| Project objectives:
The first primary objective of EUROHARP is to provide end-users (national and international European environmental policy-makers) with a thorough scientific
evaluation of the nine contemporary quantification tools and their ability to estimate diffuse nutrient (N, P) losses to surface freshwater systems and coastal
waters. Thereby facilitate the
implementation of the EC Water Framework Directive.
The second primary objective is to develop an electronic decision support system (tool-box) for the identification of benchmarking methodologies with
respect to both costs and benefits, for the quantification of diffuse nutrient losses under different environmental conditions across Europe.
EUROHARP will contribute substantially to improved comparability, transparency and reliability of the quantification of nutrient losses from diffuse
sources, and thereby to improved efficiency of abatement strategies related to the implementation of e.g. the Nitrates Directive and the Water Framework
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EUROHARP includes nine different contemporary methodologies for quantifying diffuse losses of N and P, and a total of 17 study catchments across gradients
in European climate, soils, topography, hydrology and land use. These methodologies have been selected to include those approaches - applicable at catchment
scale - that are currently used by European research institutes to inform policy makers at national and international levels.
| Achieved Objectives:
In recent decades, discharges of pollutants from waste water treatment plants and industry have been successfully identified and in many cases reduced, but
assessing inputs of diffuse pollution from land, and the degree of retention of pollutants, such as nitrogen and phosphorus, within surface water systems
is harder to achieve. A recent study has compared different methods used to estimate diffuse pollution in river catchments.
The EUROHARP project1 was a large scale comparison and evaluation of contrasting nutrient pollution models used as policy support tools to estimate river
water quality. Accurate estimation of diffuse pollution, such as nitrate and phosphorus, from agriculture is a major challenge. Results need to be accurate
and responsive to changes in land use and land management to assess compliance with EU policy instruments, to monitor trends in water quality, and to target
mitigation measures in time and space.
Contrasting types of modelling tools that predict river flows and concentrations of pollutants were compared with measured data. Models were chosen as
examples of different approaches (process based, semi-empirical, and conceptual) used as policy support tools in EU Member States. Representative river
catchments were chosen from 17 European catchments covering a range of climates (from north to south), soils, hydrology, and land uses.
Results of the models EveNFlow and PSYCHIC showed that both were capable of acceptable performance in modelling flows, nutrient concentrations and loads
in five out of six test catchment areas. In the sixth area, in Greece, results were less accurate, due to limitations in input data (rainfall, groundwater, point
sources). Accurate predictions of daily river flows were the primary factor influencing the satisfactory prediction of nitrate and phosphorus concentrations
and loads. However, both models showed adaptability and were capable of performing reasonably well when confronted with limited or unknown data in the other
five test catchments. The results demonstrated that diffuse pollution tools can be applied to catchments where climate and agricultural practices are very
different to those in the areas where such models were originally developed. This adaptability demonstrates that some diffuse pollution tools have the flexibility
required for demanding and strategic policy support purposes. Important generic principles for diffuse pollution support which emerged from this work included:
Model selection should be governed by end-user requirements, taking into account the availability of input data (e.g. screening tools may be best suited
to less complex approaches, whereas the system feedback implicit in scenario modelling would benefit from adopting relatively more complex approaches).
Modellers need to actively engage with catchment data managers to ensure valid assumptions are made. Comparison of the performance of the models evaluated
in EUROHARP is available from the project website: http://euroharp.org/diss/rep.htm, and shows that no single model was consistently superior across all