Flood forecasting is the use of real-time precipitation and streamflow data in rainfall-runoff and streamflow routing models to forecast flow rates and water levels for periods ranging from a few hours to days ahead, depending on the size of the watershed or river basin.  Flood forecasting can also make use of forecasts of precipitation in an attempt to extend the lead-time available.
Sophisticated flood forecasting systems will also account for the effects of:
- flood plains and washlands;
- flood defences, including control-gates etc.;
- tidal effects near the sea, and sea-surges.
To accomplish this, the range of models required needs to include appropriate snowmelt models, and the types of streamflow models that work well for simple applications need the addition of hydrodynamic models.
Flood forecasting is an important component of flood warning, where the distinction between the two is that the outcome of flood forecasting is a set of forecast time-profiles of channel flows or river levels at various locations, while "flood warning" is the task of making use of these forecasts to make decisions about whether warnings of floods should be issued to the general public or whether previous warnings should be rescinded or retracted.
- [Application of self-organising maps and multi-layer perceptron-artificial neural networks for streamflow and water level forecasting in data-poor catchments: the case of the Lower Shire floodplain, Malawi. http://www.iwaponline.com/nh/up/nh2014168.htm]
- Delft-FEWS, state of the art system for flood forecasting and operational water management (most advanced system available, used on national scale in Europe and the USA)
- Decision tree to choose an uncertainty method for hydrological and hydraulic modelling, Choosing an uncertainty analysis for flood modelling.
- http://www.waterlog.info/software.htm, RainOff, a conceptual rainfall-runoff model using a nonlinear reservoir.
- hepex.org for the Hydrologic Ensemble Prediction EXperiment, an informal yet highly active group of researchers in the field of predictive hydrologic uncertainty.
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