A Digital Twin for Drought Early Warning in the Alps

The Alps have been marked as the water tower of Europe for many decades because of their glacier-rich mountains, snowfields, and underground aquifers. Despite being protected from prolonged droughts due to its temperate climate and high elevation, in recent decades the Alpine region has faced several drought events. This situation primarily stems from shifting climate patterns that have resulted in a decline in water resources. Furthermore, climate projections indicate that rising water demand is expected in the future, resulting in greater susceptibility to drought in the region.

Traditionally, physically based hydrological models have been used to simulate the terrestrial water cycle and extreme events (flood and droughts) in the Alps. Nevertheless, these models require a substantial amount of data and require lengthy calibration procedures.

In accordance with the EU’s new policy on adapting to climate change, decision making should take place in view of uncertainty, and be based on the latest scientific knowledge. The use of cutting-edge digital technologies and climate services is integral to facilitating decision-making through digital transformation.

In the intertwin project, we aim to combine process-based hydrological models and machine learning methods for exploiting the potential of Earth Observation to improve the representation of surface processes and conditions in hydrological models. These methods are used to build a hydrological Digital Twin for the Alps supporting the implementation of a drought early warning and prediction system at river basin scale.

The prototype is developed and integrated into openEO as a user interface for researchers who can test the performance of a drought early warning system using a trained model and EO data. They can also contribute to further enhancing the trained model. The digital twin is also helpful for public authorities in the field of agriculture and river basin management to identify areas potentially affected by hydrological drought.

The application of the drought digital twin in this context is critical for improving risk assessment for past, present, and future climate change impacts on water availability in the and in areas which depend on Alpine water availability.