Multivariate calibration of the Agricultural Policy / Environmental eXtender model for field scale simulation of hydrologic and agronomic outcomes

Authors: Pallardy, Quinn; Baffaut, Claire; Schreiner-Mcgraw, Adam; Sudduth, Kenneth; Ransom, Curtis; Abendroth, Lori; Veum, Kristen

Submitted to: Science of the Total Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/23/2026
Publication Date: 2/3/2026
Citation: Pallardy, Q.J., Baffaut, C., Schreiner-Mcgraw, A.P., Sudduth, K.A., Ransom, C.J., Abendroth, L.J., Veum, K.S. 2026. Multivariate calibration of the Agricultural Policy / Environmental eXtender model for field scale simulation of hydrologic and agronomic outcomes. Science of the Total Environment. 1017. Article 181480. https://doi.org/10.1016/j.scitotenv.2026.181480.
DOI: https://doi.org/10.1016/j.scitotenv.2026.181480

Interpretive Summary: Farmers need information on the long-term effects of agricultural practices such as tillage, crop rotations, and cover cropping on crop yield and runoff. Models can be used to estimate these outcomes on farms across the US where direct measurements cannot be obtained. Models must be calibrated for accurate results, but important data for calibration are often unavailable. Where runoff data are lacking, remotely sensed data, including surface soil moisture and evapotranspiration, may provide substitute information for the calibration process. To examine the effects of calibration with surface soil moisture, evapotranspiration, crop yield and surface runoff, simulations were carried out with the Agricultural Policy/Environmental Extender (APEX) model on an 88-acre field in the central United States. The best results were achieved when the outcome in question was used in the calibration process. Evapotranspiration or surface soil moisture in addition to runoff improved model performance for all outcomes except for runoff. Calibration with evapotranspiration alone improved performance for runoff, compared to other calibration data combinations that did not include runoff. Improved performance for crop yields tended to come at the cost of reduced performance for runoff, and vice versa. Results suggest that remote sensing may be a useful source of calibration data for the APEX model when on-site field data are not available. This would allow the model to be applied more widely and to provide useful estimates of management outcomes to a larger number of US farmers.

Technical Abstract: The Agricultural Policy/Environmental Extender (APEX) model simulates biophysical processes at the sub-field scale. Parameter calibration of hydrological models has long been recognized as critical for accuracy of model outputs. This can be problematic when the relevant data are unobtainable at the location in question. However, surface soil moisture and evapotranspiration can be estimated with remote sensing, potentially enabling hydrological calibration where in-field data are unavailable. The objective of this study was to assess the performance of APEX when calibrated with combinations of surface soil moisture, evapotranspiration, runoff, and crop yield observations. APEX parameters were calibrated for a 36-ha field in Missouri, U.S., using all possible combinations of the aforementioned model outcomes. Since the accuracy of remote sensed evapotranspiration and soil moisture has not been evaluated at the field scale yet, data measured at the site was used. Model performance was highest for outcomes included in the calibration process. Including soil moisture or evapotranspiration with runoff in the calibration process improved their respective performance but did not significantly change runoff performance. Calibration with evapotranspiration (excluding runoff) outperformed other non-runoff calibration combinations, illustrating the potential for remotely sensed evapotranspiration to improve runoff estimation where runoff data are unavailable. However, the model struggled to simultaneously optimize crop yields and runoff performance, tending to overestimate runoff when calibrating with crop yields and to overestimate crop yields when calibrating with runoff. The results from the study provided an indication that remotely sensed data may play a beneficial role in APEX simulations at a sub-field scale.