3D hydrodynamic and bio-physical models with data assimilation – an application for Swiss Lakes

Session: Improving Model Predictions Through Coupled System and Data Assimilation (2)

Theo Baracchini, Ecole Polytechnique Federale de Lausanne (EPFL), [email protected]
Philip Chu, NOAA/GLERL, [email protected]
Damien Bouffard, EPFL, ENAC IIE APHYS, [email protected]
Alfred Wüest, Physics of Aquatic Systems Laboratory, EPFL Lausanne, Switzerland, [email protected]

Abstract

The importance of spatial and temporal heterogeneity in the distribution of lake trophic levels is now largely recognised. Understanding its dynamic is crucial to provide scientifically credible information for ecosystem management. Over the last decades, various research communities addressed this problem using different information sources, such as in-situ measurements, remote sensing observations and numerical simulations. The goal is to couple those data sources through adapted parameterization and data assimilation algorithms. This coupling approach implies mutual feedback mechanisms among those three information sources; model simulations are improved through the assimilation of in-situ measurements and remotely sensed products, remote sensing image processing is improved through parametrization with in-situ measurements and forecasts of hydrodynamic and biological models. Finally, in-situ measurements achieve a better representativeness when carried out along instantaneous gradients known from remotely sensed products and model simulation. An online platform, meteolakes.ch, is developed for monitoring and forecasting the bio-physical state of Swiss lakes. Meteolakes is a web/Android-application that disseminates 3D coupled hydrodynamic-biological model forecasts out to 4.5 days for several Swiss lakes using real-time atmospheric, rivers and WWTPs data. This integrated data-model system also aims at assisting stakeholders in evidence-based decision-making and towards the sustainable management of our lakes.