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International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308

(Print), ISSN 0976 – 6316(Online) Volume 3, Issue 2, July- December (2012), © IAEME

154

WATER QUALITY ANALYSIS OF SURFACE WATER BODIES ALONG

THE DHAKA-MAWA-BHANGA ROAD BASED ON PRE-MONSOON

WATER QUALITY PARAMETERS FOR AQUACULTURE

Rumman Mowla Chowdhury

1, Sardar Yafee Muntasir

2, Md. Niamul Naser

3, Sardar Rafee

Musabbir4

1Junior Engineer, Institute of Water Modeling, [email protected] 2Lecturer Stamford University Bangladesh, [email protected]

3Professor, Department of Zoology, Dhaka University, Dhaka, Bangladesh

4Undergraduate Student, Department of Civil Engineering, BUET

ABSTRACT Rural populations in Bangladesh often are heavily dependent on small reservoirs for their

water supply not only for drinking and domestic purposes but also for aquaculture. This

study was carried out to assess surface water quality of water bodies along the Dhaka-

Mawa-Bhanga (N8) which is of 60 km in length. As all the water bodies of are expected to be

productive due to the geophysical and climatic condition of the country, it will be better to

ensure the perfect utilization of the existing resources. In the way to finding out the feasibility

for aquaculture in the surface water the following parameters: pH, electrical conductivity,

total dissolved solids, salinity, dissolved oxygen, transparency before monsoon as it is the

suitable season for the beginning of breeding; were collected and analyzed. The results were

compared with standard values of aquaculture prescribed by South African Water Quality

Guidelines. From data analysis it was found that several water quality parameters like-

temperature, DO, BOD, electrical conductivity, salinity, TDS showed variability but they are

almost within the acceptable average range for most sampling points. Water quality of

Thandu Chowdhuryer pukur, Pachchor Bajar pukur, Arial Kha, Pulia Bajar, Sirajdhi khan

indicated that the water quality was not suitable for aquatic animals as their DO, pH and

secchi depth were not suitable enough. Proper treatment of water is necessary there before

aquaculture is commenced.

Keywords: Physicochemical parameters, Statistical Parameters, Pre-monsoon. 1Address: 2/B/A, Golden Street, Ring Road, Shamoly, Dhaka-1207.

2Address: Flat-3, Bldg-4, Road-2A, PWD Officers Quarter, Dhanmondi, Dhaka-1209.

3Address: Department of Zoology, Dhaka University.

4Address: Flat-3, Bldg-4, Road-2A, PWD Officers Quarter, Dhanmondi, Dhaka-1209.

INTERNATIONAL JOURNAL OF CIVIL ENGINEERING AND

TECHNOLOGY (IJCIET)

ISSN 0976 – 6308 (Print) ISSN 0976 – 6316(Online)

Volume 3, Issue 2, July- December (2012), pp. 154-168 © IAEME: www.iaeme.com/ijciet.html

Journal Impact Factor (2012): 3.1861 (Calculated by GISI) www.jifactor.com

IJCIET

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155

1. INTRODUCTION

The interaction of both physical and chemical properties of water plays a significant role in the composition, distribution and abundance of aquatic organism. The physical and chemical limnology of a water body is characterized by hydrologic impact, autogenic nutrient dynamics and biological aspects. These factors combine with each other to determine the water quality. The proper balance of physical, chemical and biological properties of water in ponds, lakes and reservoirs is an essential ingredient for successful production of fish and other aquatic resources (Mustafa, 2005).

Fish are totally dependent upon water to breathe, feed and grow, excrete wastes, maintain a salt balance, and reproduce; for these reasons understanding the physical and chemical qualities of water is critical to successful aquaculture (Swann, 1997). Aquaculture, also known as aqua-farming, is the farming of aquatic organisms such as fish, crustaceans, molluscs and aquatic plants. Aquaculture involves cultivating freshwater and saltwater populations under controlled conditions and can be contrasted with commercial fishing, which is the harvesting of wild fish. Success or failure of an aquaculture operation is being extremely determined by water quality. For commercial fish production water is always a limiting factor. Many of the negative chemical and environmental factors associated with most operations have their origins in the source of water selected. Both the quality and quantity of water available has to be in major concern for the site selection (Swann, 1997). The most common sources of water used for aquaculture are rivers, ponds and lakes, among the surface water bodies.

