Research

Enlarged view: Kandertal

Mountain regions are the water towers of the world because they are crucial for reliable and high-quality water supply. Thanks to their abundance in precipitation and snow and glacier storage, they can provide water to less water-rich lowland catchments. At the same time, mountain regions experience various types of extreme events including droughts, floods, or wildfires, which can negatively affect society, economy, and ecology. Both their water supply function and affectedness by extreme events are subject to global change. On the one hand, water resources and extremes are influenced by a warming climate. On the other hand, they are modulated by direct human intervention, e.g. through water regulations such as reservoir operation or water abstraction for irrigation and artificial snow production.

It is crucial to understand the effect of these influences on water availability and hydro-climatic extreme events in order to develop sustainable adaptation measures and management practices. Still, we lack an in-depth understanding of how global change affects water supply and extreme events such as extreme precipitation, droughts, floods, or wildfires. This knowledge gap is pronounced in mountain regions where observational networks are sparse and future changes in both climate and the water cycle are expected to be particularly strong. Therefore, the HYCLIMM research group develops methods to study the processes governing water availability and extreme events in mountain regions, estimate the frequency and magnitude of extreme events, and predict future changes in water availability and hydro-meteorological extremes in a warming world.

The group’s research focuses on three core areas:

  1. Understanding processes governing multivariate hydro-climatic extreme events.
  2. Assessing climate impacts on water and climate extremes in mountain regions with a particular focus on the Alps.
  3. Improving predictions of extreme events by exploiting new datasets and the latest methodological advances in statistics, data science, and climate modeling.

Ongoing research projects are listed external pagehere.

 

 

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