Integrating Inland and Coastal Water Quality Data for Actionable Knowledge.

Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making.

Meteolakes: An operational online three-dimensional forecasting platform for lake hydrodynamics.

Environmental management depends on high-quality monitoring and its meaningful interpretation. The combination of local weather dynamics, regional anthropogenic stresses and global environmental changes make the evaluation of monitoring information in dynamic freshwater systems a challenging task. While the lake ecosystems gather many complex biogeochemical interactions, they remain constrained by the same physical environment of mixing and transport. It is therefore crucial to obtain high-quality physical system insight. Three-dimensional hydrodynamic models are perfectly suited for providing such information. However, these models are complex to implement, and their use is often limited to modellers. Here, we aim to provide model output via a user-friendly platform to a broad audience ranging from scientists to public and governmental stakeholders. We present a unified approach merging the apparently diverse interests through meteolakes.ch, an online platform openly disseminating lake observations and three-dimensional numerical simulations in near real-time with short-term forecasts and data assimilation. Meteolakes is scalable to a broad range of devices, modular and distributed, hence allowing its expansion to other regions and hardware infrastructures. Since 2016, the platform has continuously provided timely synoptic lake information to more than 250,000 users. This web-based system was built not only to provide guidance to scientists in the design and analysis of field experiments and to foster interdisciplinary lake studies, but also to assist governmental agencies and professionals in the long-term policy and planning of water resources management. Finally, our system aimed at promoting awareness and understanding of the complexity of lakes and providing information to the public through user-friendly interfaces. This article details the design and operation of such a platform and its products. Applications are demonstrated by examples of a recent upwelling and a storm event. Both cases illustrate how Meteolakes help scientists in their quest for process understanding as well as water professionals and civil society in providing specific warnings.