08168958821
Home » Civil Engineering » EVALUATION OF WATER QUALITY MODELLING PARAMETERS: TOWARDS THE EVOLVEMENT OF RE-A...
EVALUATION OF WATER QUALITY MODELLING PARAMETERS: TOWARDS THE EVOLVEMENT OF RE-AERATION COEFFICIENT FOR RIVERS IN THE NIGERIAN ENVIRONMENT
Sold By: Joe Project Store | Item Type: Project Material | Report this? | Attributes: 65 pages | 1-5 chapters | Amount: ₦5,000 | 3 orders. | Marked useful: 7,446 times
INSTANT PROJECT MATERIAL DOWNLOADABSTRACT
This study was carried out on River Atuwara in Ota, Ogun State, Nigeria with the aim of developing a coefficient of re-aeration model applicable to River Atuwara and other rivers in the Nigerian environment. This was achieved by sourcing for data once every month from 22 sampling locations of interest within a pre-selected segment of the river over a period covering the dry and wet seasons. The data collected include hydraulic data (depth, width, velocity and time of travel) and water quality data such as Dissolved Oxygen (DO) and Biochemical Oxygen Demand (BOD). Excel Spreadsheet and MATLAB were used for data processing. Regression analysis was carried out where stream velocity and depth were the regressors and the re-aeration constant k2 (as a function of BOD, DO and Temperature) was the dependent variable. A coefficient of re-aeration, k2, (Atuwara re-aeration model) was developed and validated statistically. Its performance was also verified by comparing the model with 10 other internationally recognized models. It was found that even though Atuwara model performed better than Agunwamba model and most of the other well cited models, both Atuwara model and Agunwamba model could be safely adopted for future water quality modelling researches in the Nigerian environment. Results of detailed water analysis of samples from River Atuwara shows high level of pollution hence it is unfit for human consumption without adequate treatment. It is recommended that River Atuwara and similar rivers in the country should be regularly monitored for quality control.
This study was carried out on River Atuwara in Ota, Ogun State, Nigeria with the aim of developing a coefficient of re-aeration model applicable to River Atuwara and other rivers in the Nigerian environment. This was achieved by sourcing for data once every month from 22 sampling locations of interest within a pre-selected segment of the river over a period covering the dry and wet seasons. The data collected include hydraulic data (depth, width, velocity and time of travel) and water quality data such as Dissolved Oxygen (DO) and Biochemical Oxygen Demand (BOD). Excel Spreadsheet and MATLAB were used for data processing. Regression analysis was carried out where stream velocity and depth were the regressors and the re-aeration constant k2 (as a function of BOD, DO and Temperature) was the dependent variable. A coefficient of re-aeration, k2, (Atuwara re-aeration model) was developed and validated statistically. Its performance was also verified by comparing the model with 10 other internationally recognized models. It was found that even though Atuwara model performed better than Agunwamba model and most of the other well cited models, both Atuwara model and Agunwamba model could be safely adopted for future water quality modelling researches in the Nigerian environment. Results of detailed water analysis of samples from River Atuwara shows high level of pollution hence it is unfit for human consumption without adequate treatment. It is recommended that River Atuwara and similar rivers in the country should be regularly monitored for quality control.
