Modelling studies on soil-mediated response to acid deposition and climate variability

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Doctoral thesis (article-based)
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Date
2003-12-03
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Language
en
Pages
33, [82]
Series
Research reports / Helsinki University of Technology, Systems Analysis Laboratory. A, 87
Abstract
The impact of acidifying atmospheric precipitation and climate variability on forest soil was studied using three approaches: (i) dynamic process-oriented modelling, (ii) static vulnerability assessment, and (iii) non-linear response pattern identification. The dynamic soil acidification model MIDAS is presented, with applications at the plot and catchment scale in Norway, Sweden and Finland, which show that growing vegetation contributes to soil acidification and which illustrate that the recovery phase is not symmetrical to the acidification phase. I report the results of an analysis using the SMART acidification model and the DEPUPT nutrient uptake model for selected deposition and forest growth scenarios at the Integrated Monitoring site of Hietajärvi, eastern Finland. The results show the importance of how the present day deposition is estimated. A combinatory matrix approach is described that uses regional data together with expert judgement to provide an assessment of groundwater sensitivity to acidification in Europe, without the need for detailed mathematical process formulations. I also demonstrate the variability that is introduced in the Finnish critical loads of sulphur for forest soils by using alternative criteria and by extending the critical loads model to include organic complexation of aluminium and the leaching of organic anions. The impact of climate variability on runoff water quality is illustrated with an empirical stream water model that builds on artificial neural networks for reproducing patterns in the observations of TOC, Ntot and Ptot at Hietajärvi, and also at Valkea-Kotinen, an Integrated Monitoring site in southern Finland. The stream water model is used to predict changes in element fluxes from these forested catchments in response to climate change.
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Keywords
dynamic soil model, groundwater sensitivity matrix, artificial neural network, empirical stream water model, acidification, climate change
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Parts
  • Holmberg M., Hari P. and Nissinen A., 1989. Model of ion dynamics and acidification of soil: application to historical soil chemistry data from Sweden. In: Kämäri J., Brakke D. F., Jenkins A., Norton S. A. and Wright R. F. (Eds.), Regional acidification models. Geographic extent and time development. Springer-Verlag, Berlin, pages 229-241. [article1.pdf] © 1989 Springer-Verlag. By permission.
  • Holmberg M., 1990. Model of ion dynamics and acidification of soil: simulating recovery of base saturation. In: Fenhann J., Larsen H., Mackenzie G. A. and Rasmussen B. (Eds.), Environmental models: emissions and consequences. Elsevier Science, Amsterdam, pages 359-368. [article2.pdf] © 1990 by author.
  • Warfvinge P., Holmberg M., Posch M. and Wright R. F., 1992. The use of dynamic models to set target loads. Ambio 21, No. 5, pages 369-376. [article3.pdf] © 1992 The Royal Swedish Academy of Sciences. By permission.
  • Holmberg M., Rankinen K., Johansson M., Forsius M., Kleemola S., Ahonen J. and Syri S., 2000. Sensitivity of soil acidification model to deposition and forest growth. Ecological Modelling 135, No. 2-3, pages 311-325. [article4.pdf] © 2000 Elsevier Science. By permission.
  • Holmberg M., Johnston J. and Maxe L., 1990. Mapping groundwater sensitivity to acidification in Europe. In: Kämäri J. (Ed.), Impact models to assess regional acidification. Kluwer Academic Publishers, Dordrecht, pages 51-64. [article5.pdf] © 1990 International Institute for Applied Systems Analysis (IIASA). By permission.
  • Holmberg M., Mulder J., Posch M., Starr M., Forsius M., Johansson M., Bak J., Ilvesniemi H. and Sverdrup H., 2001. Critical loads of acidity for forest soils: tentative modifications. Water, Air, & Soil Pollution: Focus 1, No. 1-2, pages 91-101.
  • Holmberg M., Forsius M., Starr M. and Huttunen M., An application of artificial neural networks to carbon, nitrogen and phosphorus concentrations in three boreal streams and impacts of climate change. Ecological Modelling, to appear.
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Permanent link to this item
https://urn.fi/urn:nbn:fi:tkk-001007