The relationship between fishes and their biotic-abiotic behavior is not an isolated phenomenon. Fishes are more dependent on water temperature, pH, dissolved oxygen (DO), alkalinity and some other salts for growth and development (Alokesh Kumar, 2011). Any changes of these parameters may affect the growth, development and maturity of fish (Nahar Islam, 2007). The development of fauna and its abundance is more or less related inversely with temperature and the amount of dissolved oxygen (Metcalf Eddy, 4th Edition).Water quality standard vary significantly due to different environmental conditions, ecosystems and intended human uses. Toxic substance and high population of certain microorganisms can present a health hazard for non-drinking purpose such as irrigation, swimming, fishing and rafting, boating and industrial uses. These conditions may also affect wildlife which uses the water for drinking or as a habitat. According to Farmanfarmaian and Moore (1978), loss of species and shifts from pollution-sensitive towards pollution-tolerant organisms are the major negative impacts due to deterioration of water quality. Water quality in rivers can be reduced by high sediment loads that interfere with fish respiration and cover spawning areas and can smother bottom-living organisms.

This study was conducted in the pre-monsoon season as during this season the water remains in its worst condition, which helped to select the water bodies for aquaculture in its most negative condition. As the water depth is usually at minimum in the pre-monsoon, some parameters remain highly concentrated which is undesirable, some remain low concentrated but desirable that is why pre-monsoon water quality is predicted as worst water quality condition. The physicochemical study could also help in understanding of the structure and function of a particular water body in relation to its inhabitants.



156

2. METHODOLOGY

2.1 Study area

The present study was conducted along Dhaka-Mawa-Bhanga (N8) is a 60 Km existing road touching Dhaka, Munshiganj, Madaripur and Faridpur districts covering 8 upazilla’s namely, Keraniganj, Serajdikhan, Sreenagar, Lohajang, Shibchar, Faridpur sadar, Sadarpur and Bhanga. To monitor and for better observation of water quality of the study areas, sampling target was aimed to cover the important zones of the lakes. For BOD measurement, a 500 ml bottle was used for collection of water samples and the oxygen was fixed at the sampling site before being carried to the laboratory for further analysis. The examination and analysis of the water bodies including laboratory analysis was done as per the standard methods of USEPA (2004) and (Trivedi and Goel, 1986).12 stations were selected for sampling which is shown in Figure 1.

Figure1. A satellite view of sampling area

2.2. Analysis of water sample

For the measurement of physical and chemical parameters of sample water bodies, the methods used are illustrated in Table 1.



157

Table 1. Details of the analysis methods and the required equipment for the determination of physico-chemical parameters

Serial number

Temperature Methodology Equipments

1 Temperature Visible Centigrade Thermometer

2 Salinity Visible Sensaso-CL 410,HACH,USA

3 pH Visible Sensaso-CL 410,HACH,USA

4 Transparency Visible Secchi Disk

5 Dissolved Oxygen

Visible Dissolved Oxygen Meter (Model-YK22

DO),USA

6 BOD Dissolved Oxygen Meter (Model-YK22

DO),USA

7 Conductivity Visible Conductivity Meter (Model-CD4302,USA)

8 TDS Visible Sensaso-CL 410,HACH,USA

2.3. Statistical analysis

Mean (µ) = /x N∑

x = Value of observations N = Number of observations Standard Deviation (σ) = n∑x

2-(∑x)

2 (1) n (n-1)

x = value of parameters

N = No. of observation

Standard error = σ/√N (2) σ = Standard deviation N= Number of observation N ∑xy - ∑x ∑y Kearl Pearsons’ Coefficient of Correlation, r = (3) n∑x

2-(∑x)

2 n∑y

2-(∑y)

2

x, y = Values of array 1 and array 2 respectively.

