Researchers in the WaterMARKE project have investigated how the complementary use of research and knowledge exchange can achieve greater uptake of farm level water quality mitigation measures to ultimately secure an improvement in water quality as required by the Water Framework Directive.

The WaterMARKE project was funded by the Environmental Protection Agency (EPA) and the Department of Agriculture, Food and the Marine (DAFM) and involved economic, psychology and scientific researchers from Teagasc and the University of Galway.

Agricultural activities can impact water quality when nutrients, sediments and pesticides leave the soil and enter waterways. Nutrients such as nitrogen (nitrates) can leach downwards through light soils into groundwater, while phosphorus and sediment can be lost through overland flow on heavy/peat soils. In terms of mitigation, the biological mechanisms of nutrient and sediment loss into water are complex and site specific, making them difficult to overcome.

According to Dr Mary Ryan (Teagasc), WaterMARKE Project Coordinator, a key element of the project involved the researchers working closely with the Agricultural Sustainability Support and Advisory Programme (ASSAP) to investigate how farmers and advisors engage with water quality improvement measures.

Noel Meehan, Head of Teagasc Water Quality Knowledge Transfer Department commented; “WaterMARKE identified behavioural drivers and barriers for farmers in adopting water quality protection actions. The project also identified obstacles encountered by advisory services in providing advice and support to farmers in adopting these measures. The research shows that advisors also need training and upskilling in the provision of water quality advice, something that the Better Farming for Water Campaign is working to achieve with both Teagasc and private advisors”. Noel added that WaterMARKE findings can now be used to develop policies and supports for both farmers and advisors that incorporate behavioural drivers, to ensure the use of appropriate farming practices and mitigation actions that lead to positive water quality outcomes.

Dr Ryan highlighted the considerable growth in collaboration and innovation across all agencies, communities and farmers in actively engaging in water quality improvement. This is exemplified by the level of participation across all actors in initiatives such as the Farming for Water European Innovation Programme (EIP) - see graphic below.

Professor Cathal O’Donoghue from University of Galway, stressed the importance of adopting such ‘system-wide’ efforts in fostering meaningful change. He also noted that ‘all the ‘actors’ across government departments, researchers, Co-operatives, advisors, farmers and farming organisations need to continue to think differently and allocate time for reflexive thinking to allow for wider participation, along with the further development of trust and innovation across the innovation system’.

Key WaterMARKE findings include:

1. Local Data and Understanding: Improving local environmental issues require localised activity data and an understanding of nutrient loss pathways. This involves local information from programs like the Local Authority Waters Programme (LAWPRO) and the EPA Catchments Unit, combined with research and knowledge exchange to implement the ‘right measure, right place, right time’ approach.
2. Collaboration Effectiveness: The research highlights the growth in collaborations across all the ‘actors’ who can influence water quality. See for example, how the Local Authority Water Programme (LAWPRO), the Agricultural Sustainability Support and Advisory Programme (ASSAP) and local farmers tackled bathing water quality issues at Lough Ennell, Co. Westmeath). https://www.youtube.com/watch?v=r7Uo2lBzAZQ
3. Farmer Motivation and Support: While farmers are generally motivated to improve water quality, they need support in terms of knowledge and resources. Key drivers of behaviour change include the role of advisors in raising awareness and the importance of localised support.
4. Barriers and Challenges: Farmers and advisors face knowledge and technical challenges, as well as administrative burdens that carry compliance and psychological costs. Interviews show that advisors require enhanced supports to prioritise pro-environmental water quality advice. The research also highlighted the crucial role of trust in successful knowledge interventions and collaborations.
5. Behavioural Drivers: Farmers with strong behavioural drivers to adopt specific measures are those who are aware of a measure, believe they have the capacity to undertake it, believe others would approve, and live in areas where others have implemented the measure. Other factors that lead to greater adoption include large farm size, previous participation in agri-environmental schemes, having a point source pollution issue, engagement with advisors, and agricultural education.
6. Acceptance of Measures: Farmers are more accepting of measures that incur less cost and have a more immediate visible effect, such as drainage ditch remediation. Collective knowledge exchange interventions, like discussion groups led by local ‘champion’ farmers and facilitated by advisors, in locations where measures farmers are already being implemented can help to generate further adoption.
7. Cost and Incentives: The cost of implementing measures is often a negative driver. Measures with high implementation or transaction costs need to be differentially incentivised. The study provided evidence-based research that contributed to the justification for the Farming for Water European Innovation Partnership (EIP) collaborative project, which compensates farmers for measure implementation when the private cost is high, but the social/environmental benefit is also high.
8. Spatial Modelling: Spatial modelling highlights variation in place and farm-specific implementation costs, which must be considered when assessing appropriate measures for individual farms. Farms with high opportunity costs for loss of land/productivity may be less likely to engage with mitigation measures.
9. Generalised Behavioural Model: Socio-economic research shows that it is feasible to use a behavioural model that uses attributes of measures to generalise across individual measures, reducing the need to collect survey data on farmers' behavioural preferences across the full range of measures.

See the full WaterMARKE end of project report at https://www.epa.ie/publications/research/water/research-482-mitigating-agricultural-impacts-on-water-quality-through-research-and-knowledge-exchange.php

The support of ASSAP programme staff and advisors, and the participation of farmer and adviser interviewees are gratefully acknowledged.

Ends.