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Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
Development and sensitivity analysis of water quality index for evaluation of
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Development and sensitivity analysis of water quality index for evaluation of

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  • 1. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 119 DEVELOPMENT AND SENSITIVITY ANALYSIS OF WATER QUALITY INDEX FOR EVALUATION OF SURFACE WATER FOR DRINKING PURPOSE R. S. Sapkal1 , Dr. S. S. Valunjkar2 1 Research Scholar, Department of Civil Engineering, Government College of Engineering, Aurangabad, Maharashtra, India 2 Professor in Civil Engineering, Government College of Engineering, Karad, Sistt: Satara, Maharashtra, India ABSTRACT Water pollution not only affects water quality but also threats human health, economic developments & social prosperity Internationally there are number of attempts made to produce a method that meaningfully integrates the data sets and converts them into simple information called as Water Quality Index (WQI) Water quality indices are used as comprehensive evaluation instrument to assess the river water quality. Water quality index makes expert knowledge available to expert users and public in general. The indices are formulated based either on studies conducted by the indices developers or are formulated based on the Delphi technique which takes into account the opinion of experts or mathematical formulation or by using fuzzy logic. In this study the water quality index is developed by assigning relative weights to each parameter ranging from 1 to 6 based on the adverse effect of the water quality parameter on human health, its concentration with respect to other water quality parameters and method of treatment required. It includes twenty five water quality parameters such as Color water temperature, pH, Electrical Conductivity (EC), Turbidity, Suspended Solids (SS), Total Dissolved Solids (TDS), Total Hardness (TH), Total Alkalinity (TA), Dissolved Oxygen (DO), Biochemical oxygen demand (BOD), Chemical oxygen demand (COD), Sulfates (SO4 - - ),, Chlorides, Total Phosphates ( TP - ), Calcium (Ca++ ), Magnesium (Mg++ ), Fluorides Ammonium- Nitrogen (NH3-N), Nitrate-Nitrogen (NO3-N), Nitrite-Nitrogen (NO2-N) Total coliform (TC), Fecal coliform (FC), Sodium (Na+) and Boron(B) Water quality is categorized into five levels based on the values of water quality index as Excellent (WQI = 95 to 100), Good (WQI = 80 to 94), Fair (WQI = 65 to 79), Marginal (WQI = 45 to 64) and Poor (WQI = 0 to 44). The sensitivity analysis shows that this WQI is not influenced by any one or few parameters but it is a combined effect of all the parameters. It is applied to Purna (Tapi) river basin of Maharashtra (India). Key words: Method of aggregation, Purna River, Water Quality Index, water quality parameters INTERNATIONAL JOURNAL OF CIVIL ENGINEERING AND TECHNOLOGY (IJCIET) ISSN 0976 – 6308 (Print) ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), pp. 119-134 © IAEME: www.iaeme.com/ijciet.asp Journal Impact Factor (2013): 5.3277 (Calculated by GISI) www.jifactor.com IJCIET © IAEME
  • 2. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 120 1. INTRODUCTION Nowadays environmental protection and water quality management has become an important issue in public policies throughout the world Many countries have introduced a scheme of river water quality monitoring and assessment of surface water in terms of their physical, chemical, biological and nutrient constituents and overall aesthetic condition [1]. There are number of methods to analyze water quality data depending on informational goals, the type of samples and size of sampling area. The water quality is difficult to evaluate from a large number of samples each containing concentrations for many parameters. One of the most effective ways to communicate information on environmental trends and river water quality in particular is with indices Water quality index is a means to summarize large amount of water quality data in to simple language (i.e. good, average or poor quality) for responding to management and the general public in consistent manner. It tells us whether the overall quality of water body possesses a potential to various uses of water such as irrigation, recreation or drinking water purpose. Water Quality Index (WQI.) a great deal was given to the development of index methods by Brown R. M., McClelland N. R., Deininger R. A. and Tozer R. Z. [2] of United States proposed a WQI known as National Sanitation Foundation Water Quality Index (NSF WQI.) It was designed to evaluate general water quality irrespective of water use. It included nine water quality parameters - Dissolved Oxygen (DO), Fecal Coli form (FC), pH, Biochemical oxygen demand (BOD), Nitrate - Nitrite, Phosphorous, turbidity, temperature and total solids Initially water quality and score ranges were subdivided into seven classes as follows. Excellent (90-100), Good (80-89), slightly good (70- 79), Average (50-59), slightly bad (40-49), bad (20-39) and very bad (below 19). Initially it was based on arithmetic mean of weighted sub-index of each variable. So it was not significantly sensitive to change in the values of variables. Then it was modified by taking the geometric mean After modification the water quality and score ranges were subdivided into five classes i.e., Excellent- A (91-100), Good-B (71-90), Medium-C (51-70), Bad-D (26-50) and Very bad –E (0-25) It serves as the basis of other several water quality indices. Curtis G Cude [3], Oregon Department of Environmental Quality [4] had developed Oregon water quality index (OWQI) in 1970 and modified it in 1990. The OWQI also serves as the bench mark indicator of stream water quality for the Oregon Progress Board. Bindu M. Lohani and G. Todino [5] used factor analysis (FA) to develop water quality index for Chao Phraya river in Thailand. Bhargave D. S., (1985) [6] suggested grouping of water quality parameters for drinking purpose and evaluated a water quality index for drinking water supplies. L Gabriel T., de Azevedo, Timothy K. Gates, Darrell G. Fontane, John W. Labadie and Ruben L. Porto [7] had combined the surface water quantity and quality objectives to develop water quality routing and water allocation model for Piracizaba river in Brazil. Six management alternatives combining various reservoir policies with differing levels of treatment were suggested. Canadian Council of Ministers for Environment (CCME) [8] developed a water quality index called as Canadian Council of Ministers for Environment Water quality Index (CCME WQI) it compared observations to a bench mark where bench mark may be a water quality standard or site specific variable concentration. It included ten water quality variables including 2, 4- D and lindane, it quantifies for one station over a predetermined period of time (typical one year) the number of parameters that exceeded the bench mark the magnitude of exceedance and the number of records exceeded the bench mark. The index is flexible in terms of the bench marks that are used for calculations Sites at which water quality measurement never or rarely exceed the benchmark have high CCME WQI (near 100) where as sites that routinely have measurements that exceed benchmarks have low CCME WQI (near 0).The water quality levels suggested are Excellent (95 - 100), Good (80-94), Fair (65-79), Marginal (45-64) and Poor (below 45) Shiow - Mey Liou, Shang - Lien Lo and Shan - Hsien Wang (2004) [9] proposed a overall index for water quality in Taiwan and
  • 3. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 121 its application in Keya river. Ahmaid Said et.al [10] defined a new water quality index for Big Lost river water shed in Idhao. to assess water quality for general use Chinmoy Sarkar and S. A. Abbasi, [11] have developed a software called QUALIDEX to determine various WQI William Ocampo- Duque et.al [12], have developed WQI by using fuzzy inference system. S. S. Asadi, Padmaja Vuppala and M. Anji Reddy [13] assessed the ground water quality in Municipal corporation of Hyderabad (India) by using water quality index related to land use. They have used remote sensing and GIS techniques for evaluation of groundwater quality for development of water quality index Fuzhan Nasiri et al. [14], proposed fuzzy multiple attribute decision support system to compute water quality index and to provide alternative plans based on improvement in water quality index. Prabhata K. Swamee and Aditya Tyagi [15] used alternative method to describe water quality using aggregate index consisting of sub-indices for water quality variables. L. K. Diadovski and M. P. Atanassova [16] had developed an integral index of the tropic pollution level for Mesta river of Bulgeria. The water quality parameter considered were BOD, COD, total nitrogen, total phosphorus DO, metals like cadmium chromium copper, Zinc and lead, detergent phenol and coli form. K values for each parameter was determined and the integral index was formulated. Mohsen [17] had developed WQI to describe water contributed by mining activities in Malaysia. The water quality index was calculated by considering nine water quality parameters. Yilmaz Icaga (2007) [18] suggested a WQI model using fuzzy logic and applied it to assess the water quality of Eber Lake (Turkey). He has tried to remove the ambiguities due to concentration level of the parameter very close to the permissible limits. Prakash Raj Kannad, Seockheon Lee Young Soo Lee, Sushil Raj Kannel, Siddhi Pratap Khan [19] have investigated: WQI considering 18 water quality parameters, WQImin &WQIm (mean water quality index) and WQIDO (considering a single parameter DO) Hulya Boyacioglu [20] ,[21] developed universal WQI (UWQI) based on European Classification Scheme Andre Lermontov et al [22], used fuzzy logic to develop water quality index called as fuzzy water quality index (FWQI) for Pardo river, Brazil. Chaiwar Prakirake et al.[23], developed water quality index (WQI) applying Delphi technique Dinesh Kumar and Babu J. Allappat [24] studied National Sanitation foundation water quality index (NSF-WQI) and brought out the short comings in the formation of NSF WQI and suggested the possible improvement. M. K. Chaturvedi and J. K. Bassin (2009) [25] have assessed the water quality index for water treatment plant and bore well in Delhi area using NSFWQI to classify water quality as excellent, good, medium, bad and very bad. Abdul Hameed Jawad Alobaidy [26] developed WQI using cluster analysis and by considering thirteen water quality parameters Mohamad Ali Fulazzaky et. al [27], assessed the water quality of Selongor river from nine stations along the main stream using WQI. Avnish Chauhan and Suman Singh [28] developed WQI by considering eight water quality variables (Turbidity, DO, BOD, COD ,free CO2, Total solids( TS),Total Suspended Solids(TSS) & TDS) & applied it to evaluate Ganga water for drinking purpose & concluded that Ganga Action Plan launched by Government of India has failed to reduce the pollution level in Ganga river. Abdul Hameed M. Jawed Alobaidy, Haider S. Abid and Bahram K. Maulood [29] developed water quality index considering ten water quality parameters. This WQI was applied to assess the water quality of Docan Lake, Iraq. 1.1. Aggregation Functions It is the most important step in calculating WQI. In order to minimize ambiguity and eclipsing, it is necessary to identify an appropriate function of calculating and aggregated score. The following functions are normally used. Table 1 shows various aggregation functions
  • 4. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 122 Table 1: Various aggregation functions Aggregation function Formula Remarks Weighted sum index ܹܳ‫ܫ‬ ൌ ෍ ܳ௜ ௡ ௜ୀଵ ܹூ This method of aggregation is free from ambiguity but suffers from eclipsing. Multiplicative product index or weighted geometric function WQI ൌ ෑ Qi୛୧ ୬ ୧ୀଵ In this aggregation function, an index is zero if any one sub index is zero. This characteristic eliminates the eclipsing as well as ambiguity problem Weighted Solway function ܹܳ‫ܫ‬ ൌ 1 100 ሼܹ௜ܳ௜ሽଶ Un-weighted Solway function ܹܳ‫ܫ‬ ൌ 1 100 ൜ 1 ݊ ෍ܳ௜ሽଶ ௡ ௜ୀଵ Un-weighted geometric function WQI= ሼ∑ ܳ௜ ௡ ௜ୀ଴ }1/n Root mean square function ܹܳ‫ܫ‬ ൌ ඥ0.5ሼ‫݊݅ܯ‬ሺܳ௜ሻଶሽ ൅ ቈሺ1/݊ሻට∑ܳ௜ ଶ ቉ Un-weighted harmonic square mean function ܹܳ‫ܫ‬ ൌ ඨ ݊ ൛∑ ሺܳ௜ሻ௡ ௜ୀଵ ଶ ൟ Maximum Operator index ܹܳ‫ܫ‬ ൌ ‫ݔܽܯ‬ ሼI1, I2, I3, … … Inሽ This is ideally suited to applications in which an index must report if at least one recommended unit is violated Minimum Operator index ܹܳ‫ܫ‬ ൌ ‫݊݅ܯ‬ ሼI1, I2, I3, … … Inሽ This aggregation method is free from eclipsing as well as ambiguity Where, ܳ݅ = sub-index for ݅th variable ܹ݅ = relative weight for ݅th variable 2.0 MATERIALS AND METHODS 2.1 Development of Water Quality Index The indices are formulated based either on studies conducted by the indices developers or are formulated based on the Delphi technique which takes into account the opinion of experts or mathematical formulation or by using fuzzy logic. In this study WQI is developed as follows
  • 5. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 123 2.1.1 Selection of parameters Water quality parameters were selected based on the criteria- Parameters considered by previous researchers, parameters for which data is available and will be available over wide range of time, parameters producing adverse effect on human health It includes twenty five water quality parameters such as Color water temperature, pH, Electrical Conductivity (EC), Turbidity, Suspended Solids (SS), Total Dissolved Solids (TDS), Total Hardness (TH), Total Alkalinity (TA), Dissolved Oxygen (DO), Biochemical oxygen demand (BOD), Chemical oxygen demand (COD), Sulfates (SO4 - - ),, Chlorides, Total Phosphates ( TP - ), Calcium (Ca++ ), Magnesium (Mg++ ), Fluorides Ammonium- Nitrogen (NH3-N), Nitrate-Nitrogen (NO3-N), Nitrite-Nitrogen (NO2-N) Total coliform (TC), Fecal coliform (FC), Sodium (Na+) and Boron(B) 2.1.2 Assigning weight Each selected parameter was assigned a weight (WA) based on the criteria shown in Table 2 and Table 3. The parameter which produces adverse effect on human health, has more concentration relative to other parameters and requiring advance or special treatment method for its removal, is assigned less weight so that it should lower the WQI. The parameters which does not have any adverse effect on human health, has less concentration relative to other parameters and requires conventional method for its removal is assigned a higher weight so that it should increase the WQI. Excursion for parameter is determined based on the concentration (test value) of parameter and the guideline value. It is determined as follows. Table 2: Importance of water quality parameters Parameter Unit WHO [30], BIS [31], and CPCB [32] permissible limits Effect on human health beyond permissible limit/ guideline value Method for removal Remarks Color TCU 15 No direct health effect Aesthetically unpleasant [31] Conventional * treatment Color is due to natural organic matter and colloidal matter from suspended solids, iron, manganese, Here true color is considered. Temperature O C 18 - 22 No health effect Only aesthetic effect - Higher temperature suggests that the water has fewer amount of insoluble pollutants [33] Temperature is known to influence pH, alkalinity and DO [34] Rate of biological reaction and production of bacteria increases [1]
  • 6. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 124 pH - 6.5 – 8.5 No sufficient evidences for adverse effect are available Only aesthetic effect Conventional treatment pH > 8.5, water is bitter in taste. [35] Ammonia changes to more toxic state of un-ionized ammonia at pH> 7. Color intensity increases with increase in pH [36] Electrical Conductivity µS/cm 750 No health effect It greatly affects the taste [26] Conventional treatment Depends on amount of total dissolved solids in water. It represents he salinity It is function of temperature and number of dissolved ions in water. [10, 33] Water reach in bicarbonate, calcium and magnesium has low conductivity. Water with high conductivity has more concentration of sodium and chlorides. [7] Turbidity NTU 5 Aesthetic ally unpleasant [31] Conventional treatment Indicates more amount of suspended matter and indicates possibility of harmful matter [10] Suspended Solids mg/l 25 No direct adverse effect on human health Only aesthetic effect Conventional treatment It contributes to turbidity of water. It increases water temperature by absorbing heat from sunlight leading to depletion of DO [37] Total Dissolved Solids mg/l 500 Only aesthetic effect Conventional treatment Affects electrical conductivity Total hardness mg/l 300 Only aesthetic effect Lime softening Reduces toxicity of cadmium, lead, nickel and zinc [38] Total Alkalinity mg/l 200 Only aesthetic effect Conventional treatment If alkalinity is too high water becomes turbid.
