Previsico's Flood Forecasting Technology

State-of-the-art flood forecasting technology

Our state-of-the-art flood forecasting technology was developed following two decades of research and development at Loughborough University, together with key stakeholders including the Environment Agency and the UK Cabinet Office.

Our forecasting technology uses live modelling to produce actionable forecasts which enable people and organisations to proactively mitigate flood impacts. Uniquely, these forecasts are remodelled every 3 hours and updated using the very best weather data, in partnership with IBM’s Weather Company.

 This 2D flood simulation software uses high-quality topographic and hydrological data to produce fast and accurate representations of flow routing across flood plains including surface water, river, and coastal flooding. The model is broadly outlined in Yu and Lane (2006a,b).

 Further research that underpins the technology was published in internationally respected journals over two decades, including Nature Sustainability. These publications can be found below.

A selection of publications are listed here
  • Yin, J, Yu, D, Lin, N, Wilby, RL (2017) Evaluating the cascading impacts of sea level rise and coastal flooding on emergency response spatial accessibility in Lower Manhattan, New York City, Journal of Hydrology, 555, pp.648-658, ISSN: 0022-1694.
  • Yu, D., Yin, J., Wilby, R.L., Lane, S.N., Aerts, J.C., Lin, N., Liu, M., Yuan, H., Chen, J., Prudhomme, C. and Guan, M., 2020. Disruption of emergency response to vulnerable populations during floods. Nature Sustainability, 3(9), pp.728-736.
  • Coles, D, Yu, D, Wilby, RL, Green, D, Herring, Z (2017) Beyond ‘flood hotspots’: Modelling emergency service accessibility during flooding in York, UK, Journal of Hydrology, ISSN: 0022-1694.
  • Yu, D, Yin, J, Liu, M (2016) Validating city-scale surface water flood modelling using crowd-sourced data, Environmental Research Letters, ISSN: 1748-9326.
  • Yin, J, Lin, N, Yu, D (2016) Coupled modeling of storm surge and coastal inundation: a case study in New York City during Hurricane Sandy, Water Resources Research, ISSN: 1944-7973. DOI: 10.1002/2016WR019102.
  • Yin, J, Yu, D, Yin, Z, Liu, M, He, Q (2016) Evaluating the impact and risk of pluvial flash flood on intra-urban road net- work: A case study in the city center of Shanghai, China, Journal of Hydrology, 537, pp.138-145, ISSN: 0022-1694.
  • Yu, D and Coulthard, TJ (2015) Evaluating the importance of catchment hydrological parameters for urban surface water flood modelling using a simple hydro-inundation modelJournal of Hydrology, 524, pp.385-400, ISSN: 0022-1694.
  • Yu, D (2010) Parallelization of a two-dimensional flood inundation model based on domain decomposition, Environmental Modelling and Software, 25(8), pp.935-945, ISSN: 1364-8152. DOI: 10.1016/j.envsoft.2010.03.003.
  • Y Yu, D and Lane, SN (2006a) Urban fluvial flood modelling using a two-dimensional diffusion wave treatment, part 1: Mesh resolution effects, Hydrological Processes, 20(7), pp.1541-1565
  • Yu, D and Lane, SN (2006b) Urban fluvial flood modelling using a two-dimensional diffusion wave treatment, part 2: Development of a sub grid-scale treatment, Hydrological Processes, 20(7), pp.1567-1583
  • Yin, J, Yu, D, Yin, Z, Wang, J, Xu, S (2015) Modelling the anthropogenic impacts on fluvial flood risks in a coastal mega-city: A scenario-based case study in Shanghai, China. Landscape and Urban Planning, 136, pp.144-155.
  • Yin, J, Yu, D, Wilby, R (2016) Modelling the impact of land subsidence on urban pluvial flooding: A case study of downtown Shanghai, China, Science of the Total Environment, 544, pp.744-744.
  • Yin, J, Yu, D, Yin, Z, Liu, M, He, Q (2016) Evaluating the impact and risk of pluvial flash flood on intra-urban road net-work: A case study in the city centre of Shanghai, China, Journal of Hydrology, 537, pp.138-145.



For further reading and visit Prof Yu’s Google Scholar page or contact us at [email protected]


Our services are currently available across the whole of the UK and widely available across the USA. The service can be set up anywhere globally on request. Existing other coverage for the service includes regions in China, Indonesia, Thailand, Japan and Kenya.


Most flood impacts are avoidable with the right early warning systems. Our cutting-edge modelling technology predicts floods which are missed by traditional approaches. We work with insurers, businesses and governments to help mitigate the growing devastation caused by flooding by delivering actionable warnings, data and analytics to enable proactive measures to be taken.

For Insurers

Reduce flood losses and
improve customer support

For Government

Improve resilience and
event response

For Business

Reduce disruption
and losses

Get in Touch