A Comparison between Different Crop Models for Simulating Soil Temperature

Soil temperature is a key factor in precision agricultural management since it regulates crop production. This study is designed to compare the effectiveness of Noah with multi-parameterization (Noah-MP; along with its newly developed irrigation scheduling and groundwater abstraction schemes over croplands) and a traditional crop model, i.e., Environmental Policy Integrated Climate Model (EPIC; along with user specified multiple options for the critical agricultural parameters and management practices) in estimating soil temperature. The experiment considers a 30-year long time series (1990-2020) and focuses on the Central Valley in California, one of the most productive agricultural regions in the USA. For EPIC model, we generate three sets of soil temperature simulations using three different system-provided options (i.e., original cosine, enhanced cosine, and pseudo heat transfer). By comparing against ground-based measurements, the Pseudo Heat Transfer approach provides more accurate and realistic simulations. For Noah-MP, we generate multiple sets of soil temperature estimates with and without the irrigation or groundwater abstraction schemes. By including an irrigation scheduling scheme and a groundwater abstraction scheme, the simulated soil temperatures are in larger agreement with ground-based observations. These evaluations will provide a solid basis towards developing a decision guidance system for precision agriculture management in a nonstationary environment in the future.