N = Number of observations

% variation of CV = σ/µ*100 (4) σ = Standard deviation

µ= Mean

3. RESULTS AND OBSERVATIONS

The statistical result range, mean, SD, SE, % CV, r values for surface water are given in Table 2 and in Table 3.



158

Table 2. Summary of the Statistical analysis (Sampling Stations within Dhaka-Mawa Road)

Groups Maximum Minimum Average Standard Deviation

Standard Error

Variance (%)

Air Temperature(ºC)

30.9 25.9 28.42 1.84 0.75 6.47

Water temperature(ºC)

30.9 28.8 29.92 .99 0.41 3.44

Secchi depth(cm) 165 15 65 70 28.6 1.08

pH 8.66 7.37 7.9 0.48 0.19 6.08

DO(mg/l) 5.4 1.3 3.93 1.51 0.62 38

BOD(mg/l) 3.7 0.7 2.55 1.05 0.43 41.18

Conductivity(2ms) 632 353 536.7 108.67 44.37 20.25

Salinity(mg/l) 3 0.2 0.27 0.51 0.021 18.9

TDS 306 169.4 260.233 53.26 21.7 20.5

Table 3. Summary of the Statistical analysis (Sampling Stations within Dhaka-Mawa Road)

Groups Maximum Minimum Average Standard Deviation

Standard Error

Variance (%)

Air Temperature(ºC)

31.2 28 29.9 1.27 0.582 4.25

Water temperature(ºC)

31.2 27.9 29.98 1.35 0.55 4.5

Secchi depth(cm) 105 5 39 57.17 23.34 1.47

pH 9.45 6.8 7.65 1.05 0.43 13.73

DO(mg/l) 10.4 2 5.4 3.01 1.23 55.74

BOD(mg/l) 9.8 1.5 4.55 3.12 1.27 68.57

Conductivity(2ms) 612 203 469.5 138 56.34 29.39

Salinity(mg/l) 0.3 0.1 0.2 0.063 0.026 31.5

TDS 340 97.1 236.85 78.57 32.07 33.17

The following parameters: pH, electrical conductivity, total dissolved solids, salinity, dissolved oxygen, transparency before monsoon was collected and an analysis of data was

made as described below. All the measured values of the Dhaka-Mawa and Mawa-Bhanga road are shown in graphs in appendix.

3.1. pH

The presence of hydrogen ion concentration is measured in terms of pH range. The acceptable range is usually between pH 6.5 to pH 9.0 for fish culture. When water is very alkaline (> pH 9), ammonium in water is converted to toxic ammonia, which can kill fish. On the other hand, acidic water (< pH 5) leeches metals from rocks and sediments. These metals

have an adverse effect on the fishes’ metabolism rates and ability to take in water through their gills and can be fatal as well. pH of water of the experimental water bodies was found to be approximately natural to slightly alkaline. The highest pH

was 8.66 at Bawor bity Sarak o

Janapather pukur along the Dhaka-Mawa road. The lowest was 6.8 at Pachchor Bajar khal within Bhanga-Janjira road. The mean value of pH was 7.9 and 7.65 respectively among the



159

water bodies within the Dhaka-Mawa road. Figure 1 and Figure 2 show the comparison of pH of the 12 stations.

Figure 1. Station wise pH (Water Bodies along Dhaka-Mawa Road)

Figure 2. Station wise pH (Water Bodies along Mawa-Bhanga Road)

3.2. Temperature

Temperature tolerances of fish are broadly categorized into cold water, cool water, warm water and tropical water. For each species, there is a minimum and maximum tolerance limit, as well as an optimal temperature range for growth. This optimal temperature range, also known as the standard environmental temperature (SET), may vary with each species, even those within the same temperature tolerance category, and with each development stage of the fish. Water temperature affects the feeding pattern and growth of fish. Fish generally experience stress and disease breakout when temperature is chronically near their maximum

