Staff Profile

Having completed a PhD at Newcastle in 2020, I am working as a Research Associate in Hydrology in the School of Engineering. My PhD focused on developing a methodology for assessing flood risk from multiple sources (groundwater and surface water) and I am continuing this research in my current role within the PYRAMID project.

My work focusses on developing SHETRAN, a physically based, spatially distributed hydrological model, and increasing its capabilities through the development of supporting code (typically in the form of Python wrappers). This is funded by the PYRAMID project, aimed at developing new and innovative methods for assessing, visualising and exploring real time flood risk. My work aims to:

• Develop the 'hotstart' function for the SHETRAN model, which will allow modelling studies to assimilate real time data into simulations to increase their accuracy and to allow for real time updates as flood events occur.

• Assist with the development of automated calibration of the SHETRAN model against both river flows and groundwater levels. Such developments seek to facilitate national scale hydrological modelling.

• Develop methods for assimilating soil moisture datasets into SHETRAN.

• Update the existing national scale SHETRAN model to include costal catchments beyond the range of existing river gauges.

Throughout this work I also hope to develop the groundwater capabilities of the SHETRAN system, such as through the availability of groundwater catchments for modelling studies in permeable regions.

PYRAMID: Platform for dYnamic, hyper-resolution, near-real time flood Risk AssessMent Integrating repurposed and novel Data sources

• £1M NERC project led by Dr Elizabeth Lewis (PI: Prof Hayley Fowler)
• Current flood risk assessments are based on static models. In PYRAMID we are building a dynamic flood modelling and data system.
• It will be developed in conjunction with the Environment Agency, local authorities and community groups to ensure that it delivers relevant information for critical decision-making in near-real time
• The platform will have toolkits to make it easy for communities to incorporate their data, providing essential local information.
• A new flood component dataset will be created from novel and existing datastreams (such as old reports, flood asset registers, various types of satellite imagery, soil moisture, rainfall,  traffic and congestion. We can also monitor the condition of specific factors affecting flood risk, such as whether particular culverts are blocked or whether certain flood walls are in poor condition.)
• We will assimilate the new dataset into cutting-edge, physically-based hydrological and hydrodynamic models ​
• We will develop a web platform demonstrator to interrogate observations and model outputs, and visualise dynamic flood risk maps with (near) real-time updates. ​

• Smith B. A Methodology for Assessing Flood Risk from Multiple Sources [PhD Thesis]. Newcastle upon Tyne: School of Engineering, Newcastle University, 2020.