20 Healthy aquatic environment is crucial for preserving aquatic lives in surface waters. Increasing 21 discharge or run -off from industrial or agricultural sources can pollute water leading to an 22 unhealthy aquatic environment that can cause distress in fishes and other aquatic lives. In places 23 with lack of infrastructure and regulatory enforcement, pollution can be particularly chal lenging 24 to handle. Assignment of an indexing system can be helpful for analyzing pollution pattern in the 25 polluted rivers which can be helpful for remediation purposes and prevention of future pollution. 26 Bangladesh currently does not have any indexing syst em in place. Assignment of indices in the 27 rivers of Bangladesh can be helpful for remediation of the rivers on a preferential basis as 28 remediation of all the rivers at once will pose challenges with funding and infrastructural 29 allocation. Parameters monito red in the water monitoring stations of ten rivers were extracted 30 from the reports published by the Department of Environment (DOE) of Bangladesh. A water 31 quality index (WQI) was assigned on the rivers across seven years of time period to identify the 32 most polluted rivers. The degree of pollution in the river was in the order of Mayuri > Buriganga 33 > Korotoa > Turag > Shitalakhya > Surma > Halda > Dhaleshwari > Mathavanga > Brahmaputra 34 based on the WQI analysis. The most polluted rivers were in areas with ma nufacturing, textile 35 etc. industries. Hence, monitoring of industrial discharge intro the rivers and regulatory 36 enforcement is crucial for the prevention of pollution in rivers. Installing more monitoring 37 stations and more frequent samplings can be helpful for better assessment of WQI of the rivers. 38 However, deployment of these strategies can be challenging for Bangladesh due to funding and 39 infrastructural constraints. Hence, a formula was developed in this study to calculate WQI in a 40 resource limited situa tion (WQI = 4.42 – 0.42 Dissolved oxygen + 0.11 Biochemical oxygen 41 demand). 42 3 Keywords: Water quality, water quality index, dissolved oxygen (DO), biochemical oxygen 43 demand (BOD), industrial discharge, pollution 44 Highl ights 45 • Rivers located in industrialized areas were highly polluted 46 • The five most polluted rivers were Mayuri, Buriganga, Korotoa, Turag, and Shitalakhya 47 • Brahmaputra and Mathavanga were in good condition 48 • Water quality index (WQI) can be predicted using the relationship derived in this study. 49 4 1. Introduction 50 All living being need water for sustaining life. Quality of life is directly correlated to 51 accessibility of clean water [1]. However, to meet the increasing demand for food and various 52 products, demand for agricultural and industrial production is increasing with time which 53 consequently causes water pollution with high strength agricultural run -off and industrial 54 discharge into receiving water bodies [2 ]. With a lack of well -developed in frastructure and 55 regulatory enforcement, water pollution is particularly more prevalent in the developing 56 countries [3]. Moreover, remediation of polluted waterbodies also poses challenge for 57 implementation due to lack of financial resources [4 ]. However, use of polluted water for 58 everyday needs including for drinking, cooking, bathing, and irrigation is a common trend in the 59 developing countries [5]. This poses a public health risk along with a high risk associated with 60 sustaining healthy aquatic lives in the waterbodies. Hence, remediation of polluted waterbodies 61 is crucial for sustainable water resources management. 62 Bangladesh is relatively a small country consisting of about 700 rivers, including tributaries 63 flowing through it that are a key source of do mestic, industrial, and agricultural water use [6]. 64 These rivers are major role players in the advancement of economic growth of Bangladesh as 65 they provide multiple uses including transportation of goods and production materials [7]. 