scholarly journals The Relationship between Surface Water Quality and Watershed Characteristics

2019 ◽  
Vol 8 (3) ◽  
pp. 107-111 ◽  
Author(s):  
Amir Mansour Mohammadi ◽  
Mehdi Vafakhah ◽  
Mohammad Reza Javadi
Keyword(s):  
Water Quality ◽  
Electrical Conductivity ◽  
Water Resources ◽  
Land Cover ◽  
Absorption Rate ◽  
Total Dissolved Solids ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Sodium Absorption ◽  
Catchment Characteristics

The healthy water resources are necessary and essential prerequisite for environmental protection and economic development, political, social and cultural rights of Iran. In this research, water quality parameters i.e. total dissolved solids (TDS), sodium absorption rate (SAR), electrical conductivity (EC), Na+, Cl-, CO32-, K+, Mg2+, Ca2+, pH, HCO3- and SO42- during 2010-2011 were obtained from Iranian Water Resources Research Institute in water quality measurement stations on Mazandaran province, Iran. Then, the most important catchment characteristics (area, mean slope, mean height, base flow index, annual rainfall, land cover, and geology) were determined on water quality parameters using stepwise regression via backwards method in the 63 selected rivers. The results showed that sodium absorption rate (SAR), total dissolved solids (TDS), electrical conductivity (EC), Na+ and Cl- parameters are strongly linked to geology characteristics, while K+, Mg2+ and Ca2+ cations is linked to rainfall and geology characteristics. pH and HCO3- are related to area, rainfall, land cover and geology characteristics, CO32- is related to area, rainfall, rangeland area and geology characteristics and SO42- is related to area, rainfall, range and bar land area and geology characteristics. Adaptive Neuro-Fuzzy Inference System (ANFIS) was used for modeling the selected catchment characteristics and water quality parameters. The ANFIS models have a high Nash–Sutcliffe model efficiency coefficient (NSE)  and low root mean squares error (RMSE) to estimate water quality parameters.

scholarly journals RESPONSE SURFACE METHODOLOGY VIA DESIRABILITY FUNCTION TECHNIQUES FOR OPTIMIZING CORRELATED RESPONSES OF ELECTRICAL CONDUCTIVITY AND TOTAL DISSOLVED SOLIDS OF SELECTED BOREHOLE WATER

2020 ◽  
Vol 4 (3) ◽  
pp. 333-342
Author(s):  
KEHINDE MONSURU YUSUFF ◽  
M. Lawal ◽  
A. T. Audu ◽  
O. A. Wale-Orojo
Keyword(s):  
Water Quality ◽  
Electrical Conductivity ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Water Source ◽  
Total Dissolved Solids ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Physical Parameters ◽  
Dissolved Solids

The health benefits in the description and observation of quantitative contents of quality parameters present or contained in any water source cannot be underestimated as they determine selection of best choice from available water sources for different intended uses as well as resource consumption. It also helps to compare the observed quantity of the quality with the acceptable standards or limits to get desired results. Physical parameters like pH, temperature, electrical conductivity (EC) and total dissolved solids (TDS) among others are determined by present of other chemical properties like Cations (Mg2+, Ca2+, Na+, etc), Anions (Cl-, NO3-, SO42+, etc), heavy metals and other dissolved materials during the course of its formation in different proportions and amounts. This study observed EC and TDS of 20 selected boreholes as two close and correlated water quality parameters as well as two of the major water quality parameters that account for overall quality of any water source, despite their different quantitative contents and physical features, they are likely determined by the same set of cations and anions with similar constraint equations. In contrast to linear programming, multiple criteria optimization models were fitted for EC and TDS using Response Surface Methodology via desirability techniques, optimal values obtained in this case measured against several criteria are found to lie between acceptable standards limits for drinking water, other numerical values and descriptive features in the final results reflect that the response equations obtained were well fitted.

scholarly journals Researchof Water Quality and its Chemical Parameters by Titration Method and Instrumenal Method

