Rank regression analysis of correlated water quality data from South East Queensland

Abstract. Sampaloc Lake is providing livelihood for the residents through aquaculture. An increase in the quantity of fish pens inside the lake threatens its water quality condition. One parameter being monitored is microalgal biomass by measuring Chlorophyll-a concentration. This study aims to generate a chlorophyll-a concentration model for easier monitoring of the lake. In-situ water quality data were collected using chl-a data logger and water quality meter at 357 and 12 locations, respectively. Using Parrot Sequoia+ Multispectral Camera, 1496 of 2148 images were acquired and calibrated, producing 18x18cm resolution Green (G), Red(R), Red Edge (RE) and Near Infrared (NIR) reflectance images. NIR was used to mask out non-water features, and to correct sun glint. The in-situ data and the pixel values extracted were used for Simple Linear Regression Analysis. A model with 5 variables – R/NIR, RE2, NIR2, R/NIR2, and NIR/RE2, was generated, yielding an R2 of 0.586 and RMSE of 0.958 μg/l. A chlorophyll-a concentration map was produced, showing that chl-a is higher where fish pens are located and lowers as it moves away from the pens. Although there are apparent fish pens on certain areas of the lake, it still yields low chlorophyll-a because of little amount of residential area or establishments adjacent to it. Also, not all fish pens have the same concentration of Chlorophyll-a due to inconsistent population per fish pen. The center of the lake has low chlorophyll-a as it is far from human activities. The only outlet, Sabang Creek, also indicates high concentration of Chlorophyll-a.

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Temporal Variation of Surface Water Quality in the Swan River Catchment in Himachal Pradesh India

Hydro Nepal Journal of Water Energy and Environment ◽

10.3126/hn.v20i0.16490 ◽

2017 ◽

Vol 20 ◽

pp. 55-61

Author(s):

Avinash Kumar Sharda ◽

Harish Chander Sharma ◽

Brij Bhushan

Keyword(s):

Water Quality ◽

Regression Analysis ◽

Pollution Control ◽

Rapid Development ◽

Himachal Pradesh ◽

Quality Data ◽

Water Quality Data ◽

River Catchment ◽

Swan River

As industrial growth in the lower Shiwalik hills has risen in past two decades, the last 10 years in the Una district has seen a rapid development in industrial and urban growth due to grant of industrial package by the central government of India. As a result, several production plants have sprung up within the Swan River catchment, threatening the water quality of this area. However, the actual effects on water quality are heretofore unknown. In this paper, we assess the water quality of the Swan River catchment by calculating the National Sanitation Foundation Water Quality Indicators (NSFWQI) and Overall Index of Population (OIP) between 2003-2012. Data on monitored cross sections were collected from State Pollution Control Board of Himachal Pradesh, India. The results indicate that there has been recent (within five years) considerable improvement in the water quality due to enforcement of proper pollution control technologies. The relationship between economic growth (GDP) and water quality was also studied.We carried out regression analysis of the water quality data to determine significant parameters as independent variables and WQI and OIP as dependent variables. The regression analysis further identified that the contribution of each variable with significant values r = 0.733, R2 = 0.695. The study further suggests that sustainable development is possible through adoption of proper treatment technologies, enforcement of formal legislation, and preparation of remedial action plans to reduce the environmental stresses.HYDRO Nepal JournalJournal of Water Energy and EnvironmentIssue: 20Page: 55-61

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A GIS-based spatiotemporal study of the variability of water quality in the Dubai Creek, UAE

Water Quality Research Journal ◽

10.2166/wqrjc.2015.020 ◽

2015 ◽

Vol 51 (3) ◽

pp. 219-232 ◽

Cited By ~ 4

Author(s):

Tarig A. Ali ◽

Maruf Mortula ◽

Serter Atabay ◽

Ehsan Navadeh

Keyword(s):

Water Quality ◽

Regression Analysis ◽

Chlorophyll A ◽

Multiple Logistic Regression Analysis ◽

Sewage Treatment Plant ◽

Treatment Plant ◽

Ordinary Least Squares ◽

Spatiotemporal Variability ◽

Quality Data ◽

Water Quality Data

This paper presents the outcomes of a study on the water quality of Dubai Creek which aimed to assess its eutrophication status. Field water quality data from stations along the creek collected in 2012 and 2013 were used. Ordinary least squares (OLS) and spatial autocorrelation analyses were used as part of geographic information system (GIS)-based exploratory regression analysis to study the relationship between chlorophyll-a and nutrients, specifically total nitrogen and phosphate. Multiple logistic regression analysis was used to study the vulnerability of the creek to eutrophication. Results showed unique trends of spatiotemporal variability of chlorophyll-a and nutrients. OLS modeling showed high correlation between field and modeled chlorophyll-a values between Al Garhoud Bridge and Sanctuary stations, located about 2 km upstream and downstream of the Sewage Treatment Plant (STP) Outfall station. Furthermore, results showed the lower half of the creek was more vulnerable to eutrophication than the upper, which was believed to be due to the location of the STP station, poor flushing, shallow water depth, and irregular circulation patterns in the creek. Accordingly, this study recommends development of a mitigation plan in order to control the levels of nutrients in the creek.

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