Reducing the effects of flooding and flood water contamination
Our researchers developed a flood modelling software, which was adopted by industry and government to assist with planning and reduce hazards to health and property.
Recent events have made us all aware of the devastating effects of flooding around the globe. Flood waters can pose a major risk to property, public health, and in extreme events can cause loss of life.
Research from the School of Engineering has improved flood and health risk modelling, which has helped government stakeholders and industry to plan flood resilience more effectively and reduce health risks associated directly with flooding.
Floodwater is sometimes contaminated with sewage, animal waste and other contaminants. If present, these contaminants contain harmful bacteria that presents a risk to health.
Our researchers have also helped to improve water quality in river and coastal basins using innovative modelling of the transport of faecal contamination brought about by flooding. Our new improved framework has assisted local authorities across the UK and changed regulatory authority processes within the Environment Agency.
Managing flood risks
To enable governments and emergency services to plan and respond effectively in the event of extreme floods, like flash floods and dam break type flows associated with convective storms, it is vital that predictions of floodwater accurately represent real-life flooding and bacterial transport.
Research from the Hydro-environmental Research Centre involved modelling floodwater accurately, to minimise flood and associated health risks. The research forms a key part of industry-leading software Flood Modeller, developed in collaboration with Jacobs Engineering, which is used by private and public organisations worldwide to forecast and counter flooding issues.
This software has become one of the flood modelling suites used by the Environment Agency, Natural Resources Wales and the Scottish Environment Protection Agency. It has been applied within over 500 operational modelling studies, including designing flood defences and mitigation plans across the UK.
Flood Modeller has registered over 25,000 users across the world since August 2013.
The Water Industry National Environment Programme
Research from the School of Engineering was used by the Environment Agency to develop the Water Industry National Environment Programme. This sets out the improvements and investigations that water companies must deliver by 2025 and requires changes to protect and improve over 6000km of UK waterways, 24 bathing sites, and 10 shellfish sites.
Reducing water contamination
Our researchers further refined their flood modelling tools by developing innovative methods and integrated catchment, riverine, and coastal models to enhance bathing water quality predictions. Through improved process representation of the transport and decay of faecal bacteria in fresh and saltwater basins, they were able to find strategies to reduce contaminant levels in river and coastal bathing waters.
Our researchers evaluated the role of faecal bacteria, such as E coli, using new process models based on extensive field data. This is thought to be the first time that such a comprehensive modelling study has been undertaken from catchments to coast in the UK. This work enabled our researchers to identify strategies to reduce water contamination, which directed multi-million infrastructure projects and defined national strategies for improving water quality.
- Kvočka, D. , Ahmadian, R. and Falconer, R. A. 2018. Predicting flood hazard indices in torrential or flashy river basins and catchments. Water Resources Management 32 (7), pp.2335-2352. (10.1007/s11269-018-1932-6)
- Ahmadian, R. , Falconer, R. A. and Wicks, J. 2018. Benchmarking of flood inundation extent using various dynamically linked one- and two-dimensional approaches. Journal of Flood Risk Management 11 (S1), pp.S314-S328. (10.1111/jfr3.12208)
- Huang, G. , Falconer, R. A. and Lin, B. 2017. Integrated hydro-bacterial modelling for predicting bathing water quality. Estuarine, Coastal and Shelf Science 188 , pp.145-155. (10.1016/j.ecss.2017.01.018)
- Whittaker, P. , Wilson, C. A. M. E. and Aberle, J. 2015. An improved Cauchy number approach for predicting the drag and reconfiguration of flexible vegetation. Advances in Water Resources 83 , pp.28-35. (10.1016/j.advwatres.2015.05.005)
- Huang, G. , Falconer, R. A. and Lin, B. 2015. Integrated river and Coastal flow, sediment and Escherichia coli modelling for bathing water quality. Water 7 (9), pp.4752-4777. (10.3390/w7094752)