Development of Multiple-variable, Non-linear, Regression Models Linking Lake Erie Water Quality to Environmental and Climate Teleconnection Forcings, 1970s–2010s

Wang, Jia; Trumper, Matthew; Zhang, Hongyan; Kessler, James; Rowe, Mark; Chu, Philip; Yang, Ting-Yi; Lofgren, Brent

doi:10.25923/d9mk-jn08

i

Development of Multiple-variable, Non-linear, Regression Models Linking Lake Erie Water Quality to Environmental and Climate Teleconnection Forcings, 1970s–2010s

2022
By Wang, Jia ; Trumper, Matthew ; Zhang, Hongyan ; ...
Series: NOAA technical memorandum GLERL 177

Details

Personal Author:

Wang, Jia ; Trumper, Matthew ; Zhang, Hongyan ; Kessler, James ; Rowe, Mark ; Chu, Philip ; Yang, Ting-Yi ; Lofgren, Brent
Corporate Authors:

Great Lakes Environmental Research Laboratory
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; GLERL (Great Lakes Environmental Research Laboratory) ; CICEET (Coastal and Estuarine Environmental Technology)
Description:

This report uses relationships between biological parameters and environmental forcings to develop statistical prediction models for hypoxia and water quality in Lake Erie.
Keywords:

Climatic Changes Hypoxia (Water) Regression Analysis Teleconnections (Climatology) Water Quality Climatic Changes Regression Analysis Water Quality Cooperative Institute of Great Lakes Research (CIGLR)
Series:

NOAA technical memorandum GLERL 177 ; GLERL contribution no. 1958
DOI:

https://doi.org/10.25923/d9mk-jn08
Document Type:

Technical Memorandum
Funding:

Grant no. NA17OAR4320152
Place as Subject:

Erie, Lake ; United States
License:

https://creativecommons.org/publicdomain/zero/1.0/
Rights Information:

CC0 Public Domain
Compliance:

Submitted
Main Document Checksum:

urn:sha-512:cefa8ad57b8439baefb0d0fa754791cde2bb05affa0db2dee52228240fc7af6afc21a1aab41dee791a0e4d657a1370104f3e74a8451efe0835338b1d8cf668b6
Download URL:

https://repository.library.noaa.gov/view/noaa/38942/noaa_38942_DS1.pdf
File Type:

[PDF - 5.34 MB ]

ON THIS PAGE

Details

The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.