pubmed-article:11215642 | rdf:type | pubmed:Citation | lld:pubmed |
pubmed-article:11215642 | lifeskim:mentions | umls-concept:C0220806 | lld:lifeskim |
pubmed-article:11215642 | lifeskim:mentions | umls-concept:C0439849 | lld:lifeskim |
pubmed-article:11215642 | lifeskim:mentions | umls-concept:C0043047 | lld:lifeskim |
pubmed-article:11215642 | lifeskim:mentions | umls-concept:C1521970 | lld:lifeskim |
pubmed-article:11215642 | lifeskim:mentions | umls-concept:C0037592 | lld:lifeskim |
pubmed-article:11215642 | lifeskim:mentions | umls-concept:C0205485 | lld:lifeskim |
pubmed-article:11215642 | lifeskim:mentions | umls-concept:C0871161 | lld:lifeskim |
pubmed-article:11215642 | pubmed:issue | 1 | lld:pubmed |
pubmed-article:11215642 | pubmed:dateCreated | 2001-2-15 | lld:pubmed |
pubmed-article:11215642 | pubmed:abstractText | The Surface Waters component of the Environmental Monitoring and Assessment Program (EMAPSW) was developed by the USEPA to evaluate the extent and condition of lakes and streams over national and regional scales. Realistically, chemical or physical water properties (WPs) such as acidity or turbidity can be field-sampled for only a small portion of all lakes and streams. However, soil characteristics (SCs) affect WPs and broad-scale soil survey data have become available in the State Soil Geographic Data Base (STATSGO). We developed models relating observed WPs to SCs to extrapolate the sampled WPs to a region, potentially reducing extensive monitoring needs. Our study region consisted of 13 northeastern and Mid-Atlantic states and contained 882 STATSGO soil map units. We used map units as the spatial component of WP analysis. The WPs were sampled in 721 randomly selected EMAPSW study sites. The watersheds of these sites represent 7.1% of the region's total area and spatially intersect 400 of its soil map units. Each intersected map unit was assigned the weighted average WPs from the corresponding watersheds. Conditional expectation models were used to extrapolate sampled WPs to 882 map units. The relative standard errors ranged from low for pH (0.8%), intermediate for total P (12.1%), and very high for chloride (54.8%). The high extrapolation errors indicate outlier conditions from natural, non-soil, or anthropogenic sources. | lld:pubmed |
pubmed-article:11215642 | pubmed:language | eng | lld:pubmed |
pubmed-article:11215642 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:11215642 | pubmed:citationSubset | IM | lld:pubmed |
pubmed-article:11215642 | pubmed:chemical | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:11215642 | pubmed:chemical | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:11215642 | pubmed:status | MEDLINE | lld:pubmed |
pubmed-article:11215642 | pubmed:issn | 0047-2425 | lld:pubmed |
pubmed-article:11215642 | pubmed:author | pubmed-author:JohnsonC BCB | lld:pubmed |
pubmed-article:11215642 | pubmed:author | pubmed-author:BoersmaLL | lld:pubmed |
pubmed-article:11215642 | pubmed:author | pubmed-author:ShiraziM AMA | lld:pubmed |
pubmed-article:11215642 | pubmed:author | pubmed-author:HaggertyP KPK | lld:pubmed |
pubmed-article:11215642 | pubmed:issnType | Print | lld:pubmed |
pubmed-article:11215642 | pubmed:volume | 30 | lld:pubmed |
pubmed-article:11215642 | pubmed:owner | NLM | lld:pubmed |
pubmed-article:11215642 | pubmed:authorsComplete | Y | lld:pubmed |
pubmed-article:11215642 | pubmed:pagination | 112-20 | lld:pubmed |
pubmed-article:11215642 | pubmed:dateRevised | 2006-11-15 | lld:pubmed |
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pubmed-article:11215642 | pubmed:articleTitle | Predicting physical and chemical water properties from relationships with watershed soil characteristics. | lld:pubmed |
pubmed-article:11215642 | pubmed:affiliation | Western Ecology Division, NHEERL, US Environmental Protection Agency, Corvallis, OR 97333, USA. | lld:pubmed |
pubmed-article:11215642 | pubmed:publicationType | Journal Article | lld:pubmed |
pubmed-article:11215642 | pubmed:publicationType | Research Support, U.S. Gov't, Non-P.H.S. | lld:pubmed |