1. Work Package 2 From data theoretic to knowledge theoretic approaches to flood modelling Dr Nick Odoni and Professor Stuart Lane University of Durham

2. Work Package 2 aims To develop a Minimum Information Requirement model for flood risk –Focus on diffuse land management activities –Primarily using secondary data sets and new data where necessary To evaluate model performance –sensitivity and propagation of uncertainty –formal model assessment To simulate the effects of diffuse land management impacts on flood risk To undertake this work within the framework of Environmental Competency Groups (see Work Package 3)

3. Philosophy Odoni and Lane, in press, Progress in Physical Geography Experience Data TheoryModel-Theoretic Model-Data Knowledge- Theoretic Data-Theoretic

4. Making models ‘But then you don’t even have to have reservoirs as such. You could have a dam with a restricted outflow so it literally holds it back and releases it slowly…so the stream normally just runs straight through it and doesn’t get stopped…’ [Local member] ‘ And the other problem is that once you get down to Newtondale, you have got the railway there, which means you are causing problems at the railway, they are not going to be pleased about that.’ [Local member] ‘ So to protect Pickering, the nearer the dams are to Pickering the better?’ [Local member 1] ‘Well yes certainly’ [Local member 2] ‘the man has taken the flood banks down... and he’s put a bridge across the river at that point, and the bridge is an old articulated lorry body, which enables him to go backwards and forwards with his farm implements when he’s making silage, then the information that they would be able to collect from Ings Bridge would be useless…Because it wouldn’t be going through the gauge, it would be going over land.’ [Local member] Perceptualisation, conceptualisation, framing, of the problem What to try where Why things won’t work Why things (e.g. data) are wrong

5. The models Bunding –Pickering Assumes conditions of high Standard Percentage Runoff Identifies a critical flood onset –which becomes the target to which flows must be reduced Determines flow directions across the landscape using digital topographic data Applies a rainfall rate to those flow directions Routes the associated rainfall Produces a flow discharge rate at every point in the catchment Provides a simple interactive tool to place multiple holy bunds –enter their characteristics –assess the duration that they can store water for –in relation to preventing flows at Pickering reaching the critical flood onset Validation by comparison with ISIS-TUFLOW

6. The models Demonstration available, for Uckfield, during Conference Overflow Uckfield and Pickering Assumes conditions of high Standard Percentage Runoff Identifies a critical flood onset - which becomes the target to which flows must be reduced Determines flow directions across the landscape using digital topographic data Applies different rainfall rates to those flow directions Routes the associated rainfall for each rainfall rate Allows depth dependent routing rates Samples from routing rates according to event rainfall Integrated into time-dependent travel time maps, which are convolved with time- dependent rainfall rates, to provide time- varying flow discharge at every point in the catchment Development for uncertainty and scenario analysis in Pickering Interventions  Remeandering  Riparian vegetation  Debris dams  Channel reprofiling  Hedgerows  Woodland belts  Bunds

7. Bunding : a demonstration Files we prepared earlier –Pit filling –Flow routing (FD8 on hillslopes, D8 in channels) –Cut the catchment –Order the channel networks Our demonstration –Stage I Place the dams Calculate potential storage according to bund height –Stage II Test impacts on flood flow to identify how long Pickering (in this example) can be protected for at a given rain rate

8. Hybrid models Models as a form of ‘covering law’ – the model can ‘travel’ ‘Hybrid’ models: –the loss of the ‘generic’ rationale (but aren’t all models hybrid?) –the loss of technological lock-in: the models are forced to mutate The ‘peculiar’ model The specific case The calibrated model The generic model

9. Participating Institutions Funding Body http://knowledge-controversies.ouce.ox.ac.uk/