Alexander Engebretsen

Research Scientist

(+47) 936 39 424

Ås F20

Visiting address
Fredrik A. Dahls vei 20, 1430 Ås


Effects of mitigation measures in agriculture on abating eutrophication are difficult to evaluate by assessments of catchment monitoring data. Estimates of improved water quality by specific agricultural Best Management Practices (BMPs) are therefore often dependent on simulation modeling. A main objective was thus to assess the probable reductions in total phosphorus (TP) loading achieved by implemented agricultural mitigation measures. The case-study site was a catchment in southeastern Norway. Simulation modeling was conducted by use of The Soil and Water Assessment Tool (SWAT). The aim of this present study was to understand the model uncertainty associated both with calibration/validation (baseline) and TP loading scenarios based on BMP. The modeled decrease in TP loading by the set of implemented BMPs was assessed by comparing simulated baseline output with output where the set of abatement actions were removed. The model was set up for the years 2006–2010 and calibrated against observed monitoring data, including daily discharge, sediment- and TP fluxes. Model simulations were performed including and excluding the implemented set of mitigation measures. The simulated set of mitigation measures include decrease in amount of phosphorus fertilization, establishment of vegetated buffer strips along streams and constructed wetlands in the water courses, no autumn tilling and removal of point TP sources from scattered dwellings. Model calibration and uncertainty estimation are performed using an algorithm for Sequential Uncertainty Fitting (SUFI2; ver. 2). Probabilistic risk for given magnitudes of increased TP loading if existing BMPs were not implemented was assessed. Using this novel approach it was possible to state, with a 80th percentile confidence level, that the average annual TP loading would have been about 26% higher if no mitigation measures were implemented in the catchment. This was possible to assess even though the difference between baseline and BMP scenario was not significant.

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The main environmental stressor of the Baltic Sea is elevated riverine nutrient loads, mainly originating from diffuse agricultural sources. Agricultural practices, intensities, and nutrient losses vary across the Baltic Sea drainage basin (1.75 × 106 km2 , 14 countries and 85 million inhabitants). Six “Soil and Water Assessment Tool” (SWAT) models were set up for catchments representing the major agricultural systems, and covering the different climate gradients in the Baltic Sea drainage basin. Four fertilizer application scenarios were run for each catchment to evaluate the sensitivity of changed fertilizer applications. Increasing sensitivity was found for catchments with an increasing proportion of agricultural land use and increased amounts of applied fertilizers. A change in chemical fertilizer use of ±20% was found to affect watershed NO3-N loads between zero effect and ±13%, while a change in manure application of ±20% affected watershed NO3-N loads between zero effect and −6% to +7%.


Knowledge of hydrological processes and water balance elements are important for climate adaptive water management as well as for introducing mitigation measures aiming to improve surface water quality. Mathematical models have the potential to estimate changes in hydrological processes under changing climatic or land use conditions. These models, indeed, need careful calibration and testing before being applied in decision making. The aim of this study was to compare the capability of five different hydrological models to predict the runoff and the soil water balance elements of a small catchment in Norway. The models were harmonised and calibrated against the same data set. In overall, a good agreement between the measured and simulated runoff was obtained for the different models when integrating the results over a week or longer periods. Model simulations indicate that forest appears to be very important for the water balance in the catchment, and that there is a lack of information on land use specific water balance elements. We concluded that joint application of hydrological models serves as a good background for ensemble modelling of water transport processes within a catchment and can highlight the uncertainty of models forecast.


The term “integrated valuation” is defined and its relevance is discussed in terms of bridging the gap between cost-effectiveness analysis and economic valuation in the implementation of the European Union Water Framework Directive. We demonstrate how to integrate benefit valuation with the ecosystem services cascade framework using an Object-Oriented Bayesian Network (OOBN). The OOBN is then used to assess the benefits of nutrient abatement measures across a cascade of submodels of the driver-pressure-state-impact-response (DPSIR) chain for the Vanemfjord lake in Morsa catchment in south-eastern Norway. The lake is part of a complex lake system in a semi-urbanized catchment dominated by forest and agriculture. The catchment has highly variable seasonal climatic conditions affecting nutrient run-off and algal blooms. It has been one of the most eutrophic lakes in Norway with periodic cyanobacteria blooms, but continues to attract a large recreational user population, despite the large variations in water quality. The “DPSIR-OOBN” model is used as a case study of “integrated valuation” and evaluated for its applicability for decision support in nutrient abatement. We find that the DPSIR-OOBN model meets seven of the nine criteria we propose for “integrated valuation”. The model struggles to meet the criteria that ecological, social and economic values should be defined consistently in relation to impacts on lake quality. While the DPSIR-OOBN integrates from valuation methods across an ecosystem cascade to management alternatives, it is neither a full benefit-cost analysis, nor a multi-criteria analysis. However, we demonstrate how the DPSIR-OOBN can be used to explore issues of consistency in scaling and weighting of different ecological, social and economic values in the catchment system. Bayesian belief networks offer a consistent approach to analysing how management implementation probability may determine economic valuation. We discuss the implication of our integrated valuation not being able to account for farmer responses, in particular the incentive effects of the model not being able to predict abatement effectiveness and value. The resolution of the nutrient monitoring data and modeling technologies that were at our disposal are probably better in the Morsa catchment than for any other catchment of this size in Norway. We therefore conclude that using our integrated valuation model for assessing benefits of eutrophication abatement measures as part of the EU Water Framework Directive still lies in the realm of utopia – euphemistically speaking a “eutropia”.