NERC-NSFGEO SMARTWATER: Diagnosing controls of pollution hot spots and hot moments and their impact on catchment water quality

河流水污染的地球边界正面临被打破的危险，对人类和环境健康、经济繁荣和水安全造成危险后果。当前的环境管理范式是基于对平均条件的理解。然而，我们知道环境污染在空间和时间上有很大的差异。这个跨学科的大型基金（与非学术合作伙伴共同创建，并作为NERC-NSF合作）将在实验分析、数据科学和数学建模方面开拓创新，以对不断变化的水世界中多污染物污染热点（空间）和热点时刻（时间）的动态驱动因素产生新的机械理解。诊断这些地点和时期对大规模和长期河流流域水质的影响，对于为当地和全球河流污染适应和缓解战略提供信息，并制定干预措施，以保持在安全（或）“操作空间”内，并为人类和环境改善水质至关重要。因此，SMARTWATER将环境传感、网络和数据科学创新、数学建模与利益相关者的流域知识相结合，以改变我们诊断、理解、预测和管理水污染热点和热点时刻的方式。我们将:1。率先应用可扩展的现场诊断技术进行水质传感和采样，以识别和表征新兴（例如废水指标，药品，农药）和遗留（例如营养物质）污染物的多污染热点和热点时刻。2 .将高分辨率代理水质指标网络与多变量无人机船载纵向河网采样相结合，开发流域尺度的智能水质监测网络解决方案，了解流域污染热点和热点时刻的足迹、传播和持续。开发和应用整合深度机器学习和人工智能方法的数据科学创新，用于污染源归因，识别污染源激活、连通性和河网运输和转化如何导致多污染动态的热点和热点时刻。展示新一代智能污染数据的效用，以提高综合流域尺度水质模型的能力，以充分呈现和预测污染热点和热点时刻的出现，包括它们的大规模足迹和与集水区水污染的长期相关性。与我们的利益相关者社区共同创造途径，成功实施水质管理实践中的实践和政策相关变革，并利用我们广泛的利益相关者基础的跨学科和跨部门专业知识，为SMARTWATER的知识生成和传播管道提供信息。smartwater将开发的机械过程理解、综合技术和管理解决方案，将使水污染的诊断、预测和管理发生重大变化，并改变人们在快速变化的环境中理解和应对日益复杂的污染压力的能力。

Planetary boundaries of river water pollution are at risk of being breached, with dangerous consequences for human andenvironmental health, economic prosperity, and water security. The current paradigm for environmental management ispredicated on understanding of average conditions. However, we know environmental pollution ca vary markedly in spaceand time. This interdisciplinary Large Grant (co-created with non-academic partners and as NERC-NSF collaboration) willpioneer innovations in experimental analytics, data science and mathematical modelling to yield new mechanisticunderstanding of the dynamic drivers of multi-contaminant pollution hotspots (spaces) and hot moments (times) in achanging water world.The diagnosis of the impact of these locations and periods when average pollution conditions are far exceeded on largescale and long-term river basin water quality is critical to inform local and global adaptation and mitigation strategies forriver pollution and develop interventions to keep within a safe(r) 'operating space' and improve water quality for people andthe environment. SMARTWATER will therefore integrate environmental sensing, network and data science innovations,and mathematical modelling with stakeholders' catchment knowledge to transform the way we diagnose, understand,predict, and manage water pollution hotspots and hot moments.We will:1. Pioneer the application of scalable field diagnostic technologies for water quality sensing and sampling for identifyingand characterising multi-pollution hotspots and hot moments for emerging (e.g., wastewater indicators, pharmaceuticals,pesticides) and legacy (e.g., nutrients) contaminants.2. Develop smart water quality monitoring network solutions at river basin scale based on integrating high-resolutionnetworks of proxy water pollution indicators with multivariate UAV boat-based longitudinal river network sampling tounderstand the footprint, propagation and persistence of pollution hotspots and hot moments in river basins.3. Develop and apply data science innovations integrating deep machine learning and artificial intelligence approaches forpollution source attribution and to identify how hotspots and hot moments of multi-pollutions dynamics results from pollutionsource activation, connectivity and river network transport and transformation.4. Demonstrate the utility of the new generation of smart pollution data to improve the capacity of integrated river basinscale water quality models to adequately present and predict the emergence of pollution hotspots and hot momentsincluding their large-scale footprint and longer-term relevance for catchment water pollution.5. Co-create with our stakeholder community pathways for successfully implementing practical and policy relevant changesin water quality management practice and use the interdisciplinary and inter-sectoral expertise of our broad stakeholderbase to inform knowledge generation and dissemination pipelines in SMARTWATER.The mechanistic process understanding and integrated technological and management solutions that will be developed inSMARTWATER will allow a step change in the diagnostics, prediction and management of water pollution and transformour ability to understand and tackle pollution pressures of increasing complexity in a rapidly changing environment.