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Title: Using satellite-based estimates of evapotranspiration and groundwater changes to determine anthropogenic water fluxes in land surface models

Author
item Anderson, Raymond - Ray
item LO, MIN-HUI - National Taiwan University
item SWENSON, SEAN - National Center For Atmospheric Research (NCAR)
item FAMIGLIETTI, JAMES - Jet Propulsion Laboratory
item TANG, QIUHONG - Institute Of Geographic Sciences And Natural Resources
item Skaggs, Todd
item LIN, YEN-HENG - National Taiwan University
item WU, REN-JIE - National Taiwan University

Submitted to: Geoscientific Model Development
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/14/2015
Publication Date: 10/2/2015
Publication URL: http://handle.nal.usda.gov/10113/61549
Citation: Anderson, R.G., Lo, M., Swenson, S., Famiglietti, J.S., Tang, Q., Skaggs, T.H., Lin, Y., Wu, R. 2015. Using satellite-based estimates of evapotranspiration and groundwater changes to determine anthropogenic water fluxes in land surface models. Geoscientific Model Development. 8:3021-3031. doi: 10.5194/gmd-8-3021-2015.

Interpretive Summary: Agricultural irrigation has important impacts on regional hydrology and climatology due to its consumption of water from surface and groundwater sources, cooling of land surface from evaporation of water, and potential increases in precipitation in downwind regions from enhanced atmospheric water vapor content. Accurately representing irrigation in climate models is important for predicting the possible interactions between climate and agricultural land and irrigation management under future scenarios. However, current climate and land surface models mostly lack agricultural irrigation in their model processes, resulting in an underestimation of evaporation. In this study, we use satellite observations of evaporation and groundwater change to estimate the amount of surface and ground water necessary to be added in simulations in the Central Valley of California. The results show that satellite-based observations can greatly improve the input data for regional climate and land surface models and that using satellite observations has important advantages (conserved water budget, current data, and potential use in less developed regions) over previous approaches to estimate irrigation water application in climate models. The research benefits policymakers and future researchers who are interested in the local, regional, and national impacts of irrigation on climate; particularly under potential scenarios of climate change and irrigation reduction where restrictions on irrigation may amplify local temperature increases and reduce precipitation in downwind regions.

Technical Abstract: Irrigation is a widely used water management practice that is often poorly parameterized in land surface and climate models. Previous studies have addressed this issue via use of irrigation area, applied water inventory data, or soil moisture content. These approaches have a variety of drawbacks including data latency, accurately prescribing irrigation intensity, and conservation of water volume for soil moisture approach. In this study, we parameterize irrigation fluxes using satellite observations of evapotranspiration (ET) against ET from a suite of land surface models without irrigation. We then apply this water flux into the Community Land Model (CLM) and use an iterative approach to estimate groundwater recharge and partition the water flux between groundwater and surface water. The ET simulated by CLM with irrigation matches the magnitude and seasonality of observed satellite ET well, with a mean difference of 6.3 mm/month and a correlation of 0.95. Differences between the new CLM ET values and observed ET values are always less than 30 mm/month and the differences show no pattern with respect to seasonality. The results reinforce the importance of accurately parameterizing anthropogenic hydrologic fluxes into land surface and climate models to assess environmental change under current and future climates and land management regimes.