CNH2-L: Modeling the dynamics of human and estuarine systems with regulatory feedbacks

交通、土地利用、水资源利用和经济活动模式的变化影响着环境，并最终影响着人类生活的质量。模型使我们能够预测人类行为如何影响环境，但我们还没有能力预测环境的变化如何影响人类行为和决策。因此，我们对环境如何回应人类决策的了解，远远超过我们对人类如何应对不断变化的环境以及这些反应如何推动决策的了解。以切萨皮克湾为例，该项目将开发一个模型来预测社会、经济和政策变化如何影响水质，以及水质变化如何影响人类行为和决策。这些预测将包括几种可能的未来发展情景（例如，智能增长与一切照旧），这将使我们能够了解环境退化如何影响不同的社区，以及它们如何通过政策和行动作出反应。该项目产生的模型将帮助州和地方官员做出明智的决策，规划可持续增长。关联的社会经济和环境模型显示了预测人类行为如何驱动交通、土地利用、水质以及最终生物资源（如鱼类栖息地和海草生长）变化情景的潜力。然而，人类对环境质量变化的反应在大多数模式中没有得到充分考虑。本项目开发了一个耦合模型系统，以研究社会经济活动、交通、土地利用、土地覆盖和水质之间的复杂相互关系，以及人类社会经济系统和环境系统之间的反馈。通过开发一个将社会经济和环境模型与它们之间的双向反馈联系起来的模型，将有可能模拟和预测人类行为如何影响切萨皮克湾的营养负荷和水质，以及如何反过来，不符合水质标准的反馈影响人类行为和决策。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Changing patterns of transportation, land use, water use, and economic activity impact the environment and, ultimately, the quality of human life. Models allow us to predict how human behavior affects the environment, but we do not yet have the ability to predict how changes in the environment affect human behavior and decision making. As a result, we know much more about how the environment responds to human decisions than we do about how humans respond to a changing environment and how these responses drive decision-making. Using the Chesapeake Bay as an example, this project will develop a model to predict how social, economic and policy changes impact water quality, and how changes in water quality influence human behavior and decision-making. These predictions will include several plausible future development scenarios (e.g., smart growth versus business as usual) that will allow us to learn how environmental degradation impacts different communities and how they respond through policies and actions. The model produced by this project will help state and local officials make informed decisions to plan for sustainable growth. Linked socio-economic and environmental models demonstrate potential for forecasting scenarios of how human behaviors may drive changes in transportation, land use, water quality, and ultimately living resources (e.g., fish habitat and seagrass growth). However, the human responses to changes in environmental quality have not been sufficiently accounted for in most models. This project develops a coupled modeling system to study the complex interrelationships among socio-economic activity, transportation, land use, land cover, and water quality with feedbacks between the human social-economic system and the environmental system. Through the development of a model that links social-economic and environmental models with two-way feedbacks between them, it will be possible to simulate and forecast how human behavior impacts nutrient loading and water quality in Chesapeake Bay and how, in turn, the failure to meet water quality standards feedback to influence human behavior and decision-making.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.