SCC-IRG Track 1: Connecting coastal communities with continuous, sensor-based monitoring of water quality

沿海社区面临着在多个地方监测水质的巨大挑战，而且监测频率要高到足以发现水质问题，并记录在改善水质的项目或基础设施投资后的改善情况。传统的水质监测是通过定期采集物理水质样本进行的。然而，导致大的水质和生物影响的条件（如热浪期间的低氧期或随后的高河流流量期）很少发生，并且不能被现有的定期采样的监测程序很好地捕获。这使得市民很难记录问题，管理者也很难确定适当的水质行动。新的连续记录水质传感器现在有可能部署在多个地点，提供时间序列和信息，以更好地识别水质影响和潜在的解决方案。溶解氧是一个关键的水质参数，现在可以用可靠、低成本的传感器来测量。然而，向基于传感器的连续监测过渡是复杂的，需要同时改变进行监测的机构、规范和社会实践，以及公众和监管机构使用这种新形式水质数据的方式。该项目将确定志愿公民科学家对使用现场记录传感器而不是抓取样本的反应，并测试志愿者对部署和与传感器交互的不同程序的反应。该项目还将测试用于在沿海水域部署传感器的低成本移动平台。它将重点关注与马萨诸塞州巴兹兹湾流域水质有关的三个社区：(1)居住在沿海流域的当地居民，包括许多自愿收集水样的人；（二）负责水质规划和管理的镇官员；(3)负责制定和执行水质法规的国家官员。它将决定传感器部署的哪种组合和规模产生的数据最有可能被居民、城镇官员和政府监管机构使用和采取行动。它还将提供关于不同社区如何解释和理解来自传感器的更详细的水质数据与来自传统抓取样本的数据的知识。了解这一转变——无论是技术上还是社会上——将有助于推动美国许多组织对水和环境传感器的使用，这些组织进行环境监测，并可能在未来部署自动化的连续环境传感器。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。

Coastal communities face large challenges monitoring water quality in multiple places and frequently enough to identify water quality problems and to document improvements following investments in programs or infrastructure that improve water quality. Traditional water quality monitoring is conducted by periodic collection of physical water quality samples. However, conditions that lead to large water quality and biological impacts (such as periods of low oxygen during heat waves or following periods of high river discharge) occur infrequently and are not well captured by existing monitoring programs that sample only periodically. This makes it hard for citizens to document problems and for managers to identify appropriate water quality actions. New continuously-recording water quality sensors now have the potential be deployed across multiple locations to provide time-series and information to better identify water quality impacts and potential solutions. Dissolved oxygen is a key water quality parameter that can now be measured with reliable, low-cost sensors. However, the transition to continuous sensor-based monitoring is complex and will require concurrent changes to the institutions that conduct monitoring, their norms and social practices, and the way the public and regulatory agencies use this new form of water quality data. This project will determine how volunteer citizen scientists respond to use of in situ recording sensors rather than grab samples, and test how volunteers respond to different procedures for deploying and interacting with sensors. The project will also test low-cost mobile platforms for deploying sensors in coastal waters. It will focus on three communities connected to water quality in the watershed of Buzzards Bay, Massachusetts: (1) local residents who live within coastal watersheds, including many who volunteer to collect water samples; (2) town officials responsible for water quality planning and regulation; and (3) state officials responsible for setting and enforcing water quality regulations. It will determine which combinations and scales for sensor deployment produce data most likely to be used and acted upon by residents, town officials, and government regulators. It will also provide knowledge on how different communities interpret and make sense of more detailed water quality data derived from sensors compared with data from traditional grab samples. Understanding this transition—both technologically and socially—will help advance the use of water and environmental sensors by the many organizations across the U.S. that conduct environmental monitoring and that might in the future deploy automated continuous environmental sensors.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.