Supporting Data for Balson et al., A machine learning approach to water quality forecasts and sensor network expansion: Case study in the Wabash River Basin, USA


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Created: Aug 31, 2021 at 2:14 p.m.
Last updated: Aug 31, 2021 at 8:10 p.m.
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Abstract

This resource contains supporting data for the manuscript:

Balson & Ward
A machine learning approach to water quality forecasts and sensor network expansion: Case study in the Wabash River Basin, USA
In review at Hydrological Processes

(full citation to be updated here upon manuscript publication)

The data presented are tabular outputs of discharge and stream nitrogen concentrations (nitrate-as-N) for all USGS sites within the Wabash River Basin, spanning the period of simulation 1948-2007. Data were generated using Agro-IBIS and THMB, matching exactly previously published modeling results.

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Resource Level Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Place/Area Name:
Wabash River Basin
North Latitude
41.3446°
East Longitude
-82.1797°
South Latitude
37.2311°
West Longitude
-88.9913°

Content

How to Cite

Balson, T., A. S. Ward (2021). Supporting Data for Balson et al., A machine learning approach to water quality forecasts and sensor network expansion: Case study in the Wabash River Basin, USA, HydroShare, http://www.hydroshare.org/resource/eeab0092a798412da9c754a3b917d799

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

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

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