Modelling of Escherichia coli in The Serin River, Serian Using The

QUAL2K Model

Lim Swee Wee

Bachelor of Science with Honours

(Resource Biotechnology)

2010

Faculty of Economics and Business

Faculty of Resource Science and Technology

Modelling of Escherichia coli in The Serin River, Serian Using The QUAL2K Model

LIM SWEE WEE

(18860)

A thesis submitted in partial fulfilment of the requirement for the degree of Bachelor of

Science with Honours (Resource Biotechnology)

Faculty of Resource Science and Technology

UNIVERSITI MALAYSIA SARAWAK

2010

i

Acknowledgments

My greatest gratitude to my supervisor, Assoc. Prof. Dr. Ling Teck Yee for giving me the

opportunity to work on this project under her guidance, her valuable advice, and most

certainly her generous suggestions and encouragements. I would like to also thank my co.

supervisor, Dr. Lesley Maurice Bilung for her help in the microbiology part of my project

and her assistance in providing the microbiology lab for analysis. Besides that, I would like

to dedicate my special thanks to Ms. Kho Chui Ping (MSc candidate) for sharing her

experiences and knowledge with me throughout my project and also to Ms Koh Kai Ling

(MSc candidate) and Ms. Cheng Yik Ming (MSc candidate) for their help in the

microbiology lab. Furthermore, many thanks to the staffs, especially UNIMAS drivers, and

lab assistants that assisted me during the many field trips. Not to forget to mention my

warmest grateful and thankful to my fellow course mates that assisted me during the entire

project. Lastly, I would like to thank my parents for their understandings and supports.

