Proceedings of the 13 th International Conference of Environmental Science and Technology Athens, Greece, 5-7 September 13 WATER QUALITY MODELING FOR BOD and COD CONTROL STRATEGIES FOR THE BURIGANGA RIVER OF BANGLADESH MITHUN SIKDER 1, MD. HASANUZZAMAN 2 and MD. MAFIZUR RAHMAN 3 1 Post Graduate Student, Department of Chemical and Environmental Engineering, University of Nottingham, Nottingham, UK. Email: sikder.ce@gmail.com 2 Post Graduate Student, Department of Civil Engineering, Bangladesh University of Engineering and Technology (BUET), Bangladesh. 3 Professor, Department of Civil Engineering and Director, ITN, Bangladesh University of Engineering and Technology (BUET), Bangladesh. EXTENDED ABSTRACT BOD and COD tracking have been made with RMA2 and RMA4 module of SMS.1 for water quality control strategies. To simulate the actual existing river condition of the Buriganga river (including discharge, river cross section, roughness, turbidity, temperature, wind effect, rainfall, pollutant diffusion co-efficient, decay rate, DE oxygenation rate etc.), a 13. km segment (Hazaribagh to Fatullah) has been chosen. Dry and Wet weather conditions have been considered including full loading from three types of sources (viz. Industrial, Domestic sewage and Sewage Treatment Plant) discharging into river along both the banks. Self-cleansing system of this river is very weak, since oxygen addition from aquatic plant and incoming estuaries is very less and river contains thick sediment on the bottom demanding high dissolved oxygen. The model of the river shows a complete unhealthy condition considering both seasons and both yield contours and graphs of different transverse and longitudinal sections indicating higher values than recommended ECR values of Bangladesh for fishing, irrigation and recreation. BOD and COD are 92 mg/l and 1 mg/l respectively. Wet season concentrations are milder than the Dry season. BOD and COD become 58 and 95 mg/l respectively. If this continues without any change in the near future then this river will be turned into a complete septic condition. Three ways for rehabilitation of the Buriganga river have been identified: (I) relocation of sources to the upstream, (ii) reduction of number of sources, (iii) reduction of loading rate from the sources by compelling them to use ETP before discharging directly to the river, so that concentration at downstream reaches a relatively lower value. ECR, 1997 and DoE, 1991 regulations define that BOD should be less than 6 mg/l for fisheries and should be less than mg/l for irrigation and drinking purpose. First consideration shows that during dry season recommended value (<mg/l) will gain at ft downstream from the source. It yields maximum reduction to the downstream but not significant change in upstream, resulting low efficiency in terms of whole river pollution mitigation. Second choice of reducing pollutant source in downstream is effective than previous one, mainly in downstream of the river. Permissible limit of BOD and COD is achieved within ft. downstream from reference point. Final choice with reduced level of pollutant concentration (% less than original), model shows relatively less concentration than the existing river condition. For this option total river system attains its maximum pollution reduction. This modeling recommends the allowable limit of amount of discharge and pollutant concentration from adjacent sources of pollution and finally the required spacing between ETP to continue the rehabilitated river s water quality. Keywords: Water quality,pollutant loading,seasonal variation, Feasibility, Flow rate, Bed roughness, Diffusion, Eddy viscosity, Decay rate for BOD, Policy making.
1. INTRODUCTION Buriganga is the main peripheral river of capital Dhaka due to several reasons, mainly due to source of drinking water (meet about % of total water demand), source of irrigation water, medium of transportation as well deposition of waste water for tannery and other industries (about ) situated in bank of river inside Dhaka city. They generate huge amount of toxic wastes each day. According to Dhaka City Corporation (DCC) about tons of solid waste generate each(5), in addition to that about 9% of liquid waste coming directly or indirectly to this river. Significant water table lowering (4 feet from ground now) also accelerating the deterioration of water quality (BBS, 9). Excess pollution level in peripheral rivers of Dhaka city forced the engineers concerned to look for alternative sources of raw water for surface water treatment plant (Rahman, 7). Complete model was built to analyze current BOD and COD trend and further analysis was done to incorporate with seasonal and geomorphological variation to predict about future situation. Point sources (i.e. distinct wastewater outlets carrying domestic, industrial or certain agricultural wastes) and non-point sources (i.e. atmosphere fall out, agricultural runoff, rock soil leachates etc.) are two major categories here we considered. For the catchments area of greater Dhaka, the contribution of non-point sources is not significant in comparison with the point sources of pollutants. Three different methods are suggested to show the result of all methods of rehabilitation in both dry & wet season. Comments are made regarding the safety of this Buriganga River. 2. GENARATEING MODEL ANALYSIS USING RMA2 and RMA4 MODULE 2.1 Specifications of RMA2 module RMA2 is a general-purpose model designed for far-field problems in which vertical accelerations are negligible and velocity vectors generally point in the same direction over the entire depth of the water column at any instant of time. It expects a vertically homogeneous fluid with a free surface. It can identify errors in the computational mesh specification. Simulate wetting and drying events, which provides a more accurate account of off-channel storage, able to adjust drying and wetting, also accounts Marsh Porosity wetting and drying, effects of the earth s rotation (Coriolis), wind stress either uniformly or as a storm. Employ either direct or automatic dynamic assignment of Manning s n-value by depth, turbulent exchange coefficients. The generalized computer program RMA2 solves the depth-integrated equations of fluid mass and momentum conservation in two horizontal directions. The forms of the solved equations are: h u + t hu u + x hv u - h [ E 2 u y ρ xx E 2 u x 2 xy y2 ] + gh [ a + h ] + gun 2 1 (u 2 + v 2 ) 1/2 x x (1.486h6) 2 ζ V a2cos φ 2hvω sin = (1) h v + t hu v + x hv v - h [ E 2 v y ρ xx E 2 v a x 2 xy y2 ] + gh [ + h ] + gvn 2 1 (u 2 + v 2 ) 1/2 y y (1.486h6) 2 ζ Va2sin φ 2huω sin =..(2) h + t h( u + v ) + u h + v h =... (3) x y x y Where, h = Water depth, u and v = Velocities in the Cartesian directions, x,y,t= Cartesian coordinates and time, ρ= Density of fluid, E= Eddy viscosity coefficient, a = Elevation of bottom, n = Manning s roughness, ζ = Empirical wind shear coefficient, V a= Wind speed, ψ = Wind direction, ω = Rate of earth s angular rotation and Φ = Local latitude. 2.2 Specifications of RMA4 module RMA4 is a general purpose model designed to investigate physical processes which are responsible for the distribution of pollutants in the environment using a first order decay
and for testing the effectiveness of remedial control measures at high speed and low cost. The methodology is restricted to one-dimensional and two-dimensional systems in which the concentration distribution in the vertical dimension is assumed uniform. It is able to read 1D or 2D hydrodynamics, marsh porosity, wetting and drying data from RMA2. Also handle rainfall/evaporation that was specified in RMA2. It accepts boundary condition concentrations by node, line, or mass loading. RMA4 has the capability to simulate advection-diffusion in the aquatic environment. The generalized computer program solves the depth-integrated equations of the transport and mixing process. The form of the depth averaged transport equation is: h ( C t + u C x + v C - D x C y x y σ + kc + R(C) h ) =..(4) Where, h =water depth, c = concentration of pollutant for a given constituent, u and v = velocity in x direction and y direction, Dx, Dy, = turbulent mixing (dispersion) coefficient, k= first order decay of pollutant, σ= source of constituent, R(c) = rainfall/evaporation rate. 3. DATA COLLECTION AND SAMPLING METHODOLOGY Institute of Water Modeling (IWM) have conducted a study in 6. The study had included the assessment of water quality of peripheral rivers of Dhaka city. Parameters selected for laboratory analysis were, Biochemical Oxygen Demand (BOD) and total Ammonia (NH 3) content. The laboratory test data and the in-situ DO measurements at these river systems were compared with allowable limits of Environmental Quality Standards (EQS) for surface water for Bangladesh set by Department of Environment (DoE) to assess the prevailing water quality. It has been observed that water quality in the peripheral river system is continuing to deteriorate due to uncontrolled discharge of raw domestic sewage and industrial effluent With the increase of urbanization and industrialization, mass of wastes (waste/pollution load) being discharged into the peripheral river system is also increasing at an alarming rate. An absolute study of the Buriganga River (Hazaribagh to Fatullah) was done based on the previous research works on this river related to water quality. All background theories were reviewed on how the DO, BOD and COD parameters in river water affect the environment of a river and also the life of citizens. Loading rate data s and existing river water parameters of Industry in Hazaribagh Hotspot were used from a previous study on this same river(saha, 1). Discharge data was collected from Water Development Board (BWDB) of Bangladesh. Model is simulated with existing condition considering both winter and monsoon seasons for 24 hours duration. First revised simulation is based on % reduction of loading rate from Industrial Hotspot for both seasons and 24 hours duration. Second revised simulation is made considering industrial source reduction for both seasons and full duration. Final revised simulation is the relocation of sources towards upstream for both seasons and full duration. Each simulation for different times in a day is produced distinct variation of both parameters along the longitudinal section of the river. Both minimum and optimum reduction of BOD and COD are found out from these graphs to help environmental engineers to predict the water quality parameter along the river flow. Physical condition is monitored and data was collected along the periphery of Dhaka city starting from Hazaribagh to Fatullah (outlet). A GPS machine was used to locate the points of interest in Buriganga River and corresponding spatial features of data were recorded. Then others locations positions are included in terms of Northing & Easting using this GPS machine. Following table shows the four locations of sampling point which were selected from the 13.5km Buriganga River ridge.
