3B.5 Studying Groundwater Sustainability Using the Western Land Data Assimilation System

Monday, 7 January 2019: 3:00 PM
North 126BC (Phoenix Convention Center - West and North Buildings)
Bailing Li, Univ. of Maryland, College Park, MD; and M. Rodell, C. D. Peters-Lidard, J. M. Erlingis, and S. V. Kumar

In arid and semi-arid regions of the western U.S., aquifers are a major source of freshwater for agricultural and industrial activities as well as for municipal water needs due to the limited supplies of surface water. During the last several decades, groundwater exploitation has led to depleted aquifers, land subsidence, seawater intrusion and degraded water quality in areas with intensive farming or a dense population. In response, the state of California adopted the Sustainable Groundwater Management Act in 2014, which requires its local groundwater agencies to develop plans for sustainable use of groundwater in order to reduce those adverse consequences. Such planning and water management will require data on local to regional water budgets including groundwater recharge.

We report on our on-going effort to develop and optimize a Western Land Data Assimilation System (WLDAS) and present preliminary results on applying WLDAS for studying groundwater sustainability. WLDAS is an instance of NASA’s Land Information System framework running the Noah_Multiparameterization (MP) land surface model which simulates groundwater storage variations along with many other advanced features. WLDAS is configured at 1 km spatially and covers the area west of the Mississippi River. The high-resolution allows better representation of complex terrains and integration of high resolution forcing and remote sensing data such as those retrieved from the Airborne Snow Observatory. We present results of retrospective simulations (1979-2017) of Noah_MP driven by downscaled North American Land Data Assimilation System (NLDAS2) forcing data, with a focus on groundwater recharge and its relationship with environmental controls. Impacts of ET algorithms on groundwater along with evaluation of results using in situ soil moisture, groundwater and terrestrial water storage data derived from the Gravity Recovery and Climate Experiment (GRACE) mission are also presented.

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