Department Systems Analysis, Integrated Assessment and Modelling

Systems Analysis, Integrated Assessment and Modelling

In SIAM, we develop and apply models and formal techniques in order to understand, demonstrate, and predict the behavior of natural, technical, social and economical systems that pertain to water and other natural resources. Read more

New Publications

Prieto, C., Kavetski, D., Le Vine, N., Álvarez, C., & Medina, R. (2021). Identification of dominant hydrological mechanisms using Bayesian inference, multiple statistical hypothesis testing, and flexible models. Water Resources Research, 57(8), e2020WR028338 (32 pp.). doi:10.1029/2020WR028338, Institutional Repository
Fenicia, F., & Kavetski, D. (2021). Behind every robust result is a robust method: perspectives from a case study and publication process in hydrological modelling. Hydrological Processes, 35(8), e14266 (9 pp.). doi:10.1002/hyp.14266, Institutional Repository
Zhao, D., Liu, J., Yang, H., Sun, L., & Varis, O. (2021). Socioeconomic drivers of provincial-level changes in the blue and green water footprints in China. Resources, Conservation and Recycling, 175, 105834 (15 pp.). doi:10.1016/j.resconrec.2021.105834, Institutional Repository
Merz, E., Kozakiewicz, T., Reyes, M., Ebi, C., Isles, P., Baity-Jesi, M., … Pomati, F. (2021). Underwater dual-magnification imaging for automated lake plankton monitoring. Water Research, 203, 117524 (12 pp.). doi:10.1016/j.watres.2021.117524, Institutional Repository
Caradima, B., Scheidegger, A., Brodersen, J., & Schuwirth, N. (2021). Bridging mechanistic conceptual models and statistical species distribution models of riverine fish. Ecological Modelling, 457, 109680 (15 pp.). doi:10.1016/j.ecolmodel.2021.109680, Institutional Repository

News

Eschelisbach Thurgau (Photo: Esther Michel, Eawag)
August 12, 2021 –

Decisions in water management are often associated with large uncertainties. Quantifying and communicating these uncertainties is crucial for science to support transparent decision-making in society.

Decisions in water management are often associated with large uncertainties. Quantifying and communicating these uncertainties is crucial for science to support transparent decision-making in society.

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Events

15.09.​2022,
9.00 am
Swiss Tech Convention Center Lausanne

Projects

Bridging the gap between data science and mechanistic modelling to gain knowledge about community assembly
Heterogeneous data platform for operational modeling and forecasting of Swiss lakes in collaboration with the Swiss Data Science Center.
Deep Neural Networks (DNNs) have shown empirical performance but they are still nevertheless a black-box function modeling data
Scalable Bayesian inference framework for uncertainty quantification in stochastic models using thousands of processors in parallel at the Swiss Supercomputing Center and ETH Zurich.
Mechanistic modelling of the macroinvertebrate community composition in rivers.
We compare invasions in aquatic and terrestrial ecosystems primarily at large (national) spatial scales and among several higher-level taxa (insects, molluscs, crustaceans, all major vertebrate classes, and plants).
We use machine learning methods to predict the effects of chemicals on aquatic species.
Development of a semi-distributed hydrological model with a “flexible” approach. Testing and comparing of different model structures to combine modeling and experimenting into a learning process.