SCC-IRG Track 1: Overcoming Social and Technical Barriers for the Broad Adoption of Smart Stormwater Systems
SCC-IRG Track 1: Overcoming Social and Technical Barriers for the Broad Adoption of Smart Stormwater Systems
批准号:
1737432
负责人:
Branko Kerkez
金额:
$187.24万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2022-08-31
中文摘要
在自动驾驶汽车时代,自主技术在改善供水系统方面可以发挥什么作用?洪水是美国各地恶劣天气死亡的主要原因。此外,大量金属、营养物和其他污染物在风暴事件中被冲走,通过溪流和河流到达湖泊和沿海地区。 为了解决这些问题,美国大多数社区都维护专用基础设施(管道、池塘、盆地、湿地等),以在风暴事件期间输送和处理水。大部分雨水基础设施已接近其设计寿命,这将导致更多的洪水和水质恶化。 与其建造新的、更大的雨水基础设施(这对许多社区来说成本过高),不如更有效地利用现有基础设施。该提案的目标是实现下一代智能互联雨水系统,该系统使用传感器来预测天气和城市景观的变化,并使用主动流量控制(例如闸门、阀门、泵)来调整其运行。这将大大提高社区对洪水和水质的抵御能力。为雨水系统配备低成本传感器和控制器将提供一种经济高效的解决方案,将基础设施从静态转变为自适应,使其能够自动化并立即重新配置,以响应不断变化的社区需求和偏好。这项研究将解决真正的全国性基础设施挑战,并将为授权和教育社区采用智能和自主雨水解决方案奠定基础。启用“智能”雨水系统的研究将由工程师、社会科学家、计算机科学家和环境专家组成的团队与美国四个社区的决策者和公民密切合作进行。 该团队将弥补基础知识差距,以解释(1)实时控制在多大程度上可以改善单个雨水站点的水力和水质性能,(2)如何识别和克服公众认知对智能雨水系统采用造成的障碍,以及(3)如何实现系统级互操作性以保证整个社区(数百到数千个受控站点)规模的安全和有效性能。这将通过三个紧密结合的科学目标来实现,其中包括控制点实验室模型的测试、现场规模的水质研究、社区咨询小组的组建、每个社区的住宅调查分析以及系统级控制算法在各种不确定性来源下的稳定性分析。 因此,该方法从根本上是围绕可扩展性目标而展开的,因为结果将与美国各地的许多社区相关,无论其规模如何。通过在 Open-Storm.org 和其他公共论坛上开源,该项目还将通过减少其他人部署智能和互联雨水系统所需的开销来支持研究能力建设。
英文摘要
In the age of the self-driving car, what role can autonomous technologies play in improving water systems? Floods are the leading cause of severe weather fatalities across the United States. Furthermore, large quantities of metals, nutrients, and other pollutants are washed off during storm events, making their way via streams and rivers to lakes and costal zones. To contend with these concerns, most communities across the United States maintain dedicated infrastructure (pipes, ponds, basins, wetlands, etc.) to convey and treat water during storm events. Much of this stormwater infrastructure is approaching the end of its design life, which results in more flooding and degraded water quality. Instead of building new and bigger stormwater infrastructure, which is cost prohibitive for many communities, it is possible to use existing infrastructure more effectively. The goal of this proposal is to enable the next generation of smart and connected stormwater systems, which use sensors to anticipate changes in weather and the urban landscape, and adapt their operation using active flow controls (e.g., gates, valves, pumps). This will drastically improve community resilience to floods and water quality. Equipping stormwater systems with low-cost sensors and controllers will provide a cost-effective solution to transform infrastructure from static to adaptive, permitting it to be automated and instantly reconfigured to respond to changing community needs and preferences. This research will address a truly national-scale infrastructure challenge and will lay the foundation upon which to empower and educate communities to adopt smart and autonomous stormwater solutions.The research to enable "smart" stormwater systems will be conducted by a team of engineers, social scientists, computer scientist and environmental experts in tight collaboration with decision makers and citizens across four communities in the United States. The team will close fundamental knowledge gaps to explain (1) to what extent real-time control can improve the hydraulic and water quality performance of individual stormwater sites, (2) how to identify and overcome the barriers that public perception poses to the adoption of smart stormwater systems, and (3) how system-level interoperability can be achieved to guarantee safe and effective performance at the scale of entire communities (100s to 1000s of controlled sites). This will be achieved through three closely coupled scientific objectives, which will include testing of laboratory models of control sites, field-scale water quality studies, the formation of community advisory groups, the analysis of residential surveys in each community, and the stability analysis of system-level control algorithms under various sources of uncertainty. The approach is thus fundamentally motivated around the goal of scalability, as the results will be relevant to many communities across the United States, regardless of their size. By open-sourcing the efforts on Open-Storm.org and other public forums, the project will also support research capacity-building by reducing the overhead required by others to deploy smart and connected stormwater systems.
