ONEPlanet DTP - Legacy mine site risks to water treatment works in a changing climate (OP2141)

Abandoned mines are one of the most pervasive and widespread anthropogenic sources of freshwater pollution, due mainly to high metals and sulphate (SO4) concentrations. They enter surface waters as point and diffuse inputs. Previous research at NU has shown that direct ingress of groundwaters from deep coal mines can significantly increase metal and SO4 loads in rivers(1).
Climate change impacts, particularly hydrological extremes, has raised a major concern: risks to continuity of acceptable intake water quality to water treatment works (WTWs), particularly during low river flow conditions, and especially due to SO4. High SO4 in drinking water can have low level human health impacts and is not removed by conventional treatment technologies. Even episodic occurrence of high SO4 in WTW intake water could compromise water sector assets. The likelihood of that scenario will increase as hydrological extremes become more prevalent.
This project will investigate SO4 dynamics in rivers affected by abandoned mines, and will specifically explore: (1) drivers of observed seasonal variation in SO4 concentration in rivers (2) monitoring tools to allow cost-effective identification of SO4 (3) modelling of likely future trends in SO4 concentration due to climate change-driven hydrological extremes, and (4) possible strategies to mitigate potential risks to WTWs. Test catchments in NE England will be the focus of the field and lab work, but with outcomes that will be of relevance internationally.
The project will involve: (1) statistical analysis of historical water quality and flow data, (2) a synoptic mass balance approach(2) to flow and water quality monitoring in test catchments, (3) investigation of rapid techniques for SO4 detection, and / or proxies for SO4 concentration (4) hydrological modelling under climate change scenarios. Skills will be gained in water quality and flow monitoring techniques, constructing water balances, and hydrological modelling.
References: (1) Mayes W.M. et al., 2008, Environmental Pollution, 151(1), 165-175. (2) Jarvis, A.P. et al., 2019, Environmental Science & Technology, 53(2), 702-709.