1 Site Information: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins
type: Dataset
description: This data release component contains shapefiles of river basin polygons and monitoring site locations coincident with the outlets of those basins. A table of basin attributes is also supplied. Attributes, observations, and weather forcing data for these basins were used to train and test the stream temperature prediction models of Rahmani et al. (2021b).<\p>
issued: 2025-11-21T17:10:17.145386
modified: 20210927
spatial: Location
keyword: al
keyword: alabama
keyword: amerigeo
keyword: amerigeoss
keyword: ar
keyword: arizona
keyword: arkansas
keyword: az
keyword: ca
keyword: california
keyword: ckan
keyword: co
keyword: colorado
keyword: connecticut
keyword: ct
keyword: dc
keyword: de
keyword: deep-learning
keyword: delaware
keyword: district-of-columbia
keyword: environment
keyword: ga
keyword: geo
keyword: georgia
keyword: geoss
keyword: ia
keyword: id
keyword: idaho
keyword: il
keyword: illinois
keyword: in
keyword: indiana
keyword: inlandwaters
keyword: iowa
keyword: kansas
keyword: kentucky
keyword: ks
keyword: ky
keyword: ma
keyword: machine-learning
keyword: maine
keyword: maryland
keyword: massachusetts
keyword: md
keyword: me
keyword: mi
keyword: michigan
keyword: minnesota
keyword: mississippi
keyword: missouri
keyword: mn
keyword: mo
keyword: modeling
keyword: montana
keyword: ms
keyword: mt
keyword: national
keyword: nc
keyword: nd
keyword: ne
keyword: nebraska
keyword: nevada
keyword: new-hampshire
keyword: new-jersey
keyword: new-mexico
keyword: new-york
keyword: nh
keyword: nj
keyword: nm
keyword: north-america
keyword: north-carolina
keyword: north-dakota
keyword: nv
keyword: ny
keyword: oh

Digital Data
type: Distribution
description: Landing page for access to the data
format: XML
issued: 2022-08-06T19:45:31.965717
modified: 2025-11-21T17:10:17.094868
access URL: https://doi.org/10.5066/P9VHMO56
media type: application/http

Original Metadata
type: Distribution
description: The metadata original format
format: XML
issued: 2022-08-06T19:45:31.965711
modified: 2025-11-21T17:10:17.094381
access URL: https://data.usgs.gov/datacatalog/metadata/USGS.606db85fd34e670a7d5f61f0.xml
media type: text/xml

US Migrating
type: Agent

Organization
fn: Farshid Rahmani