ii

Table of Contents

Acknowledgement……………………………………………………………………... i

Table of Contents………………………………………………………………............ ii

List of Abbreviations…………………………………………………………….......... v

List of Tables and Figures…………………………………………………….............. vi

Abstract………………………………………………………………………………... ix

1.0 Introduction & Objectives…………………………………………………… 1

2.0 Literature Review………………………………………………………........ 3

2.1 Water Quality Monitoring ……………………………………….. 4

2.2 Conventional Water Pollutants………………………………........ 4

2.2.1 Faecal Indicator Organisms…………………………. 4

2.2.1.1 Faecal Coliforms……………………… 5

2.2.1.2 Escherichia coli………………………...... 6

2.2.2 Suspended Solids …………………………………... 7

2.3 Source of Pollutants ……………………………………………… 8

2.3.1 Animal Farming in Sarawak ………………….…..... 8

2.3.1.1 Waste Effluents from Animal Farming... 9

2.3.2 Agriculture Run-Off…………………………………. 10

2.4 Surface Water Quality Modelling………………………………… 11

2.4.1 History of QUAL Model…………………………….. 11

2.4.2 QUAL2E Model……………………………………... 12

2.4.3 QUAL2K Model……………………………………... 12

2.4.3.1 Modelling Process…………………… 14

iii

2.5 Faecal Bacteria Die-Off Rate……………………………………. 15

2.5.1 Natural Die-Off Rate of Bacteria……………………. 16

2.5.2 Effect of Solar Radiation on Die-Off Rate of Bacteria 17

2.5.3 Effect of Settling on Die-Off Rate of Bacteria……... 18

3.0 Materials and Methods……………………………………………………... 20

3.1 Study Area……………………………………………………….. 20

3.2 Sample Collection and Storage…………………………………... 22

3.3 Data Collection………………………………………………….... 22

3.3.1 In-situ Data Collection……………………………..... 22

3.3.2 Field Measurement……………............................... 22

3.3.2.1 Geometric Characteristics…………… 22

3.3.2.2 Hydraulic Characteristics……………. 24

3.3.3 Meteorological Data…………………………………. 25

3.4 Analysis of Sample……………………………………………...... 25

3.4.1 Total Suspended Solids…………………………….... 25

3.4.2 Bacterial Analysis……………………………………. 26

3.4.2.1 Enumeration and Isolation of

E. coli using Spread Plate Method..…

26

3.5 Statistical Analysis……………………………………………..... 27

3.6 Water Quality Modelling………………………………………… 27

3.6.1 Calibration and Validation…………………………... 30

3.6.2 Data Input…………………………………………... 30

3.6.3 Application of the Model…………………………… 31

4.0 Results and Discussion……………………………………………………. 32

4.1 Hydrogeometric Data……………………………………………. 32

iv

4.1.1 Depth………………………………………………... 32

4.1.2 Width………………………………………………... 33

4.1.3 Flow……………………………………………….... 34

4.2 In-situ Data………………………………………………………. 35

4.2.1 Temperature………………………………………… 35

4.2.2 Solar Radiation……………………………………... 37

4.2.3 pH…………………………………………………... 39

4.2.4 Total Suspended Solids…………………………….. 41

4.2.5 Dissolved Oxygen………………………………….. 43

4.3 E. coli Concentration……………………………………………. 45

4.4 Correlation Study………………………………………………… 47

4.5 Die-Off Rate of E. coli………………………………………...... 47

4.6 Modelling Results………………………………………………... 50

4.6.1 Calibration Results…………………………………. 51

4.6.2 Validation Results………………………………….. 54

4.6.3 Prediction Results………………………………….. 56

4.6.3.1 Prediction of Suitability for Drinking

Water Purpose...................................

56

4.6.3.2 Prediction of Suitability for

Recreational Uses……………………

57

5.0 Conclusions……………………………………………………………....... 59

References……………………………………………………………………….….... 60

Appendices…………………………………………………………………………… 66

Appendix A……………………………………………………………………...…… 66

v

List of Abbreviations

CFU Colony Forming Units

DO Dissolved Oxygen

EMB Eosin Methylene Blue

g/d Gram per Day

g/m3/d Gram per Cubic Meter per Day

IMViC Indole, Methyl Red, Voges-Proskauer, and Citrate

ly hr-1

Langleys per Hour

m2 Square Meter

m3/s Cubic Meter per Second

m/d Meter per Day

mg/d Milligram per Day

mg/m3/d Milligram per Cubic Meter per Day

MPN Most Probable Number

NWQS National Water Quality Standards for Malaysia

TCBS Thiosulfate-Citrate-Bile-Salts-Sucrose

TSS Total Suspended Solids

vi

List of Tables

Table 1: Segmentation of Serin River, Serian................................................ 29

Table 2: Data for calibration and validation.................................................. 31

Table 3: Reaction coefficients that were adopted for QUAL2K model........... 32

Table 4: Mean depth at different stations...................................................... 33

Table 5: Mean width at different stations...................................................... 34

Table 6: Mean flow at different stations........................................................ 35

Table 7: Mean temperature at different stations............................................ 37

Table 8: Mean solar radiation at different stations........................................ 39

Table 9: Mean pH at different stations....................................................... 41

Table 10: Mean total suspended solids at different stations............................. 43

Table 11: Mean DO at different stations...................................................... 45

Table 12: Mean concentrations of E. coli at different stations........................ 47

Table 13: Temperature dependent die-off rate of E. coli using Equation 6..... 49

Table 14: Solar radiation dependent die-off rate of E. coli using Equation 7.. 49

Table 15: Settling dependent die-off rate of E. coli using Equation 9............ 50

Table 16: Total die-off rate of E. coli using Equation 4................................. 50

Table 17: Diffuse flow and non-point E. coli sources.................................... 52

Table 18: Data inputs for model calibration during low tide and high tide...... 53

Table 19: Data inputs for model validation during low tide and high tide....... 55

Table 20: The maximum concentration of E. coli allowed to qualify for Class

IIB water quality........................................................................

58

Table 21: National Water Quality Standards for Malaysia (DOE, 2008)......... 67

Table 22: Water classes and uses (DOE, 2008)............................................ 67

vii

Table 23: Enumeration of E. coli and V. cholerae using Most Probable

Method..........................................................................................

68

Table 23: MPN index for 5 tubes per dilution (10 ml, 1 ml and 0.1ml)

(Clesceri et al., 1998)...................................................................

69

viii

List of Figures

Figure 1: Sampling stations of Serin River where a total of five stations

located along the main river and four tributaries that were

studied with the location of different land uses along the river.....

20

Figure 2: Geometry representation of the river…………………………….. 23

Figure 3: Segmentation of Serin River for QUAL2K model application

(Kho, 2009)…................................................................................

30

Figure 4: Graphical representation of mean temperature at different

stations…………………………………………………………....