66 However, rapid and unp lanned urbanization and industrialization to meet the demand s exerted by 67 an overly populous country resulted in an overabundant and unchecked pollution of the river 68 waters in Bangladesh with untreated discharge or run -off of chemical, industrial and agricu ltural 69 wastes, micro -organisms, or fecal matters [8,9]. In addition to the anthropogenic activities, river 70 water is also polluted for a combination of other factors such as geochemical factors, chemical 71 composition, and lithogenic structure [7,10]. About 80% of diseases in the world are caused due 72 5 to poor hygie ne and contaminated water [6]. Water pollution negatively affects the quality of life 73 for both terrestrial and aquatic beings, directly or indirectly. Therefore, water quality needs to be 74 closely monitored and maintained for achieving sustainable economic and social development, 75 and preservation of terrestrial and aquatic beings. 76 Generally, river water quality can be evaluated based on several physical, biological, and 77 chemical parameters [7]. For instance, the National Science Foundation (NSF) recommends 78 evaluation of water quality by monitoring dissolved oxygen (DO), biochemical oxygen demand 79 (BOD), fecal coliform, pH, temperature, total phosphate, nitrate, turbidity, total solids etc. and 80 assigns weights to each parameter to determine the overall qualit y of a water body [ 11]. The 81 combination of the monitored parameters in different intensities helps define the status of 82 pollution and determine the degree of it for a certain surface water body [12]. Hence, a single 83 parameter assignment considering the mon itored parameters and associated values can help 84 quantify the degree of pollution and water quality of a water body. Generally, the cumulative 85 assessment of the monitored parameters is quantified as an index termed as water quality index 86 (WQI) which is a u seful tool for overall water quality evaluation [12]. The assignment of weights 87 on different parameters and which parameters are considered for WQI calculation can vary 88 across different kind of water quality monitoring agencies. WQI has been used as a stro ng tool 89 for water quality assessment in different countries for the purposes of aquatic ecosystems 90 preservation and monitoring of water usage for different purposes [1,13]. As discussed above, 91 assessment of water quality is often poorly structured in the d eveloping countries. Consequently, 92 a universal WQI assignment and evaluation is seldom prevalent among the developing countries. 93 Similarly, Bangladesh currently monitors a few parameters only and there has been no attempt at 94 employment of WQI to assess wat er quality quantitatively and qualitatively in the country. A 95 6 WQI particularly adopted for the monitored parameters in Bangladesh will be useful for 96 determining water quality and the degree of pollution in the rivers of Bangladesh. Evaluation of 97 the pollut ion level in different waterbodies will be helpful in remediation planning and 98 management by focusing on the most polluted waterbodies on priority basis. 99 The Department of Environment (DOE) of Bangladesh monitors some parameters at different 100 monitoring stations, but DOE does not assign WQI to the different waterbodies. There are 101 several published works on assigning WQI to different water sources in Bangladesh. Two of the 102 identified studies were focused on WQI for groundwater while other studies focused on WQI for 103 surface water. Iqbal et al. (2020) studied and assigned WQI for groundwater quality evaluation in 104 Bangladesh [14]. Assignment of WQI for groundwater quality evaluation in Tala Upazila in the 105 Sathk hira district covering a smaller geographical area has also been reported [15]. However, 106 surface water is the main resource for water usage in different sectors and it is directly correlated 107 to a well -preserved aquatic ecosystem. Hence, WQI assignment to s urface water bodies will be 108 helpful for preservation of aquatic systems and remediation of the polluted waterbodies to 109 achieve sustainable water resources management [10]. Currently, there are limited studies 110 investigating different surface water quality p arameters to employ WQI to surface waterbodies in 111 Bangladesh. Hossain et al. (2019) studied water quality of the Karnaphuli river by assigning 112 WQI at five different sampling locations of the river [16]. Similar studies were published on 113 WQI assignment based on selected parameters at different sampling locations of Buriganga, 114 Turag and Dhaleshwari rivers [17,18,19,20 ]. However, a more holistic approach for WQI 115 assignment on the main rivers and more widespread area of Bangladesh is yet to be em ployed. 