Scientists propose a prognostic fertilization parameterization to model agro-ecosystems using an Earth system modeling approach.
Modeling agriculture within the Earth system is important not only to predict crop yields and assess food security but also to better understand the intertwined and complex processes in the climate-water-land nexus. Among other factors, efficiently using improved fertilizing techniques by dynamically determining fertilization timing and rates will have large impacts on crop yields.
The researchers found that fertilizers, which in the models are applied spatially uniformly with fixed amounts and timing without considering crop fertilizer demands, lead to a large bias in crop yield simulations. To address this weakness, likely present in most current-generation Earth System Models (ESMs), the team proposed a prognostic fertilization scheme in the model that dynamically determines the timing and rate of each fertilizer application, with the annual amounts and valid fertilization time-windows governed by census data.
The DOE scientists at Pacific Northwest National Laboratory applied the Community Land Model (CLM4.5) at a 0.125 degree resolution to provide the first, county-scale model validation used to simulate crop yields over the Conterminous United States. They found a large bias in simulating crop yields against the U.S. Department of Agriculture (USDA) census data, with a county-level, root-mean-square error (RMSE) of 42% and 38% for simulated U.S. mean corn and soybean (popular biofuel feedstocks) yields, respectively. The researchers then synthesized crop yield, irrigation, and fertilization datasets from the USDA and U.S. Geological Survey to constrain model simulations. Compared with fertilization, they found that irrigation has limited effects on crop yields with improvements limited to irrigated regions. In most current-generation ESMs, fertilizers are applied spatially uniformly with fixed amounts and timing without considering the specific crop fertilizer demand. To address this weakness in the model, the team proposed a prognostic fertilization calculation that dynamically determines the timing and rate of each fertilizer application, with the annual amounts and valid fertilization time-windows informed by existing census data. The optimized fertilization parameterization reduces the RMSE to 22% and 21% for the U.S. mean corn and soybean yields, respectively. Compared with the default CLM4.5, the team’s representation of fertilization substantially improved crop yield simulations, especially over major crop growing regions.
Contacts (BER PM)
Integrated Assessment Modeling Program
Pacific Northwest National Laboratory
Maoyi.Huang@pnnl.gov; (509) 375-6827
This study was supported by the U.S. Department of Energy’s Office of Science, Office of Biological and Environmental Research, Integrated Assessment Research Program for the Integrated Multi-sector, Multi-scale Modeling (IM3) Scientific Focus Area (SFA).
G. Leng, X. Zhang, M. Huang, Q. Yang, R. Rafique, G.R. Asrar, and L.R. Leung, “Simulating county-level crop yields in the conterminous United States using the community land model: The effects of optimizing irrigation and fertilization.” Journal of Advances in Modeling Earth Systems, 08, [DOI: 10.1002/2016MS000645] (Reference link)
SC-23.1 Climate and Environmental Sciences Division, BER
BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER
May 10, 2019
Quantifying Decision Uncertainty in Water Management via a Coupled Agent-Based Model
Considering risk perception can improve the representation of human decision-making processes in age [more...]
May 09, 2019
Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Scenarios
Study provides country-specific urban area growth models and the first dataset on country-level urba [more...]
May 05, 2019
Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning
A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in bu [more...]
May 03, 2019
Calibration and Uncertainty Analysis of Demeter for Better Downscaling of Global Land Use and Land Cover Projections
Researchers improved the Demeter model’s performance by calibrating key parameters and establi [more...]
Apr 22, 2019
Representation of U.S. Warm Temperature Extremes in Global Climate Model Ensembles
Representation of warm temperature events varies considerably among global climate models, which has [more...]
List all highlights (possible long download time)