scholarly journals Interactions between Irrigated Agriculture and Surface Water Quality with a Focus on Phosphate and Nitrate in the Middle Olifants Catchment, South Africa

2020 ◽  
Vol 12 (11) ◽  
pp. 4370
Author(s):  
Leushantha Mudaly ◽  
Michael van der Laan
Keyword(s):  
South Africa ◽  
Water Quality ◽  
Surface Water ◽  
Waste Water Treatment ◽  
Surface Water Quality ◽  
Summer Rainfall ◽  
Sampling Period ◽  
Water Quality Monitoring ◽  
Irrigated Agriculture ◽  
Drainage Canals

Little is understood on the interaction between irrigated agriculture and surface water quality in South African catchments. A case study was conducted on the Middle Olifants Catchment, which contains the second largest irrigation scheme in South Africa. Dams, rivers, irrigation canals, and drainage canals were sampled between the Loskop and Flag Boshielo Dams. Results were compared to historical water quality monitoring data from the Department of Water and Sanitation (DWS). While DWS data indicate that phosphate-phosphorus (PO4-P) does not pose a eutrophication risk, our monitored data were above the eutrophication threshold for the majority of the sampling period. In general, phosphorus (P) pollution is a bigger issue than nitrogen (N), and concentrations of these nutrients tend to be higher during the summer rainfall months, potentially indicating a link to agriculture and fertilization events. We estimated that waste water treatment works (WWTW), which are currently systematically failing in South Africa, have the potential to pollute as much P as irrigated agriculture. Electrical conductivity levels increased downstream, moving from the acceptable towards the tolerable category, while the sodium adsorption ratio (SAR) presents a moderate risk of infiltrability problems. The pH values were generally in the ideal range. This study has highlighted existing and looming water quality issues for irrigation and the environment in the Middle Olifants. Similar scoping studies are recommended for other intensively-irrigated catchments in the region to identify issues and allow timely intervention.

scholarly journals Innovative Solutions in Surface Water Quality Monitoring

2014 ◽  
Vol 10 ◽  
pp. 26-30 ◽  
Author(s):  
Damian Absalon ◽  
Marek Ruman ◽  
Magdalena Matysik ◽  
Krystyna Kozioł ◽  
Żaneta Polkowska
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Surface Water Quality ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Innovative Solutions

scholarly journals Monitoring surface water quality using social media in the context of citizen science

2017 ◽  
Vol 21 (2) ◽  
pp. 949-961 ◽  
Author(s):  
Hang Zheng ◽  
Yang Hong ◽  
Di Long ◽  
Hua Jing
Keyword(s):  
Water Quality ◽  
Social Media ◽  
Surface Water ◽  
Surface Water Quality ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Quality Data ◽  
Future Research ◽  
Water Quality Data ◽  
Essential Information

Abstract. Surface water quality monitoring (SWQM) provides essential information for water environmental protection. However, SWQM is costly and limited in terms of equipment and sites. The global popularity of social media and intelligent mobile devices with GPS and photography functions allows citizens to monitor surface water quality. This study aims to propose a method for SWQM using social media platforms. Specifically, a WeChat-based application platform is built to collect water quality reports from volunteers, which have been proven valuable for water quality monitoring. The methods for data screening and volunteer recruitment are discussed based on the collected reports. The proposed methods provide a framework for collecting water quality data from citizens and offer a primary foundation for big data analysis in future research.

scholarly journals Assessment of Anthropogenic Impact of Surface Water Quality, South Africa

2018 ◽  
Vol 6 (2) ◽  
pp. 12
Author(s):  
Dipitseng Manamela ◽  
Omotayo Awofolu
Keyword(s):  
South Africa ◽  
Water Quality ◽  
Surface Water ◽  
Anthropogenic Activities ◽  
Treatment Plant ◽  
Surface Water Quality ◽  
Total Coliform ◽  
Mean Values ◽  
Physico Chemical ◽  
The Impact

This article investigates the impact of anthropogenic activities on an important surface water from physico-chemical, chemical and microbial perspectives. The surface water, referred to as Blesbokspruit is in the West Rand District of South Africa. Potential impactors include wastewater treatment plant, mines, farmlands and informal settlements. Water samples were collected from nine purposively selected sampling points and analysed in 2014. The mean values of analysed variables across sampling sites and periods ranged from pH: 7.4-8.4; EC: 93.0 - 146.6 mS/m; TSS: 11.3 – 39.0 mg/L; TDS: 590.3 - 1020.3 mg/L; COD: 15.6- 34.8 mg/L. Those for anions varied from NO3-: 0.2- 2.1 (mg/L) N; PO43- : 0.4-0.9 mg/L and SO42-: 118.6 - 379.5 mg/L. The metallic variables ranged from As: 0.01-0.06 mg/L; Cd: 0.02-0.06 mg/L; Fe: 0.04-0.73 mg/L; Cu: 0.02 – 0.05 mg/L and Zn: 0.05 – 0.15 mg/L. The Faecal coliform varied from 15.9-16878.5 cfu/100 ml; Total coliform: 92.9-430294 cfu/100 ml and HPC from 4322.5-39776 cfu/1ml. Detection of toxic metals and pathogenic organisms above target safety limits indicate unsuitability of the water for domestic use with impact on the health of aquatic ecosystem. The study generally revealed the impact of anthropogenic activities on the surface water quality.

Using a conductivity–alkalinity relationship as a tool to identify surface waters in reference condition across Canada

2018 ◽  
Vol 53 (4) ◽  
pp. 231-240
Author(s):  
C. L. Proulx ◽  
B. W. Kilgour ◽  
A. P. Francis ◽  
R. F. Bouwhuis ◽  
J. R. Hill
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Monitoring Network ◽  
Surface Water Quality ◽  
Water Quality Monitoring ◽  
Reference Condition ◽  
Quality Monitoring ◽  
Surveillance Program ◽  
Disturbed Condition ◽  
Time Period

Abstract The underlying natural relationship between conductivity and alkalinity was used to identify surface water quality monitoring sites that are in a ‘reference’ or minimally disturbed condition. Data from over 40,500 freshwater samples from 1,230 sites were combined for the time period of 2005–2015 from various federal, provincial, and joint federal–provincial/territorial freshwater monitoring programs (e.g., Freshwater Quality Monitoring and Surveillance Program, Ontario's Provincial Water Quality Monitoring Network). Of the samples, 30,347 provided conductivity and alkalinity data. Surface water samples with a measured conductivity that deviated (by more than 41 μS/cm) from the predicted conductivity calculated from the sample's alkalinity were deemed to be non-representative of a reference condition, while samples within 41 μS/cm of the predicted value were deemed representative of a reference condition. The 41 μS/cm cutoff value was determined using signal detection theory. The conductivity–alkalinity model was validated through a comparison with land cover data by demonstrating that samples identified as ‘reference’ were typically from catchments that had minimal anthropogenic disturbances. The proposed approach provides a rapid means of evaluating the reference condition of a watercourse, and of identifying data that provide an estimate of reference condition.

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