Environmental Data Management

The Coal Authority generates large volumes of environmental data through the part of our business which manages the environmental legacy of mining across the UK. We operate over 75 mine water treatment schemes that remove contaminating metals from mine water prior to the treated water being discharged into a receiving watercourse. Schemes range from complex process engineering plants, through pumped wet wells and boreholes / mineshafts, to totally natural (passive) schemes without a power source. The majority of treatment schemes comprise of aeration cascades, settlement ponds and reed beds. All schemes are subject to regulatory consents and licenses.

We have an extensive monitoring network across the mine water treatment schemes monitoring scheme performance. A wider network of boreholes and sampling locations is used to monitor changes in ground water level (monitoring mine water recovery across coalfields) and water quality within mine workings and at untreated mine water discharges. The total number of monitoring locations is around 2,000 but this may rise to nearer 3,000 as new treatment schemes are built or treatment trials carried out. We are increasingly helping others with monitoring of other types of mines.

Environmental data is collected across the treatment schemes and monitoring network which includes; laboratory analysis of water and solids, onsite water quality measurements, hydrometry data including manual and logged stage and flow readings from weirs and spot flow gauging, telemetered process data (such as pump rates or electric metering), manual and logged water level and temperature measurements from boreholes or mine shafts, logged rainfall data, manual or logged gas data and solid samples of lagoon sludge. Most data types are collected as continually expanding time series. A small part of the overall data comprises geophysical surveys of boreholes and shafts.

The Coal Authority has a requirement for a single data storage system which will consolidate our environmental data sets, incorporate data processing, quality checking and editing tools (including recording of any automated, or manual data changes) and make the data more accessible for use across the business.