Water quality in Canada: validation, interpretation, and mobilization of community-based water monitoring

虽然准确和相关的数据是淡水管理中基于证据的决策的基石，但在加拿大支离破碎的监测网络中，确保这些数据的准确性和相关性仍然是一项挑战。作出健全的管理决策需要广泛的利益攸关方之间的有效沟通和合作，包括学术界、政府和非政府组织以及当地社区团体的利益攸关方之间的有效沟通和合作，但他们之间往往缺乏协调和沟通。我们提议建立的联盟将有助于将目前在这个国家运营的这些不同的水管理人员联系起来。我们提议的研究将为社区提供一种简单的方式来众包水质数据，这将改变公民对水的理解，以及他们参与水管理的能力。Kerri Finlay博士(U Regina)、Water Rangers和加拿大环境与气候变化公司之间拟议的合作伙伴关系将旨在通过提高其对学者和政府官员的合法性和有效性来应对与可持续和有意义的CBWM相关的挑战。我们的目标是以萨斯喀彻温省为案例，为加拿大各地的水测试项目的长期可持续性奠定基础。萨斯喀彻温省是一个经常受到娱乐用水质量问题的省份。我们将专注于：(1)验证、改进能够实时提供结果的廉价工具并使其合法化；(2)建立人工智能工具，使用可获得的、负担得起的测试来帮助回答有关水质的重要问题；以及(3)实现社区主导的数据管理，让所有利益相关者(社区、非政府组织、政府和学术界)参与进来。

While accurate and relevant data are the cornerstone for evidence-based decision making in freshwater management, ensuring the accuracy and relevance of these data remains a challenge in Canada's fragmented monitoring networks. Making sound management decisions requires effective communication and collaboration among a wide range of stakeholders, including those from academia, governmental and non-governmental organizations, and local community groups, yet there is often little coordination and communication among them. The Alliance we propose to build will serve to connect these diverse water stewards presently operating in this country. Our proposed research will provide communities with a simple way to crowdsource water quality data that will transform citizens' understandings of their water, as well as their ability to participate in water stewardship. The proposed partnership between Dr. Kerri Finlay (U Regina), Water Rangers, and Environment and Climate Change Canada will aim to address challenges associated with sustainable and meaningful CBWM by improving its legitimacy and validity for academics and government officials. We aim to establish the basis for long-term sustainability in water testing programs across Canada, using Saskatchewan, a province with frequent recreational water quality concerns, as our case study. We will focus on: (1) validating, improving, and legitimizing inexpensive tools that can provide results in real-time; (2) building artificial intelligence tools that use accessible, affordable tests to help answer important questions about water quality; and (3) enabling community-led data management that engages all stakeholders (Community, Non-Governmental, Government, and Academic).