Water Quality Profile of an Urbanising Catchment

2007 ◽  
Author(s):  
Ashantha Goonetilleke ◽  
Steven P Carroll ◽  
Les Dawes ◽  
Megan Hargreaves
Keyword(s):  
Water Quality ◽  
Quality Profile

scholarly journals Characteristics of Pergau Reservoir Water Quality Profile

2020 ◽  
Vol 549 ◽  
pp. 012008
Author(s):  
Alyaa Filza Effendi ◽  
Ayuni Samsul Bahri ◽  
Aiena Nur Nadira Roslan ◽  
Muhammad Zulsyahmi Rosli ◽  
Noorshariza Azura Shahbodin ◽  
...  
Keyword(s):  
Water Quality ◽  
Reservoir Water ◽  
Quality Profile

scholarly journals Water Quality Profile of Swan River Himachal Pradesh, India using GIS

2014 ◽  
Vol 13 ◽  
pp. 64-69 ◽  
Author(s):  
A. K. Sharda ◽  
M. P. Sharma ◽  
Pankaj Dumyat
Keyword(s):  
Water Quality ◽  
Ground Water ◽  
Quality Data ◽  
Water Quality Data ◽  
Energy And Environment ◽  
Tube Wells ◽  
Quality Profile ◽  
Increasing Demand ◽  
Swan River ◽  
Quality Map

To  meet  the ever increasing  demand  of drinking  water, a number of  shallow  tube wells are used to draw the water from  upper aquifers of  Swan  river. In  most  parts of  the river catchment, the  current  ground  water extraction is exceeding the recharge rate  causing  the rapid depletion of shallow ground water, resulting in serious environmental hazards like land subsidence  during  the  dry season flow and very low dilution levels in the  surface water. The water becomes polluted due to domestic and industrial waste water discharges. The present paper aims to study a water quality map of Swan River based on the computations of the National Sanitation Foundation Index (NSFWQI) and the Overall Index of Pollution (OIP) using water quality data from July to December 2012. A GIS tool has been used to prepare a water quality map of the study stretch (as a function of distance) along upstream and downstream from the pollution sources. The water quality map can help planners and designers make a quantitative assessment of the problem and better suggest long term measures to improve the health of the river. DOI: http://dx.doi.org/10.3126/hn.v13i0.10045HYDRO NEPAL Journal of Water, Energy and Environment Issue No. 13, July 2013Page: 64-69  

scholarly journals Profiles of water quality at Menjangan Besar Island, Karimunjawa, Central Java Province, Indonesia

2018 ◽  
Vol 19 (6) ◽  
pp. 2308-2315
Author(s):  
BAMBANG SULARDIONO ◽  
CHURUN A’IN ◽  
MAX RUDOLF MUSKANANFOLA
Keyword(s):  
Water Quality ◽  
Data Analysis ◽  
Water Column ◽  
Marine Biota ◽  
Mechanic Method ◽  
Central Java ◽  
Water And Sediment ◽  
Quality Profile ◽  
Total Bacteria ◽  
Central Java Province

Sulardiono B, A’in C, Muskananfola MR. 2018. Profiles of water quality at Menjangan Besar Island, Karimunjawa, Central Java Province, Indonesia. Biodiversitas 19: 2308-2315. The development of anthropogenic and tourism activities causes the ecological impact on water quality. The profile of water quality and sediment are the representation of environmental condition of ecosystems, then they could be indicators of pollution, fertility, suitability, and environmental carrying capacity on marine life. This study aimed to characterize the environmental indicator based on the quality profile of Menjangan Besar waters, Karimunjawa, Central Java. Data collection using a purposive sampling method based on water and sediment characteristics in Menjangan Besar waters. The research location is divided into three stations, namely: station A: the waters of fish cage activity; station B: floating guesthouse activity; and station C: seaweed marine culture. Variable on water quality profile consists of N-NO3 (mg/L) and PO4-P (mg/L), chlorophyll-α (mg/m3), and bacterial (CFU/mL), and other water quality support, while the variables on sediment quality profile consist of Phosphorus (mg/g) and PO4-P (mg/g), organic (%), C-organic (%) and bacterial (CFU/g), and sediment grain size. The calculation data analysis method of water and sediment total bacteria profile used Total Plate Count (TPC) by following SNI 7545.1 (2009), while analysis for nitrification bacteria (Nitrosomonas and Nitrobacter) using Most Probable Number (MPN). Data analysis of sediment grains size used two methods, i.e. (i) dry mechanic method by using sieve shaker, and (ii) wet mechanic method by using a pipette. Data analysis of nitrate and phosphate using Brucine Sulfanilik method. Mapping of the spatial distribution of measurement data for water nutrient contents (NO3-N and PO4-P), bacteria, and Chlorophyll-α in the waters using ArcGIS software application tool. The results showed that nitrification bacteria content in the water column is lower than in the sediments layer. Total bacteria content in both the water column and sediment layer varies between stations. Total bacteria in station A is higher than the other stations. The water nutrient content (Nitrate and Phosphate) is still above the quality standard for Marine Biota (Kepmen LH No. 51/2004). The condition of the fertility of Menjangan Besar waters is oligotrophic tend to mesotrophic, in the sense that the waters quality is low to medium conditions, and not yet dangerous for marine biota.

scholarly journals WATER QUALITY PROFILE OF WELLS IN ADAMANTINA – SP, BRAZIL

Nucleus ◽  
2015 ◽  
Vol 12 (2) ◽  
pp. 141-156
Author(s):  
Josiane Lourencetti ◽  
Marcelo Marconato Prates ◽  
Denilson Burkert
Keyword(s):  
Water Quality ◽  
Quality Profile

scholarly journals Determination of Changes in the Quality of Surface Water in the River—Reservoir System

2021 ◽  
Vol 13 (6) ◽  
pp. 3457
Author(s):  
Łukasz Gruss ◽  
Mirosław Wiatkowski ◽  
Krzysztof Pulikowski ◽  
Andrzej Kłos
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Statistical Analysis ◽  
Surface Water ◽  
Multivariate Statistical Analysis ◽  
Quality Data ◽  
Multivariate Statistical ◽  
Reservoir System ◽  
River Reservoir ◽  
Quality Profile

Assessing the changing parameters of water quality at different points in the river–reservoir system can help prevent river pollution and implement remedial policies. It is also crucial in modeling water resources. Multivariate statistical analysis is useful for the analysis of changes in surface water quality. It helps to identify indicators that may be responsible for the eutrophication process of a reservoir. Additionally, the analysis of the water quality profile and the water quality index (WQI) is useful in assessing water pollution. These tools can support and verify the results of a multivariate statistical analysis. In this study, changes in water quality parameters of the Turawa reservoir (TR), and the Mała Panew river at the point below the Turawa reservoir (bTR) and above the Turawa reservoir (aTR), were analyzed. The analyzed period was from 2019 to 2020 (360 samples were analyzed). It was found that TN, NO2-N, and NO3-N decreased after passing through the Turawa reservoir. Nevertheless, principal component analysis (PCA) and redundancy analysis (RDA) showed that NO2-N and NO3-N contribute to the observed variability of the water quality in the river-reservoir system. PCA showed that pH and PO4-P had a lower impact on the water quality in the reservoir than nitrogen compounds. Additionally, RDA proved that the values of the NO3-N and NO2-N indicators obtained the highest values at the aTR point, PO4-P at the bTR, and pH at the TR. This allows the conclusion that the Turawa reservoir reduced the concentration of NO2-N and NO3-N in comparison with the concentration of these compounds flowing into the reservoir. PCA and RDA showed that both parameters (NO2-N and NO3-N) may be responsible for the eutrophication process of the Turawa reservoir. The analysis of short-term changes in water quality data may reveal additional sources of water pollution. High temperatures and alkaline reaction may cause the release of nitrogen and phosphorus compounds from sediments, which indicates an increased concentration of TP, PO4-P, and Norg in the waters at the TR point, and TP, PO4-P, and NH4-N concentrations at the bTR point. The water quality profile combined with PCA and RDA allows more effective monitoring for the needs of water management in the reservoir catchment area. The analyzed WQI for water below the reservoir (bTR) was lower than that of the reservoir water (TR), which indicates an improvement in water after passing through the reservoir.

scholarly journals Evaluating the U.S. Food Safety Modernization Act Produce Safety Rule Standard for Microbial Quality of Agricultural Water for Growing Produce

2017 ◽  
Vol 80 (11) ◽  
pp. 1832-1841 ◽  
Author(s):  
Arie H. Havelaar ◽  
Kathleen M. Vazquez ◽  
Zeynal Topalcengiz ◽  
Rafael Muñoz-Carpena ◽  
MICHELLE D. DANYLUK
Keyword(s):  
Water Quality ◽  
Microbial Quality ◽  
Agricultural Water ◽  
Lognormal Distributions ◽  
E Coli ◽  
Produce Safety ◽  
Quality Profile ◽  
Safety Rule ◽  
The U.S

