Integrating Information Sources for Inland Waters - A New Global Framework for Lakes Modelling and Monitoring

Like islands, lakes are not only unique geographical features, but also ecological concepts on their own. Their exceptional variability has been studied numerous times, yet no unique framework capable of reproducing the wide range of lake dynamics observed in various regions of the World has been formulated. Increasingly facing external pressures, inland waters adaptation and changes have to be understood and monitored efficiently in order to provide timely, scientifically credible, and policy-relevant environmental information, to ultimately assist stakeholders in evidence-based decision-making and sustainable management. Such monitoring capabilities are of great importance for the management and surveillance of the necessary measures to prevent lakes deterioration, as stated by the EU Water Framework Directive, or the United Nations’ Post 2015 agenda. Those are only two among the numerous recent political actions aiming at sustainably securing the ecosystem services provided by lakes on a regional to global scale, using new approaches for water management tailored to local conditions. Over the last decades, various research communities addressed this problem using different information sources, such as in-situ measurements, remote sensing observations and mathematical models. The challenge of this thesis is to couple those information sources through adapted data assimilation algorithms. The coupling of those three data sources aims at providing a new, reliable, flexible, and global modelling framework for inland waters monitoring across Switzerland, Europe and possibly expanding to other lakes of the World. The development of this framework will consider both hydrodynamic and water quality models with one- and three-dimensional domains. Year-long in-situ campaigns will complement existing field data, including setups on permanent stations. Remote sensing products consist in the approved AVHRR surface temperature dataset and cutting-edge Sentinel-2 chlorophyll observations. In terms of system operations, the framework will be operated in real-time for several Swiss lakes, with short-term forecasting of hydrodynamic and water quality properties, available online, and open to the public. The impacts of such system are expected at public, governmental and scientific levels. For the latter, this project aims at contributing to advances in aquatic research by (i) identifying and studying mesoscale processes such as up- downwellings, horizontal distribution of ecological properties, and (ii) assessing the variability of lake responses to climate change, in terms of warming and ice cover.

Presented at:
Delft Software Days 2016, Delft, The Netherlands, November, 2016

 Record created 2017-03-14, last modified 2018-09-13

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