116 Assignment of WQI to several major rivers , especially those located in industrialized areas, will 117 be helpful for identifying the rivers requiring the most focus for remediation. Moreover, trend 118 7 analysis of water quality by studying WQI of a number of rivers across a several years of time 119 period will help understand the overall timeline, degree of improvement or deterioration in the 120 rivers. Additionally, a simplified formula for WQI prediction with one or two parameters will be 121 helpful for countries like Bangladesh where monitoring of more parameters might be challenging 122 due to lack of funds and access to other resources. Therefore, the objective of this study is to (i) 123 analyze DO and BOD trend in the selected rivers , and (ii) assign and analyze WQI t rend in ten 124 selected rivers and investigate the correlation of WQI with the observed parameters. A 125 correlation between WQI with one or two most frequently observed parameters (DO and BOD in 126 Bangladesh) will help evaluate water quality in a resource limited situation , especially in 127 developing countries, where monitoring of more parameters might be limited by availability of 128 funds and infrastructures. 129 2. Methods 130 Ten rivers were selected based on the availability of most data points both in terms of number of 131 parameters and timeline of data collection for trend analysis of parameters (DO and BOD) and 132 WQI calculation [Figure 1] . Moreover, the selected ten rivers were located in industrialized, 133 urban residential or agricultural areas. The ten selected rivers were Buriganga, Shitalakhya, 134 Turag, Dhaleshwari, Brahmaputra, Halda, Moyuri, Surma, Korotoa, Mathavanga. Among these 135 rivers, Buriganga, Shitalakhya, Turag, Dhaleshwari, Moyuri, Surma, Korotoa rivers have 136 different types of industries located on their banks or in surrounding areas. Halda flows though 137 areas where tea gardening is prevalent while Mathavanga flows through Chuadanga district that 138 is mostly agricultural economy dependent. Brahmaputra flows through an urban unindustrialized 139 residential area, Mymensing h district. 140 8 141 Figure 1: Map of Bangladesh showing the ten selected rivers and corresponding monitoring 142 stations 143 9 Water quality reports published by the DOE from 2010 till 2016 (the latest published report) 144 were extracted for analysis of DO and BOD trend for seven years (2010 – 2016) and WQI 145 calculation using DO, BOD, pH, and SS [21,22,23,24,25] . Among the four parameters used for 146 WQI calculation, DO and BOD trend over the years was analyzed for the ten selected rivers as 147 pH was found to be near the neutral range and SS data was not available for all rivers across the 148 observed time period. Moreover, DO and BOD can be a good indicator of pollution in the rivers. 149 The amount of oxygen available in water for aquatic uptake is D O and if it drops between 2 – 4 150 mg/L, fishes get distressed in a hypoxic condition [ 26]. BOD is an indirect measurement of the 151 organic matters present in water which is quantified by tracking DO depletion needed for 152 degradation of the organic matters [ 27]. Therefore, there is a DO depletion in a water sample 153 with high BOD concentration; typically, BOD greater than 15 mg/L indicates a very polluted 154 water unsustainable for healthy aquatic environment. In a limited data acquisition situation, DO 155 and BOD can be very helpful for determining water quality of a waterbody. Therefore, DO and 156 BOD was calculated for all ten rivers from 2010 – 2016 using the data extracted for DOE 157 reports . 158 In addition to DO and BOD, two other parameters, i.e. pH and SS were considered f or WQI 159 calculation. For aquatic sustainability, pH ranging from 6 – 9 is sufficient and a sudden change in 160 pH of a water indicates introduction of foreign matters into the waterbody [28]. The amount of 161 insoluble matters is quantified as SS which might be a n indicator of a number of aquatic events, 162 i.e. runoff of particulate organics, algal bloom etc. WQI was calculated using a weighted average 163 of four parameters, i.e. DO, BOD, suspended solids (SS), and pH. Weights were employed on 164 DO, BOD, SS , and pH according to their values and a n average of the assigned weighted values 165 were calculated for quantifying the water quality of the rivers as WQI [Equation 1]. 166 10 𝑊𝑄𝐼 = 1 𝑛∑ 𝐼𝑖𝑛 𝑖=1 [Equation 1] 167 where, n = the number of parameters monitored, and I is the weight normalized value assigned to 168 the monitored parameters. 