water transmission lines. The Master Plan was developed with the use of three applications of the Central Resource Allocation Model, a microcomputer‐based network‐optimization tool, which uses the Out‐of‐ Kilter Algorithm. The three applications addressed the yield of the city's native water rights, the yield of its transbasin diversion project holdings, and the economic operation of its water delivery system to meet future demands. The Master Plan recommends modifications to certain operating policies, enlargement of some delivery and treatment facilities, and sale or lease of one of the transbasin water sources.