The value of complementary data for physically consistent hydrological models in mountain regions

In the face of climate change and socio-economic developments, water scarcity is a tremendous challenge. In particular, a significant portion of the world’s population rely on water from cryospheric sources such as snow and/or glacier fed mountain rivers. However, the data coverage in mountain regions is often sparse, which substantially hampers the assessment of climate impacts on hydrological systems. Furthermore, the large impact of climate change on snow and glacier hydrology require physically sound hydrological models.

The gap between the growing need for sustainable water resources management, low data availability and uncertain hydrological projections calls for new approaches. To close this gap, a modular modelling framework was developed to foster the use of complementary data sets in hydrological models. The framework enables a flexible combination of remote sensing and in situ data for model calibration and validation providing a multi-model and multi-input ensemble. The additional consideration of data regarding snow covered area, snow water equivalent and soil moisture allows for physically meaningful representations of key hydrological processes, even in the absence of a dense network of meteorological stations and river discharge gauges.

Case studies in the European Alps (Inn and Adige/Etsch) and in Central Asia (Ala Archa and Karadarya) illustrate the high value of this approach for physically meaningful representations of the hydrological processes. Furthermore, a high impact of glacier retreat on future water availability was found for the highly glacierised basins of the Fagge river in the upper part of the Inn basin and the Ala Archa river.