NSF Convergence Accelerator Track K: Prototyping decision support and monitoring tools for equitable management of salt contamination of water supplies in tidal rivers
NSF Convergence Accelerator Track K: Prototyping decision support and monitoring tools for equitable management of salt contamination of water supplies in tidal rivers
批准号:
2344042
负责人:
Ming Li
金额:
$65.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2024
资助国家:
美国
项目状态:
已结题
起止时间:
2024-01-15 至 2024-12-31
中文摘要
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英文摘要
About 70% of the U.S. drinking water supply comes from surface waters, including tidal rivers, the tidal fresh region of estuaries. Drought and sea level rise, which lead to saltwater intrusion from the ocean, and changes in land-use, which lead to freshwater salinization, are putting this precious water resource at risk. This risk extends to water uses for thermoelectric power, irrigation, and industrial production. As yet, however, only the largest and wealthiest water users are able to prepare for increasing salinity. Many water users, like small or rural drinking water suppliers, do not have the necessary planning and technical capacity to prepare for these changes. This project proposes to develop and prototype decision support and monitoring tools for salinity management through co-production with water resource managers, under-resourced rural communities, and water suppliers. The proposed convergence research of innovative watershed–estuary models and decision support tools aligns with the grand challenge of ensuring access to clean water. This project is timely as the U.S. Congress recently passed the bipartisan Infrastructure Investment & Jobs Act, 10% of which is dedicated to renewing water infrastructure. A better decision support system for salinity management and coastal communities will be valuable for bolstering the resilience of water infrastructure and protecting public health.The researchers will develop a new coupled watershed–estuary model that simulates the transport and fate of major salt ions by leveraging recent advances in hydrological and estuarine modeling, using Chesapeake Bay and its tidal rivers as a pilot study site. The coupled model will then be used in combination with artificial intelligence algorithms, in a planning tool to identify management strategies and quantify the tradeoffs between competing needs for freshwater resources. This approach will also be used to search for long-term planning strategies in the form of adaptation pathways. Web and mobile decision support tools will be co-developed with stakeholders using a full software life cycle approach, focusing on the needs of rural communities and smaller water supplies. Prototyping of the salt monitoring tool will focus on developing relationships between conductivity and various salt ions in order to assess the associated impacts of salt contamination on water quality, water infrastructure, and public health.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.
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