37

Figure 5: Graphical representation of mean solar radiation at different

stations……………………………………………………………

39

Figure 6: Graphical representation of mean pH at different stations………. 41

Figure 7: Graphical representation of mean total suspended solids at

different stations……………………………………………….….

43

Figure 8: Graphical representation of mean DO at different stations……… 45

Figure 9: Graphical representation of mean E. coli concentration at

different stations…………………………………………..……….

47

Figure 10: Calibration results of flow and E. coli concentration during

low tide of the Serin River using QUAL2K model………………..

54

Figure 11: Calibration results of flow and E. coli concentration during

high tide of the Serin River using QUAL2K model………………

54

Figure 12: Validation results of flow and E. coli concentration during

low tide of the Serin River using QUAL2K model……………….

56

Figure 13: Validation results of flow and E. coli concentration during

high tide of the Serin River using QUAL2K model…………..….

56

Figure 14: Prediction results of E. coli concentration for drinking

water source without input from Sg. Bukah during low tide of the

Serin River using QUAL2K model. a) during low tide and b)

during high tide.............................................................................

57

Figure 15: Prediction results of E. coli concentration of the Serin River for

recreational purposes using QUAL2K model. a) during low tide

and b) during high tide...............................................................

59

ix

Modelling of Escherichia coli in The Serin River, Serian Using The QUAL2K Model

Lim Swee Wee

Resource Biotechnology Programme

Faculty of Resource Science and Technology

University Malaysia Sarawak

ABSTRACT

Serin River is an important river because it is a source of drinking water and is used for recreation by the

villagers. Hence, the objectives of this study were to determine the impact of different land uses on the faecal

bacteria concentration and to determine the suitability and reliability of QUAL2K model to predict faecal

bacteria concentration in the river water. A total of 8 trips were made from September 2009 till March 2010

with 5 stations along the main river and 4 tributaries that were studied. Results of analysis showed that

tributaries that received pig farm effluent recorded significantly higher mean concentration of Escherichia

coli (E. coli) of 3.31 log CFU/mL and total suspended solids (TSS) of 57 mg/L. Present study also showed

that there is significant correlation between E. coli concentration and TSS. According to the NWQS, all the

stations fell into Class III and Class IV based on E. coli concentration. The model was calibrated and

validated using field data from October 2009 to March 2010. The prediction results showed that for the river

water to be suitable as drinking water source, no E. coli contamination should be discharged from the

headwater and from Sg. Bukah. As for the suitability of river water for recreational purposes, the maximum

recommended concentration of E. coli allowed for the headwater, SB, SP and SR; were <400 CFU/100mL,

<900 CFU/100mL, <1000 CFU/100mL and <380 CFU/100mL respectively during low tide, and during high

tide, maximum concentration of E. coli allowed were <400 CFU/100mL, <1600 CFU/100mL, <2500

CFU/100mL and <510 CFU/100mL respectively. It is recommended that further studies be conducted on

monitoring water quality by using models to ensure long term planning and sustainability use of river water.

Key words: Water quality, animal farming, agriculture run-off, E. coli, QUAL2K.

ABSTRAK

Sungai Serin merupakan sebatang sungai yang penting kerana ia merupakan sumber air minuman serta

digunakan oleh penduduk tempatan untuk tujuan rekreasi. Maka, objektif-objektif kajian ini adalah untuk

menentukan kesan pengunaan tanah yang pelbagai jenis terhadap kepekatan bakteria najis, dan bagi

menentukan kesesuaian dan kebolehpercayaan model QUAL2K dalam meramalkan kepekatan bacteria najis

dalam air sungai. Keputusan analisa menunjukkan anak sungai yang menerima efluen ladang khinzir

mempunyai jumlah purata nyata yang lebih tinggi secara signifikan berbanding anak sungai yang tidak

menerima efluen, di mana Escherichia coli (E. coli) berjumlah 3.31 log CFU/mL dan jumlah pepejal

terampai (TSS) berjumlah 57 mg/L. Kajian menunjukkan bahawa terdapat korelasi yang signifikan antara

kepekatan E. coli dan TSS. Menurut NWQS, semua stesen jatuh ke dalam Kelas III dan Kelas IV berdasarkan

kepekatan E. coli, di mana. Model ditentukur dan disahkan menggunakan data kajian dari Oktober 2009

hingga Mac 2010. Keputusan meramal menunjukkan bahawa tiada pencemaran E. coli daripada hulu sungai

dan daripada Sg. Bukar adalah perlu supaya air sungai dapat dijadikan sebagai sumber air minuman.

