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Predicting the humus content of natural waters through GIS modelling

Authors: Mikhail Zobkov;

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).

Keywords

catchment area, morphometric characteristics, Science, dem, Q, humus content, water quality, gis

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold