Cole, Steven J.

Mattingley, Paul S.

Moore, Robert J.

Robson, Alice J.

NERC Open Research Archive

Geophysical Research AbstractsVol. 16, EGU2014-15476-1, 2014EGU General Assembly 2014© Author(s) 2014. CC Attribution 3.0 License.Probabilistic flood forecasting for Rapid Response Catchments using acountrywide distributed hydrological model: experience from the UKSteven J Cole, Robert J Moore, Alice J Robson, and Paul S MattingleyCentre for Ecology & Hydrology, Wallingford, Oxon, OX10 8BB, UK (scole@ceh.ac.uk)Across Britain, floods in rapidly responding catchments are a major concern and regularly cause significantdamage (e.g. Boscastle 2004, Morpeth 2008, Cornwall 2010 and Comrie 2012). Typically these catchments have asmall area and are characterised by steep slopes and/or significant suburban/urban land-cover. The meteorologicaldrivers can be of convective origin or frontal with locally intense features (e.g. embedded convection or orographicenhancement); saturated catchments can amplify the flood response. Both rainfall and flood forecasting for RapidResponse Catchments (RRCs)are very challenging due to the often small-scale nature of the intense rainfall whichis of most concern, the small catchment areas, and the short catchment response times.Over the last 3 to 4 years, new countrywide Flood Forecasting Systems based on the Grid-to-Grid (G2G)distributed hydrological (rainfall-runoff and routing) model have been implemented across Britain for use by theFlood Forecasting Centre and Scottish Flood Forecasting Service. This has achieved a step-change in operationalcapability with forecasts of flooding several days ahead “everywhere” on a 1 km grid now possible. The modellingand forecasting approach underpins countrywide Flood Guidance Statements out to 5 days which are used byemergency response organisations for planning and preparedness.The initial focus of these systems has been to provide a countrywide overview of flood risk. However, re-cent research has explored the potential of the G2G approach to support more frequent and detailed alerts relevantto flood warning in RRCs. Integral to this activity is the use of emerging high-resolution (∼1.5km) rainfallforecast products, in deterministic and ensemble form. High spatial resolutions are required to capture some ofthe small-scale processes and intense rainfall features such as orographic enhancement and convective stormevolution. Even though a deterministic high-resolution numerical weather prediction (NWP) model can providerealistic looking rainfall forecasts, significant uncertainties remain in timing, location and whether a particularfeature develops or not. Generally the smaller the scale of the rainfall feature, the shorter the lead-time at whichthese uncertainties become important. Therefore ensembles are needed to provide uncertainty context for longerlead-time G2G flow forecasts, particularly for small-scale RRCs.A systematic assessment framework has been developed for exploring and understanding the utility ofG2G flood forecasts for RRCs. Firstly perfect knowledge of rainfall observations is assumed for past and futuretimes, so as not to confound the hydrological model analysis with errors from rainfall forecasts. Secondly anassessment is made of using deterministic rainfall forecasts (from NWP UKV) in a full emulation of real-timeG2G forecasts, and using foreknowledge of rainfall observations as a reference baseline. Finally use of rainfallforecast ensembles with G2G to produce probabilistic flood forecasts is considered, empploying a combinationof case-study and longer-term analyses. Blended Ensemble rainfall forecasts (combining radar ensemble nowcastand NWP rainfalls) are assessed in two forms: forecasts out to 24 hours updated 4 times a day, and nowcasts outto 7 hours updated every 15 minutes. Results from the assessment will be presented along with candidates for newoperational products and tools that can support flood warning for RRCs, taking account of the inherent uncertaintyin the forecasts.

Probabilistic flood forecasting for Rapid Response Catchments using a countrywide distributed hydrological model: experience from the UK

http://nora.nerc.ac.uk/507189/1/N507189AB.pdf

Probabilistic flood forecasting for Rapid Response Catchments using a countrywide distributed hydrological model: experience from the UK

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