tolerance or fluctuates suddenly. It is therefore important to acclimatize fish gradually when moving them from one location to another. Warm water holds less dissolved oxygen than cool water. This is a point worth noting, since every 10°C increase in temperature doubles the rate of metabolism, chemical reaction and oxygen consumption in general. The value of air temperature varied between 25.9 °C to 31.2 °C. The minimum temperature (25.9 °C) was recorded in “Baworbity Sarok & Jonopather pukur.” And the maximum temperature was recorded as 31.2 °C in Thandu Chowdhurir pukur and in pachchor Bajar khal which were in along the Bhanga road. The mean values of air temperature for the total 12 station (6 within Dhaka-Mawa road and 6 within Jangira – Bhanga road) were 28.42 °C and 29.9 °C respectively. The values of water temperature varied between 27.9 °C to 31.2 °C. The

maximum temperature (31.2 °C) was recorded in Pachchor Bajar Khal and the minimum temperature 27.9 was recorded in Bhanga khal along the Jangira bhanga Road. Figure 3 and Figure 4 show the comparison of temperatures between the 12 stations.

6.57

7.58

8.59

Bawor bity sarok o janopather pokurDhalashri (1) Dhalashri (2)Shirajdi Khan KuchiamaraChaltipara PokurMasurgow khal

pH

Station Name

02468

10

Pacchor bajar

khal

Thandu

Chowdhurir

Pokur

Arial Kha Pulia bajar

pokur

Bogail Beel Bhanga khal

pH

Station Name



160

Figure 3. Station wise Water and Air Tempearature (Water Bodies along Dhaka-Mawa Road)

Figure 4. Station wise Water and Air Temperature (Water Bodies along Mawa-

Bhanga Road)

3.3. Dissolved oxygen

Dissolved oxygen is by far, the most important parameter in aquaculture. Low dissolved oxygen levels are responsible for more fish kills, either directly or indirectly, than all other problems combined. Oxygen consumption is directly linked to size, feeding rate, activity level and temperature, and it will surprise some that large fish consume less oxygen than their smaller counterparts which have higher metabolic

rates. The amount of dissolved oxygen in water increases as temperature reduces and decreases when salinity and altitude increases. Not only is dissolved oxygen important

for fish respiration, but it is also important for the survival of phytoplankton, the organism which breaks down toxic ammonia into harmless forms. The value of DO varied from1.3mg/l to 5.4mg/l along the Dhaka-Mawa road and 2 to 10.4 mg/l within Jangira-Bhanga road. The maximum DO 10.4mg/l was founded in Thandu Chowdhurir pukur along the Janjira bhanga road. Mean value of DO was 3.93mg/l of

the water bodies along the Dhaka-Mawa road and 5.4 mg/l of the water bodies along the Janjira –Bhanga road. Figure 5 and Figure 6 show the comparison of DO among

12 stations.

26272829303132

Pacchor bajar

khal

Thandu

Chowdhurir

Pokur

Arial Kha Pulia bajar

pokur

Bogail Beel Bhanga khal

Te

mp

era

ture

, ˚C

Station Name

Temperature air (˚C)

Temperature Water (˚C)

22

24

26

28

30

32


Te

mp

era

ture

,˚C

Station NameTemperature air (˚C)

Temperature water (˚C)



161

Figure 5. Station wise DO (Water Bodies along Dhaka-Mawa Road)

Figure 6. Station wise DO (Water Bodies along Mawa-Bhanga Road)

3.4. Salinity

Salinity plays an important role in the growth of culture organisms through Osmo regulations of body minerals from that of the surrounding water. For ex. the optimum

range of salinity for black tiger shrimp is between 10 and 25 ppt., although the shrimp will accept salinity between 5 and 38 ppt. since its eurihaline character. The early life stages of both shrimp and prawn require standard seawater salinities but while

growing they can with stand to brackish water or even to freshwater. However, for better survival and growth optimum range of salinity should be maintained in the

aquaculture ponds. If salinity is too high, the fish will start to lose water to the environment. As freshwater fish are not physiologically adapted to osmo regulate

within a saline water source, decreased growth and survival can occur under these conditions. The salinity of the water source that is to be used for aquaculture should be tested before a project commences. Salinity tolerances will vary amongst species therefore it is important to choose an aquaculture species that is best suited to the salinity of the water source (Boyd (1990), Walker (1994) Ingram (1997)). In present study, salinity values were observed 0.1 to 0.8. That is suitable for coastal area close and open ecology (Laws, 1993). Concentration of salinity ranged 0.1 to 0.3.the minimum value was recorded in 1 station (Arial kha) and the maximum value was

recorded in 5 stations. The average concentration was 0.27 among the water bodies along the Dhaka-Mawa road and 0.2 along the Jangira –Bhanga road. Figure 7 and

