Identifying critical source areas (CSAs) of diffuse pollution in agricultural catchments requires the accurate identification of hydrologically sensitive areas (HSAs) at highest propensity for generating surface runoff and transporting pollutants. A new GIS-based HSA Index is presented that improves the identification of HSAs at the sub-field scale by accounting for microtopographic controls. The Index is based on high resolution LiDAR data and a soil topographic index (STI) and also considers the hydrological disconnection of overland flow via topographic impediment from flow sinks. The HSA Index was applied to four intensive agricultural catchments (~7.5-12km(2)) with contrasting topography and soil types, and validated using rainfall-quickflow measurements during saturated winter storm events in 2009-2014. Total flow sink volume capacities ranged from 8298 to 59,584m(3) and caused 8.5-24.2% of overland-flow-generating-areas and 16.8-33.4% of catchment areas to become hydrologically disconnected from the open drainage channel network. HSA maps identified 'breakthrough points' and 'delivery points' along surface runoff pathways as vulnerable points where diffuse pollutants could be transported between fields or delivered to the open drainage network, respectively. Using these as proposed locations for targeting mitigation measures such as riparian buffer strips reduced potential costs compared to blanket implementation within an example agri-environment scheme by 66% and 91% over 1 and 5years respectively, which included LiDAR DEM acquisition costs. The HSA Index can be used as a hydrologically realistic transport component within a fully evolved sub-field scale CSA model, and can also be used to guide the implementation of 'treatment-train' mitigation strategies concurrent with sustainable agricultural intensification.

The removal efficiency of carbon (C) and nitrogen (N) in constructed wetlands (CWs) is very inconsistent and frequently does not reveal whether the removal processes are due to physical attenuation or whether the different species have been transformed to other reactive forms. Previous research on nutrient removal in CWs did not consider the dynamics of pollution swapping (the increase of one pollutant as a result of a measure introduced to reduce a different pollutant) driven by transformational processes within and around the system. This paper aims to address this knowledge gap by reviewing the biogeochemical dynamics and fate of C and N in CWs and their potential impact on the environment, and by presenting novel ways in which these knowledge gaps may be eliminated. Nutrient removal in CWs varies with the type of CW, vegetation, climate, season, geographical region, and management practices. Horizontal flow CWs tend to have good nitrate (NO₃⁻) removal, as they provide good conditions for denitrification, but cannot remove ammonium (NH₄⁺) due to limited ability to nitrify NH₄⁺. Vertical flow CWs have good NH₄⁺ removal, but their denitrification ability is low. Surface flow CWs decrease nitrous oxide (N₂O) emissions but increase methane (CH₄) emissions; subsurface flow CWs increase N₂O and carbon dioxide (CO₂) emissions, but decrease CH₄ emissions. Mixed species of vegetation perform better than monocultures in increasing C and N removal and decreasing greenhouse gas (GHG) emissions, but empirical evidence is still scarce. Lower hydraulic loadings with higher hydraulic retention times enhance nutrient removal, but more empirical evidence is required to determine an optimum design. A conceptual model highlighting the current state of knowledge is presented and experimental work that should be undertaken to address knowledge gaps across CWs, vegetation and wastewater types, hydraulic loading rates and regimes, and retention times, is suggested. We recommend that further research on process-based C and N removal and on the balancing of end products into reactive and benign forms is critical to the assessment of the environmental performance of CWs.

Groundwater contamination was characterised using a methodology which combines shallow groundwater geochemistry data from 17 piezometers over a 2 yr period in a statistical framework and hydrogeological techniques. Nitrate-N (NO3-N) contaminant mass flux was calculated across three control planes (rows of piezometers) in six isolated plots. Results showed natural attenuation occurs on site although the method does not directly differentiate between dilution and denitrification. It was further investigated whether NO3-N concentration in shallow groundwater (<5 m below ground level) generated from an agricultural point source on a 4.2 ha site on a beef farm in SE Ireland could be predicted from saturated hydraulic conductivity (Ksat) measurements, ground elevation (m Above Ordnance Datum), elevation of groundwater sampling (screen opening interval) (m AOD) and distance from a dirty water point pollution source. Tobit regression, using a background concentration threshold of 2.6 mg NO3-N L(-1) showed, when assessed individually in a step wise procedure, Ksat was significantly related to groundwater NO3-N concentration. Distance of the point dirty water pollution source becomes significant when included with Ksat in the model. The model relationships show areas with higher Ksat values have less time for denitrification to occur, whereas lower Ksat values allow denitrification to occur. Areas with higher permeability transport greater NO3-N fluxes to ground and surface waters. When the distribution of Cl- was examined by the model, Ksat and ground elevation had the most explanatory power but Ksat was not significant pointing to dilution having an effect. Areas with low NO3 concentration and unaffected Cl- concentration points to denitrification, low NO3 concentration and low Cl- chloride concentration points to dilution and combining these findings allows areas of denitrification and dilution to be inferred. The effect of denitrification is further supported as mean groundwater NO3-N was significantly (P<0.05) related to groundwater N2/Ar ratio, redox potential (Eh), dissolved O2 and N2 and was close to being significant with N2O (P=0.08). Calculating contaminant mass flux across more than one control plane is a useful tool to monitor natural attenuation. This tool allows the identification of hot spot areas where intervention other than natural attenuation may be needed to protect receptors.

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.