REGRESSION BASED FLOW ADJUSTMENT PROCEDURES FOR TREND ANALYSIS OF WATER QUALITY DATA

2013 ◽  
Author(s):  
A. Bekele and A. McFarland
Keyword(s):  
Water Quality ◽  
Trend Analysis ◽  
Quality Data ◽  
Water Quality Data ◽  
Flow Adjustment

Techniques of trend analysis for monthly water-quality data

1981 ◽  
Author(s):  
Robert M. Hirsch ◽  
James Richard Slack ◽  
Richard A. Smith
Keyword(s):  
Water Quality ◽  
Trend Analysis ◽  
Quality Data ◽  
Water Quality Data

WQTA — A Water Quality Trend Analysis Program

1993 ◽  
Vol 28 (2) ◽  
pp. 311-336 ◽  
Author(s):  
I.K. Tsanis
Keyword(s):  
Water Quality ◽  
Trend Analysis ◽  
Rank Correlation ◽  
Data Bank ◽  
Quality Parameters ◽  
Specific Conductance ◽  
Water Quality Parameters ◽  
Downward Trend ◽  
Quality Data ◽  
Water Quality Data

Abstract A series of programs have been developed using the statistical package Minitab to evaluate trends of water quality parameters over a time period. These programs are included in an interactive program with graphic capabilities called Water Quality Trend Analysis (WQTA). The output files from the retrieval and year programs of the National Water Quality Data Bank (NAQUADAT) are used as input files to the program. The graphic output is obtained using the graphical package Axum. Twelve-month moving averages and the Spearman’s rank correlation are applied for trend assessments. The components of variability (seasonal, trend and random) of the water quality parameters are modelled using linear regression. The methods are applied successfully to selected physical and chemical water quality parameters collected at the mouth of Niagara River, at Niagara-on-the-Lake, during the period 1976–89. The specific conductance was decreasing for the period as the discharge was increasing, due to higher dilution effects. A modest downward trend for total phosphorus was observed for the period 1976–84, and there is no trend between 1984-89. A strong decreasing trend for chloride was observed during the 1977–84 period but this has levelled off since then. A strong upward trend for iron and a weak downward trend for lead was evident over the study period.

Techniques of trend analysis for monthly water quality data

1982 ◽  
Vol 18 (1) ◽  
pp. 107-121 ◽  
Author(s):  
Robert M. Hirsch ◽  
James R. Slack ◽  
Richard A. Smith
Keyword(s):  
Water Quality ◽  
Trend Analysis ◽  
Quality Data ◽  
Water Quality Data

Non-parametric trend analysis of water quality data of rivers in Kansas

1993 ◽  
Vol 150 (1) ◽  
pp. 61-80 ◽  
Author(s):  
Yun-Sheng Yu ◽  
Shimin Zou ◽  
Donald Whittemore
Keyword(s):  
Water Quality ◽  
Trend Analysis ◽  
Quality Data ◽  
Water Quality Data ◽  
Parametric Trend ◽  
Non Parametric

scholarly journals Discovering Water Quality Changes and Patterns of the Endangered Thi Vai Estuary in Southern Vietnam through Trend and Multivariate Analysis

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1330
Author(s):  
Malte Lorenz ◽  
Hong Quan Nguyen ◽  
Trong Dieu Hien Le ◽  
Stephanie Zeunert ◽  
Duc Huy Dang ◽  
...  
Keyword(s):  
Water Quality ◽  
Trend Analysis ◽  
Pollution Abatement ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Quality Data ◽  
Rapid Improvement ◽  
Water Quality Data ◽  
Southern Vietnam

Temporal and spatial water quality data are essential to evaluate human health risks. Understanding the interlinking variations between water quality and socio-economic development is the key for integrated pollution management. In this study, we applied several multivariate approaches, including trend analysis, cluster analysis, and principal component analysis, to a 15-year dataset of water quality monitoring (1999 to 2013) in the Thi Vai estuary, Southern Vietnam. We discovered a rapid improvement for most of the considered water quality parameters (e.g., DO, NH4, and BOD) by step trend analysis, after the pollution abatement in 2008. Nevertheless, the nitrate concentration increased significantly at the upper and middle parts and decreased at the lower part of the estuary. Principal component (PC) analysis indicates that nowadays the water quality of the Thi Vai is influenced by point and diffuse pollution. The first PC represents soil erosion and stormwater loads in the catchment (TSS, PO4, and Fetotal); the second PC (DO, NO2, and NO3) determines the influence of DO on nitrification and denitrification; and the third PC (pH and NH4) determines point source pollution and dilution by seawater. Therefore, this study demonstrated the need for stricter pollution abatement strategies to restore and to manage the water quality of the Thi Vai Estuary.

Sign in / Sign up

Export Citation Format

Share Document