Please note: The algorithm descriptions in English have been automatically translated. Errors may have been introduced in this process. For the original descriptions, go to the Dutch version of the Algorithm Register.
Discharge forecast model Roer
- Publication category
- Other algorithms
- Impact assessment
- Field not filled in.
- Status
- In use
General information
Theme
Begin date
Contact information
Link to publication website
Responsible use
Goal and impact
The purpose of the algorithm is to provide the most accurate forecast of the discharge of the Roer at Stah, so that WL can take timely measures to prevent flooding as much as possible.
Considerations
With conventional hydrological tools, it was difficult to arrive at a sufficiently accurate forecast because there are spillways between Jülich and Stah. These affect the surge through the Ruhr, but the way in which is difficult to model. By using machine learning, we have overcome this problem.
Human intervention
It is a decision support model. The content expert is responsible for interpreting the output and setting out actions if necessary.
Risk management
Software-wise via management and maintenance to keep code up to date, and where necessary re-train the model when sufficient, new data is available.
Operations
Data
Runoff measurements, precipitation measurements, precipitation projections, evaporation measurements
Links to data sources
- Neerslag: https://www.hetwaterschapshuis.nl/neerslag-weer-informatie-waterbeheer
- Verdamping: https://www.knmi.nl/kennis-en-datacentrum/uitleg/automatische-weerstations
- Afvoer: https://www.waterstandlimburg.nl/Home/Waterstanden
Technical design
It is a linear regression of some 500 (non-linear) features.
External provider
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