  • 7. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 125 Biochemical oxygen demand mg/l <3 No direct health effect Conventional method High BOD causes oxygen depletion [9] Chemical oxygen demand mg/l <20 No direct health effect Conventional method -- Sulfates mg/l 250 No direct health effect It imparts taste to water [36] Ion exchange -- Chlorides mg/l 250 Impart salty taste to water [36] Desalination -- Calcium mg/l 75 It imparts taste to water Lime softening, Activated carbon Increases hardness Magnesium mg/l 30 It imparts taste to water Lime softening, Activated carbon Increases hardness Fluorides mg/l 1.5 Causes dental fluorosis, skeletal diseases, enamel mottling and bone deformations [7, 38] Excess fluoride causes sequence o changes in teeth, bone and tissues leading to simple mechanical back pain to severe crippling and neurological impairment, stiffness in the neck and joints [38] Fluoride concentration over 1.5 mg/l poses high risk of fluorosis to people. The risk increases with increase in fluoride content. [39] Concentration below 0.6mg/l causes dental carries [36] De- fluoridation by ion exchange activated alumina -- Dissolved Oxygen mg/l 6 -10 No health effect Only aesthetic effect Aeration Depends on temperature of water [10] Less concentration converts nitrates to nitrite and sulfates to sulfides
  • 8. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 126 Total phosphates mg/l 0.4 Only aesthetic effect Precipitation with Fe (III), Aluminum (III) Excess phosphorus causes algal growth decreasing the DO level & rises water temperature [10] Ammonium- nitrogen mg/l 0.5 Only aesthetic effect Ion exchange It depends on temperature, pH and total dissolved solids [3] Nitrate- nitrogen mg/l 10 High concentration causes methaemoglobinemia or blue baby disease in infants Ion exchange -- Nitrite- Nitrogen mg/l 1 Presence of nitrite in water is dangerous Nitrite reacts with nitro- sotable compounds in the body to form N- nitro -so compounds which are carcinogenic [36] Conventional treatment (Chlorination ) -- Parameter Unit WHO guideline value / IS / CPCB permissible limits Effect on human health beyond permissible limit/ guideline value Method for removal Remarks Total coliform MPN/ 100ml 0 Causes gastroentitis, urinary tract infection, diarrhea , typhoid fever, bacillary dysentery[36] Conventional treatment It is influenced by temperature Faecal coliform MPN/ 100ml 0 Causes gastroentitis, urinary tract infection, diarrhea [36] Conventional treatment It is influenced by temperature Sodium mg/l 200 Impart taste to water Ion exchange -- Boron mg/l 0.5 It develops metal toxicity It is toxic to reproductive tract Ion exchange and Reverse Osmosis --
  • 9. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 127 Table 3: Criteria for assigning weights to water quality parameters Sr. No. Criteria Description Weight (WA) Minimum weight Maximum weight 1 Effect on human health Aesthetic effect only 2 1 2Aesthetic effect and adverse effect on health 1 Only adverse effect on health 1 2 Parameter concentration related to concentration of other parameters Excursion of parameter concentration less than average excursion 2 1 2 Excursion of parameter concentration more than average excursion 1 3 Treatment method (Method for removal) Conventional treatment process 2 1 2Advance / Special treatment process 1 Minimum / Maximum weight 3 6 Test value exceeds the guideline value excursion ൌ ቂ ்௘௦௧ ௏௔௟௨௘ ீ௨௜ௗ௘௟௜௡௘ ௩௔௟௨௘ െ 1ቃ (1) Test value below the guideline value excursion ൌ ቂ ீ௨௜ௗ௘௟௜௡௘ ௏௔௟௨௘ ்௘௦௧ ௏௔௟௨௘ െ 1ቃ (2) Calculation of relative weight A relative weight ሺܹRሻ for each parameter is calculated by using “equation (3)” [i.e. dividing assigned weight of parameter (WA) by sum of assigned weights of all parameters ሺ ∑ܹA ሻ]. ܹோ ൌ ௐಲ ∑ ௐಲ , and ∑ܹRൌ 1 (3) 2.1.3 Construction of Sub-Index Equations for Individual Selected Parameter To assign the sub-index values, the water quality parameters guideline values (permissible limits) of World Health Organization [30], Bureau of Indian Standards (BIS) [31] and Central Pollution Control Board (CPCB) [32] are used The water quality sub-index equations are formulated according to the water quality classification used in this study The For a parameter which requires only conventional method of treatment, the parameter concentration equal to guideline value is considered at WQI value of 80 whereas for a parameter which requires advance or special method of treatment, parameter concentration equal to guideline value is considered at a WQI value of 60 This is done so that WQI should represent correct water quality The sub-index equations for various parameters are shown in Table 4
