Detecting pollutant sources and pathways: High-frequency automated online monitoring in a small rural French/German transborder catchment.

Great temporal and spatial variability of inputs make comprehensive monitoring in small and middle sized rivers difficult. In this study, relevant inputs in a small river were recorded with suitable online monitoring equipment coupled in mobile water quality monitoring stations, the study area being a transborder catchment with French and German (Saarland federal state) subcatchments. In addition to a pronounced spatial variability necessitating a denser net of measuring points this catchment has also to be assessed in the light of different national regulations. To identify individual pollution sources and weigh their relative importance, relevant parameters were recorded over a representative monitoring period of several months: phosphorus (P) as total phosphorus (TP) and total reactive P phosphorus (TRP), nitrate (NO3-N), ammonium (NH4-N), total organic carbon (TOC), temperature, oxygen (O2), pH, turbidity, and electrical conductivity (EC). The recorded data were subjected to adapted interpretation together with other catchment-related factors. In order to retrieve maximum information from the online data sets the relationships among certain parameter pairs were also analysed for both storm events and low flow periods. Comparison of loads at the different monitoring sites could reliably verify the majority of nutrient inputs originating in the French subcatchment. Additional sampling of output channels from sewage treatment works (STWs) in the Saarland subcatchment revealed that inputs from several decentralised STWs do not result in significant loads, as opposed to inputs from one STW in France. Our holistic approach provides a basis for adopting cost-effective measures to reduce loads in small river catchments as well as cross-border harmonisation of environmental policies.

Does problem complexity matter for environmental policy delivery? How public authorities address problems of water governance.

Problem complexity is often assumed to hamper effective environmental policy delivery. However, this claim is hardly substantiated, given the dominance of qualitative small-n designs in environmental governance research. We studied 37 types of contemporary problems defined by German water governance to assess the impact of problem complexity on policy delivery through public authorities. The analysis is based on a unique data set related to these problems, encompassing both in-depth interview-based data on complexities and independent official data on policy delivery. Our findings show that complexity in fact tends to delay implementation at the stage of planning. However, different dimensions of complexity (goals, variables, dynamics, interconnections, and uncertainty) impact on the different stages of policy delivery (goal formulation, stages and degrees of implementation) in various ways.

Can a GIS toolbox assess the environmental risk of oil spills? Implementation for oil facilities in harbors.

Oil spills are one of the most widespread problems in port areas (loading/unloading of bulk liquid, fuel supply). Specific environmental risk analysis procedures for diffuse oil sources that are based on the evolution of oil in the marine environment are needed. Diffuse sources such as oil spills usually present a lack of information, which makes the use of numerical models an arduous and occasionally impossible task. For that reason, a tool that can assess the risk of oil spills in near-shore areas by using Geographical Information System (GIS) is presented. The SPILL Tool provides immediate results by automating the process without miscalculation errors. The tool was developed using the Python and ArcGIS scripting library to build a non-ambiguous geoprocessing workflow. The SPILL Tool was implemented for oil facilities at Tarragona Harbor (NE Spain) and validated showing a satisfactory correspondence (around 0.60 RSR error index) with the results obtained using a 2D calibrated oil transport numerical model.

Modeling transport and fate of heavy metals at the watershed scale: State-of-the-art and future directions.

A predictive understanding of the source-specific (e.g., point and diffuse sources) land-to-river heavy metal (HM) loads and HM dynamics in rivers is essential for mitigating river pollution and developing effective river basin management strategies. Developing such strategies requires adequate monitoring and comprehensive models based on a solid scientific understanding of the watershed system. However, a comprehensive review of existing studies on the watershed-scale HM fate and transport modeling is lacking. In this review, we synthesize the recent developments in the current generation of watershed-scale HM models, which cover a wide range of functionalities, capabilities, and spatial and temporal scales (resolutions). Existing models, constructed at various levels of complexity, have their strengths and weaknesses in supporting diverse intended uses. Additionally, current challenges in the application of watershed HM modeling are covered, including the representation of in-stream processes, organic matter/carbon dynamics and mitigation practices, the issues of model calibration and uncertainty analysis, and the balance between model complexity and available data. Finally, we outline future research requirements regarding modeling, strategic monitoring, and their combined use to enhance model capabilities. In particular, we envisage a flexible framework for future watershed-scale HM models with varying degrees of complexity to accommodate the available data and specific applications.

Temporal variability in TiO2 engineered particle concentrations in rural Edisto River.

