Specific Conductivity Stream Network Modeling Eastern Kentucky Watershed Data, Code and Analysis HTMLS ...

This data is for 60 water quality monitoring sites in the Right Fork of Beaver Creek watershed in Eastern Kentucky where specific conductivity (SC) was measured quarterly for two years from December 2012 to August 2014. SC was modeled as a function of land use covariates and spatial autocorrelation...

Full description

Bibliographic Details
Format: Dataset
Language:unknown
Published: U.S. EPA Office of Research and Development (ORD) 2020
Subjects:
Online Access:https://dx.doi.org/10.23719/1518672
https://catalog.data.gov/dataset/4969787f-5338-4783-88f8-116ce4274f40
id ftdatacite:10.23719/1518672
record_format openpolar
spelling ftdatacite:10.23719/1518672 2023-10-01T03:55:02+02:00 Specific Conductivity Stream Network Modeling Eastern Kentucky Watershed Data, Code and Analysis HTMLS ... 2020 https://dx.doi.org/10.23719/1518672 https://catalog.data.gov/dataset/4969787f-5338-4783-88f8-116ce4274f40 unknown U.S. EPA Office of Research and Development (ORD) https://dx.doi.org/10.1086/710340 water quality stream networks spatial autocorrelation Specific Conductivity Dataset dataset 2020 ftdatacite https://doi.org/10.23719/151867210.1086/710340 2023-09-04T13:56:42Z This data is for 60 water quality monitoring sites in the Right Fork of Beaver Creek watershed in Eastern Kentucky where specific conductivity (SC) was measured quarterly for two years from December 2012 to August 2014. SC was modeled as a function of land use covariates and spatial autocorrelation between sites on the stream network, and by doing so we could compare predictions of the average SC for different portions of the network and identify areas of low and high SC. The htmls files can be opened with a browser such as Internet Explorer or Chrome. ... Dataset Beaver Creek DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic water quality
stream networks
spatial autocorrelation
Specific Conductivity
spellingShingle water quality
stream networks
spatial autocorrelation
Specific Conductivity
Specific Conductivity Stream Network Modeling Eastern Kentucky Watershed Data, Code and Analysis HTMLS ...
topic_facet water quality
stream networks
spatial autocorrelation
Specific Conductivity
description This data is for 60 water quality monitoring sites in the Right Fork of Beaver Creek watershed in Eastern Kentucky where specific conductivity (SC) was measured quarterly for two years from December 2012 to August 2014. SC was modeled as a function of land use covariates and spatial autocorrelation between sites on the stream network, and by doing so we could compare predictions of the average SC for different portions of the network and identify areas of low and high SC. The htmls files can be opened with a browser such as Internet Explorer or Chrome. ...
format Dataset
title Specific Conductivity Stream Network Modeling Eastern Kentucky Watershed Data, Code and Analysis HTMLS ...
title_short Specific Conductivity Stream Network Modeling Eastern Kentucky Watershed Data, Code and Analysis HTMLS ...
title_full Specific Conductivity Stream Network Modeling Eastern Kentucky Watershed Data, Code and Analysis HTMLS ...
title_fullStr Specific Conductivity Stream Network Modeling Eastern Kentucky Watershed Data, Code and Analysis HTMLS ...
title_full_unstemmed Specific Conductivity Stream Network Modeling Eastern Kentucky Watershed Data, Code and Analysis HTMLS ...
title_sort specific conductivity stream network modeling eastern kentucky watershed data, code and analysis htmls ...
publisher U.S. EPA Office of Research and Development (ORD)
publishDate 2020
url https://dx.doi.org/10.23719/1518672
https://catalog.data.gov/dataset/4969787f-5338-4783-88f8-116ce4274f40
genre Beaver Creek
genre_facet Beaver Creek
op_relation https://dx.doi.org/10.1086/710340
op_doi https://doi.org/10.23719/151867210.1086/710340
_version_ 1778523134385717248