  • 10. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 128 Table 4: Sub-index equations Water quality parameter Sub-index equation Water quality parameter Sub-index equation Color x ≤ 5, 15 < x ≤ 300, x ≤ 15 x > 300, y=100 y = -0.254x+81 y = -1.872x+106.1 y = 0 Chlorides x ≤ 78, 75 < x ≤ 5000 x > 5000, y = 100 y = -23.3ln(x)+198.9 y = 100 Temperature x ≤ 3, x ≤ 18, 18 > x ≤22, 22 < x ≤37, x > 37, y = 0 y = 6.441x-12.37 y = 100 y = -6.228x+233.7 y = 0 Calcium x ≤ 10, 10 < x ≤ 425, x > 425 y = 100 y = 0.0001x2 - 0.274x+98.73 y = 0 pH x ≤ 2, 2 < x < 7 7 ≤ x ≤13, x >13, y = 0 y = 2.695x2 -5.95x+2 y = 2.914x2 -78.66x+528 y = 0 Magnesium x ≤ 5, 5 < x ≤ 180, x > 180, y = 100 y = 0.001x2 -0.716x+100 y = 0 Electrical conductivity x ≤ 275, 275<x ≤ 5000 3700<x≤7500 x>7500, y = 100 y = 2E-06x2 -0.081x+108.4 y = 3E+06x-1.41 y = 0 Fluorides x ≤ 0.15, {0.15< x≤ 0.7, and 1 < x ≤ 2.2} 0,7 < x ≤ 1, x > 2.2, y = 0 y = 65.8x5 +412.2x4 - 888.8x3 +685.8x2 - 47.27x+3.415 y = 100 y = 0 Turbidity x ≤ 2, 2 < x ≤ 200, x> 200, y = 100 y = -21.4ln(x)+115 y = 0 Total phosphates x ≤ 0.1, 0.1 < x ≤7.5, x > 7.5, y = 100 y = -22.4ln(x)+47.88 y = 0 Suspended solids x ≤ 5, 5 < x ≤ 190, x > 190, y = 100 y = 0.001x2 -0.542x+102 y = 0 NH3 - N x ≤ 0.03, 0.3 < x ≤ 40, x> 40, y = 100 y = -13.8ln(x)+51.78 y = 0 Total dissolved solids x ≤ 180, 180<x < 28000 x > 28000 y = 0 y = -18.5ln(x)+196.4 y = 0 NO3 – N x ≤ 2, 2 < x ≤ 14.5, 15 < x ≤ 50, x > 40, y = 100 y = -4.356x+102 y = -30.6ln(x)+120.3 y = 0 Total hardness x ≤ 50, 50< x ≤ 2500, x > 2500, y = 100 y = 1E-05x2 -0.066x+109.8 y = 0 NO2 - N x ≤ 0.04, 0.4 < x ≤ 28, x > 28, y = 100 y = -15.3ln(x)+52.11 Total alkalinity x ≤ 20, 20 < x ≤ 780, 750<x≤3000, x>3000, y = 100 y = -0.105x+102 y = -0.008x+26 y = 0 Total Coliform x ≤ 0, 0< x ≤ 50, 50< x ≤ 400, 400 < x ≤ 70000 x>70000, y = 100 y = -0.403x+100 y = -0.028x+81.2 y = -0.001x+70.77 y = 0 Dissolved oxygen x ≤< 1, 1 ≤ x <8, 8 ≤ x ≤ 10, 10 < x ≤ 13, x >13, y = 0 y = -0.14x3 +1.468x2 + 9.519x-2.088 y = 100 y = -0.14x3 +1.468x2 + 9.519x-2.088 y = 0 Fecal Coliform x ≤ 0, 0< x ≤ 20, 20 < x ≤ 200, 200 < x ≤ 34000, x> 350000, y = 100 y = -x+100 y=-0.055+81.11 y = -0.002x+69.76 y= 0 BOD x ≤ 1, 1 < x ≤ 90, x > 90, y = 100 y = -23.3ln(x)+105.7 y = 0 Sodium x ≤ 65, 65 < x ≤ 2000, x > 2000, y = 100 y = -27.8ln(x)+212.1 y = 0 COD x ≤ 9, 9 < x ≤ 450, x > 450, y = 100 y = -25.3ln(x)+155.5 y = 0 Boron x ≤ 0.075, 0.075 < x ≤ 10, x>10, y = 100 y = -19.9ln(x)+47.22 y = 0 Sulfates x ≤ 40, 40 < x ≤ 2000, x > 2000, y = 100 y = -23.4ln(x)+188.8 y = 0 Where, x = Concentration of parameter and y = Water quality Sub-index 2.1.4 Overall WQI The multiplicative product method of aggregation is used to overcome problems of eclipsing and ambiguity Overall water quality index is determined by formula given in “equation (4)” ܹܳ‫ܫ‬ ൌ ∑ ൫ܳ௜ ௐ೔ ൯௡ ௜ୀଵ (4)
  • 11. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 129 2.1.5 Water Quality Categorization The water quality is classified into five categories Table 5 shows the water quality index (WQI) ranges and the classification of water Table 5: Ranges of Water Quality Index and water quality category (CCME, 2001) Water quality category Water Quality Index Values Water quality description Excellent 95 - 100 Water quality is protected with a virtual absence of threat or impairment. All measurements are within objectives virtually of all the time Good 80 - 94 Water quality is protected with minor degree of threat or impairment; conditions rarely depart from desirable levels Fair 65 - 79 Water quality is protected but occasionally threatened or impaired; conditions sometimes depart from desirable levels Marginal 45 - 64 