Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 302179
Title Uncertainty in long-term predictions of forest soil acidification due to neglecting seasonal variability
Author(s) Kros, J.; Groenenberg, J.E.; Vries, W. de; Salm, C. van der
Source In: Scenario studies for the rural environment : selected and edited proceedings of the symposium scenario studies for the rural environment, Wageningen, The Netherlands, 12 - 15 September 1994 / Schoute, J.T.H., Finke, P.A., Veeneklaas, F.R., - p. 287 - 291.
Department(s) Winand Staring Centre for Integrated Land, Soil and Water Research
Publication type Contribution in proceedings
Publication year 1995
Keyword(s) bosschade - zure regen - modellen - onderzoek - geostatistiek - forest damage - acid rain - models - research - geostatistics
Categories Forest Damage and Protection
Abstract Soil and soil solution responses simulated with a site-scale soil acidification model (NUCSAM) were compared with results of a regional one (RESAM). RESAM is a multi-layer model with a temporal resolution of one year. NUCSAM also takes account of seasonal variability, since it simulates solute transport and biogeochemical processes on a daily basis. Uncertainty caused by neglecting seasonal variability in long-term predictions was investigated by comparing long-term RESAM and NUCSAM simulations. Although the seasonal and interannual variations in soil solution parameters were large, the trends in soil solution parameters corresponded quite well. Generally, the uncertainty due to time resolution in long-term predictions was relatively small.
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