Comparison of rainfall-runoff models for flood forecasting. Part 1: Literature review of models
Moore, R.J.; Bell, V.A.. 2001 Comparison of rainfall-runoff models for flood forecasting. Part 1: Literature review of models. Bristol, UK, Environment Agency, 94pp. (R&D Technical Report W241, CEH Project Number: C00260)Before downloading, please read NORA policies.
Choosing a rainfall-runoff model for use in flood forecasting is not a straightforward decision and indeed may involve the selection of more than one. The aim of this Part 1 report is to provide a literature review of models in order to furnish a basic understanding of the types of model available, highlighting their similarities and differences. A sub-set of those reviewed are selected for more detailed assessment using data from a range of catchments. The results of this model intercomparison are presented in the Part 2 report. Whilst there is a plethora of “brand name” models they involve a relatively small set of model functions which are configured in a variety of different ways. This is illustrated by the models reviewed here. The initial selection of models for review is guided by those already in use for flood forecasting in the UK. To this are added well-known models developed overseas and those with a distributed formulation. From this menu of models are selected the following eight models for intercomparison in Part 2: the Thames Catchment Model (TCM), the Midlands Catchment Runoff Model (MCRM), the Probability Distributed Moisture (PDM) model, the Isolated Event Model (IEM), the US National Weather Service Sacramento model, the Grid Model, the Transfer Function (TF) model and the Physically Realisable Transfer Function (PRTF) model. The first six are conceptual soil moisture accounting models, with the Grid Model having a distributed formulation, whilst the TF and PRTF are “black box” time-series models. Also selected for review in Part 1 are the Input-Storage-Output or ISO-function model and the NAM model, which are both conceptual approaches. An outline review of some newer, general approaches to forecasting are given which include neural network (NN), fuzzy rule-based and nearest neighbour methods. An important aspect of the use of rainfall-runoff models in a real-time forecasting environment is the ability to incorporate recent observations of flow in order to improve forecast performance. The available methods for forecast updating are reviewed with particular reference to state correction and error prediction techniques. The latter aim to adjust, for example, the water contents of conceptual stores in a model and are usually tailored for a specific model. In contrast, error prediction operates independently of the rainfall-runoff model structure by exploiting the dependence in model errors to predict future ones. Parameter adjustment techniques are considered separately in the context of the simple TF and PRTF models. The Part 1 report ends with an overview of the models reviewed. This includes consideration of the ease of use of different models in calibration and in an operational forecasting environment. In conclusion, the didactic rather than judgmental approach adopted in the review is justified. It is inherently dangerous to judge the efficacy of a model by the variety of functionality it supports or processes it purports to represent. The Part 2 report presents the results of the intercomparison of models across a range of catchments. These results provide an objective basis on which to make judgements concerning the choice of models. Guidelines on model choice are presented in terms of forecast accuracy for different types of catchment together with other factors, such as ease of calibration and operational use, considered only partially in this Part 1 report.
|Item Type:||Report (UNSPECIFIED)|
|Programmes:||CEH Programmes pre-2009 publications > Water|
|CEH Sections:||_ Hydrological Risks & Resources|
|Additional Information:||The recommended citation for this report is: Moore, R.J. and Bell, V.A. (2001) Comparison of rainfall-runoff models for flood forecasting. Part 1: Literature review of models. Environment Agency R&D Technical Report W241, Research Contractor: Institute of Hydrology, September 2001, Environment Agency, Bristol, UK, 94pp.|
|Additional Keywords:||Rainfall-runoff, Floods and flooding, Flood forecasting, Flood warning, Modelling (hydrological)|
|NORA Subject Terms:||Hydrology|
|Date made live:||23 Jun 2009 14:02|
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