期刊论文(10)
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DOI:
10.1016/j.envsoft.2019.07.009
发表时间:
2019-10
期刊:
Environ. Model. Softw.
影响因子:
--
作者:
[J. Sadler;J. Goodall;Madhur Behl;Mohamed M. Morsy;T. Culver;Benjamin D. Bowes]
通讯作者:
J. Sadler;J. Goodall;Madhur Behl;Mohamed M. Morsy;T. Culver;Benjamin D. Bowes
Technology in support of nature-based solutions requires understanding everyday experiences
支持基于自然的解决方案的技术需要了解日常经验
DOI:
10.5751/es-12838-260435
发表时间:
2021
期刊:
Ecology and Society
影响因子:
4.1
作者:
[Li, Jiayang, Nassauer, Joan Iverson]
通讯作者:
Nassauer, Joan Iverson
DOI:
10.1016/j.advwatres.2020.103600
发表时间:
2020-06
期刊:
Advances in Water Resources
影响因子:
4.7
作者:
[Abhiram Mullapudi;Matthew J. Lewis;C. Gruden;B. Kerkez]
通讯作者:
Abhiram Mullapudi;Matthew J. Lewis;C. Gruden;B. Kerkez
Landscape elements affect public perception of nature-based solutions managed by smart systems
景观元素影响公众对智能系统管理的基于自然的解决方案的看法
DOI:
10.1016/j.landurbplan.2022.104355
发表时间:
2022
期刊:
Landscape and Urban Planning
影响因子:
9.1
作者:
[Li, Jiayang, Nassauer, Joan Iverson, Webster, Noah J.]
通讯作者:
Webster, Noah J.
StormReactor: An open-source Python package for the integrated modeling of urban water quality and water balance
StormReactor:用于城市水质和水平衡集成建模的开源Python包
DOI:
10.1016/j.envsoft.2021.105175
发表时间:
2021
期刊:
Environmental Modelling & Software
影响因子:
4.9
作者:
[Mason, Brooke E., Mullapudi, Abhiram, Kerkez, Branko]
通讯作者:
Kerkez, Branko
共 8 条
CIVIC-PG Track A: Smart Watersheds for Conservation and Resilience
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批准号:2228343
-
项目类别:Standard Grant
-
资助金额:$5.0万
-
财政年份:2022
-
负责人:Branko Kerkez
-
依托单位:
Collaborative Research: Reimagining Urban Watershed Management: A Systems Approach to Stormwater Control and Ecological Rehabilitation
-
批准号:2204893
-
项目类别:Standard Grant
-
资助金额:$10.0万
-
财政年份:2022
-
负责人:Branko Kerkez
-
依托单位:
CAREER: Toward a theory for smart stormwater systems
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批准号:1750744
-
项目类别:Continuing Grant
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资助金额:$50.0万
-
财政年份:2018
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负责人:Branko Kerkez
-
依托单位:
EAGER: I-Corps: Smart Water Systems
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批准号:1851362
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项目类别:Standard Grant
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资助金额:$5.0万
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财政年份:2018
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负责人:Branko Kerkez
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依托单位:
EarthCube Building Blocks: Collaborative Proposal: An Expanded Implementation of Cloud-Hosted Real-Time Data Services for the Geosciences (CHORDS)
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批准号:1639640
-
项目类别:Standard Grant
-
资助金额:$22.8万
-
财政年份:2016
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负责人:Branko Kerkez
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依托单位:
EarthCube Building Blocks: Collaborative Proposal: Cloud-Hosted Real-time Data Services for the Geosciences (CHORDS)
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批准号:1440116
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项目类别:Standard Grant
-
资助金额:$4.0万
-
财政年份:2014
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负责人:Branko Kerkez
-
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