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An ecosystem service approach was used to study the water purification service exemplified by impacts of land management scenarios. Nitrogen retention was calculated in two agricultural catchments by the dynamic Integrated Nutrients in Catchments (INCA)-N model. The monetary valuation was based on purification efficiency of artificial wetlands. The set of scenarios were based on existing agricultural water protection measures, and greening of the Common Agricultural Policy proposal. Scenarios were: wintertime crop cover on fields, increase in area of set aside land, decrease in nitrogen fertilization, crop diversification and nutrient recycling in organic farming. Nitrogen retention provided more value in the Yläneenjoki catchment where the main production line was animal husbandry. In the slowly flowing river Lepsämänjoki, the N retention was more effective than in the fast flowing river Yläneenjoki. When comparing measures some proved to have no value or even a negative value. Set aside had a high positive value when calculated per area, but on a catchment scale the value remained low because of the small area of implementation. Nutrient recycling and winter time vegetation cover were the scenarios that reduced N leaching from fields close to targets set in current political decisions. None of the scenarios increased greenhouse gas emissions. [ABSTRACT FROM AUTHOR]

Process-based nutrient models are increasingly used to determine the impact of future changes in land use, agriculture production practices and climate on the quantity and timing of nutrients reaching surface waters. Calibration of catchment-scale models to observed conditions can be difficult due to parameter uncertainty and the heterogeneity of catchment processes. Soft data, i.e. knowledge of processes gained through experimentation, have been suggested as one method of reducing uncertainty and producing a more accurate model of the processes that occur in a catchment. In this work, the Integrated Catchment model for Nitrogen was calibrated and validated for the Yläneenjoki catchment in south-western Finland by incorporating soft data. The calibration for 2003-2008 produced an adequate model of the in-stream nitrate concentrations (R² = 0.45, NS=0.42). However, model validation using data from 1997-2002 showed that the simulated in-stream nitrate concentrations were above the observed concentrations throughout the entire period (R² = 0.34, NS< 0). These results show that soft data can be used to constrain model parameters, resulting in a more accurate model of the catchment, but do not guarantee the best validation results as the simulated processes may not occur at the same time and rate as they did in the catchment. [ABSTRACT FROM AUTHOR]

The semi-distributed, dynamic INCA-N model was used to simulate the behaviour of dissolved inorganic nitrogen (DIN) in two Finnish research catchments. Parameter sensitivity and model structural uncertainty were analysed using generalized sensitivity analysis. The Mustajoki catchment is a forested upstream catchment, while the Savijoki catchment represents intensively cultivated lowlands. In general, there were more influential parameters in Savijoki than Mustajoki. Model results were sensitive to N-transformation rates, vegetation dynamics, and soil and river hydrology. Values of the sensitive parameters were based on long-term measurements covering both warm and cold years. The highest measured DIN concentrations fell between minimum and maximum values estimated during the uncertainty analysis. The lowest measured concentrations fell outside these bounds, suggesting that some retention processes may be missing from the current model structure. The lowest concentrations occurred mainly during low flow periods; so effects on total loads were small. [ABSTRACT FROM AUTHOR]

In Finland municipal and industrial waste water purification has effectively decreased nutrient emissions from point sources leading to improved water quality. No clear effects of decreasing non-point loading (atmospheric deposition, agriculture, forestry) are found, however, and nitrate concentrations are increasing in some rivers. The aim of this study was to determine the origin and timing of inorganic nitrogen loading to the Simojoki using the dynamic, semi-distributed INCA-N model. The simulation results showed that, at the river outlet, only about half of the inorganic nitrogen load originated from anthropogenic sources. The inorganic nitrogen load largely depended on runoff and half of the annual load was centred around the snowmelt period in April-May. There was a risk of increasing nitrogen load due to changes in agricultural land use. Water protection measures at all diffuse sources could decrease the anthropogenic part of the inorganic N load to the sea, but individual measures would only result in small reductions. [ABSTRACT FROM AUTHOR]

The European Water Framework Directive requires the ecological status of European water bodies to be good in light of advanced biological indicators. Multiple stressors impact ecological status in water bodies, so the diagnosis of the causes of deterioration becomes increasingly important. Currently, practical management focus on the control of single stressors which are assumed to be dominant. Modelling methods have widely been used to predict effects of altered land use and climate change on water quality. However, process based models typically predict abiotic responses and neglect biological effects of modelled changes in abiotic conditions. These, however, are important for river basin management. We applied a Bayesian network (BN) modelling approach to link future scenarios of climate change, land use change and modification of water bodies to ecological status. The objective was (i) to assess the combined effect of changes in land use and climate on the ecological status of a river and (ii) to assess the suitability of the BN modelling approach for this purpose. The BN was able to model effects of climate change and management on ecological status of a river, by combining scenarios, process-based model output and ecological, hydrological and water quality data. The results showed that the benefits of better land-use management were partly counteracted by future warming under these scenarios. Thus, the BN approach is potentially useful for water body diagnosis in river basins. [ABSTRACT FROM AUTHOR]