Kesesuaian air sungai untuk tujuan rekreasi adalah bergantung kepada kepekatan E. coli di hulu sungai dan

daripada anak sungai di mana, cadangan kepekatan maksima E. coli semasa air surut daripada hulu sungai

adalah <400 CFU/100mL, SB adalah <900 CFU/100mL, SP adalah <1000 CFU/100mL dan SR adalah

<380 CFU/100mL. Kepekatan maksima E. coli semasa air pasang daripada hulu sungai adalah ,400

CFU/100mL, SB adalah <1600 CFU/100mL, SP adalah <2500 CFU/100mL dan SR adalah <510

CFU/100mL. Adalah dicadangkan bahawa kajian lanjutan dijalankan berkaitan penilaian kualiti air dengan

menggunakan model matematik supaya perancangan masa depan dapat dijalankan dan untuk memastikan

kepelbagaian gunaan air sungai.

Kata kunci: Kualiti air, lading haiwan, peningkatan larian pertanian, E. coli, QUAL2K.

1

1.0 Introduction

Constant developments along rivers and streams have been great threats to water quality.

Effluents discharge from animals’ farms, agricultures and residential areas have been a

great source of microbial contamination along the river that prevents the usage of river

water for drinking and recreational purposes (Ganoulis et al., 2005; Ling et al., 2006;

Pappas et al., 2008). Animal wastes have been known to harbour pathogenic organisms

that could cause water-related infectious diseases such as dysentery, cholera,

gastroenteritis, salmonellosis and typhoid fever (Bitton, 1994; Maier et al., 2009; Mara &

Horan, 2003; Steynberg et al., 1995). Therefore, there is a need to understand the

persistence of bacteria in the river so that proper management of waste can be planned.

The major source of organic contamination in Malaysia rivers were caused by

continued discharge of untreated or partially treated waste from human and pigs (Muyibi et

al., 2008). DOE (2008) had reported that monitoring stations in Sarawak showed that 8

river basins were found to be clean and 13 river basins were found to be slightly polluted.

A study by Ling et al. (2006) has shown that tributary that received pig farm effluent

recorded higher level of BOD5, COD, and Escherichia coli (E. coli) when compared to

other tributaries. The DO recorded was also not suitable for aquatic life.

Microbial water quality modelling is used to predict bacterial concentration in

rivers and streams by determining the decay rate of bacteria in the environment. Faecal

coliforms are the most common indicator of microbial contamination in water (Ham &

Kobori, 2009; Mishra et al., 2008). A common approach would be to predict initial loading

concentration of fecal coliforms and the die-off rate as a function of time or distance

travelled from the source and of environmental conditions (Bowie et al., 1985).

2

Hohls et al. (1995), Steynberg et al. (1995) and Venter et al. (1997) had used

QUAL2E model to simulate microbial water quality, but most of the time, the model was

not able to predict microbial concentration accurately. DNR (2007) had used QUAL2K, a

modernised version of QUAL2E, to measure total maximum loads for E. coli but the

amount of sites studied was insufficient. Kho (2009) and Srikaran (2009) had used

QUAL2K model to simulate water quality in the Serin River but the concentration of

faecal bacteria was not simulated. Thus, in this study, QUAL2K model will be used to

simulate different scenarios on the impact of land use on faecal bacteria concentration in

the Serin River.

Objectives

The objectives of this study were:

1. to determine the impact of different land uses on the fecal bacterial concentration in

Serin River, Serian, Sarawak.

2. to determine the suitability and reliability of QUAL2K model to predict fecal

bacterial concentration in the Serin River, Serian, Sarawak.

3

2.0 Literature Review

2.1 Water Quality Monitoring

Water quality monitoring is important to provide a constant updated archive of water

quality data and also allow constant monitoring of pollution sources. Some of the pollution

sources that deteriorate surface water quality are municipal and domestic wastewater,

industrial and agricultural wastes and solid and semisolid refuse (Viessman & Hammer,

2005).

