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

CNH2-L：利用调节反馈对人类和河口系统的动态进行建模

• 批准号: 2009248
• 负责人: Raleigh Hood
• 金额: $ 143.64万
• 依托单位: University of Maryland Center for Environmental Sciences
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2009248&HistoricalAwards=false
• 关键词: CNH2; Modeling; dynamics; human; estuarine

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.

不断变化的交通、土地使用、水资源使用和经济活动模式影响着环境，并最终影响着人类的生活质量。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，我们对环境如何响应人类决策的了解远远超过了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。这些预测将包括几个合理的未来发展情景（例如，明智的增长与一切照旧），这将使我们了解环境退化如何影响不同的社区，以及他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，以规划可持续增长。链接的社会经济和环境模型展示了预测人类行为如何驱动交通、土地使用、水质以及最终生物资源变化的可能性（例如，鱼类栖息地和海草生长）。然而，在大多数模型中，人类对环境质量变化的反应并没有得到充分的考虑。本计画发展一个耦合模式系统，以研究社会经济活动、交通、土地利用、土地覆被、水质等复杂的相互关系，以及人类社会经济系统与环境系统之间的回馈。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，以及反过来，未能达到水质标准的反馈影响人类的行为和决策-该奖项反映了NSF的法定使命，并被认为是值得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的支持。