Cross-sectoral Engagement for Agricultural Water Quality Improvement

Mary Ryan (ELP 2021) | Environmental Economics Research/ Rural Development Knowledge Transfer, Teagasc, Ireland

A novel approach to improving agricultural water quality in Ireland has seen the development of a collaborative multi-stakeholder approach. As recent Environmental Protection Agency water quality indicator reports show worrying downward trends, Local Authority Waters Programme (LAWPRO) Catchment Scientists are focusing on identifying issues in Priority Areas for Action (PAA). These areas then become the focus of community engagement from LAWPRO Community Water Officer. One of the most effective ways to communicate water quality issues is to show communities and farmers how to visually assess water quality in their local streams/rivers by ‘kick-sampling’ to assess the presence and abundance of ‘indicator species’ (tiny insects) that indicate the long term ecological water quality. Following this, farmers in PAAs are invited to receive advice on how to improve water quality on individual farms. This advice is provided by the Agricultural Sustainability Support Advisory Programme (ASSAP) which is funded by cross-sectoral stakeholders.

ASSAP advisers first engage with the broader community and groups of farmers to test local water quality and explain how water quality can be affected by farming, industrial, and domestic practices, before engaging individually with farmers. ASSAP advisers collect data on the farm and farmer before identifying issues and remedial measures with the farmers. The ASSAP programme also works in collaboration with the WaterMARKE research project in developing behavioural interventions to improve water quality and cross-categorizing farm-level risk of loss of nutrients and sediment to water with the measures prescribed in different environmental contexts, the likely barriers to implementation and the level of implementation of suggested measures. Although the programme is voluntary, early analyses are positive and show high rates of completion of proposed measures.