Table 1: Location of sampling point in Buriganga river of Dhaka city. Location for sample collection GPS reading Northing Easting Latitude Longitude Buriganga River (Sadarghat) 23 o 42 51. 9 o 27 22.8 6987 5476 Outlet point of PSTP 23 o 9.4 9 o 26 56.2 617389 5462 Chandighat Intake point 23 o 42 43. 9 o 23 25.1 621895 5135 Hazaribagh 23 o 44 38.1 9 o 21 24.8 625626 536655 Table 2: Discharge Data of Buriganga river District Date Water Level (m) Discharge (m 3 /s) Maximum Velocity (m/s) Discharge (ft 3 /s) Dhaka 6-6-9 2.69 348.68.33 12315.46 Dhaka -6-9 2.66 332.59.32 11746.99 Dhaka 11-7-9 4.34 491.26.42 17351.22 Dhaka 25-7-9 3.98 466.7. 16461.52 Dhaka 8-8-9 4.42 622.91.51 2.97 Dhaka 22-8-9 4.81 739.27.57 261.75 Dhaka 12-9-9 4.4 9.58. 215.41 Dhaka 26-9-9 3.69 5.33.44 124. Dhaka 3--9 3. 468.79.42 16557.52 Dhaka 17--9 3.7 493.31.43 17423.73 Source: Bangladesh Water Development Board Annual Report (BWDB, ) Table 3: Existing Buriganga river s BOD and COD concentration. Parameters Date 9-4-9 --9 15-11-9 19-12-9-1- BOD (mg/l) 7.2 2 6.4 12.8 COD (mg/l) 18 9 9 53 84 4. RESULTS AND DISCUSSION Source: (Mahmood, 11) We collected data of BOD and COD of this river during two different seasons. The statistical characterization and analysis had been done for predicting possible choices for reduction of BOD and COD content in Buriganga River. These data have been analyzed and compared with previous and standard data collected from different sources. Here we introduced 3 possible choices for reduction of organic and nutrient contents in the downstream section. They are as follows: I. Movement of industries into upstream section. II. III. Reduction of industries (Source Reduction). Introducing ETP s in all industries (assuming % waste loading reduction due to this). At first when we introduce movement of industries towards upstream then worst scenario occur during Dry Season at ft. downstream, where its value is 85 mg/l. During wet
season these scenario is different. Here worst case occurs at ft. where BOD is 55mg/l. Worst scenario for COD occurs during Dry Season at 17 ft., where the value is 1 mg/l. During Wet Season these scenario is different. Here worst case occurs at 2 ft. where COD is mg/l. 7 BOD, Time Step: 18:: 1 1 1 1 COD, Time Step: 1 :: BOD (mg/l) COD (mg/l) 2 2 Arc 6 Figure 1: BOD variation (Dry Season) Figure 2: COD variation (Dry Season) During second case when we reduce point sources of pollution then slight reduction in ultimate BOD along longitudinal profile. In Dry Season it s become mg/l and occurs about ft. earlier. Same situation arises for Wet Season; here concentration is 42mg/l BOD at 2 ft., similar situation occurs during COD loading simulation. In Dry Season it s become 1 mg/l. Same situation arise for Wet Season, here 7 mg/l is COD concentration. BOD, Time Step: 18:: Arc 6 COD, Time Step: 18:: BOD (mg/l) 7 2 COD (mg/l) 1 1 1 2 Arc 1 Figure 3: BOD variation (Dry Season) Figure 4: COD variation (Dry Season) When we introduced ETPs in all industries then there is a significant amount of reduction in BOD both in Dry and Wet Season. In Dry condition BOD becomes 55 mg/l at ft. During Wet season ultimate BOD occur at 2 ft. which is mg/l. Also there is significant amount of reduction in COD both in Dry and Wet Season. In Dry condition COD becomes 1 mg/l at ft. During Wet season ultimate COD is 55 mg/l at 2ft. Arc 1
