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Groundwater Recharge Estimated by Land Surface Models: An Evaluation in the Conterminous United States

Fig.3 Mean annual recharge (mm, 1st column), correlation (2nd column), RMSE (mm, 3rd column) and KGE (4th column, the arrow in the color bar indicates that values
Fig.3 Mean annual recharge (mm, 1st column), correlation (2nd column), RMSE (mm, 3rd column) and KGE (4th column, the arrow in the color bar indicates that values
Fig.3 Mean annual recharge (mm, 1st column), correlation (2nd column), RMSE (mm, 3rd column) and KGE (4th column, the arrow in the color bar indicates that values <-1 are included) of the LSMs and the ensemble mean recharge with respect to USGS annual recharge estimates (top) for 2000-2013. Numbers in parentheses represent domain averages. The KGE color bar reflects the fact that -0.41 represents the skill of using mean observations for prediction.

ESSIC/CISESS Assistant Research Scientists Bailing Li and Jessica M. Erlingis are authors of a paper in the Journal of Hydrometeorology titled “Groundwater Recharge Estimated by Land Surface Models: An Evaluation in the Conterminous United States”.

In this study, the research team evaluated diffuse recharge over the conterminous United States simulated by a suite of land surface models (LSMs) that were forced using a common set of meteorological input data. They found spatial patterns that were similar among the LSMs, with the highest values in the eastern United States and Pacific Northwest. However, the magnitudes of annual recharge varied significantly among the models and were associated with differences in simulated ET, runoff, and snow. This study highlights the need to employ dynamic flow models in LSMs, among other improvements, to enable more accurate simulation of recharge.

Li works at the Hydrological Sciences Laboratory of NASA Goddard Space Flight Center. Her research interests include understanding spatial and temporal variability of soil moisture and groundwater using in situ, remotely sensed and modeling data and its role on water and energy balances at regional to global scales.

Erlingis works in the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center. Her research interests include precipitation estimation as well as numerical modeling of the land surface, atmosphere, and the interaction between them in order to improve the understanding of hydrometeorological extremes, such as floods and droughts.

To access the article, click here: “Groundwater Recharge Estimated by Land Surface Models: An Evaluation in the Conterminous United States”.

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