Figure 8 show the comparison of salinity among the 12 stations.

0123456


DO

(mg

/l)

Station Name

02468

1012

Pacchor bajar khal Thandu Chowdhurir PokurArial Kha Pulia bajar pokur Bogail Beel Bhanga khal

DO

(m

g/L

)

Station Nmae



162

Figure 7. Station wise Salinity (Water Bodies along Dhaka-Mawa Road)

Figure 8. Station wise Salinity (Water Bodies along Mawa-Bhanga Road)

3.5. Turbidity

Turbidity (clarity of water) in aquaculture systems is also an important water

quality variable. Turbidity is affected by zooplankton and phytoplankton densities in the water column and also suspended particulate matter such as silt, fecal matter and

uneaten feed. Turbidity affects the level of light penetration in the water column which has influential effects on photosynthesis and hence algal growth. Highly turbid ponds have shallow light penetration which lowers the temperature as well as photosynthetic activity. Highly turbid ponds often have decreased amounts of algae growing on the bottom of ponds. In ponds with low turbidity, we see the opposite

effect (Aquaculture 1999). Evidence for light limiting phytoplankton growth has been found in both commercial penaeid prawn ponds (Burford 1997) and in M. rosenbergii

ponds (Costa-Pierce et al. 1984). When ponds are too turbid, farmers may flush ponds with fresh, clean water to reduce nutrient levels to discourage phytoplankton growth. Flushing can also dilute the amount of particulate matter to reduce turbidity. If not sufficiently turbid they may add fertilizer to stimulate phytoplankton blooms. The colors of water and soil samples of different sampling spots were observed by naked eyes. The ponds and canals were classified by transparent, turbid, brownish and greenish.

3.6. Conductivity

Conductivity is the ability of a substance to conduct electricity. The conductivity of water is a more-or-less linear function of the concentration of dissolved ions. Conductivity itself is not a human or aquatic health concern, but because it is easily measured, it can serve as an indicator of other water quality problems. If the conductivity of a stream suddenly increases, it indicates that there is a source of

0

0.1

0.2

0.3

0.4


Sa

lin

ity

Station Name

0

0.1

0.2

0.3

0.4


Sa

lin

ity

Station Name



163

dissolved ions in the vicinity. Therefore, conductivity measurements can be used as a quick way to locate potential water quality problems. Conductivity is measured in

terms of conductivity per unit length, and meters typically use the unit microsiemens/cm. The values of water conductivity varied from 352µs/cm to

632µs/cm along the Dhaka-Mawa road and 203µs/cm to 505µs/cm within jangira –Bhanga road. Figure 9 and Figure 10 shows the comparison of conductivity among 12

stations along Dhaka-Mawa-Vannga road.

Figure 9. Station wise Conductivity (Water Bodies along Dhaka-Mawa Road)

Figure 10. Station wise Conductivity (Water Bodies along Mawa-Bhanga Road)

3.7. Total dissolved solids

"Dissolved solids" refer to any minerals, salts, metals, cations or anions dissolved in

water. This includes anything present in water other than the pure water (H20) molecule and suspended solids. (Suspended solids are any particles/substances that are neither dissolved nor settled in the water)In general, the total dissolved solids

concentration is the sum of the cations (positively charged) and anions (negatively charged) ions in the water. A constant level of minerals is necessary for aquatic life.

