Assessment of surface water quality of Mayur River in Khulna City

13 River water quality is one of the foremost concerns now a days as it plays a significant role in 14 human and aquatic life. Mayur River, located on the northwestern side of the Khulna city, is 15 important from numerous points of view like freshwater reservoir, navigation, water source for 16 irrigation, ground for fishing and the main wastewater route of Khulna city. However along 17 with human interruption, the unplanned and untreated crude dumping of domestic, industrial 18 and household waste into it, the natural flow of the river is totally retarded and the river water 19 quality has been degraded on a large scale due to water pollution. This pollution has colossal 20 negative impact on day to day life of the inhabitants living alongside of this river as they use 21 this water for domestic and sometimes drinking purposes. That is where the significance of 22 assessing the water quality of Mayur River has come from. The core objectives of this study is 23 to assess the water quality of Mayur River and to develop a model using statistical analysis 24 between water quality parameters (WQP) and water quality index (WQI) to interpret 25 relationship among them. Water quality was assessed on the basis of WQI calculation using 26 National Sanitary Foundation water quality index method. The temporal WQI value showed 27 that the water quality in Mayur River got worse in dry season than that of wet season due to 28 dilution. Much higher values were obtained in case of biochemical oxygen demand (BOD), 29 turbidity, total solids (TS), chloride, phosphate, nitrate and fecal coliform (FC). Pearson 30 correlation coefficient shows negative relationship among temporal average WQI with other 31 parameters except pH. Regression analysis indicates that 99.7% proportion of variance of 32 dependent variable (temporal average WQI) can be predicted from the independent variables 33 (Dissolved Oxygen (% saturation), BOD, turbidity, TS, pH, temperature change, phosphate, 34 nitrate and FC). Total nine prediction equations were formed using regression coefficients that 35 may be helpful to predict the WQI on the basis of WQP in future.

assessing the water quality of Mayur River has come from. The core objectives of this study is 23 to assess the water quality of Mayur River and to develop a model using statistical analysis 24 between water quality parameters (WQP) and water quality index (WQI) to interpret 25 relationship among them. Water quality was assessed on the basis of WQI calculation using 26 National Sanitary Foundation water quality index method. The temporal WQI value showed 27 that the water quality in Mayur River got worse in dry season than that of wet season due to 28 dilution. Much higher values were obtained in case of biochemical oxygen demand (BOD), 29 turbidity, total solids (TS), chloride, phosphate, nitrate and fecal coliform (FC). Pearson 30 correlation coefficient shows negative relationship among temporal average WQI with other 31 parameters except pH. Regression analysis indicates that 99.7% proportion of variance of 32 dependent variable (temporal average WQI) can be predicted from the independent variables 33 6 Khulna [1]. Zaman and Islam [21] worked on characteristics of KCC drainage water of existing 113 outlets over Mayur River and its treatment for safe disposal. They found the water having 114 excessive range of values in case of some water quality parameters. 115 All the above works focused mainly on the water quality parameters, water logging and 116 security of water and influence of development projects on water quality of Mayur River. In 117 most of the studies water quality was assessed on the basis of values water quality parameters 118 and comparison of them with the standard values. Here lies the reason why, the study on Water 119 Quality Index (WQI) came from. No research work has not really done for calculation of water 120 quality index to assess the water quality of Mayur River. The main objectives of this study are 121 to assess the water quality of Mayur River on the basis of WQI using NSF WQI method and to 122 conduct statistical analysis (correlation and regression) to form a model to predict the future 123 water quality of Mayur River. 124

Study Area 126
Khulna is the third largest city in Bangladesh which is located on the banks of the 127 Rupsha and Bhairab Rivers. Total of 8 sampling stations were selected on the basis of 128 reconnaissance survey conducted from Gallamari to Rayermahal including Boyra and 129 Sonadanga. The sample stations were selected on the basis of intensity of pollution of river 130 water. The stations were designated as S1, S2, S3, S4, S5, S6, S7 and S8 where "S" indicates 131 the term "Station" as shown in Table 1  (1) 153 Where I is the water quality sub-index. 154

Statistical Modeling 155
The collected data were analyzed by SPSS statistical software version 16. The related 156 correlation equation is showed at Eq. (2). 157 Where, x ̅ and y ̅ are the sample means and x and y are the individual values of related 160 water quality parameter. The regression equation will be as follows-161

3.1.Temporal Variation of Water Quality Parameters 173
Dissolved Oxygen (DO) is the one of the best parameter to assess water quality. In 174 many cases of fish kills the mortality is unswervingly due to asphyxiation as the DO levels 175 drop immensely because of organic contamination [23]. Temporal average DO is shown in 176 Table 3 during the study period. Highest average DO was 2.40 mg L -1 in July-2019 while the 177 lowest average was 1.53 mg L -1 in January-2020. DO limit should be more than 6 mg L -1 [24] 178 for surface water. The massive lowering of DO is causing the fish to die and the water of this 179 Mayur River has got worsen by dumping of different waste into water. 180 Table 3 Table 4 shows the temporal and spatial WQI distribution of Mayur River. The water 243 quality was found "Very Bad" in March-2019, April-2019 and May-2019 from station 1 to 244 station 8 except station 4 in June-2019. From July-2019 to February-2020 the water quality 245 was found "Bad" with some exception like station 6 in February-2020. 246

Correlation Analysis between Temporal average WQI and average WQP 247
The correlation data shows that the (r) value between temperature change-TS, turbidity-

3.5.Regression Analysis of between Temporal average WQI and average WQP 256
Regression analysis was carried out between temporal average WQI and nine WQP that 257 were used to calculate the water quality index using SPSS version-16.

Availability of data and materials 291
All data generated or analyzed during this study are authentic. 292

Competing interests 293
The authors declare they have no competing interests. 294

Funding 295
This work was supported by Khulna University of Engineering and Technology (KUET) 296

Authors' contributions 297
All authors read and approved the final manuscript. 298

Acknowledgement(s) 299
The authors wish to express thanks to Dr. S. M. Moniruzzaman, Professor, Department of 300 Civil Engineering, KUET who supervised with great care to complete this research. The 301 authors of this article also wish to express whole hearted appreciation and thanks to Md. 302 Shafiqul Islam, Assistant Professor, IDM, KUET for his sincere support and guidance. Thanks 303 also goes to all officers and staff of environmental laboratory the department of civil 304 engineering, KUET for providing assistance in this study. 305