The Haltwhistle Burn catchment responds rapidly to rainfall, experiencing many flash flood events over recent years and like many small rural catchments in the UK, it does not benefit from any traditional flood defences, flood warning systems or monitoring stations. The Burn is subject to multiple pressures which are exacerbated during high flow, including water quality and sediment issues.

Enthusiastic ‘River Watch’ volunteers are sharing their catchment-related knowledge and regularly monitoring various catchment parameters in order to understand their water environment. Using training cards and several data collection, submission and visualisation tools, low-cost monitoring techniques are now being used successfully. Lengthy flood, rainfall, river level and water quality datasets are now available for this catchment and are shared online with the wider community. The quality of the observations are being compared to that of data collected using a traditional hydrometric monitoring network. This local information is also being used to improve the performance of catchment models, design runoff management plans and motivate the wider community to be involved in the catchment management process.

Other community groups in Northumberland are also adopting a similar approach within the 14km2 Red Burn Catchment, following Haltwhistle’s success. Although environmental citizen science and the co-production of knowledge is not a new phenomenon, evolving technology and communications provide timely and low-cost solutions to mass data collection whilst offering various social benefits.

This is a Newcastle University PhD project which has been part funded by Tyne Rivers Trust (through Defra’s CRF project) and NERC. It is focussing on data collection, data quality and use of citizen science data within a catchment context and is supporting Tyne Rivers Trust’s wider restoration project.

Follow Haltwhistle Burn on Twitter

Read the Report on Demonstrating the value of community-based (‘citizen science’) observations for catchment modelling and characterisation here.