2019 ◽  
Vol 8 (6S4) ◽  
pp. 871-874
Keyword(s):  
Water Quality ◽  
Electrical Conductivity ◽  
Water Samples ◽  
Total Dissolved Solids ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Analysis ◽  
Instrumental Method ◽  
Titration Method ◽  
Dissolved Solids

he water quality analysis is an important aspect in understanding the behavior of water and what can they be used for. This study gives us a valuable information on the general properties of water quality parameters like pH, electrical conductivity, TDS, Bicarbonate, Sulfate, Nitrate, chloride etc. of the study area . Water samples were analyzed at the water quality lab. NIH, Roorkee for pH, electrical conductivity and total dissolved solids. The pH of water varied from 7.14 to 7.75. The electrical conductivity (EC) of sample falls from 620µS/cm to 2000µS/cm. The overall total dissolved solids in water of study area varied from 120mg/l to 900mg/l. Overall the range of the Chloride in water of the study area tend to falls between 13mg/l to 375mg/l. Sulfate of all the water samples that were collected from the study area have ranged from 28mg/l to 250mg .The range of the Bicarbonate of all the water samples varied from 320mg/l to 1051mg/l. The study area helps to know about water quality parameters and how to find their values by usingtwo methods : 1) titration method 2) instrumental method .It also helps us to apply these water quality parameters in ArcGis. It helps us to show the values of different parameters in different blocks ofambala for different years In this we have studied different blocks of ambala district Haryana .We have taken the samples from different places from the blocks and also samples are from wells, canal , rivers, ponds.

scholarly journals Evaluation of Temporal and Spatial Variations of Water Quality Parameters in Zohreh River, Iran

2019 ◽  
Vol 6 (2) ◽  
pp. 75-82
Author(s):  
Maryam Ravanbakhsh ◽  
Yaser Tahmasebi Birgani ◽  
Maryam Dastoorpoor ◽  
Kambiz Ahmadi Angali
Keyword(s):  
Water Quality ◽  
Electrical Conductivity ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Data ◽  
Sodium Absorption ◽  
Data Sets ◽  
Water Quality Data ◽  
Data Set ◽  
Temporal And Spatial

Discriminant analysis (DA) and principal component analysis (PCA), as multivariate statistical techniques, are used to interpret large complex water quality data and assess their temporal and spatial variation in the basin of the Zohreh river. In this study, data sets of 16 water quality parameters collected from 1966 to 2013) in 4 stations (1554 observations for each parameter) were analyzed. PCA for data sets of Kheirabad, Poleflour, Chambostan and Dehmolla stations resulted in 4, 4, 4, and 3 latent factors accounting for 88.985%, 93.828%, 88.648%, and 88.68% of the total variance in water quality parameters, respectively. It is indicated that total dissolved solids (TDS), electrical conductivity (EC), chlorides (Cl−), sodium (Na), sodium absorption ratio (SAR), and %Na were responsible for water quality variations which are mainly related to natural and anthropogenic pollution sources including climate effects, gypsum, and salt crystals in the supratidal of Zohreh river delta, fault zones of Chamshir I and II, drainage of sugarcane fields, and domestic and industrial wastewaters discharge into the river. DA reduced the data set to only seven parameters (discharge, temperature, electrical conductivity, HCO3-, Cl-, %Na, and T-Hardness), affording more than 58.5% correct assignations in temporal evaluations and describing responsible parameters for large variations in the quality of the Zohreh river.

scholarly journals Modeling Water Quality Parameters Using Data-Driven Models, a Case Study Abu-Ziriq Marsh in South of Iraq

Hydrology ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. 24 ◽  
Author(s):  
Mustafa Al-Mukhtar ◽  
Fuaad Al-Yaseen
Keyword(s):  
Water Quality ◽  
Electrical Conductivity ◽  
Total Dissolved Solids ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Performance Criteria ◽  
Total Hardness ◽  
Efficiency Coefficient ◽  
Dissolved Solids ◽  
South Of Iraq

Total dissolved solids (TDS) and electrical conductivity (EC) are important parameters in determining water quality for drinking and agricultural water, since they are directly associated to the concentration of salt in water and, hence, high values of these parameters cause low water quality indices. In addition, they play a significant role in hydrous life, effective water resources management and health studies. Thus, it is of critical importance to identify the optimum modeling method that would be capable to capture the behavior of these parameters. The aim of this study was to assess the ability of using three different models of artificial intelligence techniques: Adaptive neural based fuzzy inference system (ANFIS), artificial neural networks (ANNs) and Multiple Regression Model (MLR) to predict and estimate TDS and EC in Abu-Ziriq marsh south of Iraq. As so, eighty four monthly TDS and EC values collected from 2009 to 2018 were used in the evaluation. The collected data was randomly split into 75% for training and 25% for testing. The most effective input parameters to model TDS and EC were determined based on cross-correlation test. The three performance criteria: correlation coefficient (CC), root mean square error (RMSE) and Nash–Sutcliffe efficiency coefficient (NSE) were used to evaluate the performance of the developed models. It was found that nitrate (NO3), calcium (Ca+2), magnesium (Mg+2), total hardness (T.H), sulfate (SO4) and chloride (Cl−1) are the most influential inputs on TDS. While calcium (Ca+2), magnesium (Mg+2), total hardness (T.H), sulfate (SO4) and chloride (Cl−1) are the most effective on EC. The comparison of the results showed that the three models can satisfactorily estimate the total dissolved solids and electrical conductivity, but ANFIS model outperformed the ANN and MLR models in the three performance criteria: RMSE, CC and NSE during the calibration and validation periods in modeling the two water quality parameters. ANFIS is recommended to be used as a predictive model for TDS and EC in the Iraqi marshes.