The water in an aquarium should have the same levels of TDS and pH as the fish and reef's original habitat. TDS levels can represent different states of osmosis (Niels Jensen). Total dissolved Solid content in the water samples collected from different sampling stations of the study lakes varied greatly. The TDS level found to fluctuate from 169.4 S/m to 306 S/m within the water bodies along the Dhaka-Mawa road.97.1S/m to 340 S/m within the water bodies along the Janjira Bahnga road. The TDS content was maximum in Bogail Beel along the Janjira road and minimum was 97.1 at Arial kha along the same road. The mean value was 260.233 S/m and 236.85

0

200

400

600

800


Co

nd

uct

ivit

y

Station Name

0

200

400

600

800

Pacchor bajar khal Thandu Chowdhurir Pokur Arial Kha Pulia bajar pokur Bogail Beel

Co

nd

uct

ivit

y

Station Name



164

S/m among the two roads. Figure 11 and Figure 12 show the comparison of TDS between 12 stations.

Figure 11. Station wise TDS (Water Bodies along Dhaka-Mawa Road)

Figure 12. Station wise TDS (Water Bodies along Mawa-Bhanga Road)

3.8. Biochemical oxygen demand

Biochemical oxygen demand is a measure of the quantity of oxygen used by

microorganisms (e.g., aerobic bacteria) in the oxidation of organic matter. Natural levels of oxygen in aquatic systems are always somewhat depleted by normal levels of aerobic bacterial activity. In most cases, if dissolved oxygen concentrations drop below 5 parts per million (ppm), fish will be unable to live for very long. All clean water species such as trout or salmon will die well above this level and even low

oxygen fish such as catfish and carp will be at risk below 5 ppm. BOD varied between 0.7 to 3.7 mg/l within the water bodies along the Dhaka-Mawa road and 1.5mg/l to

9.8mg/l within the water bodies along the Jangira –Bhanga road. The maximum values were found in Thandu Chowdhurir pukur which is along the Jangira Bhanga road. The mean value was 2.55 mg/l and 47.55 mg/l respectively. Figure 13 and Figure 14 show the comparison of BOD among the 12 stations.

0

100

200

300

400


TD

S

Station Name

0

100

200

300

400


TD

S

Station Name



165

Figure 13. Station wise BOD (Water Bodies along Dhaka-Mawa Road)

Figure 14. Station wise BOD (Water Bodies along Mawa-Bhanga Road)

4. CORRELATION AMONG PARAMETERS

The physico-chemical parameters are correlated with each other. Table 4 and 5 describes the correlation among the parameters of the sample water stations along Dhaka-Mawa and Mawa- Bhanga respectively. It is clear from the correlation table that Conductivity and TDS has a maximum correlation value. Not only these two but also at the same time BOD and DO is correlated with a very good value close to 1. But at the same time DO with Conductivity, DO with TDS, pH with TDS, Conductivity with BOD and TDS with BOD are badly correlated with each other. As the road has a break due to the Padma river it is classified as a road form Dhaka to Mawa and then Mawa to Bhanga.

Table 4. Co-relations among Parameters within Dhaha-Mawa

BOD Salinity TDS Conductivity DO pH Air

Temperature

Air

Temperature

0.333 pH

0.682 0.574 DO

0.077 0.611 0.391 Conductivity

0.999 0.063 0.609 0.375 TDS

0.784 0.767 0.428 0.190 0.167 Salinity

0.406 0.045 0.045 0.913 0.716 0.274 BOD

0

1

2

3

4


BO

D

(mg

/l)

Station Name

0

5

10

15


BO

D (

mg

/L)

Station Name



166

Table 5. Co-relations among Parameters within Mawa-Bhanga

BOD Salinity TDS Conductivity DO pH Air

Temperature

Air

Temperature

0.523 pH

0.978 0.342 DO

000 0.045 0.110 Conductivity

0.980 0.063 0.055 0.265 TDS

0.977 0.937 0.114 0.095 0.232 Salinity

0.130 0.095 0.00 0.991 0.995 0.457 BOD

The standards of water quality for aquaculture have been given in Table 6. There has been given a checklist in Table 7 and 8 which represents the aquatic feasibility of the water bodies in comparison with the standard value form Table 6.