ABSTRACT The U.S. Food and Drug Administration (FDA) has defined standards for the microbial quality of agricultural surface water used for irrigation. According to the FDA produce safety rule (PSR), a microbial water quality profile requires analysis of a minimum of 20 samples for Escherichia coli over 2 to 4 years. The geometric mean (GM) level of E. coli should not exceed 126 CFU/100 mL, and the statistical threshold value (STV) should not exceed 410 CFU/100 mL. The water quality profile should be updated by analysis of a minimum of five samples per year. We used an extensive set of data on levels of E. coli and other fecal indicator organisms, the presence or absence of Salmonella, and physicochemical parameters in six agricultural irrigation ponds in West Central Florida to evaluate the empirical and theoretical basis of this PSR. We found highly variable log-transformed E. coli levels, with standard deviations exceeding those assumed in the PSR by up to threefold. Lognormal distributions provided an acceptable fit to the data in most cases but may underestimate extreme levels. Replacing censored data with the detection limit of the microbial tests underestimated the true variability, leading to biased estimates of GM and STV. Maximum likelihood estimation using truncated lognormal distributions is recommended. Twenty samples are not sufficient to characterize the bacteriological quality of irrigation ponds, and a rolling data set of five samples per year used to update GM and STV values results in highly uncertain results and delays in detecting a shift in water quality. In these ponds, E. coli was an adequate predictor of the presence of Salmonella in 150-mL samples, and turbidity was a second significant variable. The variability in levels of E. coli in agricultural water was higher than that anticipated when the PSR was finalized, and more detailed information based on mechanistic modeling is necessary to develop targeted risk management strategies.

Assessment of irrigation water quality. A proposal of a quality profile

2007 ◽  
Vol 142 (1-3) ◽  
pp. 149-152 ◽  
Author(s):  
César Almeida ◽  
Silvya Quintar ◽  
Patricia González ◽  
Miguel Mallea
Keyword(s):  
Water Quality ◽  
Irrigation Water ◽  
Irrigation Water Quality ◽  
Quality Profile

scholarly journals Water Quality Profile of Yamuna River, India

2009 ◽  
Vol 3 ◽  
pp. 19-24
Author(s):  
M. P. Sharma ◽  
S. K. Singal ◽  
S. Patra
Keyword(s):  
Water Quality ◽  
Industrial Effluents ◽  
Longitudinal Direction ◽  
Yamuna River ◽  
Policy Makers ◽  
Energy And Environment ◽  
Untreated Sewage ◽  
Physico Chemical ◽  
Quality Profile ◽  
Quality Map

The water quality profile of a river represents the extent of its pollution in terms of health of a river with respect to its longitudinal direction. This paper deals with the water quality profile of north India’s Yamuna river using physico-chemical and bacteriological parameters that converge into a single value NSF WQI. The water quality map of the river has been prepared showing that the Delhi stretch is highly polluted due to dumping of waste and discharge of untreated sewage and industrial effluents. The water quality map is a useful tool for policy makers, decision makers and environmentalists to suggest and implement appropriate conservation measures to improve the health of the water body.Key words: Water quality; pollution; river profile; indices; mapping; Indiadoi: 10.3126/hn.v3i0.1914Hydro Nepal Journal of Water, Energy and Environment Issue No. 3, July 2008. Page: 19-24

scholarly journals Water quality profile of fresh water wetland of Atpadi in Sangli District, Maharashtra (India)

2013 ◽  
Vol 14 (3) ◽  
pp. 95-99
Author(s):  
Alaka A. Patil
Keyword(s):  
Water Quality ◽  
Oxygen Demand ◽  
Environmental Parameters ◽  
Biological Oxygen Demand ◽  
Total Alkalinity ◽  
World Health ◽  
Total Hardness ◽  
Quality Profile ◽  
Calcium Magnesium ◽  
Health Organization

This paper presents a study on influence on environmental parameters on water quality at wetland of Atpadi in Atpadi tehsil of Sangli district on the basis of water quality index (WQI). WQI was determined on the basis of various parameters like pH, dissolved oxygen, total alkalinity, total hardness, calcium, magnesium, chlorides, total dissolved solids and biological oxygen demand for which no earlier reports are available on these water bodies. During this investigation, it was observed that some parameters are within the range prescribed by World Health Organization, Indian Council of Medical Research, Bureau of Indian Standard etc. But some parameters are beyond the permissible limit.

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