169 The weights assigned to the parameters for WQI calculation was conducted following weight 170 assignment proposed by Liou et al. (2004) [28]. Table 1 lists the weight assignment to the 171 parameters use d in this study for WQI calculation. 172 Table 1: Weight assignment on the parameters (pH, dissolved oxygen, biochemical oxygen 173 demand, suspended solids) used for water quality index ( WQI ) calculation 174 Parameter weight Parameters for WQI calculation Qualitative interpretation Quantitative weight pH DO (mg/L) BOD (mg/L) SS (mg/L) Good 1 6.5 – 8.5 > 6.5 < 3 < 20 Slightly polluted 3 4.6 – 6.4, 8.6 – 10.4 4.6 – 6.4 3 – 4.9 20 – 49 Moderately polluted 6 2 – 4.5, 10.5 – 12 2 – 4.5 5 – 15 50 – 100 Very polluted 10 < 2, > 12 < 2 > 15 > 100 175 A qualitative interpretation of the WQI was made according to Table 2. 176 Table 2: Qualitative interpretation of water quality index (WQI) assigned to the rivers 177 Water quality index (WQI) Quantitative interpretation < 2 Good 2 – 2.9 Slightly polluted 3 – 4.9 Moderately polluted ≥ 5 Very polluted 178 In addition to the assigned weights and WQI calculation, regression analysis of the data points 179 across seven years were performed to analyze correlation of WQI with DO or BOD or both to 180 11 help predict water qualit y of rivers in resource -limited situations where only DO or BOD 181 parameters are available for monitoring. The regression analysis was performed using the 182 Analysis ToolPak add -on provided with Microsoft Excel. 183 3. Results & Discussion 184 3.1. Dissolved oxygen (DO) level in ten selected rivers 185 The amount of gaseous form of oxygen (O 2) dissolved in the water is measured as DO which 186 indicates the availability of oxygen for aquatic uptake. DO is therefore crucial for all forms of 187 aquatic lives [29]. By the direct absorp tion of O 2 from the atmosphere, rapid movement of water 188 and byproduct of photosynthetic activities atmospheric oxygen enters water. A number of factors 189 including temperature, salinity, presence of organic matter can affect DO level in water. The DO 190 levels in the ten selected rivers were extracted from the DOE reports and then annual average 191 was calculated to analyze trends of DO change 2010 -2016 for all ten rivers as presented in 192 Figure 2. 193 12 194 Figure 2: Level of dissolved oxygen (DO) in ten rivers of Bangladesh across a time period of 195 seven years starting from 2010 till 2016. 196 Three rivers, Buriganga, Turag and Mayuri had overall the lowest DO for the seven years of 197 period. Except for 2013, DO level was near or below 2 mg/L (1.575 – 2.150 mg/L) in Buriganga 198 in all other years. Similarly, DO of Turag was in the range of 1.66 – 2.455 mg/L all through the 199 seven years. The extremely hypoxic conditions in Buriganga and Turag might have been caused 200 by indus trial pollution as both these rivers are located in the heavily industrialized areas of 201 Bangladesh [5,18] . The surrounding areas of Buriganga is a hotspot for the tannery industry 202 while many textile industries are located on or near the banks of Turag. May uri had 0.280 – 203 1.675 mg/L DO in all through the seven years. Apart from industrial pollution, another reason for 204 low level of DO in Mayuri can be relatively higher salinity in Mayuri as the river is very closely 205 located near the Bay of Bengal. 206 Shitalakhy a, Dhaleshwari, and Korotoa had DO level near 4 mg/L in the recent reported years, 207 showing an overall downward trend. Shitalakhya river water sampling locations were near two of 208 biggest factories in the country, Advanced Chemical Industries (ACI) Factory a nd Ghorashal 209 0246810DO (mg/L) 2010 2011 2012 2013 2014 2015 2016 13 Fertilizer Factory. Dhaleshwari river water sampling stations were in Munshiganj and 210 Hemayetpur surrounded by manufacturing and textile industries. Korotoa river sampling 211 locations were in Bogura district where economy is heavily agriculture d ependent with some 212 minor industries in the area. While DO level of Shitalakhya and Dhaleshway rivers were above 4 213 mg/L in 2016, it showed an ever -decreasing trend for Korotoa river reaching 2.565 mg/L in 214 2016. 