DOE OSTI · 3484660
Data and Code for: Observation-constrained agroecosystem model inversion reveals continental-scale variation of winter wheat traits
Abstract
This repository contains the simulation outputs and processing scripts associated with the study of winter wheat traits across the United States, utilizing the Ecosys agroecosystem model. The dataset includes model results for both rainfed and irrigated winter wheat systems, supporting the findings presented in the manuscript titled "Observation-constrained agroecosystem model inversion reveals continental-scale variation of winter wheat traits." Data includes the original Ecosys simulation outputs (archived in .db format within the compressed .zip files) and extracted analysis data (stored in .pkl files for efficient processing). Python code for data processing and figure generation is provided in a Jupyter notebook. External Observational Datasets should refer to the following official repositories for the input and validation data used in this study. The eddy covariance data from the AmeriFlux network (https://ameriflux.lbl.gov/). Climate-forcing data of NLDAS-2 from NASA LDAS (https://ldas.gsfc.nasa.gov/nldas/nldas-2-forcing-data). Soil data from the Gridded Soil Survey Geographic Database (gSSURGO), available at (https://www.nrcs.usda.gov/resources/data-and-reports/gridded-soil-survey-geographic-gssurgo-database). Crop yields, planting and harvest dates from the USDA public databases (https://quickstats.nass.usda.gov/; https://webapp.rma.usda.gov/apps/actuarialinformationbrowser/CropCriteria.aspx). Satellite-derived SLOPE GPP data from ORNL DAAC (https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1786). Land use and crop progress information from the USDA Crop Data Layer and Crop Progress and Condition Gridded Layers (https://www.nass.usda.gov/Research_and_Science/). The Ecosys model code is available online at https://github.com/jinyun1tang/ECOSYS.
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Zhang, Zhenyu [Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana- Champaign, Urbana, Illinois,USA; College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana- Champaign, Urbana, Illinois, USA] (ORCID:0000000291557378), Guan, Kaiyu [Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana- Champaign, Urbana, Illinois,USA; College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana- Champaign, Urbana, Illinois, USA; National Center for Supercomputing Applications, University of Illinois Urbana- Champaign, Urbana, Illinois, USA; Siebel School of Computing and Data Science, University of Illinois Urbana- Champaign, Urbana, Illinois, USA; DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA], Grant, Robert [Department of Renewable Resources, University of Alberta, Edmonton, Alberta, Canada], Zhou, Wang [Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana- Champaign, Urbana, Illinois,USA], Peng, Bin [Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana- Champaign, Urbana, Illinois,USA; College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana- Champaign, Urbana, Illinois, USA; DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA], Qin, Rongzhu [Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana- Champaign, Urbana, Illinois,USA; College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana- Champaign, Urbana, Illinois, USA], Hu, Tongxi [Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana- Champaign, Urbana, Illinois,USA; College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana- Champaign, Urbana, Illinois, USA], Asseng, Senthold [Department of Life Science Engineering, Chair of Digital Agriculture, HEF World Agricultural Systems Center, Technical University of Munich, Freising, Germany], Zhang, Jingting [Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana- Champaign, Urbana, Illinois,USA; College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana- Champaign, Urbana, Illinois, USA], Li, Ziyi [Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana- Champaign, Urbana, Illinois,USA; College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana- Champaign, Urbana, Illinois, USA], Kidwell, Kimberlee K. [College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana- Champaign, Urbana, Illinois, USA], Zhang, Jiaying [Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana- Champaign, Urbana, Illinois,USA; College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana- Champaign, Urbana, Illinois, USA]. 2026-04-14. Data and Code for: Observation-constrained agroecosystem model inversion reveals continental-scale variation of winter wheat traits. https://doi.org/10.5281/zenodo.19563527
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