scholarly journals Cladoceran abundance in relation to water quality parameters of Chakki Talab, Bodhan, Telangana

2018 ◽  
Vol 8 (01) ◽  
Author(s):  
Vasudha Lingampally ◽  
V.R. Solanki ◽  
D. L. Anuradha ◽  
Sabita Raja
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Oxygen Demand ◽  
Total Dissolved Solids ◽  
Quality Parameters ◽  
Biological Oxygen Demand ◽  
Water Quality Parameters ◽  
Total Alkalinity ◽  
Total Hardness ◽  
One Year

In the present study an attempt has been made to evaluate water quality and related density of Cladocerans for a period of one year, October 2015 to September 2016. Water quality parameters such as temperature, PH, total dissolved solids, dissolved oxygen, biological oxygen demand, total alkalinity, total hardness, chlorides, phosphates, and nitrates are presented here to relate with the abundance of Cladocerans. The Cladoceran abundance reflects the eutrophic nature of the Chakki talab.

scholarly journals Evaluation of Water Quality Parameters in Shatt AL-Arab, Southern Iraq, Using Spatial Analysis

Hydrology ◽  
2020 ◽  
Vol 7 (4) ◽  
pp. 79 ◽  
Author(s):  
Zahraa Q. Lateef ◽  
Abdul-Sahib T. Al-Madhhachi ◽  
Dawood E. Sachit
Keyword(s):  
Water Quality ◽  
Spatial Analysis ◽  
Arabian Gulf ◽  
Total Dissolved Solids ◽  
Quality Parameters ◽  
Data Availability ◽  
Water Quality Parameters ◽  
Total Hardness ◽  
Dissolved Solids ◽  
Southern Iraq

The present work illustrates the potential application of techniques of spatial analysis via geographic information systems (GIS) to categorize the distribution of temporal and spatial of water prediction characteristics to determine the water quality parameters of the Shatt Al-Arab River (SAA), southern Iraq. Eight main water quality parameters and three heavy metals were measured from December 2018 to October 2019. The total dissolved solids, chloride, sulfate, and total hardness were compared with previous data that were measured from 2014 to 2018 based on data availability. The geochemical characteristics were also investigated to analyze water quality parameters. The study was performed by selecting eleven stations according to the nature areas of SAA. Water samples were acquired from the eleven stations for four seasons (winter of 2018 through autumn of 2019). Results revealed that total dissolved solids ranged between 950 to 8500 mg/L, total hardness varied from 400 to 2394 mg/L as calcium carbonate (CaCO3), the sulfate ranged from 149 to 1602 mg/L, and chloride ranged from 330 to 3687 mg/L. The results showed that SAA had high salinity with a low hazard of sodicity. The SAA waters mainly fall below the Dolomite-Magnesite tie-lines which indicated the dissolution of carbonate rocks. This research also found that the study area confined from Al-Maqal station to Abu Flus port station where the salty marine water coming from the Arabian Gulf remains for longer periods. The SAA is not suitable for drinking and irrigation water according to Iraqi and World Health Organization (WHO) standards. This study suggested building a blocking dam downstream of the SAA to prevent salty water from coming back from Arabian Gulf.

scholarly journals Extracting the spatio-temporal linkages between land use/land cover and water quality parameters using spatio-temporal weighted regression

2018 ◽  
Vol 53 (4) ◽  
pp. 205-218
Author(s):  
Farid Karimipour ◽  
Arash Madadi ◽  
Mohammad Hosein Bashough
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Land Cover ◽  
Temporal Variations ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Spatial And Temporal Variations ◽  
Weighted Regression ◽  
Land Use Land Cover ◽  
Spatio Temporal