The Department of Environment (DOE) has set up a total of 1,063 monitoring

stations located at 143 river basins during 2008 to detect water quality changes in river

water quality and to identify the pollution sources (DOE, 2008). Using Water Quality

Index (WQI) stipulated by the National Water Quality Standards for Malaysia (NWQS), it

was found that, out of these 1,063 monitoring stations, 612 (58%) were found to be clean,

412 (38%) were found to be slightly polluted and 39 (4%) were polluted. Out of the 143

river basins monitored, 21 were located at Sarawak with 8 river basins found to be clean

and 13 river basins found to be slightly polluted (DOE, 2008). The amount of clean river

basins had also dropped from 91 clean rivers in 2007 to 76 clean rivers in 2008. This was

due to increased in pollutant from sewage treatment plants, agro-based factories and pig

farms. In addition to that, prolonged dry spell in Pahang (5 rivers) and Sarawak (11 rivers)

resulted in deterioration of clean rivers to slightly polluted rivers (DOE, 2008).

The DOE had also reported that 4.48% of water pollution sources were from pig

farming. The rest of the pollution sources were from sewage treatment plants (54.01%),

manufacturing industries (38.73%) and agro-based industries (2.78%). The amount of pig

farms had also increased from 779 in 2007 to 788 farms in 2008 which partly explained the

deterioration of clean rivers in Malaysia (DOE, 2008). Muyibi et al. (2008) had pointed out

4

that the major source of organic contamination in Malaysia rivers were caused by

continued discharge of untreated or partially treated waste from human and pigs.

2.2 Conventional Water Pollutants

Some of the conventional water pollutants are biochemical oxygen demand (BOD),

suspended solids, fecal coliforms, pH, ammonia nitrogen, phosphorus, oil and grease, and

chlorine residual (Viessman & Hammer, 2005). National Water Quality Standards for

Malaysia (NWQS) has set up a guideline to control the concentration of pollutants in the

river by designating water quality index for different degrees of contaminations. Refer

Appendix A for classification.

2.2.1 Fecal Indicator Organisms

Fecal microorganisms are commonly used as an indicator for fecal contamination in the

river (Ham & Kobori, 2009; Mishra et al., 2008). Some of the characteristics of an ideal

fecal indicator organisms are member of the intestinal microflora of warm-blooded

animals, present when pathogens are present and absent in uncontaminated samples,

present in greater numbers than the pathogen, at least equally resistant as the pathogen to

environment harshness and to disinfection in water and wastewater treatment plants, not

multiply in the environment, detectable by means of easy, rapid and inexpensive methods,

and indicator organisms should be non-pathogenic (Bitton, 1994).

5

2.2.1.1 Faecal Coliforms

The coliforms group consists of faecal and non-faecal coliforms. Some of the

characteristics of coliforms group include aerobic and facultative anaerobic, gram-

negative, non-spore-forming, rod-shaped bacteria that ferment lactose with gas production

within 48 hours. Coliforms group are discharged in high numbers (2 X 109 coliforms per

day per capita) in human and animal faeces (Bitton, 1994).

The faecal coliforms are mainly from the Escherichia and Klebsiella genera

whereas the non-faecal coliforms are mainly from the Enterobacter and Citrobacter genera

(Bowie et al., 1985). Faecal coliforms are the most common indicator of microbial

contamination in water due to their risk of infectious diseases towards human. The most

common test to enumerate and isolate faecal coliforms is through multiple-tube

fermentation where incubation is elevated to a higher temperature at around 44.5°C ±0.2°C

(Bowie et al., 1985; Mara & Horan, 2003).

Faecal coliforms can be introduced into the river through point and non-point

sources that include runoff from agriculture lands (Mishra et al., 2008), from discharges of

domestic effluents (Jordao et al., 2007), effluents from animal farm (Ling et al., 2006) and

wildlife animals (Ahmed et al., 2006), from combined sewer overflow and stormwater

effluents (Ham & Kobori, 2009), from industrial discharge (Akaninwor et al., 2006) and

effluents from wastewater treatment plants (Garcia-Armisen & Servais, 2007).

