Flood Forecasting and Management of the Goldersbach
Although draining only an area of 75 km2 the Goldersbach caused severeflooding in the town of Tuebingen-Lustnau several times in the second half of thelast century. Because of local constrictions the city decided after severalfeasibility studies to set up a flood management system based on three columns:flood forecasting, partial storage in retention reservoirs and local protectivemeasures.
The goal was to develop a reliable operational flood-forecasting system, but dueto the small catchment size, the anticipated lead time of 3.5 hours could not beachieved by gauge observations only. The principal approach was then todevelop a weather radar-based, short-term rainfall forecasting system, valid forroughly 2 hours lead time, and to use its forecasts in combination with real-timeobservations in a rainfall-runoff model to gain the desired lead time.
A gauge system in the Goldersbach catchment was established, along with adata transmittal and storage system to retrieve and store measurements fromrain-gauges, river-gauges and a Doppler weather radar. In case of exceedingcertain rainfall and discharge threshold values based on synthetic rainfall timeseries, the local authorities are alarmed. Following a predefined alarm planpreparatory procedures are initiated and if necessary the retention reservoirsfilled and local protective measures implemented. The gauging system iscurrently optimized and the forecast system tested under operation. Theretention reservoirs are going to be planned next year.
As especially for short-term rainfall forecasting, knowledge of the current rainfieldadvection is crucial, two estimation techniques are applied: one based onthe Doppler effect, the other on covariance maximization. Based on theadvection estimates, a short-term, auto-regressive forecast model wasdeveloped. To combine the advantages of the available sources of rainfallobservation, namely radar and rain-gauges, a new method termed 'Merging' istested. It preserves both the mean rainfall field estimated by the rain-gauges andthe spatial variability of the radar image.
For short-term rainfall forecasting, a new model named 'SCM model', short for'Spectrum-Corrected Markov chain' is used. Based on radar data, it follows atwo-step hierarchical approach. A bi-variate, auto-regressive process isforecasting the large-scale development of rainfall in a radar image. Theindividual development of each grid-cell in the image is forecasted by a Markovchain approach.
Finally, two rainfall-runoff models are used for short-term flood forecasting. Thefirst, FGMOD/LARSIM, is an event-based model, the second, HBV-IWS, is acontinuous water balance model. Both rainfall-runoff models, in combination withthe rainfall forecast, allow reasonable discharge estimates for up to 3 hours.
- Project manager
- Research assistants
- Cooperation partners
Ingenieurbüro Pirker-Pfeiffer, Ingenieurbüro Ludwig, Radar-Gysi, Umeg GmbH