Water quality is frequently threatened or impaired; conditions often depart from desirable levels Poor 0 - 44 Water quality is almost always threatened or impaired; conditions usually depart from desirable levels Source: Canadian water quality guidelines for protection of aquatic life : CCME water quality index”, User’s manual. CCME 2001 3.0 STUDY AREA The study area includes Purna (Tapi) river basin of Maharashtra, INDIA Purna river originates at It flows southwards through Amravati district, then westwards through Akola and Buldana districts to discharge itself into Tapi river near Changdeo in Jalgaon district Total length of Purna river is 334 m The river is perennial and has many tributaries The climate of this area is dry and hot except for monsoon (June-September) The basin area is about 7800 Km2 out of which central 3000 Km2 is known as saline track Yearly rainfall is 700-800 mm Six stations were identified for development of WQI Fig 1 shows Purna (Tapi) river basin and location of identified stations Fig 1: Purna (Tapi) river basin
  • 12. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 130 4.0 RESULTS AND DISCUSSION Table 6 shows typical water quality characteristics of Purna (Tapi) river basin WQI so developed is applied to selected stations of Purna (Tapi) river basin Temperature, total coliform, Fecal coliform, Suspended solids and turbidity exceeded the guideline value deteriorating the water quality and lowering WQI Fig shows parameters that are exceeded (as percentage of total exceedance) over the guideline value More than 50% exceedance is due to temperature, total coliform and Fecal coliform together where as parameters like Sulfates, Chlorides, Calcium, Magnesium, Total phosphates, Nitrate Nitrogen and sodium are not exceeded the guideline value at all The water quality of these stations is categorized as good. Table 6: Water quality characteristics of Purna (Tapi) river basin Parameter Mean± SD Parameter Mean± SD Parameter Mean± SD Color 6 ±0.167 DO 6.29±0.669 TP 0.066±0.079 Temperature 28.7 ± 8.440 BOD 2.73±0.924 NH3-N 0.202±0.041 1.041pH 8.34±0.213 COD 10.05±0.637 NO3-N 0.688±0.597 EC 438±162 Sulfates 12.44±6.152 NO2-N 0.07±0.200 Turbidity 32±70 Chlorides 51.78±41.903 Total Coli 91±99 SS 33±48 Calcium 26.50±8.091 Faecal Coli 37±48 TDS 289±120 Magnesium 22.25±9.886 Sodium 87.24±27.552 TH 158± Fluorides 0.534±0,267 Boron 0.151±0.152 TA 164±51 Fig 2 shows variation in WQI in winter and summer for these stations Due to increased concentration of turbidity, suspended solids, total coliform and fecal coliform in winter lower the WQI whereas the water is very clean with concentration of turbidity and suspended solids improved the WQI in summer Fig 3 shows variation in WQI for these stations during 2005- 2008. Table 7 show correlation coefficient between WQI and concentration of parameters All parameters shown negative correlation with negative correlation with WQI except for color, pH, temperature, dissolved oxygen, sulfates and fluorides Positive correlation between WQI and dissolve oxygen indicates that as dissolved oxygen increases WQI also increases pH values are mostly less than 8.5 As pH concentration approaches to guideline value of 6.5-8.5, WQI increases Guideline value range for temperature is 18 O C–22 O C as water temperature approaches to this range WQI increases For color and sulfates the concentrations are well within guideline value, so the decrease in WQI is not due to these parameters but it is due to the combined effect of all other parameters. While deciding the water quality sub-index equation, lower guideline value of 0.6 mg/l is decided to avoid dental carries Fluoride concentration are well within guideline value and as these concentrations approaches to 0.6 mg/l, it lowers the WQI
