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    Author(s): James A. Lynch; Jeffery W. Grimm; Edward S. Corbett
    Date: 1996
    Source: In: Hom, John; Birdsey, Richard; O'Brian, Kelly, eds. Proceedings 1995 meeting of the northern global change program; Gen. Tech. Rep. NE-214. Radnor, PA: U. S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station: 8-9.
    Publication Series: General Technical Report (GTR)
    Station: Northeastern Research Station
    PDF: View PDF  (125.47 KB)

    Description

    Application of a variety of two-dimensional interpolation algorithms to precipitation chemistry data gathered at scattered monitoring sites for the purpose of estimating precipitation- born ionic inputs for specific points or regions have failed to produce accurate estimates. The accuracy of these estimates is particularly poor in areas of high topographic relief. Because wet deposition of pollutants is a function of both the ionic concentration of precipitation and precipitation volume and because the local distribution of precipitation can be strongly influenced by terrain, incorporation of orographic effects into the wet deposition modeling process should markedly improve the accuracy of estimated depositions. This presentation describes progress made in the development and application of a model which utilizes topographic features for the purpose of estimating wet deposition of major ions for any portion of the region encompassed by US. Forest Service Northern Global Change Program (NGCP).

    Publication Notes

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    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

    Citation

    Lynch, James A.; Grimm, Jeffery W.; Corbett, Edward S. 1996. Enhancement of regional wet deposition estimates based on modeled precipitation inputs. In: Hom, John; Birdsey, Richard; O''Brian, Kelly, eds. Proceedings 1995 meeting of the northern global change program; Gen. Tech. Rep. NE-214. Radnor, PA: U. S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station: 8-9.

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