ELEMENTS: DATA: HDR: SWIM to a Sustainable Water Future

该项目开发了一个系统，该系统可以自动地将数据摄取到模型中，集成解耦模型，以及动态地生成和解释模型。重点是水资源。该团队利用正在进行的美国农业部资助项目的软件开发，以及跨学科的国际科学家和学生团队的专业知识，他们正在调查新墨西哥州南部，德克萨斯州西部和奇瓦瓦州（墨西哥）北部中部里约热内卢格兰德山谷的水可用性和使用的未来情景。该项目通过创建可持续水集成建模（SWIM）框架来提高水的可持续性研究能力，该框架可自动将数据导入模型，促进解耦模型的集成，并支持模型的动态生成和解释。四个目标是：1)通过基于网络的界面和来源捕获实现的直接参与，促进利益相关者（非建模者）使用水模型；2)通过服务驱动的数据交换和转换实现模型到模型的无缝集成；3)开发基于数据和技术的方法，用生物物理和社会模型进行推理；4)让数据提供者、建模者和利益相关者参与构思和测试框架。该项目的研究和产品有助于提高水可持续性的先进研究能力。通过提供科学数据和模型的无缝集成，并生成来源数据以创建动态用户界面，该项目向通过参与式分析生成的模型灌输信任。这种方法是建立在对涉众参与和实现所描述目标的一致性的价值的强烈赞赏之上的。这项研究由一个多元化和经验丰富的团队进行，将有助于了解如何更有效地与研究人员和利益相关者进行融合研究。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。

The project develops a system that automates ingestion of data into models, the integration of decoupled models, and the dynamic generation and interpretation of models. The focus is on water resources. The team leverages software development from an ongoing USDA-funded project, and the expertise of an interdisciplinary, international team of scientists and students who are investigating future scenarios of water availability and use in the Middle Rio Grande valley of southern New Mexico, west Texas, and northern Chihuahua (Mexico).This project advances water sustainability research capabilities by creating a Sustainable Water through Integrated Modeling (SWIM) framework that automates ingestion of data into models, facilitates integration of decoupled models, and supports dynamic generation and interpretation of models. The four objectives are to: 1) foster use of water models by stakeholders (non-modelers) through direct participation enabled by a web-based interface and provenance capture; 2) enable seamless model-to-model integration through service-driven data exchange and transformation; 3) develop data- and technology-enabled approaches for reasoning with biophysical and social models; and 4) engage data providers, modelers and stakeholders in conceiving and testing the framework.The research and products of this project contribute to advanced research capabilities on water sustainability. By providing seamless integration of scientific data and models, and generating provenance data to create dynamic user interfaces, the project instills trust in the models generated through participatory analysis. This approach is built around a strong appreciation of the value of stakeholder engagement and alignment to achieving the described goals. The research is carried out by a diverse and experienced team, and will contribute to understanding of how to more effectively conduct convergent research with researchers and stakeholders.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.