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1 Site Information: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins

Dates

Publication Date
Start Date
2010-10-01
End Date
2016-09-30

Citation

Rahmani, F., Shen, C., Oliver, S.K., Lawson, K., David Watkins, and Appling, A.P., 2021, Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins: U.S. Geological Survey data release, https://doi.org/10.5066/P9VHMO56.

Summary

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>

Contacts

Attached Files

Click on title to download individual files attached to this item.

basin_attributes.csv 105.77 KB text/csv
Shapefile: basins.zip
basins.dbf 36.06 KB
basins.prj 145 Bytes
basins.shp 100.99 MB
basins.shx 3.65 KB
Shapefile: gages.zip
gages.dbf 93.02 KB
gages.prj 145 Bytes
gages.shp 12.54 KB
gages.shx 3.65 KB

Purpose

Water quality research, advancement of machine learning in hydrology, improve predictions of stream temperature in ungagged or dammed basins.

Additional Information

Shapefile Extension

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files
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size36921
dateUploadedMon Aug 23 07:47:17 MDT 2021
namebasins.prj
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dateUploadedMon Aug 23 07:47:17 MDT 2021
namebasins.shp
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dateUploadedMon Aug 23 07:47:17 MDT 2021
namebasins.shx
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dateUploadedMon Aug 23 07:47:17 MDT 2021
geometryTypeMultiPolygon
namebasins
nativeCrsEPSG:4326

Shapefile Extension

boundingBox
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files
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imageWidth580
imageHeight435
size95257
dateUploadedMon Aug 23 11:51:56 MDT 2021
namegages.prj
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dateUploadedMon Aug 23 11:51:56 MDT 2021
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dateUploadedMon Aug 23 11:51:56 MDT 2021
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geometryTypePoint
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