Reducing surface water pollution through the assessment of the cost-effectiveness of BMPs at different spatial scales.

Two kinds of agricultural Best Management Practices (BMPs) were examined with respect to cost-effectiveness (CE) in reducing sediment, nitrates-nitrogen (NO(3)-N) and total phosphorus (TP) losses to surface waters of the Arachtos catchment in Western Greece. The establishment of filter strips at the edge of fields and a non-structural measure, namely fertilization reduction in alfalfa, combined with contour farming and zero-tillage in corn and reduction of animal numbers in pastureland, were evaluated. The Soil and Water Assessment Tool (SWAT) model was used as the non-point-source (NPS) estimator, while a simple economic component was developed estimating BMP implementation cost as the mean annual expenses needed to undertake and operate the practice for a 5-year period. After each BMP implementation, the ratio of their CE in reducing pollution was calculated for each Hydrologic Response Unit (HRU) separately, for each agricultural land use type entirely and for the whole catchment. The results at the HRU scale are presented comprehensively on a map, demonstrating the spatial differentiation of CE ratios across the catchment that enhances the identification of locations where each BMP is most advisable for implementation. Based on the analysis, a catchment management solution of affordable total cost would include the expensive measure of filter strips in corn and only in a small number of pastureland fields, in combination with the profitable measure of reducing fertilization to alfalfa fields. When examined for its impact on river loads at the outlet, the latter measure led to a 20 tn or 8% annual decrease of TP from the baseline with savings of 15€/kg of pollutant reduction. Filter strips in corn fields reduced annual sediments by 66 Ktn or 5%, NO(3)-N by 71 tn or 9.5% and TP by 27 tn or 10%, with an additional cost of 3.1 €/tn, 3.3 €/kg and 8.1 €/kg of each pollutant respectively. The study concludes that considerable reductions of several pollutant types at the same time can be achieved, even at low total cost, by combining targeted BMP implementation strategies only in small parts of the catchment, also enabling policy makers to take local socio-economic constraints into consideration. The methodology and the results presented aim to facilitate decision making for a cost-effective management of diffuse pollution by enabling modelers and researchers to make rapid and reliable BMP cost estimations and thus being able to calculate their CE at the local level in order to identify the most suitable areas for their implementation.

Evaluation of diffuse pollution model applications in EUROHARP catchments with limited data.

The application of diffuse pollution models included in EUROHARP encompassed varying levels of parameterisation and approaches to the preparation of input data depending on the model and modelling team involved. Modellers consistently faced important decisions in relation to data interpretation, especially in those catchments with unfamiliar physical or climatic characteristics, where catchment conditions were beyond the range for which a particular model was originally developed, or where only limited input data were available. In addition to a broad discussion of data issues, this paper compares the performance of the four sub-annual output models tested in EUROHARP (EveNFlow, NL-CAT, SWAT and TRK) in three test catchments without the modelling teams having sight of measured flow and nitrate concentration data. Model performance in this "blind test" indicate that the range of predictions generated by any individual models pre and post calibration exceed the differences between the estimates yielded by all four models. Comparison of Analysis of Variance (ANOVA) statistics for simulated and observed flow, concentration and loads underscores the benefits of calibration for these intermediate and complex model formulations. Interpretation of input data (e.g. rainfall interpolation method and pedotransfer functions selected) appeared equally (or more) important than process representation. In the absence of calibration data, modeller unfamiliarity with a particular catchment and its environmental processes sometimes resulted in questionable assumptions and input errors which highlight the problems facing modellers charged with implementing policies under the Water Framework Directive (2000/60/EC) in poorly monitored catchments. Catchment data owners and modellers must therefore work more closely given that the output from diffuse pollution models is clearly modeller-limited as well as model-limited.

Description of nine nutrient loss models: capabilities and suitability based on their characteristics.

