Location: Agroecosystems Management Research
Title: Agriculture model comparison framework and MyGeoHub hosting: Case of soil nitrogenAuthor
BHAR, ANUPAM - Iowa State University | |
FEDDERSEN, BENJAMIN - Iowa State University | |
Malone, Robert - Rob | |
KUMAR, RATNESH - Iowa State University |
Submitted to: Inventions
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 3/26/2021 Publication Date: 3/29/2021 Citation: Bhar, A., Feddersen, B., Malone, R.W., Kumar, R. 2021. Agriculture model comparison framework and MyGeoHub hosting: Case of soil nitrogen. Inventions. 6(2). Article 25. https://doi.org/10.3390/inventions6020025. DOI: https://doi.org/10.3390/inventions6020025 Interpretive Summary: Accurate prediction of soil nutrient processes such as nitrogen dynamics are crucial to agricultural system modeling. The Carbon and related Nitrogen dynamics (i.e., C/N dynamics) as captured in advanced agricultural models such as the Root Zone Water Quality Model (RZWQM) are highly complex. Determining input variables for these complex models requires considerable time and effort. A study of trade-offs among model of different complexity versus calibration speed in determining input variables is desirable. This paper surveys several soil nitrogen models with different complexity defined partly in terms of number of parameters. This paper also examines a less complex soil C/N model and compares it with the more complex RZWQM. The less complex model soil nitrate simulations compared well with RZWQM, while calibration time was considerably less. Identifying the most accurate and efficient methods to predict soil C/N dynamics will help agricultural scientists and the agriculture industry more effectively and efficiently design sustainable systems. Technical Abstract: Accurate simulation of primary soil nutrient Nitrogen is a crucial aspect of agriculture system modeling. The Nitrogen dynamics and related Carbon dynamics, as captured in advanced agricultural models such as RZWQM are highly complex, involving numerous processes and parameters. Calibrating a large number of parameters requires more time and effort. The execution time of a complex model is higher as well. A study of tradeoff among modeling complexities vs speed-up, and corresponding impact on modeling accuracy, is desirable. This paper surveys soil Nitrogen models and lists those by their complexity in terms of number of parameters and N-pools. This paper also examines a lean soil N and C dynamics model, and compares it with an advanced model, RZWQM. Since nitrate and ammonia are not directly measured, we first calibrate RZWQM using the available data from an experimental field in Greeley, CO, and next use the daily nitrate and ammonia data generated from RZWQM as ground truth, against which the lean model’s N dynamics parameter are calibrated. In both cases, the crop growth was removed to zero out the plant uptake, so as to compare only the soil N-dynamics. The comparison results showed good accuracy with a coefficient of determination (R2) match of 0.99 and 0.62 for Nitrate and Ammonia respectively, while affording significant speed-up in simulation time. The lean model is also hosted in MyGeoHub cyberinfrastructure for an universal online access. |