  • 13. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 131 Fig 2: Variation in WQI in winter and summer Fig 3: Variation in WQI during 2005-2008 Table 7: Correlation coefficient between WQI and Concentration of parameters Parameter r Parameter r Parameter r Color 0.435 DO 0.880 TP -0.901 Temperature 0.486 BOD -0.898 NH3-N -0.597 pH 0.411 COD -0.838 NO3-N -0.255 EC -0.610 Sulfates 0.172 NO2-N -0.250 Turbidity -0.689 Chlorides -0.795 Total Coli -0.955 SS -0.960 Calcium -0.303 Fecal Coli -0.831 TDS -0.7 Magnesium -0.449 Sodium -0.804 TH -0.777 Fluorides 0.346 Boron -0.064 TA -0.496 r =Correlation coefficient 4.1 Sensitivity Analysis WQI was also determined by removing each parameter at a time Fig 6 shows WQI after removal of the said parameter. It is observed that WQI is not varied much due to removal of an individual parameter. Table 8 shows correlation coefficient between WOI and WQI after a particular parameter is removed. All parameters have shown positive correlation with WQI after its removal. No parameters have shown negative correlation with WQI after its removal. It shows that WQI is not influenced only by one or few parameters but it is the combined effect of all the parameters. It is varied much due to turbidity, temperature and fluorides. Turbidity is exceeded much the guideline value during winter particularly in monsoon which contributed to lower the overall WQI After removal of turbidity, WQI is increased. Climate of Purna (Tapi) river basin being dry and hot throughout the year, water temperature exceeded the guideline value to lower WQI. After removal of temperature WQI is increased Fluoride concentration is well within guideline value. The water quality sub-index equation is such that it lowers WQI if concentration of fluoride is less than 0.6 mg/l to avoid dental carries, after its removal WQI is increased. Though percentage exceedance of concentration is more, but as it is within certain limit which have not contributed much to lower WQI after removal of these parameter. 78 80 82 84 86 88 90 S1 S2 S3 S4 S5 S6 WQI Winter WQI Summer WQI 70 75 80 85 90 S1 S2 S3 S4 S5 S6 2005 2006 2007 2008 WQI
  • 14. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 132 Table 8: Correlation coefficient between WQI and WQI after removal of particular parameters Parameter r Parameter r Parameter r Color 0.840 DO 0.872 TP 0.830 Temperature 0.913 BOD 0.901 NH3-N 0.895 pH 0.843 COD 0.827 NO3-N 0.843 EC 0.748 Sulfates 0.809 NO2-N 0.880 Turbidity 0.896 Chlorides 0.840 Total Coli 0.830 SS 0.872 Calcium 0.830 Fecal Coli 0.830 TDS 0.757 Magnesium 0.895 Sodium 0.840 TH 0.783 Fluorides 0.651 Boron 0.871 TA 0.895 r =Correlation coefficient 5.0 CONCLUSION In this study, WQI based mathematical formulation by assigning weights to various physio- chemical water quality parameters are proposed based on its adverse effect on human health, its concentration relative to the concentration of other parameters and method of treatment required for it. The new WQI is believed to assist the decision makers in reporting the state of water quality for drinking purpose. The applicability & usefulness of proposed methodology is revealed by a case study. The sensitivity analysis shows that this WQI is not influenced by any one or few parameters but it is a combined effect of all the parameters this WQI could be used to evaluate the water quality of any water body to judge its suitability for drinking purpose. This WQI forces the researchers to assign same weight to the same parameter, moreover this WQI is free from ambiguity and eclipsing. REFERENCES [1] A. A. Najufpoor, Z. Vojodur, M. H. Dehgani, H. Acidadi, (2007), “Quality assessment of Kashif river in North-east of Iran in 1996-2005” Journal of Applied Sciences 7(2), 2007, pp 253-257. [2] Brown, R. M: McClell and, N. I, Deininger, R. A and Ronald, G. T “A water quality index – Do we dare?” Water Sewage Works 11, 1970, pp 335- 343 [3] Curtis G. Cude, “Oregon water quality index: A tool for evaluating water quality management effectiveness” Journal of American water works association Vol. 37, No. 1, 2001, pp 125-137. [4] Curtis G. Cude, “Reply to discussion on Oregon water quality index: A tool for evaluating water quality management” by, David G. Smith, Robert J. Davies- Colley and John W. Nagels, Journal of the American management” by, David G. Smith, Robert J. Davies- Colley and John W. Nagels, Journal of the American Water Resources Association, Vol. 38, No. 1, Feb, 2002, 315-318 [5] Bindu N. Lodhani (1985), “Water quality index for Chao Phraya River” Journal of Environmental Engineering Vol. 110, No. 6, 1984 pp 1663. [6] Bhagava D. S., “Expression for drinking water supply standards” Journal of Environmental Engineering Vol 3 No. 3, 1985 pp 304-316. [7] L .Gabriel T, de Azevedo, Timothy K. Gates, “Integration of water quality and quantity in strategic river basis planning” Journal of water resources planning & management Vol. 126, No. 2, 2000, pp 85-97. [8] CCME (2001), “Canadian water quality guidelines for protection of aquatic life: CCME water quality index”, User’s manual. CCME 2001
