Estimation of CONUS stream water quality using LSTM and WRTDS

Authors:
Kuai Fang
Owners: Kuai Fang
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Type: Resource
Storage: The size of this resource is 5.0 GB
Created: Aug 15, 2024 at 3:55 p.m.
Last updated: Sep 03, 2024 at 5:21 p.m. (Metadata update)
Published date: Sep 03, 2024 at 5:20 p.m.
DOI: 10.4211/hs.8da6ebf2ee9a491490bb09a6349e70fe
Citation: See how to cite this resource
Sharing Status: Published
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Abstract

This dataset offers a comprehensive collection of water quality data for approximately 500 stations across the Continental United States (CONUS). It includes 20 common water quality parameters, along with meteorological, hydrological, and land use variables such as streamflow, precipitation, temperature, evapotranspiration, and vegetation indices. To support water quality modeling research, we provide model outputs from both conventional statistical (WRTDS) and advanced deep learning (LSTM) approaches. This dataset is designed to facilitate model development, validation, and application, and to promote reproducible research.

Subject Keywords

Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Place/Area Name:
continental US
North Latitude
50.0000°
East Longitude
-65.0000°
South Latitude
24.0000°
West Longitude
-125.0000°

Temporal

Start Date: 01/01/1982
End Date: 12/31/2018
Leaflet Map data © OpenStreetMap contributors

Content

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Credits

Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
United States Department of Energy DE-SC0018155
Stanford University Human-Centered AI (HAI) program and Data Science fellowship

Contributors

People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.

Name Organization Address Phone Author Identifiers
Kate Maher

How to Cite

Fang, K. (2024). Estimation of CONUS stream water quality using LSTM and WRTDS, HydroShare, https://doi.org/10.4211/hs.8da6ebf2ee9a491490bb09a6349e70fe

This resource is shared under the Creative Commons Attribution CC BY.

 http://creativecommons.org/licenses/by/4.0/
CC-BY

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