Field scale SWAT+ modeling of corn and soybean yields for the contiguous United States: National Agroecosystem Model Development

Natalja Čerkasova*, Michael White, Jeffrey Arnold, Katrin Bieger, Peter Allen, Jungang Gao, Marilyn Gambone, Manyowa Meki, James Kiniry, Philip W. Gassman

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

7 Citations (Scopus)
5 Downloads (Pure)

Abstract

CONTEXT: Despite a steady increase in staple crop yields over the past ten years, current agricultural production must escalate even more to keep pace with the expected world population growth, which in turn will require improved agricultural methods that are adapted to many environmental pressures. Comprehensive models that can simulate crop production systems and the impact of management and conservation practices on natural resources and the environment, including water quality at large scale present important contributions to this challenge. OBJECTIVE: To this end we developed the National Agroecosystem Model (NAM): a comprehensive model that uses the updated Soil and Water Assessment Tool (SWAT+) to accurately simulate staple crop yields across the contiguous United States (CONUS), with an initial focus on Corn (Zea mays L.) and Soybean (Glycine max L. Merr.) yields. METHODS: Available open-access data was used to setup this high-resolution modeling system, where every 8-digit hydrologic unit (HUC8) is represented as an individual SWAT+ simulation. A total of 2201 HUC8 simulations across the CONUS were interconnected from upstream to downstream to make the NAM. Field boundary data was used to setup the NAM in such a way that every identified cultivated field is modeled as a unique Hydrologic Response Unit (HRU). Simulated corn and soybean yield from over 2.5 million field-type HRUs were compared to reported average annual corn and soybean yields for the respective area for the 2015–2020 period. RESULTS AND CONCLUSIONS: Results show a good agreement between simulated and reported yields (R2 = 0.90 for corn and R2 = 0.70 for soybeans), with a very good model performance in the high corn and soybean production region of the US Corn Belt (Relative Error < ±5%). SIGNIFICANCE: Apart from assessing the capability of the updated SWAT+ model, we also demonstrate the new crop yield calibration module embedded in SWAT+, highlight changes to the plant growth module, and model parameterization. Results of an analysis of possible crop production differences for corn and soybeans in irrigated, tiled, and non-irrigated-non-tiled fields are also discussed. The versatility of the NAM provides the possibility to analyze information on impacts of changing conservation practices and enables identification of conservation gains and remaining conservation needs at the national scale.

Original languageEnglish
Article number103695
JournalAgricultural Systems
Volume210
Number of pages16
ISSN0308-521X
DOIs
Publication statusPublished - Aug 2023

Keywords

  • Crop yield calibration
  • Crop yields
  • Large-scale modeling
  • SWAT+ model

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