NSF Convergence Accelerator Track K: Spatially Resolved Solutions for Field to Regional Irrigation Water Management to Promote Equitable Sharing of Limited Water Resources

为了应对淡水短缺的紧迫挑战，特别是对脆弱社区的影响，“融合加速器”K轨道项目建议以加利福尼亚州中央山谷为重点，开发一个用户定制的灌溉用水管理决策支持中心。利用卫星遥感、天气预报和土壤/作物模型，该项目旨在综合土壤水分和作物需水量，以高空间分辨率为个体种植者提供日常灌溉建议。此外，该工具将为水区和监管机构提供汇总的作物用水需求和消耗数据，支持区域一级关于公平用水分配的决策。当拟议的工具被开发并分发给公众使用时，它将有助于缓解地下水枯竭，提高用水效率，降低灌溉成本，并有助于考虑到水资源公平、水资源可用性和环境限制的区域水资源分配。项目的技术目标包括涉众参与、概念模型开发、基于web的工具创建以及测试和评估。利益相关者将参与整个研究，为设计需求和评估分析做出贡献。该概念模型集成了创新的遥感产品、天气预报和用户输入，将指导基于网络的决策支持工具的开发。这项研究将涉及创建创新的遥感产品，例如基于卫星数据的近地表土壤湿度、根区土壤湿度和蒸散发的高分辨率（10米，每日）数据。该工具将产生农场一级的产出，包括灌溉咨询，以及区域一级的产出，包括总用水量和需求数据。该原型工具将在中央山谷的多个试点农场进行测试，包括不同的气候、作物类型和灌溉方法。这个测试阶段将包括安装传感器来测量土壤湿度和蒸散数据，以及监测作物生长条件和灌溉调度决策的田间活动。此外，还将进行经济分析，以评估种植者采用该工具的意愿，并量化其对灌溉效率和农业生产力的影响。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。

In response to the pressing challenge of freshwater scarcity, particularly impacting vulnerable communities, this Convergence Accelerator Track K Project proposes the development of a user-tailored irrigation water management decision-support hub, focusing on Central Valley, California. Utilizing satellite remote sensing, weather forecasts, and soil/crop models, the project aims to provide individual growers with daily irrigation advice at a high spatial resolution, integrating available soil water and crop water demand. Additionally, the tool will offer water districts and regulators aggregated crop water demand and consumption data, supporting regional-level decisions on equitable water allocation. When the proposed tool is developed and distributed for public use, it will help mitigate groundwater depletion, enhance water use efficiency, lower irrigation costs, and contribute to regional water allocations that take into account water equity, water resource availability, and environmental constraints. The project's technical goals encompass stakeholder engagement, conceptual model development, web-based tool creation, and testing and evaluation. Stakeholders will be engaged throughout the research, contributing to design requirements and evaluation analysis. The conceptual model, which integrates innovative remote sensing products, weather forecasts, and user inputs, will guide the development of a web-based decision-support tool. This research will involve creating innovative remote sensing products, such as high-resolution (10-m, daily) data for near-surface soil moisture, root-zone soil moisture, and evapotranspiration based on satellite data. The tool will produce farm-level outputs, including irrigation advice, and regional-level outputs including aggregated water consumption and demand data. The prototype tool will undergo testing on various pilot farms in Central Valley, encompassing diverse climates, crop types, and irrigation methods. This testing phase will include the installation of sensors to measure soil moisture and evapotranspiration data, as well as field campaigns to monitor crop growth conditions and irrigation scheduling decisions. Additionally, economic analysis will be conducted to assess growers' willingness to adopt the tool and quantify its impacts on irrigation efficiency and farm productivity.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.