Use of Multiple Linear Regression Models for Setting Water Quality Criteria for Copper: A Complementary Approach to the Biotic Ligand Model

2017 ◽  
Vol 51 (9) ◽  
pp. 5182-5192 ◽  
Author(s):  
Kevin V. Brix ◽  
David K. DeForest ◽  
Lucinda Tear ◽  
Martin Grosell ◽  
William J. Adams
Keyword(s):  
Water Quality ◽  
Linear Regression ◽  
Regression Models ◽  
Quality Criteria ◽  
Water Quality Criteria ◽  
Linear Regression Models ◽  
Complementary Approach ◽  
Biotic Ligand ◽  
Ligand Model ◽  
Multiple Linear Regression Models

scholarly journals The effects of precipitation, river discharge, land use and coastal circulation on water quality in coastal Maine

2015 ◽  
Vol 2 (7) ◽  
pp. 140429 ◽  
Author(s):  
Charles E. Tilburg ◽  
Linda M. Jordan ◽  
Amy E. Carlson ◽  
Stephan I. Zeeman ◽  
Philip O. Yund
Keyword(s):  
Water Quality ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
River Discharge ◽  
Regression Models ◽  
Mechanistic Model ◽  
Commercial Fishing ◽  
Coastal Circulation ◽  
Linear Regression Models ◽  
Multiple Linear Regression Models

Faecal pollution in stormwater, wastewater and direct run-off can carry zoonotic pathogens to streams, rivers and the ocean, reduce water quality, and affect both recreational and commercial fishing areas of the coastal ocean. Typically, the closure of beaches and commercial fishing areas is governed by the testing for the presence of faecal bacteria, which requires an 18–24 h period for sample incubation. As water quality can change during this testing period, the need for accurate and timely predictions of coastal water quality has become acute. In this study, we: (i) examine the relationship between water quality, precipitation and river discharge at several locations within the Gulf of Maine, and (ii) use multiple linear regression models based on readily obtainable hydrometeorological measurements to predict water quality events at five coastal locations. Analysis of a 12 year dataset revealed that high river discharge and/or precipitation events can lead to reduced water quality; however, the use of only these two parameters to predict water quality can result in a number of errors. Analysis of a higher frequency, 2 year study using multiple linear regression models revealed that precipitation, salinity, river discharge, winds, seasonality and coastal circulation correlate with variations in water quality. Although there has been extensive development of regression models for freshwater, this is one of the first attempts to create a mechanistic model to predict water quality in coastal marine waters. Model performance is similar to that of efforts in other regions, which have incorporated models into water resource managers' decisions, indicating that the use of a mechanistic model in coastal Maine is feasible.

DEVELOPING SITE-SPECIFIC WATER QUALITY CRITERIA FOR METALS USING THE BIOTIC LIGAND MODEL

2003 ◽  
Vol 2003 (4) ◽  
pp. 997-1009 ◽  
Author(s):  
Robert C. Santore ◽  
Rooni Mathew ◽  
Paul R Paquin ◽  
Kuen Ben Wu ◽  
Dominic DiToro
Keyword(s):  
Water Quality ◽  
Quality Criteria ◽  
Biotic Ligand Model ◽  
Water Quality Criteria ◽  
Site Specific ◽  
Biotic Ligand ◽  
Ligand Model

Framework for derivation of water quality criteria using the biotic ligand model: Copper as a case study

2018 ◽  
Vol 14 (6) ◽  
pp. 736-749 ◽  
Author(s):  
John C Gondek ◽  
Robert W Gensemer ◽  
Carrie A Claytor ◽  
Steven P Canton ◽  
Joseph W Gorsuch
Keyword(s):  
Water Quality ◽  
Quality Criteria ◽  
Biotic Ligand Model ◽  
Water Quality Criteria ◽  
Biotic Ligand ◽  
Ligand Model
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