# Integrating Inland and Coastal Water Quality Data for Actionable Knowledge
## 1 Introduction  
Considered the most valuable natural resource, water is essential to human life and the health of the environment. Accurate monitoring and forecasting of the quality of inland waters, defined here as lakes, reservoirs, estuaries, and coastal marine waters, is fundamental for developing sustainable water resource management strategies and ensuring the health of communities, ecosystems, and economies [1]. Yet, our knowledge of water quality is often disconnected in time and space across various measurement techniques and platforms that may fail to capture dynamic ecosystem changes. This disconnection represents an inefficiency and redundancy in research and monitoring activities. A major challenge for water resource management is how to integrate multiple sources of water quality data and indices into usable information of economic, social, infrastructural, environmental, or administrative value [2]. In addition, realizing the full application potential of emerging technologies requires solutions for merging various measurement techniques and platforms into useful information for actionable management decisions, requiring effective communication between data providers and water resource managers [3]. The Group on Earth Observations (GEO) AquaWatch is a community of practice that aims to develop and build the global capacity and utility of water quality data, products, and information to support water resources management and decision making. GEO AquaWatch targets a wide range of stakeholders, from economists to scientists, to industry representatives, resource managers, nongovernmental groups, and policy makers at the local, regional and national levels ([[https://www.geoaquwatch.org/](https://www.geoaquwatch.org/)]([https://www.geoaquwatch.org/](https://www.geoaquwatch.org/)), accessed on July 2021). Integration of inland and coastal water quality data products are required for the successful implementation of the United Nations 2030 Sustainable Development Goals (SDG) and the Sendai Framework for Disaster Risk Reduction. Water quality monitoring is relevant toward SDG 6.3 to improve water quality by reducing pollution, eliminating dumping and minimizing release of hazardous chemicals and materials; SDG 6.6 to protect and restore water-related ecosystems; SDG 14.1 to prevent and significantly reduce marine pollution of all kinds; and for disaster risk reduction water quality monitoring and forecasting is critical for the development and assessment of safe water and sanitation systems. Here, we provide a conceptual approach developed through GEO AquaWatch for integrating data products to create water quality nowcasts (very short time forecast) and forecasts. Some of the main challenges in water quality data integration are discussed in Section 2. Integrated data products are derived from data assimilation of observations collected over various scales in space and time and from a range of platforms, discussed in Section 3. These data (Figure 1) include in situ discrete samples, from professional and citizen science/volunteer (or, community) monitoring programs, automatic in situ sensors, satellite, drone, or aircraft remote sensing, and model outputs. The actual integration process is addressed with a recommendation for a framework to take forward, discussed in Section 4. Beyond water quality data integration, translating this information to actionable knowledge and linking to stakeholder needs requires an iterative approach. GEO AquaWatch has developed such an approach based on an iterative development model used in the climate science community [4; 5; 6]. Briefly, the iterative development model enables research agendas to be created and modified by both scientists and stakeholders [5].