NSF Convergence Accelerator, Track K: Mapping the nation's wetlands for equitable water quality, monitoring, conservation, and policy development

该项目将为美国加速开发国家规模的湿地决策支持工具。湿地维持了生活质量，为应对气候变化影响和许多其他挑战提供了基于自然的解决方案，但在美国和全球，超过50%的湿地已经消失。关于湿地管理、政策、保护和恢复的公平和明智的决策需要准确的地图和科学的能力，以考虑湿地在广泛社会问题中的作用，如水质、野生动物栖息地、土著第一食物、用于缓解干旱或洪水的蓄水、农业用水供应、娱乐、底泥清除、碳固存等。美国目前的湿地地图源于上一代科学，而且有限，往往不准确，与其他类型的空间信息联系很差。该项目将整合湿地科学、计算、遥感和地理空间工具开发方面的进展，以预测湿地的位置和提供的服务。我们的总体目标是创建一个湿地工具包，提供公平获取最先进的湿地科学的机会；支持关于水、水管理和湿地政策的积极和公平的对话；并为知情和环境公正的决策提供必要的综合信息。在第一阶段，我们将1)收集和综合湿地工具包不同用户对优先用途和需求的意见，2)确定可用的数据和必要的计算资源，3)创建原型，4)制定公平交付和可持续商业模式的计划。在第二阶段，我们将开发和实施湿地工具包，在全国范围内广泛使用。湿地位置(即地图)构成了工具包的基础，而上层则以生态系统服务为特征，可适应不同的用户关切。该工具包将生成一个连续的(栅格)数据集，该数据集可以与不同空间、时间和光谱分辨率的其他连续空间显式数据层分层，例如湿地的水文重建、碳储量核算、生境特征、水储存、土著First Foods恢复优先顺序、保护和监管优先顺序、植被物候重建、长期监测等。最后的工具包将包括分析信息层(即连续栅格/像素)、离散(矢量/多边形)和报告(pdf和word文档)选项和格式，这些选项和格式将使技术熟练的研究人员和资源有限的从业人员都能使用。该项目还将利用人工智能和平台设计等新兴技术，以随时间推移改进工具包产出和模型的方式激励用户参与。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project will accelerate development of the a national-scale wetlands decision support tool for the United States. Wetlands sustain quality of life and provide nature-based solutions to climate change impacts and many other challenges, yet more than 50% have been lost in the United States and globally. Equitable and informed decisions about wetlands management, policy, conservation, and restoration require accurate maps and scientific capacity to consider the role of wetlands in relation to a wide range of societal concerns such as water quality, wildlife habitat, indigenous First Foods, water storage for drought mitigation or flood control, farm water provisioning, recreation, sediment removal, carbon sequestration, and more. Current maps of wetlands in the United States derive from an earlier generation of science and are limited, often inaccurate, and poorly linked to other kinds of spatial information. This project will integrate advances in wetland science, computing, remote sensing, and geospatial tool development to predict where wetlands are and the services they provide. Our overarching goal is to create a Wetland Toolkit that provides equitable access to state-of-the-art wetlands science; supports proactive and equitable conversations about water, water management, and wetlands policy; and provides the integrated information necessary for informed and environmentally just decision-making. In Phase 1 we will 1) gather and synthesize input on priority uses and needs from diverse users of the Wetland Toolkit, 2) identify available data and necessary computing resources, 3) create a prototype, and 4) develop plans for equitable delivery and a sustainable business model. In Phase 2 we will develop and implement the Wetland Toolkit for broad use at a national scale. Wetland locations (i.e. maps) form the foundation of the Toolkit, while upper layers characterize ecosystem services, adaptable to different user concerns. The Toolkit will generate a continuous (raster) dataset that can be layered with other continuous spatially explicit data layers at various spatial, temporal, and spectral resolutions, such as hydrologic reconstructions of wetlands, carbon stock accounting, habitat characterization, water storage, indigenous First Foods restoration prioritization, conservation and regulatory prioritization, vegetation phenological reconstruction, long-term monitoring, and more. The final toolkit will encompass both analytical information layers (i.e. continuous rasters/pixels), discrete (vectors/polygons), and reporting (pdf and word doc) options and formats that will make it accessible for users ranging from technically skilled researchers to practitioners with limited resources. This project also will draw upon emerging technologies such as artificial intelligence and platform designs that incentivize user participation in ways that improve the Toolkit outputs and models over time.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.