Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 2 Observations

<p>This data release component contains mean daily stream water temperature observations, retrieved from the USGS National Water Information System (NWIS) and used to train and validate all temperature models. The model training period was from 2010-10-01 to 2014-09-30, and the test period was from 2014-10-01 to 2016-09-30.</p>

Data and Resources

Field Value
accessLevel public
bureauCode {010:12}
catalog_@context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
catalog_describedBy https://project-open-data.cio.gov/v1.1/schema/catalog.json
identifier USGS:5f986594d34e198cb77ff084
metadata_type geospatial
modified 20201209
old-spatial -123.32988684, 30.1454932, -70.97964444, 48.90595739
publisher U.S. Geological Survey
publisher_hierarchy Department of the Interior > U.S. Geological Survey
resource-type Dataset
source_datajson_identifier true
source_hash 2b59102566471669f3caef42df8d2e91b619a573
source_schema_version 1.1
spatial {"type": "Polygon", "coordinates": [[[-123.32988684, 30.1454932], [-123.32988684, 48.90595739], [ -70.97964444, 48.90595739], [ -70.97964444, 30.1454932], [-123.32988684, 30.1454932]]]}
theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
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  • deep-learning
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  • ok
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  • or
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  • pa
  • pennsylvania
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  • streams
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  • usgs-5f986594d34e198cb77ff084
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  • washington
  • water-resources
  • water-temperature
  • west-virginia
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  • wisconsin
  • wv
  • wy
  • wyoming
isopen False
license_id notspecified
license_title License not specified
maintainer Farshid Rahmani
maintainer_email fzr5082@psu.edu
metadata_created 2025-11-22T15:27:18.612244
metadata_modified 2025-11-22T15:27:18.612249
notes &lt;p&gt;This data release component contains mean daily stream water temperature observations, retrieved from the USGS National Water Information System (NWIS) and used to train and validate all temperature models. The model training period was from 2010-10-01 to 2014-09-30, and the test period was from 2014-10-01 to 2016-09-30.&lt;/p&gt;
num_resources 2
num_tags 78
title Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 2 Observations