The need of having accurate short and mid-term forecasting of the water flow generated from snowmelt in mountain basins is an important component for water management and hydropower activities in several areas at a global scale. Due to the remoteness and difficult access to basins especially in cold weather conditions, where in-situ snow measurements, water level monitoring and meteorological stations are scarce, flow model predictions are not easily implemented. In this context, empirical, statistical calibrated forecasting systems can give acceptable results only during seasons with meteorological conditions close to the climatological average. On the contrary, during those years when conditions depart significantly from the average, streamflow becomes unpredictable by those means. Precisely under these conditions, the smallest improvement in flow predictions, can have a tremendous positive economic impact for hydropower companies.
To overcome this limitation, a consortium led by Starlab, with partners FutureWater, Hispasat and PUC proposed INTOGENER, a system using Earth Observation data together with in situ measurements transmitted in near real time to drive a distributed hydrological model, capable of assimilating external measurements, to better estimate the water flow. The INTOGENER Service aims to deliver streamflow predictions at specific points of interest in remote mountainous areas: the service adapts the hydrological prediction to terrain operations by providing the exact information needed by hydropower companies in their day-to-day practices.
INTOGENER Demonstration (or Demo) project aims at implementing, based on user requirements, a demonstration service able to prove the viability and sustainability of INTOGENER Service, in pre-operational conditions. The Chilean Andes region has been selected as the first place to implement the INTOGENER Demo. This is an area where the limitations above mentioned are strong and where the water management system is highly complex due to the large number of mountain basins, volume of electricity generated, and number of companies involved.