Transactions of the Karelian Research Centre of the Russian Academy of Sciences (Mar 2017)
Predicting the humus content of natural waters through GIS modelling
Abstract
The paper investigates the relationship between water humus content and the catchment’s morphometry. Contemporary watershed data were obtained by digital elevation model (DEM) processing, from 1:100 000 raster topographic maps and vector maps with the aid of geographical informational system (GIS) software. Strong correlation was found to exist between water humus content in lakes and forest coverage of the catchment. On the basis of this relation a model was developed which allows predicting the humus content of lakes relying on some of their watershed characteristics determined with the help of GIS tools. The confidence interval for this prognosis was ±6 units of humus content (a = 0.95), while its seasonal variation was ±3 units (a = 0.95).
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