Based on field experiments and analysis, the study examined the spectral characteristic and spatial variability of turbidity in the Pearl River Estuary by using the EO-1 ALI satellite imagery collected on December 18, 2005. A negative regression model (turbidity = −439.52 ×  R (570) + 22.913, R 2  = 0.9042, n  = 11) between the in-situ turbidity and the reflectance at 570 nm (maximum correlation spectral band between 350 and 2500 nm), resulting from increasing of organic matters in suspended solids, was built and applied to ALI band 4 (0.525–0.605 nm). Simple in-water spectral pairs calibration method of bright and dark targets provided the good atmospheric correction of ALI with a root mean square error of 0.00061, and mean absolute percentage error of 2.04%. The study also found the seawater turbidity is a more accurate indicator of Chl_ a concentration ( R 2  = 0.7442) than TSS ( R 2  = 0.7061). Also, there is a large correlation between TSS and the turbidity ( R 2  = 0.86, N  = 22) for Modaomen watercourse. The model-deduced turbidity distribution from ALI band 4 exhibited distinctive spatial variability of turbidity in the dry season, accordant with seasonal in-situ investigation. The ALI data provides accurate estimates of the mean water clarity conditions in the PRE ( RMSE  = 1.878 and MAPE  = 11.7%) and has potential importance for water quality monitoring of optical remote sensing in the similar estuaries and its future operation.

Remote sensing of turbidity in seawater intrusion reaches of Pearl River Estuary – A case study in Modaomen water way, China

Updating the physicochemical properties of surface water is important to water quality researchers and decision-makers Routine surface water quality monitoring methods are inadequate; whereas, rem

A novel approach for surface water quality modelling based on Landsat-8 tasselled cap transformation

Student Number : 0107471X -
MSc research report -
School of Civil and Environmental Engineering -
Faculty of Engineering and the Built Environment

/pdf/water-quality-monitoring-in-the-sadc-region-2gyvrwdzb3.pdf

Water Quality Monitoring in the SADC region

Landuse/land cover change is the key factor causing water quality changes worldwide. Stellenbosch town in the Western Cape, South Africa depends on Eerste River water for drinking and irrigation. The water quality of Eerste River downstream of Stellenbosch has been reported to be deteriorating. The main objective of this study wasto assess the spatial and temporal variation of water quality due to land use changes in Eerste River. Water samples were collected from 8 selected sampling points on the river during the period 12 February to 1 April 2016. To assess the variation of water quality, temperature, DO, EC, TDS, total phosphorus, nitrogen ammonia, turbidity, salinity, oxidation reduction potential, and chemical oxygen demand were analysed using standard methods. The Principal Component Analysis (PCA) was used toextract the most important factors and physico-chemical parameters affecting water quality while Cluster Analysis (CA) was used to group similar sampling sites.PCA results for historical data,Factor 1 describes 31.4 % total variance with a strong significant loading of ammonia, orthophosphate and total phosphorusCA identified 3 classes from 8 sampling points. Site 1, 2, 3 and 4 formed Group 1; at these sample sites the water is relatively clean and Site 1 and 2 fall within in a protected area. Site 5 and 6 are classified in the same group situated after industries and wineries and site 7 and 8 form group 3 located before and after the wastewater treatment plant.The status of water quality indicates that turbidity, nitrates and nitrogen, ammonia exceed the South African Water Targets from sampling sites. It can be concluded that water quality variation is mainly driven by and nitrates. As such the City of Cape Town which monitors water quality downstream of Stellenbosch should decrease the number of monitoring sites from four to three sampling points. For the year 1985to 2015, the forest cover has been decreasing from about 15 % to about 10% and from 2010 to 2015 decline was about 8% to about 2% while there is an increase of settlements from 1985 to 2015 about 38% to 55%. Bareland has been decreasing from 8% to 3%. There is a strong significant correlation (p<0.05) between water quality and land use changes.,WAterNet

Effects of land use changes on water quality in Eerste River, South Africa

This thesis is largely the documentation of two passive tracer release studies performed in Sterling Pond (SP), a small embayment on the southern coast of Lake Ontario (LO). SP has a large watershed and is strongly connected to LO by a long and narrow channel. The experiments were designed to decipher the effects of aquatic vegetation (macrophytes) on flow and transport through SP and through shallow embayments dominated by macrophytes in general. Towards this objective, the studies captured the residence time distribution (RTD) of water entering SP from its watershed under two different spatial distributions of macrophytes, and they were conducted in synchrony with extensive surveys of macrophyte density, height, and species composition. Variables relevant to the dynamics of SP were continuously monitored at its boundaries, including meteorological conditions, water surface elevation, flow, and temperature (temperature was continuously monitored within SP as well); bathymetric data was collected once. The first study took place when watershed flow was high and macrophytes were sparse – mean residence time was measured to be 0.6days. The second took place under moderate barotropic forcing from LO when watershed flow was low and macrophytes were dense and uniform across SP – mean residence time was measured to be 20days. As the studies were conducted under fairly extreme environmental conditions, the measured RTD’s roughly capture the range of residence time scales of water entering SP from its watershed. The tracer experiments, macrophyte surveys, and auxiliary data comprise a benchmark data set that may be used for development and validation of numerical models of flow through flexible vegetation.

Field Measurements of Bulk Flow and Transport through a Small Coastal Embayment Having Variable Distributions of Aquatic Vegetation

This paper describes the possibility of surface water quality monitoring using remote sensing technology and the spectral signatures of pure water and other types of water quality. Using airborne and spaceborne data (TM and ERS\|2) analysed with in situ measurements of ground truth points for water quality parameters, some major factors of surface water quality can be derived from remote sensing data by case studies. Concurrent in situ surface water quality measurments, Landsat TM data and ERS\|2 SAR data were obtained in the selected locations in August1997. In situ data included measurements of chlorophyll\|a, total dissolved organic carbon and turbidity, Secchi disk depth, color index, estimated wave height, salinity and surface temperature. The Landsat TM and ERS\|2 SAR data from locations of water samples were extracted and the digital data were examined in their raw states as well as numerous transformations. Significant correlations were observed between digital numbers and surface water quality parameters. The results indicate that it may be possible to derive surface water quality parameters using remote sensing data in our case study area. However, the technique still needs to be refined to detect differences within the range of water quality which is typically found in the area under study.

Surface Water Quality Monitoring Using Remote Sensing

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Surface Water Quality Monitoring Using Remote Sensing