HR Wallingford is leading a consortium to use space-data to develop a system called DAMSAT that can help improve the monitoring of tailings dams. Aimed primarily at regulators responsible for monitoring many tailings sites over a large area, this system will help improve transparency within the sector. It could also provide vital extra time to deal with a potentially risky situation.
Funded by the UK Space Agency’s International Partnership Programme, we are using meteorological forecasts coupled with hydrological models to try to predict the impacts of rainfall on the reservoirs and the embankment structures. By exploiting Global Navigation Satellite System (GNSS) data with base stations, we can gather accurate movement data for key points on a structure, and by using Interferometric Synthetic-Aperture Radar (InSAR) data we can monitor movement over wide areas to give warning of landslides or slips. Optical satellite data sets will allow us to monitor indicators of pollutants that may leak from a tailings dam. All of this data will be gathered and analysed in a secure cloud-based system provided by project partner Siemens, and pre-modelled dam-breach flood scenario data can be stored here for use by emergency planners to call upon in the event of an emergency.
The DAMSAT project runs from April 2018 to October 2020 and the team is making good progress. Work is funded by the UK Space Agency’s International Partnership Programme, and the international collaboration includes Telespazio VEGA, Siemens Corporate Technology, Satellite Application Catapult, Oxford Policy Management, and the Smith School of Enterprise and the Environment at Oxford University. Partners in Peru are Ciemam SAC, the National Foundation for Hydraulic Engineering (Peru), and the National University of Cajamarca: School of Hydraulic Engineering and Faculty of Engineering.
The UK Space Agency’s International Partnership Programme (IPP ) is a five-year, £152 million programme designed to partner UK space expertise with overseas governments and organisations. It is funded from the Department of Business, Energy and Industrial Strategy’s Global Challenges Research Fund (GCRF).