Evaluating Recharge Estimates of three LSMs across the Western U.S.

Abstract:

Groundwater is a major source of water in the western U.S. Aquifer systems in this region depend on variable recharge rates influenced by local climatology, vegetation, soils, and geology. There are limited recharge estimates in this region due to the complexity of recharge processes and limited observations. Reliable recharge estimates are important for management of these aquifer systems in response to projected increases in population, land use and climate changes. Several Land Surface Models (LSMs) have been developed over the last few decades to better represent the land surface and atmospheric processes aimed at improving the estimates of various water, energy and carbon fluxes. The complexity of these LSMs varies in simulating exchanges of energy, mass, and momentum between the land surface and overlying atmosphere. In this study, simulations of three LSMs (Noah, Mosaic and VIC) obtained from North American Land Data Assimilation System (NLDAS) are used for assessing recharge estimates across the western U.S. Modeled recharge was then compared with published recharge estimates for several aquifers in the region. Mosaic consistently generated higher evapotranspiration compared to Noah and VIC, thereby generating lower recharge. Estimates of recharge from Noah and VIC were similar to each other. While the average annual recharge values varied between the models, the models were consistent in identifying high and low recharge areas in the region. For an average annual precipitation ranging between 58-5051 mm across the western U.S., the estimated average annual recharge ranged between 0-3479 mm based on Mosaic, 0-4128 mm based on Noah and, 0-2209 mm based on VIC simulations. Annual recharge to precipitation ratios across the study basins, varied from 0.04-3.3% based on Mosaic; 4.3-35.5% based on Noah; and 3.9-24.3 % based on VIC simulations. Models tend to agree in seasonality of recharge occurring dominantly during the spring across the region. Our results highlight that LSMs have the potential to capture the spatial and temporal patterns of recharge at large scales; however more observational studies are required for improved parameterization.