Titanium dioxide (TiO2) is widely used in engineered particles including engineered nanomaterial (ENM) and pigments, yet its occurrence, concentrations, temporal variability, and fate in natural environmental systems are poorly understood. For three years, we monitored TiO2 concentrations in a rural river basin (Edisto River, < 1% urban land cover) in South Carolina, United States. The total concentrations of Ti, Nb, Al, Fe, Ce, and La in the Edisto River trended higher during spring/summer compared to autumn/winter. Upward trending Ti/Nb ratio in the spring/summer compared to near-background autumn/winter ratios of 255.7 ± 8.9 indicated agricultural preparation and growing-season-related increases in TiO2 engineered particles. In contrast, downward trending of the Ti/Al and Ti/Fe ratios in the spring and summer compared to the near-background autumn/winter ratios of 0.05 indicated greater mobilization of Fe and Al, relative to Ti during spring/summer. Surface-water concentrations of TiO2 engineered particles varied between 0 and 128.7 ± 3.9 µg TiO2 L-1. Increases in TiO2 concentrations over the spring/summer were associated with increases in phosphorus, orthophosphate, nitrate, ammonia, anthropogenic gadolinium, water temperature, suspended sediments, organic carbon, and alkalinity, and with decreases in dissolved oxygen. The association between these contaminants together with the timing of the increases in their concentrations is consistent with diffuse wastewater sources, such as reuse application overspray, biosolids fertilization, leaking sewers, or septic tanks, as the driver of instream concentrations; however, other diffuse sources cannot be ruled out. The findings of this study indicate spatially-distributed (non-point source) releases can result in high concentrations of TiO2 engineered particles, which may pose higher risks to rural stream aquatic ecosystems during the agricultural season. The results illustrate the importance of monitoring seasonal variations in engineered particles concentrations in surface waters for a more representative assessment of ecosystem risk.

Grey water footprint of agricultural production: An assessment based on nitrogen surplus and high-resolution leaching runoff fractions in Turkey.

Agricultural activities are responsible for three quarter of global nitrate (NO3) pollution. Many surface and ground water resources have been detrimentally affected from high rate of nitrogen (N) deposition due to excessive fertilizer and manure application. Grey water footprint (GWF) is one of the internationally accepted indicators quantifying the environmental effects of contaminants on water bodies. The main scope of this study is to assess GWF of agricultural nitrogen utilization in Turkey using Tier-1 approach, which is proposed by Water Footprint Network considering detailed spatially continuous soil, climate and agricultural data in order to provide quantifications at both provincial and basin level. Leaching runoff fractions of diffuse N loads are very important for GWF accounts. However, the previous studies are mainly relied on assigning constant leaching runoff fractions and superficial N applications rates. Nevertheless, many studies reported remarkable variations in leaching fractions due to heterogeneities in soil and water resources. To the author's knowledge, this is the first GWF assessment of the study area employing high resolution leaching runoff fractions which is estimated using soil texture, natural drainage and climate data maps. Nitrogen emissions and GWF accounts of 81 administrative provinces and 25 hydrological basins were quantified using provincial N application and surplus amounts. Accordingly, GWF of anthropogenic N accumulation is estimated to be 24.7 Gm3/y corresponding to an average water height of 114 mm per agricultural land area and 340 m3 per capita for the time period of five years (2007-2011). The water pollution level (WPL) is found to be critical (>0.75) at several river basins while the national average WPL is around 0.13. This study is expected to contribute to the national and international water and agricultural management and planning studies in order to decrease the water pollution levels by providing suitable information to policy-makers.

Success of lake restoration depends on spatial aspects of nutrient loading and hydrology.

Many aquatic ecosystems have deteriorated due to human activities and their restoration is often troublesome. It is proposed here that the restoration success of deteriorated lakes critically depends on hitherto largely neglected spatial heterogeneity in nutrient loading and hydrology. A modelling approach is used to study this hypothesis by considering four lake types with contrasting nutrient loading (point versus diffuse) and hydrology (seepage versus drainage). By comparing the longterm effect of common restoration measures (nutrient load reduction, lake flushing or biomanipulation) in these four lake types, we found that restoration through reduction of nutrient loading is effective in all cases. In contrast, biomanipulation only works in seepage lakes with diffuse nutrient inputs, while lake flushing will even be counterproductive in lakes with nutrient point sources. The main conclusion of the presented analysis is that a priori assessment of spatial heterogeneity caused by nutrient loading and hydrology is essential for successful restoration of lake ecosystems.