215 Brahmaputra, Halda, and Surma had near 6.5 mg/L DO in recent reported years while 216 Mathavanga shows a downward trend for DO starting from 2012, the only year it had DO greater 217 than 6.5 mg/L. Mathavanga river sampling locations were in Chuadanga, an agriculture 218 dependent district. Brahmaputra and Halda sampling locations were in unindustrialized areas 219 where sampling locations of Surma were near a few manufacturing industries including Chhatak 220 Cement Factory. Level of DO in Brahmaputra was above 6.5 mg/L in 2012, 2013 and then 221 decreased in the next few years. Surma’s DO level stayed at the same level ranging from 6.04 – 222 7.315 mg/L across the seven reported years while Halda’s DO level showed an upward trend, 223 reaching 6.915 mg/L in 2016. Overall, location and surrounding industrialization level might be 224 an important factor leading to low DO in industrialized and high DO in relatively less 225 industrialized areas. 226 3.2. Biochemical oxygen demand (BOD) in ten selected rivers 227 Biochemical oxygen demand (BOD) is generally an indicator of presence of organic matter. 228 With a high level of organic matter present in water, consumption of DO for breaking down 229 organic matter causes DO depletion in water. Consequently, aquatic systems with high level of 230 BOD generally has low level of DO in the system. Accordingly, it was ob served that BOD was 231 generally high in the rivers with low level of DO. Figure 2 shows the annual average BOD 232 14 calculated from the data extracted from DOE reports published from 2010 till 2016. DO was 233 very low in Buriganga, Turag , Moyuri and these three rive rs had BOD always in the toxic regime 234 across the observed time period [Figure 3]. Buriganga river’s BOD level dropped from 17.6 235 mg/L in 2014 to 11.8 mg/L in 2016, but it was still toxic for aquatic healthy environment. 236 Similarly, Turag and Mayuri rivers’ B OD level was in the range of 18.9 – 21.6 mg/L and 12.6 – 237 17.3 mg/L, respectively. Notably, the BOD level in Mayuri river was not available from 2014 238 through 2016. However, low level of DO in Mayuri’s water in 2015 (1.830 mg/L) and 2016 239 (1.765 mg/L) is like ly an indicator of a toxic level of BOD in the river in 2015 and 2016. 240 241 Figure 3: Level of biochemical oxygen demand (BOD) in ten rivers of Bangladesh across a time 242 period of seven years starting from 2010 till 2016. 243 Brahmaputra, Halda, Mathavanga rivers showed a downward trend for BOD likely because of 244 the less of an industrialization in the locations the rivers are located ; especially, Mathavanga 245 rivers’ BOD level were in the healthy range of BOD (< 3 mg/L) in recent years. Notably, 246 Halda’s BOD levels in the most recent years were not available, but referring to the relatively 247 high le vel of DO in Halda and the overall trend of DO And BOD in the river, it can be presumed 248 010203040BOD (mg/L) 2010 2011 2012 2013 2014 2015 2016 15 that Halda’s BOD was still within the healthy range in 2014, 2015, and 2016. Korotoa’s BOD 249 indicates moderate pollution (< 8 mg/L) but its BOD level stayed almost at th e same level after 250 2010 indicating the pollution level in the river likely did not deteriorate further till 2016. 251 Dhaleshwari, Shitalakhya, and Surma rivers’ BOD level was above the range for healthy level (> 252 3 mg/L). The level of BOD in Surma was in the r ange of 16.4 – 34.2 mg/L in recent years while 253 Dhaleshwari’s BOD was below 8 mg/L indicating a moderate pollution level in Dhaleshwari 254 based on the recent BOD level in the river. The BOD level was above the healthy range in recent 255 years in Shitalakhya with the exception in 2015 (5.1 mg/L) . 256 3.3. Water Quality index (WQI) in ten selected rivers 257 Water quality index (WQI) can indicate the overall quality of water. In absence of a universal 258 indexing of water quality different water quality agencies adopt different methods for WQI 259 assignment . In this study, DO, BOD, pH, and SS - these four parameters were considered for 260 WQI calculation. However, SS data was not available for all rivers. But weights were assigned to 261 each parameter according to the associated intensity and then an average of the total weight was 262 used for WQI employment to minimize the effect of lack of one or two parameters (if any). The 263 level of DO and BOD in all ten rivers across a seven -year period was discussed in the previous 264 sections. A separate section on pH level in the rivers was not provided as pH was within the 265 range of 6.5 – 8.5 in all the rivers which is a normal pH level for surface water [30]. Moreover, 266 no drastic fluctuation of pH was observed in the rivers. Additional ly, SS values were also 267 considered for WQI calculation, when available. Figure 4 shows the calculated WQI for all ten 268 rivers in a seven -year period (2010 – 2016). 