[en] Highlights: • Pathways to good drinking water quality in agricultural areas involve many actors. • Exploratory network analysis of stakeholders' knowledge and perception was conducted. • Hierarchy Index examined stakeholder's view on hierarchical or democratic structure. • Scenario testing highlighted pathways to good agriculture and environmental outcomes. • The methodology presented is parsimonious and globally relevant in similar subjects. Drinking water governance is challenging with different perceptions and priorities among stakeholders in different countries. To make provision for drinking water protection in agricultural areas, governance systems need to be mapped for bottlenecks to be identified and solutions highlighted. To address this a system thinking approach was used in an explanatory network analysis of Fuzzy Cognitive Maps (FCM) that were created during face to face interviews with stakeholder representative groups (individuals, policy developers, researchers, and regulators). Two exercises were designed and facilitated to obtain stakeholder maps on A) the water governance framework from stakeholders' own perspective with a ranking of actors in terms of their perceived importance and B) a list of importance factors and how these were connected for the provision of good drinking water quality supplies in agricultural areas. Causal relationships were subsequently drawn around each subject allowing mapping. A graph theory Hierarchy Index (h) approach examined if stakeholder groups preferred top down hierarchical governance or a more inclusive democratic governance approach. Finally, an auto-associative neural network method was deployed on group maps for examination during steady-state conditions for three scenarios to be explored i.e. changing “Farmers knowledge”, “best management practice (BMP) uptake” and “Farmers behaviour and belief” to the highest level of influence and seeing how the system reacted. Results of Exercise A showed that all stakeholder representative groups had a different perception of the water governance framework. Most stakeholder groups had a democratic point of view regarding water governance structures and the ranking and importance of the actors within the framework. Results of Exercise B demonstrated that most of the groups have similar opinions regarding the highest ranked factors affecting drinking water quality and the possible environmental ecological policy options. In this second exercise, only one representative group showed a democratic outlook whereas all others had a hierarchal outlook. Scenario testing of policy options enabled bottlenecks and possible solutions to be identified. By boosting “Farmers behaviour and belief” to the highest possible level, resulted in a large increase in other factors – a scenario where farmers could benefit from the outcome. This would be achieved by enhancing farmers' willingness and intention to participate and implement BMPs. Better results would be achieved if farmers believed in the method and could benefit from the outcome. Also keeping “Farmers knowledge” at the highest point had a positive influence on the other factors. This can be achieved by enhancing farmers training and knowledge transfer by local and national actors. This method is widely applicable and should be considered for more integrated and participatory approaches to drinking water governance.

[en] Highlights: • In reviewed catchments, it took 1–10 years for policies to have a measurable effect on water quality. • Positive mitigation effects on surface water quality took 4–20 years to measure. • Time lags explain why positive effects aren’t always evident within governance cycles. - Abstract: Measuring the environmental impacts of agricultural practice is critical for policy formulation and review, including policies implemented to improve water quality. Here, studies that measured such impacts in surface waters of hydrologically diverse meso-scale catchments (1–100 km²) were reviewed. Positive water quality effects were measured in 17 out of 25 reviewed studies. Successful farm practices included improved landscape engineering, improved crop management and reductions in farming intensity. Positive effects occurred from 1 to 10 years after the measures were implemented, with the response time broadly increasing with catchment size. However, it took from 4 to 20 years to confidently detect the effects. Policy makers and scientists should account for these hydrological and biogeochemical time lags when setting policy and planning monitoring in meso-scale catchments. To successfully measure policy effects, rates of practice change should also be measured with targeted water quality parameters.

[en] Highlights: • We measured overland, drainage and ground water flows and the associate soil nitrate, ammonium and phosphorus losses following the installation of drainage. • Drainage treatment deepened the water table and decreased the overland flow. • M and gravel GM drainage increased losses of nitrate-N and ammonium-N in drainage flow and also losses to ground water. • M and GM lowered total P losses -- Abstract: Mole (M) and gravel-mole (GM) drainage systems improve the permeability of soils with high clay contents. They collect and carry away infiltrating water during episodic rainfall events. Characterisation of nutrient fluxes (concentration and flows) in overland flow (OF) and in mole drain flow (MF) across sequential rainfall events is important for environmental assessment of such drainage systems. The objective of this study is to assess the impact of drainage systems on soil nutrient losses. Three treatments were imposed on grazed permanent grassland on a clay loam soil in Ireland (52°30′N, 08°12′W) slope 1.48%: undrained control (C), mole drainage (M) and gravel mole drainage (GM). Plots (100 m × 15 m) were arranged in a randomized complete block design with four replicated blocks. Nitrogen (N) and phosphorus (P) concentrations in OF, MF and groundwater (GW) were measured from each plot over 15 consecutive rainfall events. The results showed that M and GM (P < 0.05) deepened the watertable depth and decreased OF. M and GM increased losses of nitrate-N (22%) and ammonium-N (14%) in GW. Nitrate-N concentrations from all the flow pathways (mean and standard error (s.e.): 0.99 s.e. 0.10 mg L⁻¹) were well below the 11.3 mg L⁻¹ threshold for drinking water. Ammonium-N concentrations from all the flow pathways (mean: 0.64 s.e. 0.14 mg L⁻¹) exceeded drinking water quality standards. On the other hand M and GM lowered total P losses (mean annual losses from C, M and GM: 918, 755 and 853 s.e. 14.1 g ha⁻¹ year⁻¹) by enhancing soil P sorption. Hence M and GM can be implemented on farms under similar management to that described in the present study with a minor impact on N (increased concentration on averaged 18% to GW) and P (reduced by on avenged 114 g ha⁻¹ year⁻¹).

[en] Treated municipal sewage sludge (“biosolids”) and dairy cattle slurry (DCS) may be applied to agricultural land as an organic fertiliser. This study investigates losses of nutrients in runoff water (nitrogen (N) and phosphorus (P)), metals (copper (Cu), nickel (Ni), lead (Pb), zinc (Zn), cadmium (Cd), chromium (Cr)), and microbial indicators of pollution (total and faecal coliforms) arising from the land application of four types of treated biosolids and DCS to field micro-plots at three time intervals (24, 48, 360 h) after application. Losses from biosolids-amended plots or DCS-amended plots followed a general trend of highest losses occurring during the first rainfall event and reduced losses in the subsequent events. However, with the exception of total and faecal coliforms and some metals (Ni, Cu), the greatest losses were from the DCS-amended plots. For example, average losses over the three rainfall events for dissolved reactive phosphorus and ammonium-nitrogen from DCS-amended plots were 5 and 11.2 mg L"−"1, respectively, which were in excess of the losses from the biosolids plots. When compared with slurry treatments, for the parameters monitored biosolids generally do not pose a greater risk in terms of losses along the runoff pathway. This finding has important policy implications, as it shows that concern related to the reuse of biosolids as a soil fertiliser, mainly related to contaminant losses upon land application, may be unfounded. - Highlights: • This study investigated surface runoff of contaminants from biosolids in field plots. • Contaminants investigated were nutrients, metals, microbes and trace elements. • Compared to slurry, biosolids do not pose a greater risk of contaminant losses. • Fears concerning contaminant losses from land applied biosolids may be unfounded.