TABLE OF CONTENTS PAGE
Title Page i
Declaration ii
Certification iii
Dedication iv
Acknowledgement v
Table of Contents vii
List of Figures x
List of Tables xi
List of Plates xiv
Abbreviations and Symbols xv
Abstract xvi
CHAPTER ONE: INTRODUCTION
1.1 Background Information 1
1.2 Water Quality modelling 3
1.3 Description of Study Location 5
1.4 Statement of The Problem 6
1.5 Aim 6
1.6 Objectives 6
1.7 Significance of Study 6
1.8 Scope of Study 7
CHAPTER TWO: LITERATURE REVIEW
2.1 Water Quality Modelling as a Field of Study 8
2.2 Coefficient of Re-aeration, k2 9
2.2.3 The Indian k2 Model 13
2.2.4 The Chilean k2 Model 14
2.2.5 The Nigerian k2 Model 15
2.3 Water Laws and Standards 15
2.4 Statistical Analysis 17
2.4.1 Some Relevant Statistical Operations 17
2.4.2 Statistical Software 19
2.4.3 Model Calibration and Validation in Water Quality
Data 20
2.4.3.1 Sum of Squares Due to Error 21
2.4.3.2 R-Square 21
2.4.3.3 Degrees of Freedom Adjusted R-Square 22
2.4.3.4 Root Mean Squared Error 22
CHAPTER THREE: METHODOLOGY
3.1 Selection of the Study Area 24
3.2 Determination of Sampling Stations 27
3.3 Field Activities 49
3.3.1 Field Observations 31
3.3.2 Field Sampling Visits 31
3.3.2.1 Rationale for Gathering Data Once Every Month 32
3.3.2.2 Activities During the Field Exercises 33
3.4 Materials 34
3.5 Laboratory Analysis 36
3.6 Data Analysis 37
3.6.1 Time of Travel 38
3.6.2 Re-aeration Coefficient Model 39
CHAPTER FOUR: DATA PRESENTATION AND INTERPRETATION
4.1 Data Gathering 40
4.1.1 Hydraulic Data 41
4.1.2 Physico-Chemical Data 50
4.1.3 Monthly Variations in DO, Temperature, Stream Depth 57
4.2 Computation of Measured k2 63
4.3 Re-arrangement of Sampling Stations 67
4.3.1 Time of Travel 68
4.3.2 Hydraulic Radius 80
4.3.3 Ultimate BOD and De-oxygenation Rate 80
4.3.4 Saturation DO and the Upstream and Downstream DO deficits 80
4.3.5 Determination of k2 80
4.3.6 Model Parameters 80
4.3.7 The Model 83
4.3.8 Comparison with other Selected Models 83
4.4 Water Use Practices 103
4.5 Pollutants and Public Health Implications 106
CHAPTER FIVE: CONCLUSION AND RECOMMENDATION
5.1 Conclusion 110
5.2 Contribution to Knowledge 111
5.3 Recommendations 111
REFERENCES 113
APPENDICES
Appendix 1: Matlab Code for Beta 121
Appendix 2: Matlab Model Output 128
Appendix 3: Matlab Code and Output for Plot of all Models 132
Appendix 4: Mix Calculations 140
Appendix 5: Laboratory Reports 147
Appendix 6: Procedure for data Analysis 160
LIST OF FIGURES PAGE
Figure 1.1 - Nigerian Household distribution by source of water supply 2
Figure 1.2 - Nigerian Household distribution by Toilet Facilities 3
Figure 1.3 " General Layout of the Study area 5
Figure 3.1" Field Sampling Stations 28
Figure 3.2 " Linear representation of Sampling Points 29
Figure 3.3 - Sampling Cross-section 33
Figure 4.1 " An 8-month mean stream velocity record 59
Figure 4.2 " An 8-month mean ambient temperature record 60
Figure 4.3 " An 8-month mean water temperature record 61
Figure 4.4 " An 8-month mean stream depth record 61
Figure 4.5 " DO Fluctuations over an 8-month period 62
Figure 4.6 - Flowchart showing 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 against computed k2 using January data 94
Figure 4.9 " Plot of 11 models using March data 96
Figure 4.10 - Plot of measured k2 against computed k2 using March data 97
Figure 4.11 " Plot of 11 models using 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 different water bodies at 20oC 9
Table 2.2 " Solubility of Oxygen in water 10
Table 3.1 - Details of Sampling Stations 30
Table 3.2 " Parameters Measured with Relevance to study 32
