NFMtool
Demonstration of innovative implementation of data science tools for evaluation of climate change mitigation by Natural Flood Management
Sept 2016 to Mar 2017
Flooding within 2007 stimulated agencies of the UK and regional governments to implement so called Natural Flood Management (NFM) measures as an additional strategy for the cost-effective mitigation of flooding (e.g., Flood and Water Management Act, 2010; POST, 2011; SEPA, 2016). This strategy is part of a desire to increase the resilience of UK communities and infrastructure to extreme rainfall events with future climate change (Defra, 2016). NFM schemes include planting trees to enhance infiltration on slopes or when overbank flows have occurred; longer retention of water on floodplains to reduce peak-flows; changes to agricultural practices to enhance infiltration; adding small detention basins on slopes; and enhancing channel storage using leaky dams. Surprisingly, these schemes are being implemented nationwide before a scientifically-acceptable level of experimental evidence indicates that they will be effective in mitigating floods. Our established research quantifying the effects of trees on flood behaviour and related ecosystem services, in both tropical and temperate environments (e.g., Chappell et al., 2006, 2007; Chappell and Thang, 2007; Chandler and Chappell, 2008; Van Dijk et al., 2009; Wohl et al., 2012), has demonstrated the beneficial effects of trees to flood mitigation in certain circumstances, but equally has highlighted the lack of experimental evidence appropriate for the UK context. As a result, it is not known if NFM schemes can be effective at mitigating the incidence of flooding in UK catchments.
It is our belief that cross-disciplinary implementation of novel data science tools, such as those developed by systems engineers at Lancaster (in LEC and Department of Engineering: Taylor et al., 1997; Chappell and Tych, 2012; Jones et al., 2014; Chappell et al., 2017), should be an essential part of assessing the value of NFM measures to flood mitigation in a UK context. The effectiveness of NFM measures should be assessed with the same rigor as flood mitigation methods based upon hard engineering structures. Consequently, this pilot study will involve new alliances between researchers in LEC, Engineering and Computing, and strengthen ties with those organisations external to the university with an ongoing interest in natural flood management (notably JBA Consulting, Woodland Trust, Rivers Trust).
Funding sources
EPSRC institutional sponsorship grant (EAA7743)
Investigators
Nick A Chappell (PI), Ethan Wallace, Wlodek Tych, Trevor Page, Peter Metcalfe, and Ruth Alcock with external partners Barry Hankin (JBA), Ian Craigen (JBA), Pete Leeson (Woodland Trust), Rivers Trust (David Johnson), Eden Rivers Trust (Daniel Brazier), Jodie Mills (West Cumbria Rivers Trust).
Project Publications (ongoing)
Chappell, N.A., 2017. NFMtool: Demonstration of innovative implementation of data science tools for evaluation of Natural Flood Management. Final report. 8pp.