No abstract

Nature‐based approaches to flood risk management are increasing in popularity. Evidence for the effectiveness at the catchment scale of such spatially distributed upstream measures is inconclusive. However, it also remains an open question whether, under certain conditions, the individual impacts of a collection of flood mitigation interventions could combine to produce a detrimental effect on runoff response. A modelling framework is presented for evaluation of the impacts of hillslope and in‐channel natural flood management interventions. It couples an existing semidistributed hydrological model with a new, spatially explicit, hydraulic channel network routing model. The model is applied to assess a potential flood mitigation scheme in an agricultural catchment in North Yorkshire, United Kingdom, comprising various configurations of a single variety of in‐channel feature. The hydrological model is used to generate subsurface and surface fluxes for a flood event in 2012. The network routing model is then applied to evaluate the response to the addition of up to 59 features. Additional channel and floodplain storage of approximately 70,000 m3 is seen with a reduction of around 11% in peak discharge. Although this might be sufficient to reduce flooding in moderate events, it is inadequate to prevent flooding in the double‐peaked storm of the magnitude that caused damage within the catchment in 2012. Some strategies using features specific to this catchment are suggested in order to improve the attenuation that could be achieved by applying a nature‐based approach.

Natural flood management (NFM) has recently invigorated the hydrological community into redeploying its process understanding of hydrology and hydraulics to try to quantify the impacts of many distributed, 'nature-based' measures on the whole-catchment response. Advances in spatial data analysis, distributed hydrological modelling and fast numerical flow equation solvers mean that whole-catchment modelling including computationally intensive uncertainty analyses are now possible, although perhaps the community has not yet converged on the best overall parsimonious framework. To model the effects of tree-planting, we need to understand changes to wet canopy evaporation, surface roughness and infiltration rates; to model inline storage created by 'leaky barriers' or offline storage, we need accurate channel hydraulics to understand the changes to attenuation; to model the complex behaviour of the whole network of NFM measures, and the possibility of flood peak synchronisation effects, we need efficient realistic routing models, linked to key flow pathways that take into account the main physical processes in soils and the antecedent moisture conditions for a range of different rainfall events. This paper presents a new framework to achieve this, based on a cascade of the Dynamic Topmodel runoff generation model and the JFlow or HEC-RAS 2D hydraulic models, with an application to the Swindale Catchment in Cumbria, UK. We demonstrate the approach to quantify both the effectiveness of a relatively large 'runoff attenuation feature' in the landscape and the uncertainty in the calculation given model parameter uncertainty.

This paper builds on the ‘Flooding from Other Sources’ project (HA4a), funded as part of Defra's Making Space for Water strategy. The HA4a study concluded that flood risk mapping is feasible for many of the sources of flooding that were investigated, which are not currently covered by the Environment Agency Flood Map, using existing flow modelling and GIS tools. However, there are some major constraints in terms of the need to undertake extensive data collection to allow the generation of useful flood maps that are not dominated by modelling uncertainties. The project anticipated that different levels of data collection and modelling might be needed for different purposes, given the hierarchical nature of UK flood risk assessment and management in the United Kingdom under PPS25 and the EC Floods Directive. This paper compares and contrasts three different approaches to urban flood modelling using topographic analysis, blanket extreme rainfall and semi‐coupled sewer/overland routing. The UK summer floods 2007 have highlighted the pressing need for mapping the risk from urban flash flooding, and the Pitt Review has recommended that areas at high risk from surface waters should be urgently identified. This can be done now at some level of detail, and we can be guided as to what level, from our increasing knowledge of vulnerable populations, from records of historical flooding and by using some of the screening methods described herein.

Abstract. Enhanced hillslope storage is utilised in “natural” flood management in order to retain overland storm run-off and to reduce connectivity between fast surface flow pathways and the channel. Examples include excavated ponds, deepened or bunded accumulation areas, and gullies and ephemeral channels blocked with wooden barriers or debris dams. The performance of large, distributed networks of such measures is poorly understood. Extensive schemes can potentially retain large quantities of run-off, but there are indications that much of their effectiveness can be attributed to desynchronisation of sub-catchment flood waves. Inappropriately sited measures may therefore increase, rather than mitigate, flood risk. Fully distributed hydrodynamic models have been applied in limited studies but introduce significant computational complexity. The longer run times of such models also restrict their use for uncertainty estimation or evaluation of the many potential configurations and storm sequences that may influence the timings and magnitudes of flood waves. Here a simplified overland flow-routing module and semi-distributed representation of enhanced hillslope storage is developed. It is applied to the headwaters of a large rural catchment in Cumbria, UK, where the use of an extensive network of storage features is proposed as a flood mitigation strategy. The models were run within a Monte Carlo framework against data for a 2-month period of extreme flood events that caused significant damage in areas downstream. Acceptable realisations and likelihood weightings were identified using the GLUE uncertainty estimation framework. Behavioural realisations were rerun against the catchment model modified with the addition of the hillslope storage. Three different drainage rate parameters were applied across the network of hillslope storage. The study demonstrates that schemes comprising widely distributed hillslope storage can be modelled effectively within such a reduced complexity framework. It shows the importance of drainage rates from storage features while operating through a sequence of events. We discuss limitations in the simplified representation of overland flow-routing and representation and storage, and how this could be improved using experimental evidence. We suggest ways in which features could be grouped more strategically and thus improve the performance of such schemes.