Table 3.3 " Parameters, equipment and Processes of parameter determination
Schedule for field work 34
Table 4.1 - Sampling dates and conditions 40
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- Goodness of fit using July Data 92
Table 4.31: Graphical Goodness of fit using January, March and July Data 102
Table 4.32 " Order of Composite Goodness of Fit 103
Table 4.33 " Comprehensive River water and Industrial Effluent Analysis 107
LIST OF PLATES PAGE
Plate 3.1 " The industrial effluent flowing along the road down 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 " Villagers of Iju tapping the river water for domestic use 26
Plate 3.5 " Sewage being taken near the river for disposal 27
Plate 3.6 " Field pH meter 35
Plate 3.7 " Eurolab digital thermometer with sensitive probe 35
Plate 3.8 - Geopacks Stream flow sensor with its pole and fan-like impeller 36
Plate 3.9 - Measuring the river width with a tape 36
Plate 3.10 " the Speedtech Portable Depth Sounder (yellow torchlight shaped
instrument) 57
Plate 4.1 " Sampling Station 10 in Rainy season (August) 58
Plate 4.2 " Sampling Location 10 in Dry season (March) 58
Plate 4.3 " Human skeleton found in the River 104
Plate 4.4 " Pollution along the river channel 104
Plate 4.5 " The research team could not proceed because of blockage of the river 105
Plate 4.6 " Water intake station for Ogun State Water Corporation 105
Plate 4.7 " Man swimming after the day’s work 106
ABBREVIATIONS AND SYMBOLS
1. DO " Dissolved Oxygen
2. BOD - Biochemical Oxygen Demand
3. QUAL " Stream Water Quality models
4. CORMIX " Cornell Mixing Zone Expert
5. WASP " Watershed Quality Analysis Simulation Programme
6. FEPA " Federal Environmental Protection Agency
7. USEPA " United States Environmental Protection Agency
8. USGS " United States Geological Society
9. UNESCO " United Nations Education, Scientific and Cultural Organization
10. DV " Dependent Variable
11. IV " Independent Variable
12. ANOVA " Analysis of Variance
13. SSE " Error Sum of Squares
14. SSR " Residual sum of squares
15. SST " Total sum of squares
16. R2 " correlation coefficient
17. Adj. R2" Adjusted Correlation coefficient
18. RMSE " Root mean square error
19. APHA - American Public Health Association
20. SPSS " Statistical Package for Social Sciences
21. MATLAB " Matrix Laboratory software
22. GPS " Global Positioning System
23. k2 " re-aeration coefficient
24. k1 " de-oxygenation coefficient
25. f " self purification factor
26. 2 ^σ - estimated variance
27. mg/l " milligram per litre
Title Page i
Declaration ii
Certification iii
Dedication iv
Acknowledgement v
Table of Contents vii
List of Figures x
List of Tables xi
List of Plates xiv
Abbreviations and Symbols xv
Abstract xvi
CHAPTER ONE: INTRODUCTION
1.1 Background Information 1
1.2 Water Quality modelling 3
1.3 Description of Study Location 5
1.4 Statement of The Problem 6
1.5 Aim 6
1.6 Objectives 6
1.7 Significance of Study 6
1.8 Scope of Study 7
CHAPTER TWO: LITERATURE REVIEW
2.1 Water Quality Modelling as a Field of Study 8
2.2 Coefficient of Re-aeration, k2 9
2.2.3 The Indian k2 Model 13
2.2.4 The Chilean k2 Model 14
2.2.5 The Nigerian k2 Model 15
2.3 Water Laws and Standards 15
2.4 Statistical Analysis 17
2.4.1 Some Relevant Statistical Operations 17
2.4.2 Statistical Software 19
2.4.3 Model Calibration and Validation in Water Quality
Data 20
2.4.3.1 Sum of Squares Due to Error 21
2.4.3.2 R-Square 21
2.4.3.3 Degrees of Freedom Adjusted R-Square 22
2.4.3.4 Root Mean Squared Error 22
CHAPTER THREE: METHODOLOGY
