This study evaluates the applicability of numerical weather prediction output supplemented with remote sensing data for near real-time operational estimation of hourly evapotranspiration (ET). Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) systems were selected to provide forcing data for a Penman-Monteith model to calculate the Actual Evapotranspiration (AET) over Iowa. To investigate how the satellite-based remotely sensed net radiation ( $R_n$ ) estimates might potentially improve AET estimates, Geostationary Operational Environmental Satellite derived $R_n$ (GOES- $R_n$ ) data were incorporated into each dataset for comparison with the RAP and HRRR $R_n$ -based AET evaluations. The authors formulated a total of four AET models—RAP, HRRR, RAP-GOES, HRRR-GOES, and validated the respective ET estimates against two eddy covariance tower measurements from central Iowa. The implementation of HRRR-GOES for AET estimates showed the best results among the four models. The HRRR-GOES model improved statistical results, yielding a correlation coefficient of 0.8, a root mean square error (mm hr⁻¹) of 0.08, and a mean bias (mm hr⁻¹) of 0.02 while the HRRR only model results were 0.64, 0.09, and 0.04, respectively. Despite limited in situ observational data to fully test a proposed AET estimation, the HRRR-GOES model clearly showed potential utility as a tool to predict AET at a regional scale with high spatio-temporal resolution.

Between July 2011 and February 2013, the City of Cedar Rapids observed water level declines in their horizontal collector wells approaching 11 meters. As a result, pumping from these production wells had to be halted, and questions were raised about the reliability of the alluvial aquifer under future drought conditions. The U.S. Geological Survey, in cooperation with the City of Cedar Rapids, completed a study to better understand the effects of drought stress on the Cedar River alluvial aquifer using a numerical groundwater flow model. Previously published groundwater flow models were combined with newly collected airborne, waterborne, down-hole, and land-based geophysical survey data and provided a detailed three-dimensional lithologic model of the Cedar River alluvial aquifer and surrounding area. An improved conceptual model for the groundwater flow system and a lithologic model were used to build and inform a numerical groundwater flow model capable of simulating water levels observed in the City of Cedar Rapids horizontal collector wells during the 2012 drought. Model performance was assessed primarily on the ability of the model to simulate water table elevation at six monitoring wells. Statistical tests were used to assess the numerical model during the calibration period, and results varied from satisfactory to unsatisfactory, likely because of stage changes in the Cedar River and production well withdrawal rates near monitoring wells. Simulated water levels during the 2012 drought indicated a depression near the horizontal collector wells, although simulated elevations at these locations and at monitoring wells were generally overestimated compared to measured values. The numerical groundwater flow model was modified to account for a decrease in seepage rate caused by low flow in the Cedar River and increased production. With seepage rate modification, model results improved; the simulated water table elevations were like those observed in horizontal collector and monitoring wells. Results demonstrated the ability of the model to simulate water levels observed in the horizontal collector wells during the 2012 drought when accounting for a decrease in infiltration from the Cedar River.