USEPA has recommended that the geometric mean bacterial concentration in

freshwater should be at 33 CFU/100ml for Enterococci and 126 CFU/100mL for E. coli

(USEPA, 2006). Previous studies by Ling et al. (2006) showed that E. coli concentration at

stations situated away from effluents discharge was in the range of 4-141 CFU/mL while

6

E. coli concentration at stations situated near effluents discharge was in the range of 4-10

000 CFU/mL.

2.2.1.2 Escherichia coli

E. coli is a non-sporing, gram negative, rod shape bacterium. It is a facultative anaerobic

microorganism and it ferments lactose. The common way to isolate E. coli would be to

streak on Eosin Methylene Blue (EMB) agar and observe for green metallic sheen colony

which indicates positive result for isolation of E. coli. EMB agar contains lactose which is

used by E. coli for fermentation and acid produced will result in precipitation of green

metallic pigment. The biochemical tests that are used usually to identify E. coli are gram

staining and IMViC test. E. coli will be stained pink or red colour due to the absence of a

thick peptidoglycan cell wall. IMViC test is an acronym that stands for indole, methyl red,

Voges-Proskauer and citrate test. A typical positive result of IMViC test for E. coli will be

++-- (Clesceri et al., 1998).

In recent years, E. coli had substituted faecal coliforms as the ideal indicator

organism because it is easier to distinguish than other faecal coliforms and have a high

occurrence rate in feces (Baudisova, 1997; Bitton, 1994; Edberg et al., 2000; Garcia-

Armisen & Servais, 2004; Tallon et al., 2005). There are several strains of E. coli in

gastrointestinal tract of humans and warm-blooded animals. Diarrhoea is caused by several

virulence strains, such as enterotoxigenic, enteropathogenic, enterohemorrhagic and

enteroinvasive strains where these strains represented approximately 2%-8% strains of E.

coli found in water (Bitton, 1994).

E. coli O157:H7 strain is of great importance because of its ability to cause severe

bloody diarrhea with abdominal cramping, especially with the very young and the very old

7

(Mara & Horan, 2003). In severe case, haemolytic uremic syndrome might occur and cause

kidney damage. There were several outbreak of this strain where in Cabool, Missouri

during winter of 1990, 243 diarrhea cases were reported and 4 registered deaths among the

elderly, and in Sakai, Japan, 1996, 6000 people were infected and 3 children dead (Bitton,

1994).

2.2.2 Suspended Solids

Suspended solids in river or streams are usually from eroded silt, organic silt, organic

detritus and plankton (Kinson et al., 2001). High suspended solids are present in polluted

rivers or streams (Ling et al., 2006; Ling et al., 2007). Several studies had shown that

surface water with high total suspended solids had higher fecal bacteria concentrations

(Fries et al., 2006; Hipsey et al., 2006; Rehmann & Soupir, 2009)

Fecal coliforms concentration in the river could be influenced by sediment

resuspension (Fries et al., 2008). Anderson et al. (2005) showed that fecal coliforms

recorded a higher decay rate when inoculated in saltwater sediments and water column

when compared to freshwater sediments and water column. The study had also shown that

fecal coliforms in freshwater sediments had lower average decay rate when compared to

fecal coliforms in freshwater column. Garcia-Armisen & Servais (2009) had reported that

the decay rate of free E. coli was on average twice higher than the decay rate of attached E.

coli. McFeters (1974) had shown that fecal coliforms had a lower average die off rate (half

life = 17.0 hours) than Vibrio cholerae (half life = 7.2 hours).

8

2.3 Source of Pollutants

The sources of pollutants can be divided into 2 types; point and nonpoint sources. Point

sources are sources that have been well categorized while nonpoint sources cannot be

categorized accurately, i.e. the location of the emission cannot be pinpoint accurately

(Dunnivant & Anders, 2006).

2.3.1 Animal Farming in Sarawak

Pig farming is a lucrative economic opportunity in animal farming industry in Sarawak. It

was estimated that there were 154 farms in Sarawak housing around estimated standing pig

population of 461, 289 which generated about RM 60 million a year (Kinson et al., 2001).

This in turn caused high amount of waste production and thus, the Control of Livestock

Pollution Rules of the Natural Resources and Environmental Board (NREB) Sarawak

specifies that farms with more than 100 animals are required to install oxidation ponds

(Ainon et al., 2005; Ling et al., 2007).

