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MODFLOW 6 models for assimilating remote sensing evapotranspiration in ensemble-based framework to enhance cascade routing and re-infiltration concept in integrated hydrological models applied to support decision making

Published by U.S. Geological Survey | Department of the Interior | Metadata Last Checked: January 07, 2026 | Last Modified: 2024-06-14T00:00:00Z
This data release contains MODFLOW 6 integrated hydrological model (IHM) that helps characterize the groundwater/surface-water interaction within the Sardon Catchment of western Spain. The model was used to quantify and reduce the overall model uncertainty to improve its reliability as a Decision Support Modeling (DSM) tool by improving the conceptualization and simulation of the overland flow process. The model was calibrated to groundwater heads, surface flows at the outlet of the model, and remotely sensed evapotranspiration data collected by the MODIS satellite. To help constrain the roughly 500,000 estimated parameters, observations of "actual" evapotranspiration (ET) were obtained from the remotely sensed MODIS-ET product, an atypical calibration target. The MODIS-ET observations complemented the more traditional hydraulic heads and streamflow observations, yielding approximately 150,000 total observations for calibration. The data assimilation was carried using the PEST++ iterative ensemble smoother (IES). As discussed in the accompanying model documentation, including the MODIS-ET observations improved the cascade routing and re-infiltration (CRR) implementation, and subsequently reduced the uncertainties associated with other model parameters. Additionally, it significantly reduced the uncertainties of fluxes of interest, specifically the net recharge, a critical flux for water management which is not easily measured and is typically a modeled quantity within most IHM simulations that is of particular interest. This USGS data release contains all the input and output files for the simulations described in the associated journal article (https://doi.org/10.1016/j.jhydrol.2024.131411)

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