Abstract Studies in water quality management have indicated significant relationships between land use/land cover (LULC) variables and water quality parameters. Thus, understanding this linkage is essential in protecting and developing water resources. This article extends the conventional geographical weighted regression (GWR) to a temporal version in order to take both spatial and temporal variations of such linkages into account, which has been ignored by many of the previous efforts. The approach has been evaluated for total nitrates and nitrites' concentration as the case study. For this, observations of 45 water quality sampling stations were examined in a time interval of 20 years (1992–2011), and the linkages between LULC variables and NO2 + NO3 concentration were extracted through Pearson correlation coefficient as a global regression model, the conventional geographic weighted regression, and the proposed spatio-temporal weighted regression (STWR). Comparing the results based on two global criteria of goodness-of-fitness (R2) and residual sum of squares (RSS) verifies that the simultaneous consideration of spatial and temporal variations by STWR substantially improves the results.

scholarly journals Tingkat dan laju penurunan kualitas air di DAS Brantas Malang Raya

2019 ◽  
Vol 5 (2) ◽  
pp. 185
Author(s):  
Ima Yudha Perwira
Keyword(s):  
Water Quality ◽  
Electrical Conductivity ◽  
Dissolved Oxygen ◽  
Organic Materials ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Decrease Rate ◽  
Better Than

The decrease level of water quality of Brantas Watershed in Malang Raya was observed in this study. The aim of this study was to observe the decrease level of water quality of Brantas Watershed from Batu to Malang City. This study was carried out in the Brantas Watershed of Malang Raya (8 stations: A, B, C, D, E, F, G, and H) for 18,4 Km. The water quality parameters observed in this study were: CODmn (permanganometry), CODcr (CODmn correlation based analysis), dissolved oxygen (DO) (Winkler iodometry), TDS and electrical conductivity (EC) (EC meter), pH (pH meter), and turbidity (Turbidity meter). The result showed the value of CODmn: 1,8-10,2 mg/L, CODcr: 5,6-31,5 mg/L, DO: 4,0-6,1 mg/L, TDS: 204-289 mg/L, EC: 430-617 µS/cm, pH: 7,1-7,6, and turbidity: 2,02-10,30 NTU. There are 3 stations (A, B, and C) with 1st class water quality, 1 station (D) with the 2nd class water quality, and 4 stations (E, F, G, and H) with 3rd class water quality. The decrease of water quality in the Brantas Watershed from Batu to Malang City was up to 3 times with a decrease rate of 2,3 mg/L-1Km-1. The decomposition of organic materials in the water of Batu City and western part of Malang City is relatively better than that of central parts of Malang City which might be caused by the over capacity of recovery (Self-purification mechanism).

scholarly journals Many Oil Wells, One Evil: Potentially toxic metals concentration, seasonal variation and Human Health Risk Assessment in Drinking Water Quality in Ebocha-Obrikom Oil and Gas Area of Rivers State, Nigeria.

2021 ◽  
Author(s):  
Morufu Olalekan Raimi ◽  
Henry Olawale Sawyerr ◽  
Clinton Ifeanyichukwu Ezekwe ◽  
Gabriel Salako
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Water Resources ◽  
Niger Delta ◽  
Human Health Risk ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Indigenous Populations ◽  
Potentially Toxic Metals ◽  
Groundwater Supply