269 16 270 Figure 4: Calculated water quality index (WQI) for ten rivers from 2010 till 2016. 271 Among the ten rivers, Brahmaputra had the lowest WQI in recent years with a downward trend 272 over the years while Halda showed an upward trend in WQI. As discussed earlier, Brahmaputra 273 flows through a residential urban area that is not industrialized. Halda flows thr ough hilly areas 274 with tea gardens. One possible reason for Halda’s increasing WQI over the years could be due to 275 run-off from tea gardens that would carry sediments, nutrients with it. Buriganga, Turag, and 276 Mayuri are the three most polluted rivers in term s of WQI across the observed time period, 277 showing no major fluctuations over the years. Buriganga, Turag, and Moyuri are in the most 278 industrialized areas of Bangladesh where s ome of the industries include tanneries, textiles, and 279 manufacturing industries. Lack of regulatory enforcement and infrastructure for industrial 280 discharge control very likely contributed to the high level of WQI in those three rivers. 281 Contribution of industrial discharge can be more clearly observed by comparing WQI of these 282 three riv ers to that of Brahmaputra and Mathavanga. Being in relatively under -industrialized 283 areas, Brahmaputra and Mathavanga had lower WQI compared to Buriganga, Turag, and 284 Moyuri. 285 0246810WQI 2010 2011 2012 2013 2014 2015 2016 17 Shitalakhya (4.5 – 5.0), Surma (4.3 – 4.7), and Korotoa (4.5 – 4.8) rivers had WQI almost at the 286 same level in recent years (2014 – 2016) indicating moderate pollution in the rivers. Pollution in 287 Shitalakhya and Surma rivers might be because these rivers are adjacent to some of the largest 288 factories in the country, i.e. ACI, Chhatak cement factory. Korotoa’s moderate pollution might 289 have been caused by the small industries located in the adjacent area. Dhaleshwari river showed 290 a downward trend of WQI from 4.3 in 2014 to 2.1 in 2016. However, Dhaleshwari river is 291 located in an area with manufacturing and textile industries. There is no evidence or 292 documentation of any drastic regulatory enforcement in the area for controlling industrial 293 discharge. The downward t rend of WQI in the river might be due to lack of sampling in the 294 monitoring stations which is a very common phenomena in many of the monitoring stations 295 across the country. Overall, Brahmaputra and Mathavanga were the only two rivers with a WQI 296 for healthy aquatic environment identified in this study. All the other rivers were either slightly 297 or moderately polluted and not healthy for aquatic lives. The degree of pollution in the ten rivers 298 in 2016 based on WQI was in the order of Mayuri > Buriganga > Korot oa > Turag > Shitalakhya 299 > Surma > Halda > Dhaleshwari > Mathavanga > Brahmaputra. A qualitative interpretation was 300 made based on the WQI calculated in this study for a convenient identification of the polluted 301 rivers [Table 3]. 302 303 Table 3: Degree of polluti on in the ten selected rivers presented with different color codes 304 305 18 306 As presented in Table 3, Buriganga, Shitalakhya, Turag, Halda, Mayuri, Surma, Korotoa rivers 307 were moderately polluted in 2016, and Dhaleshwari was slightly polluted while Brahmaputra an d 308 Mathavanga were in good conditions. This shows a trend of rivers being more polluted when 309 there are industries in surrounding areas which coincides observations made by other reports 310 [5,16,17,18,19,20] . 311 Monitoring of more parameters and incorporation of them into WQI will be helpful for 312 calculation of more accurate WQI representative of the actual water quality. However, 313 monitoring of more parameters might be challenging due to lack of resources and infra structure 314 in developing countries like Bangladesh. Therefore, WQI prediction with a few parameters will 315 be helpful in resource limited situations. Hence, a correlation between DO, BOD and WQI was 316 analyzed in this study [Figure 5]. 317 19 318 319 Figure 5: Regression analysis of (a) dissolved oxygen (DO) and water quality index (WQI), and 320 (b) biochemical oxygen demand (BOD) and WQI to determine correlation between them. 321 Predicted WQI using DO and BOD as variable resulted in R2 of 75.16% and 79.44%, 322 respectively. 