Operating effectively in the market requires a thorough planning of water harvesting for the next months.
“Will the reservoir capacity be sufficient to accommodate incoming water? Will I be subject to water stress?“
Addressing these questions is necessary to optimize the reservoir level and anticipate possible drought conditions.
Seasonal inflow forecast is the right way to answer these questions, with consequent optimization of water resources in the long-range.
Current prediction methods adopted by most water managers are based on a “past-to-future” approach, i.e. historical data are simply averaged and extrapolated to the future. Sometimes the snow water equivalent estimate is used to update the current prediction.
This approach is subject to several drawbacks:
Waterjade is the answer to the new climatic and technological challenges, because it adopts an innovative multiple modeling – multiple data approach. It leverages on data sources available in the hydro-meteorological sector, like satellite images, numerical weather predictions and in-situ observations. The obtained big data are feeding multiple modeling architecture, comprising physical models and machine learning, capable to follow the physical processes occurring in the catchment and adapt to the local configuration.
The results are: