DEVELOPMENT OF NON-POINT SOURCE POLLUTION MODEL FOR MAIZE CULTIVATION UNDER TROPICAL CONDITION

RUSNAM

DOCTOR OF PHILOSOPHY UNIVERSITI PUTRA MALAYSIA

2006

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DEVELOPMENT OF NON-POINT SOURCE POLLUTION MODEL FOR MAIZE CULTIVATION UNDER TROPICAL CONDITION

By

RUSNAM

Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia,

in Fulfilment of the Requirement for the Degree of Doctor of Philosophy

June 2006

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DEDICATION

This work is dedicated to my family members

who are always giving me encouragement

and support

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Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment of the requirement for the Degree of Doctor of Philosophy

DEVELOPMENT OF NON-POINT SOURCE POLLUTION MODEL FOR MAIZE CULTIVATION UNDER TROPICAL CONDITION

By

RUSNAM

June 2006

Chairman : Professor Ir. Mohd Amin Mohd Soom, PhD

Faculty : Engineering

Land development activities contribute to water quality impairment. The use of

models plays an important role in the assessment of diffuse pollution sources and

their delivery to the receiving water bodies. Pollutant export equations or event

mean concentration (EMC) values are the basic requirement for storm water

quality assessment and control. This is not yet available for tropical areas such as

the Malaysian environment. This research project was carried out at the Precision

Agriculture Experimental Plot in Universiti Putra Malaysia (UPM). It is located at

latitude 3° 02’ N and longitude 101° 42’ E, with 31 m above mean sea level. The

soil in the study area is Serdang series and the crop grown in the 0.56 ha area was

maize (Zea Mays). The plot was isolated from the surrounding areas by building

perimeter bunds to protect from runoff produced by the adjacent areas. Rainfall is

mainly the driving force for non-point source (NPS) pollution. Therefore, the

daily rainfall data was collected and analysed to study the distribution of daily

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rainfall from 1985 to 2003. Twenty rain events in crop season I, nineteen events in

crop season II and eight events in crop season III were monitored to calculate the

EMC (event mean concentration) values of the parameters which contributed

mostly from the NPS pollution. The median EMC values for BOD, COD, NO3,

TKN, TP, TSS and Turbidity were calculated to be 10.3, 101.2, 1.1, 2.6, 0.7, 1027.1

mg/L and 879.4 NTU in crop season I, 9.0, 88.1, 1.0, 2.1, 0.5, 867.8 mg/L and 856.2

NTU in crop season II and 10.5, 102.5, 0.5, 1.1, 2.6, 0.7, 950.8 mg/L and 886.5 NTU

in crop season III, respectively. From the correlation study, it was observed that

EMC values were significantly related to runoff quantity, dry period between the

storm events and the day after fertilizer application. Multiple regression analyses

among these four parameters were conducted to determine regression models for

the selected pollutants. There was no significant difference between observed and

model data for all parameters, after calibration and validation. It can be concluded

that prediction by the regression model was satisfactory and can be applied to

agricultural areas of similar characteristics. These pollutant export equations

would be useful to predict EMC values and NPS pollution loading under tropical

condition. First flush phenomenon was analyzed for selected parameters. The

strongest first flush phenomenon was observed for Total Suspended Solid (TSS),

where about 60% of pollutant mass (load) could be captured by isolating 42% of

runoff volume. Other parameters exhibited weak and closed to uniform. The

existing Water Quality Index (WQI) proposed by the Department of

Environmental (DOE) Malaysia was reviewed and found to have a few limitations

when applied to agricultural areas. A runoff quality index (RQI) was proposed to

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assess the runoff quality an agricultural area such as a maize field, which includes

Total Kjeldhal Nitrogen (TKN) and Total Phosphorous (TP).

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Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai memenuhi keperluan untuk ijazah Doktor Falsafah

PEMBANGUNAN MODEL PUNCA PENCEMARAN BUKAN TITIK UNTUK TANAMAN JAGUNG DI BAWAH IKLIM TROPIKA

Oleh

RUSNAM

Jun 2006

Pengerusi: Profesor Ir. Mohd Amin Mohd Soom, PhD Fakulti : Kejuruteraan Aktiviti pembangunan tanah menyumbang kepada kemerosotan kualiti air.

Penggunaan model memainkan peranan penting dalam menaksir punca

pencemaran berserak dan penghantaran ke sumber air. Persamaan eksport

pencemar atau nilai kepekatan min peristiwa (EMC) adalah keperluan asas untuk

penaksiran dan kawalan kualiti air hujan. Ini masih belum didapati bagi kawasan

tropika seperti Malaysia. Projek penyelidikan ini telah dijalankan di Plot

Eksperimen ladangan Presis di Universiti Putra Malaysia (UPM). Ia terletak di

latitud 3° 02’ Utara dan longitud 101° 42’ Timur, dengan ketinggian 31 m di atas

paras air laut. Tanah dalam kawasan kajian adalah siri Serdang dan ditanam

dengan jagung (Zea Mays) di kawasan seluas 0.56 ha. Plot kajian diasingkan dari

kawasan keliling dengan membinakan batas untuk menahankan air larian yang

dihasilkan oleh kawasan yang berhampiran. Data hujan adalah pemandu utama

bagi pencemaran punca bukan titik (NPS). Justeru, data hujan harian dikutip dan

dianalisis untuk kajian pertaburan hujan harian dari tahun 1985 ke 2003. Dua

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puluh peristiwa hujan dalam musim tanaman I, sembilan belas peristiwa hujan

dalam musim tanaman II dan lapan peristiwa hujan dalam musim III telah

diperhati untuk mengira EMC bagi parameter yang banyak disumbang oleh

pencemaran NPS. Nilai midian EMC bagi BOD, COD, NO3, TKN, TP, TSS dan

kekeruhan yang dikira terdapat 10.3, 101.2, 1.1, 2.6, 0.7, 1027.1 mg/L dan 879.4

NTU bagi musim tanaman I, 9.0, 88.1, 1.0, 2.1, 0.5, 867.8 mg/L and 856.2 NTU bagi

musim tanaman II dan 10.5, 102.5, 0.5, 1.1, 2.6, 0.7, 950.8 mg/L and 886.5 NTU bagi

musim tanaman III. Dari kajian korelasi, ia dapat diperhatikan bahawa nilai EMC

berhubungan penting terhadap jumlah air larian, tempoh kemarau di antara

peristiwa hujan dan hari selepas pembajaan. Analisis multi-regresi di antara

empat parameter telah dilakukan untuk menentukan model regresi bagi

pencemaran yang terpilih. Tidak ada perbezaan di antara data model dan data

pengamatan untuk semua parameter, selepas kalibrasi dan validasi. Ia boleh

disimpulkan bahawa ramalan dengan mengguna model regresi adalah

memuaskan dan boleh diguna untuk kawasan tropika seperti Malaysia bagi

kawasan pertanian yang serupa. Persamaan eksport pencemaran ini berguna

untuk meramalkan nilai EMC dan muatan pencemaran NPS di bawah iklim

tropika. Fenomena pancur pertama telah pun dianalisis bagi parameter terpilih.

Fenomena pancur pertama yang paling kuat telah diperhatikan bagi jumlah

pepejal terampai (TSS), yang mana sekitar 60% bagi berat pencemaran (muatan)

boleh ditangkap dengan mengasingkan 42% bagi isipadu air larian dan parameter

lain mempamerkan hubungan lemah dan hampir seragam. Indeks Kualiti Air

(WQI) Jabatan Alam Sekitar (DOE) Malaysia telah ditinjau balik dan didapat ada

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kelemahan jika diaplikasikan untuk kawasan pertanian. Indeks Kualiti Larian

(RQI) telah dicadangkan untuk anggaran kualiti air larian bagi kawasan pertanian

seperti ladang jagung yang mencakupi Total Kjeldhal Nitrogen (TKN) dan Total

Phosphorous (TP).

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ACKNOWLEDGEMENTS

First of all I should thank the Almighty, for without His blessings it would not

have been possible for me to do this study. I wish to extend my gratitude to my

employe the Andalas University and the Indonesia government through the

Ministry of Education, for granting me the financial support. Special thanks to

Professor Ir Dr Mohd Amin Mohd Soom, who besides being my supervisor,

tirelessly worked hard to ensure that I managed to complete this study. His

commitment all through my studies was overwhelming. I would also like to thank

my other supervisory committee members, Prof Ir Azni Idris and Assoc. Prof Ir Dr

Lee Teang Shui for their guidance and advice whenever I encountered problems in

the course of my research. I would like to thank the Director of the Institute of

Advanced Technology (ITMA) and Dean of Environmental Science Faculty,

Universiti Putra Malaysia for providing me the use of the laboratory facilities.

Moreover, I would like to extend my thanks to Department of Biological and

Agricultural Engineering, UPM and University Agricultural Park, UPM.

I would like to express my special thanks to all of my friends and colleagues:

Aimrun Wayayok (Thailand), Abdullah Al-Mamun (Bangladesh), Md Rowshon

Kamal (Bangladesh), Ahmed Ibrahim Khmaj (Libya), Mustafa Yusif (Sudan),

Hassan Saad Mohd Hilmi (Sudan), Abdullah and Yousef (Saudi Arabia) and

others who are not mentioned here, for their moral supports during my study.

Last but not least I will never forget to thank my immediate family members

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especially my wife Neni Gusmanizar and my son Ikhwanul Ihsan for their

patience and encouragements, and all friends and colleagues.

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I certify that an Examination Committee has met on the 14th of June 2006 to conduct the final examination of Rusnam on his Doctor of Philosophy thesis entitled “Development of Non Point Source Pollution Model for Maize Cultivation under Tropical Condition” in accordance with Universiti Pertanian Malaysia (Higher Degree) Act 1980 and Universiti Pertanian Malaysia (Higher Degree) Regulations 1981. The Committee recommends that the candidate be awarded the relevant degree. Members of the Examination Committee are as follows:

Ir. Desa Ahmad, PhD Professor Faculty of Engineering Universiti Putra Malaysia (Chairman)

Wan Nor Azmin Sulaiman, PhD Associate Professor Faculty of Environmental Studies Universiti Putra Malaysia (Internal Examiner)

Krishnan Vijayaraghavan, PhD Lecturer Faculty of Engineering Universiti Putra Malaysia (Internal Examiner)

Ir. Mohd. Omar Ab. Khadir, PhD Professor School of Industrial Technology Universiti Sains Malaysia (External Examiner)

_________________________________

HASANAH MOHD GHAZALI, PhD Professor/Deputy Dean School of Graduate Studies Universiti Putra Malaysia Date :

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This thesis submitted to the Senate of Universiti Putra Malaysia and has been accepted as fulfilment of the requirement for the degree of Doctor of Philosophy. The members of the Supervisory Committee are as follows: Ir. Mohd Amin Mohd Soom, PhD Professor Faculty of Engineering University Putra Malaysia (Chairman) Azni Idris, PhD Professor Faculty of Engineering Universiti Putra Malaysia (Member) Ir. Lee Teang Shui, PhD Associate Professor Faculty of Engineering University Putra Malaysia (Member)

________________________ AINI IDERIS, PhD Professor/Dean School of Graduate Studies Universiti Putra Malaysia

Date :

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DECLARATION

I hereby declare that the thesis is based on my original work except for quatations and citations which have been duly acknowledged. I also declare that it has not been previously or currently submitted for any other degree at UPM or other institutions.

_________ RUSNAM

Date: 22 AUG 2006

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TABLE OF CONTENTS

Page

DEDICATION ii ABSTRACT iii ABSTRAK vi ACKNOWLEDMENTS ix APPROVAL xi DECLARATION xii LIST OF TABLES xviii LIST OF FIGURES xx LIST OF PLATES xxiv LIST OF ABBREVIATIONS xxv

CHAPTER

1 INTRODUCTION 1.1

2 LITERATURE RIVEW 2.1 2.1 Introduction 2.1 2.2 Effect from Agricultural Land on Water Quality 2.3 2.3 Rainfall Characteristics in Malaysia 2.6 2.4 Rainfall Seasons in Malaysia 2.8 2.5 Classification of Rain Events 2.8 2.6 Temporal Variation of Rainfall 2.11 2.7 Variation of Rainfall 2.12 2.8 Spatial Variability of Soil 2.13

2.8.1 Basic Knowledge for Electrical Conductivity (EC) 2.16 2.8.2 Global Positioning System 2.21 2.8.3 Electrical Conductivity (EC) Map and Its Uses 2.21

2.9 First Flush Phenomenon 2.23 2.10 History of NPS Pollution Study 2.28 2.11 NPS Pollution Study in Malaysia 2.31 2.12 Estimation of Pollution Loads 2.32

2.12.1 Events Mean Concentration (EMC) Method 2.32 2.12.2 Pollution Loading Rate Method 2.34 2.12.3 Export Equations Method 2.35

2.13 Modelling of Agricultural Runoff Quality 2.36 2.13.1 Deterministic Models 2.36 2.13.2 Regression Models 2.37 2.13.3 Conceptual Models 2.37

2.14 Water Quality Assessment 2.38 3 RESEARCH METHOLODOLOGY 3.1

3.1 Study Area 3.1 3.2 Site Selection Criteria 3.1

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3.3 Cultivation Practices at the Study Area 3.6 3.4 Soil EC Data Collection 3.7 3.5 Research Framework 3.9 3.6 Instrumentation for Collecting Runoff 3.9

3.6.1 Rainfall 3.9 3.6.2 Storm Runoff and Flow 3.11 3.6.3 Sample Collection 3.12 3.6.4 Sample Storage and Preservation 3.13 3.6.5 Laboratory Testing 3.14

3.7 Pollutants Studied 3.15 3.8 Others Parameters Considered 3.16 3.9 Secondary Data Collection 3.16 3.10 Data Screening 3.18 3.11 Data Archiving 3.18 3.12 Quality Control and Quality Assurance 3.18 3.13 Data Analysis 3.19

3.13.1 Graphical Tools 3.19 3.13.2 Analytical Tools 3.19

3.14 Establishment of the Regression Model 3.19 3.14.1 Advantage of the Regression Model 3.21 3.14.2 Limitation of the Regression Model 3.23 3.14.3 Assumption Considered for the Model 3.24 3.14.4 Selection of Variables 3.25 3.14.5 Method of Analysis 3.25 3.15 Calibration and Validation of the Model 3.27 3.16 Runoff Quality Index (RQI) 3.27

4 RESULT AND DISCUSSIONS 4.1 4.1 Soil Physical Properties 4.1 4.2 Soil Chemical Properties 4.2

4.3 Bulk Electrical Conductivity (ECa) Study 4.3 4.3.1 Post Map of ECa 4.3 4.3.2 Kriging Map of ECa 4.6

4.4 Rainfall Analysis 4.15 4.4.1 Monthly Rainfall Pattern 4.21 4.4.2 Design Rainfall for NPS Pollution Control 4.22

4.5 Rainfall Runoff Relationship 4.25 4.6 Rainfall Runoff Coefficient 4.26 4.7 Rainfall Hydrograph at Site 4.27 4.8 Variation of Rainfall and Flow at Site 4.27 4.9 Pollutant Concentration of Storm Runoff 4.32 4.10 Pollutographs of Various Parameters 4.47 4.11 Loadographs of Various Parameters 4.47 4.12 Generation of Annual Loading 4.56 4.13 NPS Pollution Loading Rates 4.65 4.14 First Flush Analyses for the Site 4.67

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4.15 Relation between NPS Pollution and Rainfall Characteristics 4.73

4.16 Development of NPS Pollution Models 4.75 4.16.1 Loading Rate Model 4.78 4.16.2 EMC Model 4.78 4.16.3 Regression Model 4.79

4.17 Water Quality Index (WQI) of the Study Area 4.87 4.18 Proposed Runoff Quality Index for Agricultural Area

(RQI) 4.87 4.19 Application of the Study 4.94

5 SUMMARY, CONCLUTIONS AND RECOMMENDATION 5.1 Summary 5.1 5.2 Conclusions 5.4 5.3 Recommendation 5.5

REFERENCES R1 APPENDICES A1 BIODATA OF THE AUTHOR B1

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LIST OF TABLES Table Page

2.1 A Few Climatic Feature of Malaysia 2.7 2.2 Classification of Malaysian Rainfall (MMS, 1975) 2.10

2.3 Summary of Stormwater Runoff Quality in the Residential Areas of Malaysia 2.33

3.1 Sampling Collection and Preservation Procedure 3.12 3.2 Analytical Methods Used in the Study 3.15 4.1 Soil Physical Properties 4.2 4.2 Soil Chemical Properties 4.3 4.3 Basic Statistic Description for Soil ECa 4.10 4.4 Correlation Coefficient for Soil Properties and ECa 4.12 4.5 Summary Curve Estimation for Soil Available P and

Exchangeable K when ECas is Independent 4.12 4.6 Summary Curve Estimation for Soil Available P and

Exchangeable K when ECad is Independent 4.13 4.7 ANOVA report for Linear Regression of ECas 4.15 4.8 ANOVA report for Linear Regression of ECad 4.15 4.9 Recorded Rainfall Amount at Various Stations for the Sampling Events Crop Season I 4.17 4.10 Recorded Rainfall Amount at Various Stations for the Sampling Events Crop Season II 4.18 4.11 Recorded Rainfall Amount at Various Stations for the Sampling Events Crop Season III 4.18 4.12 Statistical Summary of the Rainfall Data during the Sampling

Events Crop season I 4.19

4.13 Statistical Summary of the Rainfall Data during the Sampling

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Events Crop season II 4.20

4.14 Statistical Summary of the Rainfall Data during the Sampling Events Crop season III 4.20

4.15 Concentration of the Pollutants from the Maize Cultivation Area Crop Season I 4.36

4.16 Concentration of the Pollutants from the Maize Cultivation Area Crop Season I 4.37

4.17 Concentration of the Pollutants from the Maize Cultivation Area Crop Season I 4.38

4.18 Statistical Summary of the Final EMC Values Season I 4.40

4.19 Concentration of the Pollutants from the Maize Cultivation Area Crop Season II 4.42

4.20 Concentration of the Pollutants from the Maize Cultivation Area Crop Season II 4.43

4.21 Concentration of the Pollutants from the Maize Cultivation Area Crop Season III 4.45

4.22 Concentration of the Pollutants from the Maize Cultivation Area Crop Season III 4.46

4.23 Pollution Loading from the Study Area 4.65 4.24 Pollution Loading Rates from the Study Area 4.66 4.25 Pollution Loading Rates from Agricultural and Residential

Area 4.67 4.26 Statistical Summary of the Storm Runoff Characteristics at the Drainage Outlet 4.74 4.27 Regression Models for the All Parameters 4.81 4.28 Model without Inter-event Dry Duration (Dd) 4.82 4.29 Calibration Models with Student t-test at α = 0.05 4.83 4.30 Validation Models with Student t-test at α = 0.05 4.84

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4.31 Existing Water Quality Index (WQI) and Classes 4.93

4.32 Proposed Runoff Quality Index (RQI) and Classes for Agricultural

Areas 4.93

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LIST OF FIGURES

Figure Page

2.1 Main Monsoon Rainfall Season in Malaysia (DID, 2000) 2.9

2.2 Temporal Variation of Monthly Rainfall at Various Location In Malaysia (DID, 2000)) 2.11

2.3 Spatial Variation of Mean Annual Rainfall in Malaysia (DID, 2000) 2.12

2.4 The System Components of Veris Soil EC Mapping-Model:

Veris3100 2.17 2.5 Schematic of Configuration A (Shallow) and B (Deep) 2.18 2.6 Contour Plots of the Measured Signal by Each Unit Soil

Volume 2.20 2.7 Types of First Flush Phenomenon of Storm Runoff

(Griffin et al., 1980) 2.24

2.8 Median and Event First Flush Pattern of Various Pollutants at Same Site (Bertrand-Krajewski, 1998) 2.27

2.9 Variation of Existing Water Quality Sub-indices with Pollutant

Concentration 2.44

3.1 Map of Study Area in UPM Campus, Serdang 3.2 3.2 The Schematic Drawing of the Drains within the Study Area 3.4 3.3 Elevation Height of the Study Area above Mean Sea Level

(MSL) 3.5 3.4 Flowchart of the Research Methodology 3.10 3.5 Steps of Regression Modelling Used in the Study 3.20

4.1 Class Post Map for Shallow ECa (mSm-1) Values within the Study Area (a) Season I, (b) Season II and (c) Season III 4.4

4.2 Class Post Map for Deep ECa (mSm-1) Values within the Study Area (a) Season I, (b) Season II and (c) Season III 4.5 4.3 Kriged Map Map for Shallow ECa (mSm-1 (a) Season I,

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(b) Season II and (c) Season III 4.7

4.4 Kriged Map Map for Deep ECa (mSm-1 (a) Season I, (b) Season II and (c) Season III 4.8

4.5 Varian of Mean Monthly Rainfall at UPM Station (data 1985–2003) 4.21

4.6 Monthly Return Period of Rainfall at UPM Station 4.23 4.7 IDF Curves of Kuala Lumpur 4.24 4.8 Frequency of Daily Rainfall at UPM Rain Gauge 4.24 4.9 Relations with Rainfall and Runoff of the Study Area 4.25 4.10 Relations with Rainfall and Runoff Coefficient of the

Study Area 4.26 4.11 Rainfall Events Analysed for Sampling Program 4.28 4.12 Variation of Rainfall and Flow at Moderate Rainfall 4.33 4.13 Variation of Rainfall and Flow at Heavy Rainfall 4.34 4.14 Variation of Rainfall and Flow at Very Heavy Rainfall 4.35 4.15 Pollutographs at Moderate Rainfall (25.6 mm) in Crop

Season I (29 March 2004) 4.48 4.16 Pollutographs at Moderate Rainfall (26.1 mm) in Crop

Season II (15 October 2004) 4.49 4.17 Pollutographs at Moderate Rainfall (25.2 mm) in Crop

Season III (12 February 2005) 4.50 4.18 Pollutographs at Heavy Rainfall (42.1 mm) in Crop Season I (19 April 2004) 4.51 4.19 Pollutographs at Heavy Rainfall (42.5mm) in Crop Season II (17 October 2004) 4.52 4.20 Pollutographs at Heavy Rainfall (41.1 mm) in Crop Season III (26 February 2005) 4.53 4.21 Pollutographs at Very Heavy Rainfall (79.0 mm) in Crop

Season I (2 April 2004) 4.54

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4.22 Pollutographs at Very Heavy Rainfall (74.1 mm) in Crop

Season II (21 October 2004) 4.55 4.23 Loadographs at Moderate Rainfall (25.6 mm) in Crop Season I (29 March 2004) 4.57 4.24 Loadographs at Moderate Rainfall (26.1 mm) in Crop

Season II (15 October 2004) 4.58 4.25 Loadographs at Moderate Rainfall (25.2 mm) in Crop

Season III (12 February 2005) 4.59 4.26 Loadographs at Heavy Rainfall (42.1 mm) in Crop Season I (19 April 2004) 4.60 4.27 Loadographs at Heavy Rainfall (42.5mm) in Crop Season II (17 October 2004) 4.61 4.28 Loadographs at Heavy Rainfall (41.1 mm) in Crop Season III (26 February 2005) 4.62 4.29 Loadographs at Very Heavy Rainfall (79.0 mm) in Crop

Season I (2 April 2004) 4.63 4.30 Loadographs at Very Heavy Rainfall (74.1 mm) in Crop

Season II (21 October 2004) 4.64 4.31 The First Flush Curves in Crop Season I 4.69 4.32 The First Flush Curves in Crop Season II 4.70 4.33 The First Flush Curves in Crop Season III 4.71 4.34 The First Flush Curves in All Crop Season 4.72

4.35 Correlation of BOD, COD, NO3, TKN and TP (EMC) with the Day after Fertilization 4.76

4.36 Correlation of TSS and Turbidity (EMC) with the Day after Fertilization 4.77 4.37 Calibration of the Regression Models for Various Pollutants 4.85 4.38 Validation of the Regression Models for Various Pollutants 4.86

4.39 Variation of Sub-indices with Pollutant Concentrations for the

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Parameters Required for the Proposed RQI 4.92

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LIST OF PLATES Plate Page

3.1 Aerial Photo of the Study Area 3.3 3.2 Automatic Raingauge 3.11 3.3 Sensor of Water in Drainage Outlet 3.12 3.4 The Sampler had 24 bottles of 1000 ml capacity 3.13 3.5 Rainfall Station Operated by UPM 3.17 3.6 Rainfall Station Operated by MMS 3.17

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LIST OF ABBREVIATIONS

AN Ammoniacal Nitrogen

ANOVA Analysis of Variance

APHA American Public Health Association

ARI Average Recurrence Interval

BMP Best Management Practice

BOD Biological Oxygen Demand

COD Chemical Oxygen Demand

CV Coefficient of Variation

Dd Dry duration between two consecutive rain events

DID Department of Irrigation and Drainage

DOE Department of Environment

EMC Event Mean Concentration

EC Electrical Conductivity

EMI Electromagnetic Induction

IDF Intensity-Duration-Frequency

JICA Japan International Cooperation Agency

L Pollution Load

Lr Pollution Loading Rate

MMS Malaysian Meteorological Services

MPN Most Probable Number

MSMA Manual Saliran Mesra Alam

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NPS Nonpoint Source

NTU Nephelometric Turbidity Unit

NURP Nationwide Urban Runoff Program

PS Point Source

RMSE Root Mean Square Error

RQI Runoff Quality Index

SIAN Sub-index of Ammoniacal Nitrogen

SIBOD Sub-index of Biochemical Oxygen Demand

SICOD Sub-index of Chemical Oxygen Demand

SIDO Sub-index of Dissolved Oxygen

SIpH Sub-index of pH

SITP Sub-index of Total Phosphorus

SITSS Sub-index of Total Suspended Solids

SITUR Sub-index of Turbidity

SPSS Statistical Package for Social Sciences

TKN Total Kjeldhal Nitrogen

TP Total Phosphorus

TSS Total Suspended Solids

TUR Turbidity

UPM Universiti Putra Malaysia

USA United States of America

USAEC United States Atomic Energy Commission

USGS United States Geological Survey

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USMM Urban Stormwater Management Manual for Malaysia

WQI Water Quality Index