Improve the Science of Processes within the Cryosphere by Integrating Hydrological Modelling with Remote Sensing in a Multi-Level Data Fusion Approach - a Contribution to Cryosphere Monitoring in the EUREGIO Region
01.02.2016 - 31.01.2019
The cryosphere (here: snow, ice and glaciers) is the most important inter-seasonal water storage component in the Alps. Apart from direct observations, hydrological models are the most common approach to study cryospheric processes. However, particularly at larger scales (>10’000 km²), critical processes such as radiative transfer, snow albedo and the energy balance remain underdetermined due to missing spatially explicit data. Satellite remote sensing is a promising technology for generating spatially explicit information on snow for larger areas, but operational products are mostly limited to the detection of snow cover only.
In view of this, the central idea of CRYOMON-SciPro is to exploit the complementary character of physically based hydrological modelling and improved satellite remote sensing products for monitoring key processes within the cryosphere, by integrating both methods in an innovative approach (multi-level data fusion). The innovations expected to result from this project include:
- An improved representation and understanding of the spatial and temporal dimension of key processes within the cryosphere at larger scales
- A flexible data integration concept based on machine learning and pattern recognition techniques
- The integration of data from new and innovative field measurement techniques and satellite data (Sentinel 1 and 2).
CRYOMON-SciPro makes use of the EUREGIO region as a field laboratory for cryosphere research with well-instrumented test-sites, high data availability, good contact to authorities and climatological conditions, representative of different Alpine zones. The results of the project will thus have a scientific value that is well beyond the EUREGIO region.
The Institute for Applied Remote Sensing of EURAC is the lead partner of the project. Its main role is related to the development of innovative remote sensing products for a better understanding of the cryosphere and to the development of the machine learning methods to integrate remotely sensed products and hydrological simulation to derive parameters such as snow water equivalent, glacier mass balance and run-off.
The CRYOMON project supports the consolidation of our cryosphere related products.
Contact person: Claudia Notarnicola, Mattia Callegari