Analysis of inorganic nitrogen leaching in a boreal river basin in northern Finland

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Doctoral thesis (article-based)
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Date
2006-03-24
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Language
en
Pages
65, [117]
Series
Helsinki University of Technology Water Resources publications, Teknillisen korkeakoulun vesitalouden ja vesirakennuksen julkaisuja, 13
Abstract
In this study the dynamic, semi-distributed INCA-N model was applied to the boreal Simojoki river basin in northern Finland to outline inorganic nitrogen (N) leaching patterns and N processes in catchment scale. Special emphasis was paid to the quality assurance of the modelling work. The dominant human impacts in the area are forestry, agriculture, scattered settlement and atmospheric deposition. In order to assess the effectiveness of current environmental policies and to implement river basin management plans, it is essential to know the relative significance of the different sources of pollution. INCA-N explained main features of the hydrological pattern and seasonality of inorganic N concentrations in river water when N processes in soil in sub-zero temperatures were included. Over-winter N mineralization processes in soil accounted for 38% of annual N mineralization. The lowest concentrations during the growing season were not reproduced, which indicates that there are some retention processes missing from the model. As summer is typically a low flow period the simulation results are reliable as long as the interpretation is based on daily or annual loads. Loading from the river basin was mostly dependent on annual hydrology and it was concentrated to peaks during the snow melting period. In the upper parts of the river inorganic N load originated mainly from commercial forests. At the outlet of the river anthropogenic sources accounted for more than half of the overall inorganic N load, with agriculture, forestry and scattered settlements making almost equal contributions. Expected changes in atmospheric N deposition would not have any significant effect but the combination of water protection measures both in agricultural and forestry areas and in scattered settlement areas would decrease inorganic N load by 18% of the total load. The expected increase in forest felling of 20% would not have an influence, but increase in agricultural land due to the EU's Common Agricultural Policy might lead to increased N load to the sea.
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Keywords
hydrology, nitrogen, river basin, semi-distributed modeling, uncertainty analysis
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Parts
  • Rankinen K., A. Lepistö and K. Granlund. 2002. Hydrological application of the INCA (Integrated Nitrogen in CAtchments) model with varying spatial resolution and nitrogen dynamics in a northern river basin. Hydrology and Earth System Sciences 6 (3): 339-350.
  • Rankinen K., A. Lepistö and K. Granlund. 2004. Integrated nitrogen and flow modelling (INCA) in a boreal river basin dominated by forestry: scenarios of environmental change. Water, Air, & Soil Pollution: Focus 4 (2-3): 161-174.
  • Rankinen K., T. Karvonen and D. Butterfield. 2004. A simple model for predicting soil temperature in snow-covered and seasonally frozen soil: model description and testing. Hydrology and Earth System Sciences 8 (4): 706-716.
  • Rankinen K., K. Granlund and I. Bärlund. 2004. Modelling of seasonal effects of soil processes on N leaching in northern latitudes. Nordic Hydrology 35 (4-5): 347-357.
  • Rankinen K., H. Lehtonen, K. Granlund and I. Bärlund. 2004. Assessing the effects of agricultural change on nitrogen fluxes using the Integrated Nitrogen CAtchment (INCA) model. Complexity and Integrated Resources Management, Transactions of the 2nd Biennial Meeting of the International Environmental Modelling and Software Society. Manno, Switzerland, iEMSs, 2004, volume 2: 1057-1063.
  • Rankinen K., K. Kenttämies, H. Lehtonen and S. Nenonen. Nitrogen load predictions under land management scenarios for a boreal river basin in northern Finland. Boreal Environment Research, accepted.
  • Rankinen K., T. Karvonen and D. Butterfield. Application of the GLUE methodology in estimating the parameters of the INCA-N model. Science of the Total Environment, accepted.
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https://urn.fi/urn:nbn:fi:tkk-006700