3.1 Selection of the Study Area 24
3.2 Determination of Sampling Stations 27
3.3 Field Activities 49
3.3.1 Field Observations 31
3.3.2 Field Sampling Visits 31
3.3.2.1 Rationale for Gathering Data Once Every Month 32
3.3.2.2 Activities During the Field Exercises 33
3.4 Materials 34
3.5 Laboratory Analysis 36
3.6 Data Analysis 37
3.6.1 Time of Travel 38
3.6.2 Re-aeration Coefficient Model 39
CHAPTER FOUR: DATA PRESENTATION AND INTERPRETATION
4.1 Data Gathering 40
4.1.1 Hydraulic Data 41
4.1.2 Physico-Chemical Data 50
4.1.3 Monthly Variations in DO, Temperature, Stream Depth 57
4.2 Computation of Measured k2 63
4.3 Re-arrangement of Sampling Stations 67
4.3.1 Time of Travel 68
4.3.2 Hydraulic Radius 80
4.3.3 Ultimate BOD and De-oxygenation Rate 80
4.3.4 Saturation DO and the Upstream and Downstream DO deficits 80
4.3.5 Determination of k2 80
4.3.6 Model Parameters 80
4.3.7 The Model 83
4.3.8 Comparison with other Selected Models 83
4.4 Water Use Practices 103
4.5 Pollutants and Public Health Implications 106
CHAPTER FIVE: CONCLUSION AND RECOMMENDATION
5.1 Conclusion 110
5.2 Contribution to Knowledge 111
5.3 Recommendations 111
REFERENCES 113
APPENDICES
Appendix 1: Matlab Code for Beta 121
Appendix 2: Matlab Model Output 128
Appendix 3: Matlab Code and Output for Plot of all Models 132
Appendix 4: Mix Calculations 140
Appendix 5: Laboratory Reports 147
Appendix 6: Procedure for data Analysis 160
LIST OF FIGURES PAGE
Figure 1.1 - Nigerian Household distribution by source of water supply 2
Figure 1.2 - Nigerian Household distribution by Toilet Facilities 3
Figure 1.3 " General Layout of the Study area 5
Figure 3.1" Field Sampling Stations 28
Figure 3.2 " Linear representation of Sampling Points 29
Figure 3.3 - Sampling Cross-section 33
Figure 4.1 " An 8-month mean stream velocity record 59
Figure 4.2 " An 8-month mean ambient temperature record 60
Figure 4.3 " An 8-month mean water temperature record 61
Figure 4.4 " An 8-month mean stream depth record 61
Figure 4.5 " DO Fluctuations over an 8-month period 62
Figure 4.6 - Flowchart showing 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 against computed k2 using January data 94
Figure 4.9 " Plot of 11 models using March data 96
Figure 4.10 - Plot of measured k2 against computed k2 using March data 97
Figure 4.11 " Plot of 11 models using 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 different water bodies at 20oC 9
Table 2.2 " Solubility of Oxygen in water 10
Table 3.1 - Details of Sampling Stations 30
Table 3.2 " Parameters Measured with Relevance to study 32
Table 3.3 " Parameters, equipment and Processes of parameter determination
Schedule for field work 34
Table 4.1 - Sampling dates and conditions 40
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- Goodness of fit using July Data 92
Table 4.31: Graphical Goodness of fit using January, March and July Data 102
Table 4.32 " Order of Composite Goodness of Fit 103
Table 4.33 " Comprehensive River water and Industrial Effluent Analysis 107
LIST OF PLATES PAGE
Plate 3.1 " The industrial effluent flowing along the road down 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 " Villagers of Iju tapping the river water for domestic use 26
Plate 3.5 " Sewage being taken near the river for disposal 27
Plate 3.6 " Field pH meter 35
Plate 3.7 " Eurolab digital thermometer with sensitive probe 35
Plate 3.8 - Geopacks Stream flow sensor with its pole and fan-like impeller 36
Plate 3.9 - Measuring the river width with a tape 36
Plate 3.10 " the Speedtech Portable Depth Sounder (yellow torchlight shaped
