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We describe a framework for deploying agent-based models as a tool for decision-making during resilience planning, with an emphasis on flood mitigation. Prior work has demonstrated that agent-based models can be effective tools for modelling evolving community flood resilience and risk perception when they incorporate elements of individual decision-making. We argue for extending this methodology and incorporating it into regional infrastructure and resilience planning in order to 1) create more distributed and robust green infrastructure implementations and performance management systems; 2) provide a critique and alternatives to existing planning and delivery processes based on public sector jurisdictional boundaries; and, 3) validate and improve the modelling process by connecting it directly to stakeholder decision-making processes. This final point will effectively merge these systems-centric modelling approaches with human-centred community organising that employs various co-design methods. In regard to the ABMs, co-design methods can be a useful source of real-world data about individual decision-making that can inform and validate iterations of the models. For stakeholders, they can be a valuable source of information and education about flood risk and climate-related impacts that might not be available through other channels. And finally, hands-on workshops coupled with potential small implementation grants can be effective ways of providing skills and incentives to stakeholders who may wish to undertake projects on their own property, reshaping the way green infrastructure planning and implementation can be accomplished.
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DAWN: Dashboard for Agricultural Water Use and Nutrient Management—A Predictive Decision Support System to Improve Crop Production in a Changing Climate
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 provide credible, usable information to support decisions by creating infrastructure to make subseasonal-to-seasonal forecasts accessible. DAWN uses an integrated approach to 1) engage stakeholders to coproduce a decision support and information delivery system; 2) build a coupled 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 presents DAWN’s framework for 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, specifically in infrastructure development, coproduction and trust building with stakeholders, product design, effective communication, and moving tools toward use.
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- Award ID(s):
- 1828910
- PAR ID:
- 10525589
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- https://journals.ametsoc.org/view/journals/bams/105/2/BAMS-D-22-0221.1.xml
- Date Published:
- Journal Name:
- Bulletin of the American Meteorological Society
- Volume:
- 105
- Issue:
- 2
- ISSN:
- 0003-0007
- Page Range / eLocation ID:
- E432 to E441
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1175/BAMS-D-22-0221.1
