Environmental Modelling

Environmental models translate our understanding of the processes controlling the environment into a system of mathematical relationships and support decision-making in the field of environmental management. They have proven to be particularly valuable in regions where observations do not exist as well as in making predictions of future conditions in times of climate change.

Our working group engages in the development and application of process models to answer research questions at the human-environment-interface. While the development of physical descriptions of hydrological processes makes up for the largest part of our model-related work, extending the models by a human dimension in order to account for human-environment interaction is becoming a part of our research of growing importance. With respect to the models developed and applied, we are working with model solutions developed within our group (e.g., the CliMap-R Remapping Tool), as well as with well-established, open-source community models (e.g., the WRF-Hydro model). The model solutions developed and applied range from physically-based water balance models and energy balance snow models to model coupling and downscaling/regionalization tools.

Downscaling and regionalization

Model development

Model validation

Model application

Model intercomparison

Scenario simulations

In the framework of the Earth System Model-Snow Model Intercomparison Project (ESM-SnowMIP) we are contributing snow simulations generated with the Fortran version of the physically based energy balance snow model ESCIMO.spread (v2) to a larger ensemble of snow simulations in order to support the quantification of snow-related feedbacks in the Earth system and improve future generations of Earth System Models. Furthermore, the provided simulations built a solid data basis to analyze climate change impacts on snow conditions at various sites all over the world, covering a wide range of different settings from alpine to arctic and boreal to maritime conditions.

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ACWR is a research group associated to the University of Innsbruck