Water returned to the atmosphere as evapotranspiration (ET) is approximately 1.6x greater than global river discharge and has wide-reaching impacts on groundwater and streamflow. In the U.S. Midwest, widespread land conversion from prairie to cropland has altered spatiotemporal patterns of ET, yet there is no consensus on the direction of change in ET or the mechanisms controlling changes. We aimed to harmonize findings about how land use change affects ET in the Midwest. We measured ET at three locations within the Long-Term Agroecosystem Research (LTAR) network along a latitudinal gradient with paired rainfed cropland and prairie sites at each location. At the northern locations, the Upper Mississippi River Basin (UMRB) and Kellogg Biological Station (KBS), the cropland has annual ET that is 84 and 29 mm/year higher, respectively, caused primarily by higher ET, likely from soil evaporation during springtime when agricultural fields are fallow. At the southern location, the Central Mississippi River Basin (CMRB), the prairie has 69 mm/year higher ET, primarily due to a longer growing season. To attribute differences in springtime ET to specific mechanisms, we examine the energy balance using the Two-Resistance Method (TRM). Results from the TRM demonstrate that higher surface conductance in croplands is the primary factor leading to higher springtime ET from croplands, relative to prairies. Results from this study provide critical insight into the impact of land use change on the hydrology of the U.S. Corn Belt by providing a mechanistic understanding of how land use change affects the water budget.
Accurate simulation of plant water use across agricultural ecosystems is essential for various applications, including precision agriculture, quantifying groundwater recharge, and optimizing irrigation rates. Previous approaches to integrating plant water use data into hydrologic models have relied on evapotranspiration (ET) observations. Recently, the flux variance similarity approach has been developed to partition ET to transpiration (T) and evaporation, providing an opportunity to use T data to parameterize models. To explore the value of T/ET data in improving hydrologic model performance, we examined multiple approaches to incorporate these observations for vegetation parameterization. We used ET observations from 5 eddy covariance towers located in the San Joaquin Valley, California, to parameterize orchard crops in an integrated land surface – groundwater model. We find that a simple approach of selecting the best parameter sets based on ET and T performance metrics works best at these study sites. Selecting parameters based on performance relative to observed ET creates an uncertainty of 27% relative to the observed value. When parameters are selected using both T and ET data, this uncertainty drops to 24%. Similarly, the uncertainty in potential groundwater recharge drops from 63% to 58% when parameters are selected with ET or T and ET data, respectively. Additionally, using crop type parameters results in similar levels of simulated ET as using site-specific parameters. Different irrigation schemes create high amounts of uncertainty and highlight the need for accurate estimates of irrigation when performing water budget studies.