Wastes from animal farming have to be properly treated before being introduced to

the environment. This problem is aggravated with report from Kinson et al. (2001) showed

that a mature pig of an average weight of 150 kg produces three times the waste a person

does which amounted to approximately 21.1 kg/animal/day of solid material and 15.9

liters/animal/day of liquid wastes. Ainon et al. (2005) had reported that in Serian, Sarawak,

there were 2 farms which have been operated for 10 years with 8000 and 800 pigs each.

This would result in approximately 185,680 kg of solid wastes and 139,920 litres of solid

wastes per day.

Due to the high temperature and high humidity of our country, the pigs are hosed

down with water twice a day (Teoh et al., 1988). As a result, the washwater carried pigs’

9

feces, urine and spilled feed from the pig pens. This causes high amount of indirect wastes

being released into the environment in addition to the wastes that have been treated in

oxidation ponds. Kinson et al. (2001) had reported that the oxidation ponds installed in

Sabah were considered too small which caused over spilled of pigs’ wastes. Ling et al.

(2007) had recommended that the pond size had to be in proportionate with the standing

pig population and construction of 3-pond system for better efficiency.

Serin River is an important river in Sarawak because it is a source of drinking water

(Ling et al., 2008). A study by Ling et al. (2006) showed that tributaries that received

wastewater discharge from the pig farms reported high TSS, BOD, and E. coli

concentrations and decreased DO value.

2.3.1.1 Waste Effluents from Animal Farming

Ainon et al. (2005) reported that pollution from animal farming caused generation of

malodor, release of harmful ammonia gas to the atmosphere, under-utilization of persistent

chemicals and spreading of zoonotic diseases. The potential presence of faecal bacteria is

of great concern because of their pathogenicity to transmit diseases. Some of the diseases

transmitted are such as cholera, dysentery, and typhoid fever (Bitton, 1994; Maier et al.,

2009; Mara & Horan, 2003).

Bitton (1994) reported that fecal matter can contained up to 1 X 1012

bacteria per

gram of faeces which represented about approximately 9% by wet weight. There were

about 400 different species of bacteria present in feces where member of

Enterobacteriaceae amounted to an average of 8.6 log/g dry weight (Mara & Horan, 2003).

It had also been reported that the average number of E. coli were 3.3 X 106 per gram of

pig’s feces and daily load E. coli of 8.9 X 109. E. coli concentration in sewage and sewage

10

effluent were 3.4 X 105-2.8 X 10

7 per 100 mL and 1 X 10

3-1 X 10

7 per 100 mL

respectively.

2.3.2 Agricultural Run-Off

Wastewater is often reuse for agricultural irrigation and can be considered as land

treatment and/or disposal (Viessman & Hammer, 2005). It is used to recycle nutrient back

to the land rather than dispose treated wastewater into the river. Manure is also used on

agricultural lands to increase soil fertility and tilth but in many cases, improper usage

caused fecal contamination of the receiving water body (Jamieson et al., 2002; Mishra et

al., 2008; Pachepsky et al., 2006; Pappas et al., 2008; Thiagarajan et al., 2007).

Thiagarajan et al. (2007) had reported that application of dairy manure on field

drainage sites produced annual E. coli loads that varied from 4.1 X 1010

CFU/ha to 5.5 X

1010

CFU/ha. The timing of manure application had effect on run-off of E. coli

concentration where heavy rainfall can increase transport of E. coli from land surface to

water body (Pappas et al., 2008; Shehane et al., 2005).

Indicator organisms can be transported from soil into water body through

movement carrying water and the movement of sediment and waste particles (Jamieson et

al., 2002). Overland flow can be a predominant way for indicator organisms to be

transported from land to surface water (Tyrrel & Quinton, 2003).

11

2.4 Surface Water Quality Modelling

Surface water quality is more reliable and prone to faecal contamination than underground

water as underground water had undergone various types of natural filtration (Mara &

Horan, 2003). During the past decades, water quality has been evaluated and simulated by

mathematical models. The most commonly used models are: multimedia fate models

(Mackay and EUSES models), hydrodynamic models (Mike 11 and QUASAR models),

steady state models (QUAL2E and QUAL2K models) and finally stochastic models

(TOMCAT and GREAT-ER models) (Hassanin, 2007).