  • 15. International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME 133 [9] Shiow Mey Lion, Shang-Lien Lo and Shan-Hsien Wang, “A generalized water quality index for Taiwan “Environmental Monitoring Assessment,96 : 35-52, 2004 [10] Ahmaid Said, David Stevens, Gerald Sehlke, (2004), “An innovative index for evaluating water quality in streams”, Environmental Assessment, Vol. 34 No. 3, 2004, pp 406-414 [11] Chinmoy Sarkar and S. A. Abbasi, “QUALIDEX – A new software for generating water quality indices”, Environmental monitoring Assessment, 119, 2006, 201-231 [12] William Andre Ocampo Duque, “On the development of decision making systems based on fuzzy models to assess water quality in rivers”, Ph. D. Thesis, Universitat Rovira I Virgili, Tarragona, 2008 [13] S. S. Aadi, Padmaja Vapulla, M Anji Reddy, “ Remote sensing and GIS technique for evaluation of ground water quality In Municipal Corporation Hyderabad (Zone-V) India” International Journal of Environmental Research and Pollution Health, 4(1), 2007 pp 45-52 [14] Furhan Iqbal, M. Ali, Abdus Salam,B. A. Khan, S. Ahmad, M. Qamar and Kashif Umer,”Seasonal variation of physio-chemical characteristics of River Soan water at Dhoak Pathan Bridge (Chakwal), Pakistan”, International Journal of Agricultural and Biology, 6 (1), 2004, 89-92 [15] Prabhata Swamee and Aditya Tyagi, “Improved method for Aggregation of water quality sub- indices “Journal of Environmental Engineering Vol. 13 No. 2, 2007 pp 220-225 [16] L. K. Diadovski and M. P. Atanasaova (2007), “Water quality management based on the integral approach” Water Quality Management, Chem. Biochem. Engg. 21 (2) 2007 pp 189- 194. [17] Mohsen Nasirin, 2007 “A new water quality index for environmental contamination controlled by mineral processing: A case study of among (Tin Talling) processing activity” Journal of Applied Science 7(20)2977-2987, 2007 [18] Yilmaz Icaga, “Fuzzy evaluation of water quality classification”, Ecological Indicators, 7, 2007, 710-718 [19] Prakash Raj Kannad, Seockheon Lee Young Soo Lee, Sushil Raj Kannel, Siddhi Pratap Khan,“Application of water quality indices and Dissolved oxygen as indicators for river water classification and urban impact assessment”, Environmental monitoring Assessment, 132,2007, 93-110 [20] Hulya Boyacioglu, “Development of water quality index based on a European classification scheme”, Water SA, Vol. 33, No. 1. Jan. 2007, pp 101-106 [21] Hulya Boyacioglu, “Utilization of water quality index method as a classification tool”, Environmental monitoring Assessment, 167 (2010), 115-124 [22] Andre Lormontov, Lidia Yokoyama, Mihail Lermontov and Maria Augusta Soares Machado, “River quality analysis using fuzzy water quality index: Riberia do Iguape river watershed, Brazil”, Ecological indicators, 9, 2009,1188-1197 [23] Chaiwat Prakirake, Pawinee Chaipraset and Sudarut Tripetchkul, (2009) “Development of Specific water quality index for water supply in Thailand” Songklanakarin J. Science Technology 31, (1) 2009 pp 91-104. [24] Dinesh Kumar, Babu J. Alappat, “N.S.F. Water quality index : Does it represents the Expert opinion?”Practice Periodical of Hazardous, Toxic and Radioactive Waste Management Vol. 13 No. 1, 2009 pp 75-79 [25] M. K. Chaturvedi and K. Basin, “Assessing water quality index of water treatment plant and bore wells in Delhi, India”, Environment monitoring Assessment, 163 ,2010, 449-453 [26] Abdul Hameed Jawad Alobaidy, “Evaluating raw and treated water quality of Tigris river within Baghdad by Index analysis”, 2010, file;//localhost/E/wqi121109.mht
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