Linked Life Data

21051075

Source:http://linkedlifedata.com/resource/pubmed/id/21051075

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2010-12-6
pubmed:abstractText
We hypothesise that stream sediment elemental composition can predict mean and minimum concentrations of alkalinity, Ca and Mg in the river water throughout a river network. We tested this hypothesis for the River Derwent catchment in North Yorkshire, England, by using 6 years of water chemistry data from the Environment Agency and a digital elevation model to flow path-weight British Geological Survey (BGS) sediment element concentration data. The predictive models for mean concentrations were excellent for Ca and alkalinity, but less good for Mg, and did not require land use data inputs as stream water sediment composition seems to reflect all aspects of the riparian zone soil system. Predictive model forms were linear. Attempts to predict minimum values for Ca and alkalinity also were less satisfactory. This probably is due to variations in hydrological response times to individual precipitation events across the catchment.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1879-1026
pubmed:author
pubmed:copyrightInfo
Copyright © 2010 Elsevier B.V. All rights reserved.
pubmed:issnType
Electronic
pubmed:day
15
pubmed:volume
409
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
404-11
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Can sediment data be used to predict alkalinity and base cation chemistry of surface waters?
pubmed:affiliation
Environment Department, The University of York, Heslington, York, UK. sb641@york.ac.uk
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't