Background Oil and natural gas extraction have produced environmental pollution at levels that affect reproductive health of indigenous populations. Accordingly, polluted drinking water from physical, chemical and heavy metals can result in serious health problems, like anemia, kidney failure, immunosuppression, neurological impairments, gastrointestinal as well as respiratory irritation, skeletal system abnormalities, liver inflammation, liver cancer, cardiovascular diseases after chronic exposure and other cancer diseases with negative health effects. These diseases types remain associated to high amounts of heavy metal elements such as lead, chromium, zinc, copper, cadmium, manganese as well as nickel etc. Objectives Compare differences in water quality parameters in the study area (determine the level of pollutions in the different sites). Methodology: The investigation made use of standard analytical procedures. All sampling, conservation, transportation and analysis followed standard procedures described in APHA (2012). To prevent degradation of the organic substances, all obtained samples were transferred to the laboratory, while keeping in an icebox. Results: Result shows that during wet season, the mean values obtained for water quality parameters were significantly lower in site 9 compared with that obtained in other sites (p<0.05) with the exemptions of temperature, DO, BOD, COD, acidity, TH, TDS, K, Mg, Zn, Mn, Cd, Pb, Cu, Cr, NH3, NO2, NO3, Ni though slightly lower in most cases in site 9 were not significantly different (p>0.05) and both alkalinity and SO4 which were significantly higher in site 9 than site 1 (p<0.05). Result obtained during dry season reveals that there is no remarkable difference in pH, acidity, Pb and Ni between the nine sites (p>0.05) while other water quality parameters were significantly lower in site 9 than other sites excluding Cl and Mg which were both significantly higher in site 9 than site 8 (p<0.05). Conclusion: To guarantee quality groundwater supply for various purposes in Nigeria's core Niger Delta region, extra efforts must be taken to fully understand hydrogeochemical features and its suitability. Thus, this study will aid in the development of a quantitative understanding of the effects of diverse causes on groundwater level fluctuations in any aquifer around the world. Also, this analysis reinforces a valuable resource for researchers, activists and public officials seeking to help enhance community awareness, planning and performance. The verdicts would remain a valuable guideline for policymakers, the Ministry of Water Resources and development practitioners, as this highlights the requirement for suitable approaches toward mitigating toxic element of water resources contamination in the core Niger Delta toward safeguarding health of the public from carcinogenic as well as non-carcinogenic risks.

scholarly journals Limnology of lake Surinsar, Jammu, J&K: Part II – Water chemistry

2009 ◽  
Vol 1 (2) ◽  
pp. 159-165
Author(s):  
D. Slathia ◽  
S. P. S. Dutta
Keyword(s):  
Water Quality ◽  
Electrical Conductivity ◽  
Drinking Water ◽  
Quality Parameters ◽  
International Standards ◽  
Water Quality Parameters ◽  
Total Hardness ◽  
Human Consumption ◽  
Raw Water ◽  
Detectable Limit

Water quality parameters viz. air temperature (15.21 0 C -36 0 C/16.71 0 C - 39.42 0 C), water temperature (13 0 C-32.42 0 C/15 0 C-32.8 0 C), depth (42cm-69.08cm/ 25cm-121.92cm), turbidity (3.88-46.27NTU/3.67-69.39 NTU), salinity (0.10-0.31ppt/ 0.10-0.37ppt), electrical conductivity (0.101-0.172mS/cm/0.114-0.279mS/cm), TDS (49.63-111.78 mg/l/57.64-177.01mg/l), pH (7.92-9.82/7.80-9.09), free CO2 (0-19.22mg/l/0-15.32mg/l), DO (6.82-9.90mg/l/4.65-9.40mg/l), carbonate (0-18.38mg/l/0-20.63mg/l), bicarbonate (60.99-170.70mg/l/77.62-168.70mg/l, chloride (7.41-12.35mg/l/9.59-19.60mg/l), calcium (6.85-38.50mg/l/11.81-140.49mg/l), magnesium (4.62-7.22mg/l/3.86-39.05mg/l), total hardness (40.29-125.50 mg/l/56.61-511.05mg/l), BOD (3.12-5.79mg/l/1.31-16.21 mg/l), COD (17.74-75.42 mg/l/ 26.57-73.03mg/l), sodium (14.2-22.5mg/l/12.2-30.9mg/l), potassium (1.83-4.17mg/l/2.25-6.21mg/l), phosphate (0.048-0.233mg/l/0.008-0.603mg/l), nitrate (0.13-1.3mg/l/0.11-4.08mg/l), sulphate (1.60-19.19mg/l/1.36-15.70mg/l), silicate (0.14-4.23mg/l/0.27-7.05mg/l), iron (0-0.65/0-0.40mg/l), copper (below detectable limit) and zinc (below detectable limit), of lake Surinsar-the only source of drinking water to the inhabitants of the Surinsar village, have been reported monthly, during the year 2002-03/2003-04. WQI range falls from poor (70.45, December; 73.55, October; 74.4, November and 74.56, September/ 74.52, January and 75.36, September), very poor(82.54, February; 89.25, May; 80.76, August and 78.86, January/ 80.89, February; 98.25, April; 80.03, June; 82.26, July; 86.55, October and 83.03, November) to unfit (100.44, June; 101.9, July; 103.86, April and 119.5, March/ 103.73, May; 108.28, March; 122.56, August and 103.72, December). Comparison of range of various water quality parameters of Surinsar lake water, with national and international standards has also revealed that most of these parameters are beyond permissible limits. This clearly indicates the unsuitability of raw water, generally consumed by local inhabitants, for human consumption.

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