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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #421034
Research Project: Linkages Between Crop Production Management and Sustainability in the Central Mississippi River Basin

Location: Cropping Systems and Water Quality Research

Title: The effects of dynamic weather-dependent parameters on runoff and crop yield estimation for the APEX model

Author
item Pallardy, Quinn
item Baffaut, Claire

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 8/29/2024
Publication Date: 11/10/2024
Citation: Pallardy, Q.J., Baffaut, C. 2024. The effects of dynamic weather-dependent parameters on runoff and crop yield estimation for the APEX model [abstract]. ASA-CSSA-SSSA International Annual Meeting, November 11-13, 2024, San Antonio, Texas. Paper No. 159819. Available: https://scisoc.confex.com/scisoc/2024am/meetingapp.cgi/Paper/159819

Interpretive Summary:

Technical Abstract: The APEX, or Agricultural Policy/Environmental Extender Model, simulates many of the bio-physical processes that take place on a farm or small watershed. The parameters APEX uses to detail how these processes are simulated are typically determined through calibration and validation procedures based on a comparison of model output to observational data. However, traditional methods of parameterization assume a static set of optimal parameters for the full simulation. To investigate the validity of the assumption of stationarity in optimal parameter values, this study assessed whether the introduction of parameters allowed to vary based off past weather conditions could offer improved runoff and crop yield estimation for the APEX model. The hypothesis examined was that optimal parameters under dry conditions were different than those under wet conditions. Results indicated that dynamic parameters calibration resulted in improvements in a model performance indicator that combined water yields and crop yields. At the validation stage, the performance indicator improved to a lesser degree and less consistently across the examined plots. The dynamic calibration process led to changes in optimal values for several parameters based on soil moisture levels. These results have potential implications for both the accuracy of APEX outcomes under current scenarios and for APEX outcomes under changing environmental conditions.