EVALUATION OF WATER QUALITY

EVALUATION OF WATER QUALITY MODELLING PARAMETERS: TOWARDS THE EVOLVEMENT OF RE-AERATION COEFFICIENT FOR RIVERS IN THE NIGERIAN ENVIRONMENT

ABSTRACT

This research was conducted on the River Atuwara in Ota, Ogun State, Nigeria, with the goal of producing a coefficient of re-aeration model that could be applied to the River Atuwara and other rivers in the Nigerian environment. This was accomplished by collecting data once a month from 22 sampling locations of interest within a pre-selected portion of the river during the dry and wet seasons. Hydraulic data (depth, width, velocity, and time of passage) as well as water quality data such as Dissolved Oxygen (DO) and Biochemical Oxygen Demand (BOD) were obtained. For data processing, Excel Spreadsheet and MATLAB were utilized. The re-aeration constant k2 (as a function of BOD, DO, and temperature) was the dependent variable in a regression analysis using stream velocity and depth as regressors. A re-aeration coefficient, k2, (Atuwara re-aeration model), was created and statistically confirmed. The model’s performance was also validated by comparing it to ten other highly renowned models. Even though the Atuwara model outperformed the Agunwamba model and the majority of the other well-cited models, both the Atuwara model and the Agunwamba model could be safely used for future water quality modeling studies in the Nigerian setting. The results of rigorous water analysis of River Atuwara samples show a significant level of pollution, making it unsafe for human consumption without adequate treatment. River Atuwara and other comparable rivers in the country should be frequently checked for quality management.

PAGE TABLE OF CONTENTS

Title Page i Declaration ii Certification iii Dedication iv Acknowledgement v Table of Contents vii Figure List x Table of Tables xi

Plates Catalogue xiv

Symbols and abbreviations xv

xvi Abstract

INTRODUCTION TO CHAPTER ONE

1.1 Historical Background Modeling Water Quality 1 1.2 3 1.3 Study Location Description 5 1.4 Statement of the Problem 6 1.5 Aim 6 1.6 Objectives 6 1.7 Importance of the Study 6 1.8 Scope of the Study 7

REVIEW OF LITERATURE IN CHAPTER TWO

2.1 Water Quality Modeling as a Study Subject 8

2.2 k2 9 Coefficient of Re-aeration

2.2.3 Model 13 of the Indian k2

2.2.4 The k2 Model 14 from Chile

The Nigerian k2 Model 15 is described in detail in Section 2.2.5.

2.3 Water Laws and Regulations 15

2.4 Statistical Evaluation 17

2.4.1 Several Statistical Operations 17

2.4.2 Statistical Software 20

2.4.3 Water Quality Data Model Calibration and Validation 20

2.4.3.1 Sum of Squares as a result of Error 21

R-Square 21 is defined as 2.4.3.2

2.4.3.3 R-Square Adjusted Degrees of Freedom 22

2.4.3.4 Error in Root Mean Squared 22

METHODOLOGY IS THE THIRD CHAPTER.

3.1 Selection of the Study Area 24

3.2 Establishment of Sampling Stations 27

3.3 Experiential Activities 49

3.3.1 Observations in the Field 31

3.3.2 Visits to Field Sampling Sites 31

3.3.2.1 Justification for Gathering Data Once a Month 32 3.3.2.2 Activities During Field Exercises 33

3.4 Resources 34

3.5 Laboratory Examination 36

3.6 Data Interpretation 37

3.6.1 Duration of Travel 38

3.6.2 Model of Re-aeration Coefficient 39

DATA PRESENTATION AND INTERPRETATION IN CHAPTER FOUR

4.1 Data Collection 40

4.1.1 Hydraulic Data 41 4.1.2 Physico-Chemical Data 50

4.1.3 Monthly Changes in DO, Temperature, and Stream Depth 57

4.2 Measured k2 Computation

4.3 Reorganization of Sampling Stations 67

4.3.1 Travel Duration 68

4.3.2 Hydraulic Radius of 80 mm

4.3.3 De-oxygenation Rate and Ultimate BOD Rate 80

4.3.4 Deficits in Saturation DO and Upstream and Downstream DO 80

4.3.5 Determination of the k2 80

4.3.6 Parameters of the Model 80

The Model 83 (Chapter 4.3.7)

4.3.8 Model Comparison with Other Models 83

4.4 Water Consumption Practices 103

4.5 Pollutants and Their Implications for Public Health 106

CONCLUSION AND RECOMMENDATIONS IN CHAPTER FIVE

5.1 Concluding Statement 110

5.2 Contributions to Knowledge 111

5.3 Advice 111

INCLUDED REFERENCES 113

APPENDICES

Appendix 1 contains the Matlab code for Beta 121.

128 Matlab Model Output

Appendix 3: Matlab Code and Output for All Model Plots 132

Appendix 4: Calculations for Mixtures 140 Appendix 5: Laboratory Reports 147

Appendix 6: Data Analysis Procedures 160

PAGE OF FIGURES

Figure 1.1: Distribution of Nigerian households by water supply source. 2

Figure 1.2: Distribution of Nigerian Households by Toilet Facilities 3

Figure 1.3 “General Study Area Layout 5 ”

Figure 3.1 “Field Sampling Stations 28”

Figure 3.2 “Sampling Points Linear Representation 29”

Figure 3.3 – Cross-section of a Sampling 33

Figure 4.1 “An eight-month mean stream velocity record 59

Figure 4.2 “An 8-month average ambient temperature record 60”

Figure 4.3 “An 8-month average water temperature record 61”

Figure 4.4 “An eight-month mean stream depth record 61”

Figure 4.5 “DO Fluctuations during an Eight-Month Period 62

Figure 4.6 depicts the progression of the statistical analysis. 86

Figure 4.7 ” Plot of 11 models using January data 93 ”

Figure 4.8 ” Plot of measured k2 versus computed k2 using January data 94″

Figure 4.9 ” Plot of 11 models based on March data 96

Figure 4.10 – Plot of measured k2 versus estimated k2 using March data 97

Figure 4.11 “Plot of 11 models based on July data 99″

Figure 4.12 – Plot of measured k2 against computed k2 using July data 100.

LIST OF TABLES PAGE

Table 2.1 ” The self-purification factor, f, of various water bodies at 20oC 9 Table 2.2 ” Oxygen Solubility in Water 10 Table 3.1 – Sampling Station Details 30 Table 3.2 ” Parameters Measured with Relevance to Study 32

Table 3.3 ” Parameters, equipment, and parameter determination processes Schedule for field work 34

Table 4.1 shows the sampling dates and conditions.

Table 4.2a ” Hydraulic Data for January 42 Table 4.2b ” Hydraulic Data for February 43 Table 4.2c ” Hydraulic Data for March 44 Table 4.2d ” Hydraulic Data for April 45 Table 4.2e ” Hydraulic Data for May 46 Table 4.2f ” Hydraulic Data for July 47 Table 4.2g ” Hydraulic Data for August 48 Table 4.2h ” Hydraulic Data for September 49 Table 4.3a ” Physico-Chemical Parameters for January 50 Table 4.3b ” Physico-Chemical Parameters for February 51 Table 4.3c ” Physico-Chemical Parameters for March 52 Table 4.3d ” Physico-Chemical Parameters for April 53 Table 4.3e ” Physico-Chemical Parameters for May 54 Table 4.3f ” Physico-Chemical Parameters for July 55 Table 4.3g ” Physico-Chemical Parameters for August 56 Table 4.3h” Physico-Chemical Parameters for September 57 Table 4.4 ” Mean Monthly Ambient and Water Temperatures 60 Table 4.5 ” Determination of Reaches for the River 64 Table 4.6 – Dilution Effects for January 65 Table 4.7 – Dilution Effects for February 65 Table 4.8 – Dilution Effects for March 65 Table 4.9 – Dilution Effects for July 66 Table 4.10 – Dilution Effects for August 66 Table 4.11 – Dilution Effects for September 66 Table 4.12 ” Re-arrangement of station numbers 67