323 With u sing DO and BOD both as variables, WQI can be predicted as follows (R2 = 86.68% and 324 standard error = 0.68) 325 WQI = -0.6803 DO + 6.5756 R² = 0.7516 0246810 0 2 4 6 8 10 12WQI DO (mg/L) Actual WQI Predicted WQI Fitted Predicted WQI(a) WQI = 0.1661 BOD + 2.0663 R² = 0.7944 0246810 0 5 10 15 20 25 30 35 40WQI BOD (mg/L) Actual WQI Predicted WQI Fitted Predicted WQI (b) 20 WQI = 4.42 – 0.42 DO + 0.11 BOD [Equation 2] 326 In challenging situations with difficulty in monitoring multiples parameters, the correlation of 327 WQI with DO and BOD individually or both parameters can be helpful for prediction of water 328 quality. Notably, BOD levels for some rivers in some years were not available (Halda and 329 Moyuri: 2014 – 2016; Korotoa: 2013). In the correlation analy sis, those data points were hence 330 not considered. 331 4. Conclusion 332 Access to clean water is essential for all living beings. Similarly, clean and pollution free surface 333 water is crucial for a healthy aquatic environment where all aquatic beings can sustainably 334 thrive. However, with an increasing industrial and agricultural production to meet the demand of 335 the ever -increasing population, water pollution is becoming challenging for sustainable 336 development. This phenomenon is particularly more challenging in develop ing countries like 337 Bangladesh where lack of infrastructure and regulatory enforcement pose higher risk for water 338 pollution. Anthropogenic activities generated huge transformations in the river water quality and 339 ecosystem in the country. Because of economic benefit many industries are established near the 340 river side and the subsequent discharge of untreated and semi treated toxic waste into the river is 341 likely to negatively affect the water quality in the receiving waterbodies. 342 The water quality index can b e helpful for reducing the bulk of the monitored parameters into a 343 single value to communicate in a rearranged and consistent manner. Hence, a well -adopted water 344 quality indexing system can be helpful for remediation planning and implementation purposes. 345 However, currently the country does not have a country wide indexing system in place. There are 346 a few published works on assignment of WQI on some selected waterbodies. But an overall 347 21 indexing to apply on a vast region of the country covering both industria lized and under - 348 industrialized areas is yet to be explored. This study proposed an indexing system considering 349 four parameters (DO, BOD, pH, and SS) generally monitored in the monitoring stations of DOE. 350 An analysis of DO, BOD, and WQI in the ten selected rivers showed that rivers located in the 351 heavily industrialized areas were highly polluted and the degree of pollution were generally 352 lower in the areas with fewer industries. Rivers in the industrialized areas showed a general trend 353 of having low DO and h igh BOD. The rivers can be in the order of Mayuri > Buriganga > 354 Korotoa > Turag > Shitalakhya > Surma > Halda > Dhaleshwari > Mathavanga > Brahmaputra 355 in terms of the degree of pollution based on the WQI assignment in this study. This order can be 356 helpful for identifying which rivers need remediation on a preferential basis. 357 Similarly, WQI can be calculated for other rivers in the country to gather a better understanding 358 of the degree of pollution in the rivers and make a holistic plan for remediation of th e rivers. 359 However, setting up more monitoring stations in the rivers and frequent sampling is crucial for 360 assignment of WQI for development and implementation of remediation plans. In a resource 361 limited situation where only one or two parameters are availa ble for monitoring , a simplified 362 WQI formula can be helpful. The relationship derived in this study can be useful for prediction 363 of WQI using DO, BOD or both parameters. 364 Author Contributions 365 Mallick, Z.: Conceptualization, Methodology, Investigation, Data Curation, Writing – Original 366 draft, Writing – Review & Editing. Hossain, M .R.B.: Investigation, Data Curation, Writing – 367 Original draft, Writing – Review & Editing. Ayshi, F.T.: Investigation, Data Curati on, Writing – 368 Original draft, Writing – Review & Editing. Tahsin, A.: Data Curation, Writing – Review & 369 22 Editing. Mallick, S .P.: Conceptualization, Methodology, Validation, Formal Analysis, 370 Investigation, Data Curation, Writing – Original draft, Writing – Review & Editing , Supervision . 371 Funding 372 This research received no external funding . 373 Conflicts of Interest 374 The authors declare no conflict of interest. 375