In EUROHARP, an EC Framework V project, which started in 2002 with 21 partners in 17 countries across Europe, a detailed intercomparison of contemporary catchment-scale modelling approaches was undertaken to characterise the relative importance of point and diffuse pollution of nutrients in surface freshwater systems. The study focused on the scientific evaluation of different modelling approaches, which were validated on three core catchments (the Ouse, UK; the Vansjo-Hobøl, Norway; and the Enza, Italy), and the application of each tool to three additional, randomly chosen catchments across Europe. The tools involved differ profoundly in their complexity, level of process representation and data requirements. The tools include simple loading models, statistical, conceptual and empirical model approaches, and physics-based (mechanistic) models. The results of a scientific intercomparison of the characteristics of these different model approaches are described. This includes an analysis of potential strengths and weaknesses of the nutrient models.

Evaluation of the difference of eight model applications to assess diffuse annual nutrient losses from agricultural land.

The capability of eight nutrient models to predict annual nutrient losses (nitrogen and phosphorus) at catchment scale have been studied in the EUROHARP project. The methodologies involved in these models differ profoundly in their complexity, level of process representation and data requirements. This evaluation is focused on model performance in three core catchments: the Vansjø-Hobøl (Norway), the Ouse (Yorkshire, UK) and the Enza (Italy). These three different model applications have been evaluated by comparing calculated annual nutrient loads (total N or nitrate and total P), based on observed flow and total nitrogen or nitrate and total phosphorus concentrations, and the annual nutrient loads that were simulated by the eight nutrient models. Four statistics have been applied for this purpose: the root mean squared error (RMSE), the mean absolute error (MAE), the mean error (ME), and Nash-Sutcliffe's model efficiency (NS). The results show that all model approaches can predict the calculated annual discharges. Depending on the observed statistics (RMSE, MAE, ME and NS) the scores of the model application differed, therefore no overall 'best model' could be identified. Although the water and nutrient loads from (sub)catchments can be predicted, the modelled pathways of nutrients within agricultural land and the nutrient losses to surface waters from agricultural land vary among the catchments and among those model approaches which are able to make this distinction.

Basin characteristics and nutrient losses: the EUROHARP catchment network perspective.

The EC-funded EUROHARP project studies the harmonisation of modelling tools to quantify nutrient losses from diffuse sources. This paper describes a set of study areas used in the project from geographical conditions, to land use and land management, geological and hydro-geological perspectives. The status of data availability throughout Europe in relation to the modelling requirements is presented. The relationships between the catchment characteristics and the nutrient export are investigated, using simple data available for all the catchments. In addition, this study also analyses the hydrological representativity of the time series utilised in the EUROHARP project.

Impact assessment of agricultural driven stressors on benthic macroinvertebrates using simulated data.

Agricultural land use poses a significant threat to the ecological integrity of rivers in Europe. Particularly in the Mediterranean, water abstraction and nutrient application are anthropogenic pressures that have a significant impact on aquatic habitats and biodiversity. In this article, we assessed the effects of agricultural management practices on benthic macroinvertebrates in a large river basin of central Greece using simulated data based on the application of SWAT (Soil Water Assessment Tool) model. Physicochemical and hydrological output variables of the model were used as predictors of the ASPT (Average Score Per Taxon) metric based on a correlated component regression analysis (CCR) built on empirical data. The estimation of ASPT was performed for the wet and dry seasons within a 20-year period for a total of 47 subbasins under the baseline conditions and after implementing three management scenarios that reduced: a) irrigation water applied to crops by 30%, b) chemical fertilization applied to crops by 30% and c) both irrigation and fertilization by 30%. The results revealed that application of the reduced irrigation resulted to a slight increase of the simulated dissolved inorganic nitrogen concentration (DIN), which in turn decreased the mean ASPT in 21 of the 47 subbasins implying a negative effect on the macroinvertebrate communities. On the contrary, the reduction of fertilization as well as the combined scenario decreased both the simulated DIN and phosphate concentration causing an increase of the mean ASPT for a total of 40 of the 47 subbasins. Based on these results, we suggest that the best management option is a combined practice of deficit irrigation and fertilization reduction since it improved water quality, increased ASPT values and saved a considerable amount of water. Overall, this work demonstrates a simple methodology that can efficiently assess the effects of agricultural management practices on biotic indicators.