Table 4.13 ” Computation of time of travel on Programmed Excel Spreadsheet for January 68 Table 4.14 ” Computation of time of travel on Programmed Excel Spreadsheet for February 69 Table 4.15 ” Computation of time of travel on Programmed Excel Spreadsheet for March 70 Table 4.16 ” Computation of time of travel on Programmed Excel Spreadsheet for July 71 Table 4.17 ” Computation of time of travel on Programmed Excel Spreadsheet for August 72 Table 4.18 ” Computation of time of travel on Programmed Excel Spreadsheet for September 73 Table 4.19 ” Computation of k1 and k2 on Programmed Excel Spreadsheet for JanuaryTable 4.20 ” Computation of k1 and k2 on Programmed Excel Spreadsheet for February 75 Table 4.21 ” Computation of k1 and k2 on Programmed Excel Spreadsheet for March 76 Table 4.22″ Computation of k1 and k2 on Programmed Excel Spreadsheet for July 77 Table 4.23 ” Computation of k1 and k2 on Programmed Excel Spreadsheet for August 78 Table 4.24 ” Computation of k1 and k2 on Programmed Excel Spreadsheet for September 79 Table 4.25″ Model fit and goodness of fit Summary for Dry Season 81 Table 4.26″ Model fit and goodness of fit Summary for Rainy Season 82 Table 4.27 ” Selected Models for Model Validation (Test of performance) 84

Table 4.28″ Goodness of Fit Using January Data 91

Table 4.29- Goodness of Fit Using March Data 91

Table 4.30- July Data Goodness of Fit 92

Table 4.31: Graphical Goodness of Fit Using Data from January, March, and July 102

“Order of Composite Goodness of Fit” Table 4.32 103

“Comprehensive River Water and Industrial Effluent Analysis,” Table 4.33 PAGE 107 OF PLATES LIST

Plate 3.1 “The industrial effluent flowing down the road towards the river” 25 Plate 3.2 “The effluent accumulates (left) from where it seeps into the river body” 25 Plate 3.3 ” Effluent accumulation beside the river body” 26 Plate 3.4 “Iju villagers drawing river water for domestic use” 26 Plate 3.5 “Wastewater being transported to the river for disposal Field pH meter 27 Plate 3.6 ” Eurolab digital thermometer with sensitive probe 35 Plate 3.7 ” 35

Geopacks Stream flow sensor with pole and fan-like impeller (Plate 3.8) 36 Plate 3.9 – Using a tape measure to determine the width of the river 36 Plate 3.10 ” the Speedtech Portable Depth Sounder (yellow torchlight shaped instrument) 57 Plate 4.1 ” Sampling Station 10 during the rainy season (August) 58 Plate 4.2 ” Sampling Station 10 during the dry season (March) 58 Plate 4.3 ” Human skeleton discovered in the River 104 Plate 4.4 ” Pollution along the river channel 104 Plate 4.5 ” The study team was unable to advance due to river blockage 105 Plate 4.6 ” Water intake station for Ogun State Water Corporation 105 Plate 4.7 ”

Plate 4.7 “A man swimming after a hard day’s work” 106

SYMBOLS AND ABBREVIATIONS

1. “Dissolved Oxygen”

BOD stands for Biochemical Oxygen Demand.

3. QUAL “Models of Stream Water Quality”

4. ” Cornell Mixing Zone Expert” CORMIX

WASP stands for “Watershed Quality Analysis Simulation Programme.”

FEPA stands for “Federal Environmental Protection Agency.”

“USEPA” stands for “United States Environmental Protection Agency.”

“USGS” stands for “United States Geological Society.”

UNESCO stands for “United Nations Educational, Scientific, and Cultural Organization.”

DV stands for “Dependent Variable.”

IV. “Independent Variable”

ANOVA stands for “Analysis of Variance.”

SSE stands for “Error Sum of Squares.”

SSR stands for “Residual Sum of Squares.”

SST = “Total sum of squares”

R2 is the correlation coefficient.

17. Adjusted R2″ Correlation coefficient

RMSE stands for “Root Mean Square Error.”

APHA stands for American Public Health Association.

SPSS is an abbreviation for “Statistical Package for Social Sciences.”

MATLAB stands for “Matrix Laboratory Software.”

GPS stands for “Global Positioning System.”

k2 is the re-aeration coefficient.

k1 “de-oxygenation coefficient” 24.

f ” self-purification factor” 25.

26. 2 – calculated variance

27 milligrams per litre