Simulation allows an integrated and robust way to evaluate waste load abatement

alternatives, thus able to predict the effects on surface water (Bowie et al., 1985; Ennet et

al., 2008; Mohamed, 2001). A simple model is preferable over a complex model because

of the uncertainty nature of a complex model due to the abundance of data required for

simulation. Several studies had successfully used basic water quality models to simulate

conditions of surface water quality (Fan et al., 2009; Ganoulis et al., 2005; Park & Lee,

2002).

2.4.1 History of QUAL Model

QUAL-1 was built in the late 1960s by the Texas Water Development Board (TWDB)

which was used for steady state predictions of DO, BOD, and NBOD including effects of

longitudinal dispersion, nonpoint runoff and SOD (McCutcheon, 1989). QUAL-1 model

later served as a foundation for later model where in early 1970s, the United States

Environmental Protection Agency (USEPA) built a newer, more advanced model, known

as QUAL-II. Soon, this lead to an enhanced model called QUAL2E which was later

modified to a version named QUAL2K model (Hassanin, 2007).

12

2.4.2 QUAL2E Model

QUAL2E model has been used extensively to simulate surface water quality (Chapra,

1997; McCutcheon, 1989; Paliwal et al., 2007; Park and Lee, 2002). Furthermore the

model is numerically accurate and most conventional pollutants are provided with an

updated kinetic structure (Chapra, 1997; Park and Lee, 2002). The model is able to

simulate the river condition and up to 15 different water quality parameters (Mohamed,

2001).

QUAL2E model is able to simulate concentration of coliforms by determining the

bacteria die-off rate which is expressed as a first order decay functions and represented as:

= - K5 E (1)

where E = concentration of coliforms [colonies/100ml], K5 = temperature dependent

coliforms die-off rate [day-1

] (Brown & Barnwell, 1987). Several studies by Hohls et al.

(1995), Steynberg et al. (1995) and Venter et al. (1997) had used QUAL2E model as a

management tool for microbial water quality control. These studies showed that the

microbial die-off rate and dilution were of little effect considering the concentration of

bacteria at downstream station were still high even though away from the pollution source.

2.4.3 QUAL2K Model

QUAL2K is a modernized version of QUAL2E model that was developed by Brown &

Barnwell (1987). QUAL2K model is mainly used to simulate river and stream condition to

allow a better understanding of the river and stream characteristics. Some of the

characteristics of QUAL2K model include; a one dimensional model where river channel

13

is thought to be well-mixed vertically and laterally; employs steady state hydraulics; uses

diel heat budget and calculates diel water-quality kinetics (Chapra et al., 2007). QUAL2K

model simulates a river by representing a river as a series of reaches which have constant

hydraulics characteristics and these reaches can be further divided into a series of elements.

QUAL2K can simulate several elements including temperature, conductivity,

inorganic solids, dissolved oxygen, carbonaceous biochemical demand, organic nitrogen,

ammonia nitrogen, nitrate nitrogen, organic and inorganic phosphorus, phytoplankton,

detritus, pathogen, alkalinity and pH. Each model elements is simulated as steady-state

flow balance:

Qi= Qi-1 + Qin,i + Qout,I (2)

where Qi = outflow from element i into the downstream element i + 1 [m

3

/d], Qi–1

= inflow

from the upstream element i – 1 [m3

/d], Qin,i

is the total inflow into the element from point

and nonpoint sources [m3

/d], and Qout,i

is the total outflow from the element due to point

and nonpoint withdrawals [m3

/d] (Chapra et al., 2007). A general mass balance for all

constituents except temperature and pH in an element is represented by the equation

below:

i

i

i

ii

i

i

ii

i

i

i

i

iout

i

i

i

i

i

ii SV

Wcc

V

Ecc

V

Ec

V

Qc

V

Qc

V

Q

dt

dc

1

'

1

'

1,

1

1

(3)

where Wi = the external loading of the constituent to element i [g/d or mg/d], Si = sources

and sinks of the constituent due to reactions and mass transfer mechanisms [g/m3/d or

mg/m3/d], iQ

= outflow from element i into element i + 1 [m

3/d], iQ -1 = outflow from the

upstream element i [m3/d],

ioutQ , = total outflow from element due to point and nonpoint