Combining stable isotopes with contamination indicators: A method for improved investigation of nitrate sources and dynamics in aquifers with mixed nitrogen inputs.

Excessive nitrate (NO3-) concentration in groundwater raises health and environmental issues that must be addressed by all European Union (EU) member states under the Nitrates Directive and the Water Framework Directive. The identification of NO3- sources is critical to efficiently control or reverse NO3- contamination that affects many aquifers. In that respect, the use of stable isotope ratios 15N/14N and 18O/16O in NO3- (expressed as δ15N-NO3- and δ18O-NO3-, respectively) has long shown its value. However, limitations exist in complex environments where multiple nitrogen (N) sources coexist. This two-year study explores a method for improved NO3- source investigation in a shallow unconfined aquifer with mixed N inputs and a long established NO3- problem. In this tillage-dominated area of free-draining soil and subsoil, suspected NO3- sources were diffuse applications of artificial fertiliser and organic point sources (septic tanks and farmyards). Bearing in mind that artificial diffuse sources were ubiquitous, groundwater samples were first classified according to a combination of two indicators relevant of point source contamination: presence/absence of organic point sources (i.e. septic tank and/or farmyard) near sampling wells and exceedance/non-exceedance of a contamination threshold value for sodium (Na+) in groundwater. This classification identified three contamination groups: agricultural diffuse source but no point source (D+P-), agricultural diffuse and point source (D+P+) and agricultural diffuse but point source occurrence ambiguous (D+P±). Thereafter δ15N-NO3- and δ18O-NO3- data were superimposed on the classification. As δ15N-NO3- was plotted against δ18O-NO3-, comparisons were made between the different contamination groups. Overall, both δ variables were significantly and positively correlated (p < 0.0001, rs = 0.599, slope of 0.5), which was indicative of denitrification. An inspection of the contamination groups revealed that denitrification did not occur in the absence of point source contamination (group D+P-). In fact, strong significant denitrification lines occurred only in the D+P+ and D+P± groups (p < 0.0001, rs > 0.6, 0.53 ≤ slope ≤ 0.76), i.e. where point source contamination was characterised or suspected. These lines originated from the 2-6‰ range for δ15N-NO3-, which suggests that i) NO3- contamination was dominated by an agricultural diffuse N source (most likely the large organic matter pool that has incorporated 15N-depleted nitrogen from artificial fertiliser in agricultural soils and whose nitrification is stimulated by ploughing and fertilisation) rather than point sources and ii) denitrification was possibly favoured by high dissolved organic content (DOC) from point sources. Combining contamination indicators and a large stable isotope dataset collected over a large study area could therefore improve our understanding of the NO3- contamination processes in groundwater for better land use management. We hypothesise that in future research, additional contamination indicators (e.g. pharmaceutical molecules) could also be combined to disentangle NO3- contamination from animal and human wastes.

Characterising phosphorus and nitrate inputs to a rural river using high-frequency concentration-flow relationships.

The total reactive phosphorus (TRP) and nitrate concentrations of the River Enborne, southern England, were monitored at hourly interval between January 2010 and December 2011. The relationships between these high-frequency nutrient concentration signals and flow were used to infer changes in nutrient source and dynamics through the annual cycle and each individual storm event, by studying hysteresis patterns. TRP concentrations exhibited strong dilution patterns with increasing flow, and predominantly clockwise hysteresis through storm events. Despite the Enborne catchment being relatively rural for southern England, TRP inputs were dominated by constant, non-rain-related inputs from sewage treatment works (STW) for the majority of the year, producing the highest phosphorus concentrations through the spring-summer growing season. At higher river flows, the majority of the TRP load was derived from within-channel remobilisation of phosphorus from the bed sediment, much of which was also derived from STW inputs. Therefore, future phosphorus mitigation measures should focus on STW improvements. Agricultural diffuse TRP inputs were only evident during storms in the May of each year, probably relating to manure application to land. The nitrate concentration-flow relationship produced a series of dilution curves, indicating major inputs from groundwater and to a lesser extent STW. Significant diffuse agricultural inputs with anticlockwise hysteresis trajectories were observed during the first major storms of the winter period. The simultaneous investigation of high-frequency time series data, concentration-flow relationships and hysteresis behaviour through multiple storms for both phosphorus and nitrate offers a simple and innovative approach for providing new insights into nutrient sources and dynamics.