Dr Alma Schellart
Senior Lecturer in Water Engineering
Department of Civil and Structural Engineering
Sir Frederick Mappin Building
Mappin Street, Sheffield, S1 3JD
Telephone: +44 (0) 114 222 5765
Fax: +44 (0) 114 222 5700
By aiming to understand water flow and quality throughout the whole catchment, and how uncertainty is introduced into numerical modelling, I can advise the water industry on how to better manage our existing sewer infrastructure, and make it more cost-effective and sustainable.
dr alma schellart
Alma studied her MSc degree in Civil Engineering specialising in Water Management at Delft University of Technology in the Netherlands. After completing her PhD on uncertainty in sewer sediment transport with us, she worked as a researcher here on uncertainty in integrated water quality modelling and the use of rainfall radar data. From 2011 to 2013 Alma lectured at the University of Bradford where she expanded her research on urban rainfall and started research on energy balance in the urban water cycle and heat recovery from urban drainage systems. She rejoined the Department in 2013.
Alma’s research focuses on improving our existing sewer systems and finding better ways to manage them as the global population grows. By using computer modelling, fieldwork and laboratory measurements she seeks to improve the numerical models used to manage sewer systems. She looks at water quality and quantity as both are vital for managing and monitoring for our existing systems.
Alma’s work in water quality explores uncertainty and involves predicting the amount of run-off and sediments that may enter our water systems. The pattern and amount of water which enters our sewer systems is expected to change significantly because of climate change and population growth. Alma aims to find solutions to make better use of our existing sewer infrastructure, which are more sustainable and cost-effective.
Alma has coordinated a large European project, looking into quantifying uncertainty in integrated catchment studies. This involved seven other universities and several commercial partners in their exploration of uncertainty in different models and data collection methods, in order to gain a bigger picture of simulating water flow and quality throughout the whole catchment.
Activities and Distinctions
- Coordinator of Marie-Curie Initial Training Network on Quantifying Uncertainty in Integrated Catchment Studies – 2014 to 2018
- Co -Investigator on CENTAUR H2020 project: https://www.sheffield.ac.uk/centaur - 2015 - 2018
- Co-Investigator on TWENTY65 - https://twenty65.ac.uk/ - 2016 - 2021
- Member of IWA Working Group in Data and Models, and IWA working group Sewer Processes and Networks
- Rico-Ramirez MA, Liguori S & Schellart ANA (2015) Quantifying radar-rainfall uncertainties in urban drainage flow modelling. Journal of Hydrology, 528, 17-28.
- Schellart AN, Liguori S, Kraemer S, Saul A & Rico-Ramirez M (2014) Comparing quantitative precipitation forecast methods for prediction of sewer flows in a small urban area. Hydrological Sciences Journal, 59(7).
- Schellart ANA, Shepherd WJ & Saul AJ (2012) Influence of rainfall estimation error and spatial variability on sewer flow prediction at a small urban scale. Advances in Water Resources, 45, 65-75.
- Liguori S, Rico-Ramirez MA, Schellart ANA & Saul AJ (2012) Using probabilistic radar rainfall nowcasts and NWP forecasts for flow prediction in urban catchments. Atmospheric Research, 103, 80-95.
- Schellart ANA, Tait SJ & Ashley RM (2010) Estimation of uncertainty in long-term sewer sediment predictions using a response database. Journal of Hydraulic Engineering, 136(7), 403-411.
- Schellart ANA, Tait SJ & Ashley RM (2010) Towards quantification of uncertainty in predicting water quality failures in integrated catchment model studies. Water Research, 44(13), 3893-3904.
- Schellart A, Veldkamp R, Klootwijk M, Clemens F, Tait S, Ashley R & Howes C (2005) Detailed observation and measurement of sewer sediment erosion under aerobic and anaerobic conditions. Water Science and Technology, 52(3), 137-146.