55 45 BOD, Time Step: 18:: 1 1 1 9 COD, Time Step: 1 :: BOD (mg/l) 35 25 15 COD (mg/l) 7 5 2 Figure 5: BOD variation (Dry Season) 2 Figure 6: COD variation (Dry Season) 5. CONCLUSION AND RECOMMENDATION In existing condition Buriganga River contains maximum BOD during Dry Season which is 92 mg/l along longitudinal profile. During Wet Season it reduces to 58 mg/l as there is increment in water volume so there will be more dilution. So from this analysis we find that maximum BOD reduction occurred in case of Option 3 but for Option 2 it attains recommended BOD concentration (< mg/l) faster than other two options. Similarly in case of COD concentration, during dry season maximum value is 1 mg/l and 95 mg/l during wet season along its longitudinal profile. Here a reasonable decrease in COD concentration has been found when Option 3 is adopted. Here same COD limit exerts at ft. for Dry season and same here for Wet season. Actually this COD value is not very essential, as total oxygen demand essential for consideration. Under this study BOD and COD in Buriganga River is observed along longitudinal profile and we also discussed three possible choices for reduction of pollution. Recommendation for further study can be summarized below: Continuous monitoring of water quality parameters of the river will give a better picture of the variation of water quality variables. For getting picture of diurnal variation of water quality parameters and thus characterizing river, sample should be collected every hours from particular location for a whole day and it should be done for both Dry and Wet season. For getting a reasonable analysis we have to demonstrate a perfect model. For this reason data collection has to be done very carefully about river sectional properties. Thus accurate values of velocity, flow rate, water depth and also location of river banks should be carefully converted into UTM standard. More physical accurate data will give an accurate analysis result. Dissolved oxygen (DO) is the most important parameter for water quality characterization of river. Monitoring of DO content should be continued and reasons for low dissolved oxygen in river water should be investigated for necessary actions. There are many unknown sluices and waste water disposal outlets along the periphery of river and bottom of the river. Water quality monitoring of the waste water in these outlets should be continued to examine to get better analysis result. For developing a characterization profile of Buriganga River about pollution status in sense of all controlling parameters in peripheral rivers around Dhaka. So that it can be used by environmental decision makers to judge the kind of use of water from river. Also decision makers can use this analysis to decide about the best possible solution to control these water quality parameters.
Study should be made on public participation in pollution control efforts of government of Bangladesh and how public awareness can be increased should also be studied. REFERENCES 1. BBS, 9. Compendium of Environment Statistics of Bangladesh. Bangladesh Bureau of Statistics. 2. BWDB,. Discharge Data for Various Rivers in Bangladesh. Dhaka: BWDB. 3. DCC, 5. The Study On The Solid Waste Management In Dhaka City. Dhaka: Dhaka City Corporation The People's Republic of Bangladesh. 4. MAHMOOD, S. 11. Characterization of Nutrient and Organic content of water in the peripheral rivers of Dhaka city. M.Sc in Engineering Thesis. Dhaka, Bangladesh: Bangladesh University of Engineering and Technology. 5. RAHMAN, A. 7. Characteristics of Major Industrial Liquid Pollutants in Bangladesh. M.Engg. Project Report. Dhaka, Bangladesh: Bangladesh University of Engineering & Technology. 6. SAHA, G. C. 1. Assessment of groundwater contamination in Dhaka City from tannery waste. M.Sc Engineering Thesis.