Water depths during the Sheffield Flood of 1864. Information adapted from: Machan, Peter. 'The Dramatic Story of The Sheffield Flood?' 1999 ISBN 1-901587-05-3. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2010-07-01 and migrated to Edinburgh DataShare on 2017-02-21.

Locations and descriptions of damage which occurred during the Sheffield Flood of 1864. Information adapted from: Machan, Peter. 'The Dramatic Story of The Sheffield Flood?' 1999 ISBN 1-901587-05-3. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2010-07-06 and migrated to Edinburgh DataShare on 2017-02-21.

Locations and details of victims whose deaths occurred during the Sheffield Flood of 1864. Information adapted from: Machan, Peter. 'The Dramatic Story of The Sheffield Flood?' 1999 ISBN 1-901587-05-3. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2010-07-06 and migrated to Edinburgh DataShare on 2017-02-21.

This dataset shows Sheffield City Council Strategic Flood Risk Assessment Zone 3ai / 3b. It was produced for Sheffield City Council by JE Jacobs in 2008 and shows areas subject to flooding up to (and including) once in every 20 years on average.

A map showing locations of structures affected by Alternatives A1, D, and E of the Pearl River Federal Flood Risk Management Project

This dataset concerns recovery after major floods in the UK 2007 and Germany 2013. It contains two sheets. The first sheet contains data from a survey of residents and local businesses in Catcliffe, between Sheffield and Rotherham in South Yorkshire and in Dreiflüsse-Eck, the "Three Rivers Corner" in Passau in Bavaria conducted in late 2018 and early 2019. The second sheet conatisn data from a survey with flood experts in the UK and Germany.

The two events were comparable in terms of impacts, levels of preparedness and government response and show similar patterns of speed and quality of recovery. The two case study areas are similar in size and were amongst places most badly hit in each country. Both floods were considered to be "game-changers" and resulted in a heightened awareness of flood risk, increased investment in flood defences and an increasing emphasis on citizens taking more responsibility for flood preparedness.

This dataset contains results from testing carried out at a laboratory facility at the University of Sheffield (UK) as part of the CENTAUR project. CENTAUR is an EC funded Horizon 2020 Innovation Action. The project has developed a system to reduce flood risk in urban areas by utilising existing available storage capacity in urban drainage networks through the use of a gate installed in an existing manhole. The gate is controlled by Fuzzy Logic, using data from level sensors.

The laboratory facility is described in the paper 'Demonstrating a Fuzzy Logic algorithm for real-time flow control in a full-scale laboratory environment' which is currently under review with the Urban Water Journal (https://www.tandfonline.com/toc/nurw20/current). Further details of the sensors and logging system are provided in 'Data_File_Column_Descriptions.csv'.

The file 'Test_Record.csv' describes all tests carried out. This dataset contains 83 csv data files in for days when good data was collected, these are zipped into 'DataFiles.zip'. Each csv file within the .zip contains the test results for one day, the files are named with the date of testing in the format yymmdd. The csv data files do not include column headers, but a full description of the data in each column is provided in 'Data_File_Column_Descriptions.csv'. The csv files contain data from all sensors, but the time period of the data from each sensor (or sensor set) and timesteps are not the same, hence for each sensor / sensor set there is a separate time column. The sampling interval for the level sensors is given in column 26 of 'Test_Record.csv', this will be correct for the test period, but outside the tests the interval was often increased and this may be seen in the data files. The gate / FCD sampling interval is the same as the Fuzzy Logic interval in column 27 of 'Test_Record.csv', although the position is only reported when the gate / FCD is active - i.e. not fully open. At the end of a test the FCD will return to the fully open position (100%), but this final datapoint is not recorded. The flow rate and downstream valve position sampling interval are given in column 12 of 'Test_Record.csv'.

Test numbers and fuzzy logic version ids are simplified for the journal paper 'Demonstrating a Fuzzy Logic algorithm for real-time flow control in a full-scale laboratory environment' which is currently under review with the Urban Water Journal. A correlation between the information in the paper and in 'Test_Record.csv' can be found in 'Paper_Test_Numbers.csv'.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 641931.