Table 6. Standards of water Quality for aquaculture

Items Value of standard

Color, offensive smell

Fish, shrimp, shell fish and kelp should not have odd color, odd offensive smell

Temperature 26-33ºC

pH value Freshwater 6.5-8.5

Dissolved oxygen In successive 24th, above 16h should be higher than 5mg/l, and the

other time should not be lower than 3mg/l

Biochemical oxygen demand

Should not surpass 5mg/l, frozen period should not surpass 3 mg/l

Secchi Disc visibility

25-45 cm

Salinity 10-25 ppt

TDS NA

Electrical Conductivity

NA

Table 7. Checklist for aquaculture according to water quality parameters (Dhaka-Mawa)

Name of the station



Secchi

depth (cm)

pH

DO

BOD

Salinity

TDS

Conductivity

Pacchor bajar khal

� � T � � � � � �

Thandu Chowdhuri

r Pokur � � � � � � � � �

Arial Kha � � � � � � � � �

Pulia bajar � � � � � � � � �



167

pokur

Bogail Beel � � T � � � � � �

Bhanga Khal

� � T � � � � � �

Table 8. Checklist for aquaculture according to water quality parameters (Mawa-

Bhanga)

Name of the station



Secchi

depth (cm)

pH

DO

BOD

Salinity

TDS

Conductivity

Bawor bity sarok o

janopather pokur

� � � � � � � � �

Dhalashri (1)

� � � � � � � �

Dhalashri (2)

� � � � � � � � �

Shirajdi Khan

Kuchiamara

� � � � � � � �

Chaltipara Pokur

� � � � � � � � �

Masurgow Khal

� � � � � � � � �

5. DISCUSSION

Water quality parameters of 12 water bodies along the Dhaka-Mawa-Bhanga road were investigated to assess the suitability of the water bodies for aquaculture during the pre monsoon season. It is evident from our study that several water quality parameters like- temperature, DO, BOD, electrical conductivity, salinity, TDS showed variability but they are almost within the normal range. Some of the water parameters of closed water ponds indicated that the water quality was not suitable for aquatic animals. The reason behind the unsuitable parameters is due to some undesirable phenomena happening within the particular water bodies. As an example Pulia bajar pukur along the Mawa-Bhanga road is supposed to be unsuitable for aquaculture due to the deviation of BOD and DO level from the standard value which may be because of the presence of organic wastes - generated mainly by local people, in the water body.



168

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2. Aquaculture (1999). “Water quality in freshwater aquaculture ponds. Primary

Industries and Resources SA”. 3. Burford, M. (1997). “Phytoplankton dynamics in shrimp ponds”. Aquaculture

Research. 28:351-360. 4. Costa-Pierce, B. A., Craven D. B., Karl D. M., and Laws E. A. (1984). “Correlation of

in situ respiration rates and microbial biomass in prawn (Macrobrachium rosenbergii) ponds”. Aquaculture 37:157-168.

5. Farmanfarmaian and R.Moor (1978). “Diseasonal thermal aquaculture”.

6. Laws (1993). Code of Conduct for Responsible Fisheries

7. Metcalf and Eddy (2002). “Waste Water Engineering, Treatment and Reuse, 4th

Edition”.

8. M. K. Mustapha and J. S. Omotosho (2005). “An assessment of the physicochemical

properties of Moro Lake, Kwara State, Nigeria”. African Journal of Applied Zoology and Environmental Biology. Vol-7, pp73-77.

9. Niels Jensen (2009). “The Importance of Total Dissolved Solids in the Freshwater

Aquarium”.

10. Sharifun Nahar Islam (2007). “Physico-chemical condition and occurrence of some

Zooplankton in a pond of Rajshahi University”. Journal of fisheries and Hydrobiology. 2(2) Pp-21-25.

11. Swann (1997). “A fish Farmers Guide to understanding water quality in Aquaculture.”

12. Trivedi, R. K. and Goel, P. K. (1986). “Chemical and Biological methods for water

pollution studies”. Environmental Publication Karad (India). pp 250.

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