DAWN: Dashboard for Agricultural Water use and Nutrient management - A predictive decision support system to improve crop production in a changing climate

Authors: LIANG, XIN-ZHONG - University Of Maryland; GOWER, DREW - University Of Maryland; KENNEDY, J - University Of Maryland; KENNEY, M - University Of Minnesota; MADDOX, M - University Of Maryland; BALBOA, G - University Of Nebraska; BECKER, T - University Of Nebraska; CAI, X - University Of Illinois; ELMORE, R - University Of Nebraska; GAO, X - Colorado State University; GERST, M - University Of Maryland; HE, Y - University Of Illinois; LIANG, K - University Of Maryland; LOTTON, SHANE - Colorado State University; MALAYIL, LEENA - University Of Maryland; MATTHEWS, MEGAN - University Of Illinois; MEADOW, ALISON - University Of Arizona; MEALE, CHRISTOPHER - University Of Nebraska; NEWMAN, GREG - Colorado State University; SAPKOTA, AMY - University Of Maryland; SHIN, SANGHOON - University Of Maryland; STRAUBE, JONATHAN - Colorado State University; SUN, CHAO - University Of Maryland; WU, YOU - University Of Maryland; YANG, YUN - Mississippi State University; Zhang, Xuesong

Submitted to: Bulletin of the American Meteorological Society
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/23/2023
Publication Date: 2/1/2024
Citation: Liang, X., Gower, D., Kennedy, J.A., Kenney, M., Maddox, M.C., Balboa, G., Becker, T., Cai, X., Elmore, R., Gao, X., Gerst, M., He, Y., Liang, K., Lotton, S., Malayil, L., Matthews, M.L., Meadow, A.M., Meale, C., Newman, G., Sapkota, A.R., Shin, S., Straube, J., Sun, C., Wu, Y., Yang, Y., Zhang, X. 2024. DAWN: Dashboard for Agricultural Water use and Nutrient management - A predictive decision support system to improve crop production in a changing climate. Bulletin of the American Meteorological Society. 105:E432–E441. https://doi.org/10.1175/BAMS-D-22-0221.1.
DOI: https://doi.org/10.1175/BAMS-D-22-0221.1

Interpretive Summary: Climate change is causing significant problems for American farmers who already face difficult decisions. A group of scientists, educators, and farmers, funded by the USDA, is working on a science modeling system called DAWN - Dashboard for Agricultural Water use and Nutrient management - to support farmers' decision-making in a changing climate. DAWN combines weather and agroecosystem models to provide seasonal-to subseasonal weather forecasts and assess the effects of various nutrient and water management practices on crop yields and environmental quality. Through extensive education and extension efforts, the team is working closely with farmers and other stakeholders to co-produce knowledge and information that are highly relevant to improving farming practices in the Corn Belt. Lessons learned from applying DAWN are discussed to facilitate future development and application of agricultural decision support systems.

Technical Abstract: Climate change presents huge challenges to the already complex decisions faced by U.S. agricultural producers, as seasonal weather patterns increasingly deviate from historical tendencies. Under USDA funding, a transdisciplinary team of researchers, extension experts, educators, and stakeholders is developing a climate decision support Dashboard for Agricultural Water use and Nutrient management (DAWN) to provide Corn Belt farmers with better predictive information. DAWN’s goal is to create infrastructure to make seasonal-tosubseasonal forecasts accessible, providing credible, usable information to support decisions. DAWN uses an integrated approach to: [1] engage stakeholders to coproduce a decision support and information delivery system; [2] build a coupled science modeling system to represent and transfer holistic systems knowledge into effective tools; [3] produce reliable forecasts to help stakeholders optimize crop productivity and environmental quality; and [4] integrate research and extension into experiential, transdisciplinary education. This article highlights DAWN’s main achievements and challenges in integrating climate-agriculture research, extension, and education to bridge science and service. We also present key challenges to the creation and delivery of decision support, particularly in infrastructure development, building trust and understanding for active engagement in system coproduction, product design, effectively communicating with stakeholders, and moving tools towards actual use.