instrument) 57
Plate 4.1 " Sampling Station 10 in Rainy season (August) 58
Plate 4.2 " Sampling Location 10 in Dry season (March) 58
Plate 4.3 " Human skeleton found in the River 104
Plate 4.4 " Pollution along the river channel 104
Plate 4.5 " The research team could not proceed because of blockage of the river 105
Plate 4.6 " Water intake station for Ogun State Water Corporation 105
Plate 4.7 " Man swimming after the day’s work 106
ABBREVIATIONS AND SYMBOLS
1. DO " Dissolved Oxygen
2. BOD - Biochemical Oxygen Demand
3. QUAL " Stream Water Quality models
4. CORMIX " Cornell Mixing Zone Expert
5. WASP " Watershed Quality Analysis Simulation Programme
6. FEPA " Federal Environmental Protection Agency
7. USEPA " United States Environmental Protection Agency
8. USGS " United States Geological Society
9. UNESCO " United Nations Education, Scientific and Cultural Organization
10. DV " Dependent Variable
11. IV " Independent Variable
12. ANOVA " Analysis of Variance
13. SSE " Error Sum of Squares
14. SSR " Residual sum of squares
15. SST " Total sum of squares
16. R2 " correlation coefficient
17. Adj. R2" Adjusted Correlation coefficient
18. RMSE " Root mean square error
19. APHA - American Public Health Association
20. SPSS " Statistical Package for Social Sciences
21. MATLAB " Matrix Laboratory software
22. GPS " Global Positioning System
23. k2 " re-aeration coefficient
24. k1 " de-oxygenation coefficient
25. f " self purification factor
26. 2 ^σ - estimated variance
27. mg/l " milligram per litre
This material content is developed to serve as a GUIDE for students to conduct academic research
Find What You Want By Category:
DOWNLOAD THIS PROJECT MATERIAL NOW!
Advertise Here
For advertisement, call 08168958821
Not what you were looking for? Perform a search
What's your project topic?
Comment on Facebook:
Related Project Materials
- 1.
COMPARATIVE ANALYSIS OF THE STRENGTH OF CONCRETES MADE FROM VARIOUS AGGREGATE
COMPARATIVE ANALYSIS OF THE STRENGTH OF CONCRETE MADE FROM VARIOUS AGGREGATE CHAPTER ONE INTRODUCTION This work was to present in one weight, the fund...More »
Item Type: Project Material | 52 pages | 4,406 engagements |
- 2.
BUILDING COST MANAGEMENTS
CHAPTER ONE INTRODUCTION 1.1 Background to the Study Approaches to the total cost management of construction works are now changing rapid...More »
Item Type: Project Material | 53 pages | 3,709 engagements |
- 3.
AWARENESS AND PRACTICES OF GREEN CONSTRUCTION
AWARENESS AND PRACTICE OF GREEN CONSTRUCTION CHAPTER ONE INTRODUCTION 1.1 Background to study. Green or Sustainable buildings are the future and w...More »
Item Type: Project Material | 60 pages | 3,525 engagements |
- 4.
EFFECT OF THE USE OF SUB-STANDARD MATERIALS ON BUILDING CONSTRUCTION (CASE STUDY OF MINISTRY OF HOUS...
EFFECT OF THE USE OF SUB STANDARD MATERIALS ON BUILDING CONSTRUCTION (CASE STUDY OF MINISTRY OF HOUSING, LAGOS STATE) CHAPTER ONE INTRODUCTION 1.1 ...More »
Item Type: Project Material | 53 pages | 5,522 engagements |
- 5.
BUILDING COLLAPSE : A CHALLENGE FOR THE REAL ESTATE INDUSTRY AND CONSTRUCTION COMPANIES IN NIGERIA
CHAPTER ONE INTRODUCTION 1.1 Background of the study Incidences of the fall of buildings in Nigeria are posing major concerns and challenge to all ...More »
Item Type: Project Material | 53 pages | 4,017 engagements |
- 6.
EFFECTIVENESS OF QUALITY ASSURANCE STRATEGIES IN PROJECT EXECUTION (A STUDY OF ROAD CONSTRUCTION PR...
EFFECTIVENESS OF QUALITY ASSURANCE STRATEGIES IN PROJECT EXECUTION (A STUDY OF ROAD CONSTRUCTION PROJECTS IN OWERRI) CHAPTER ONE INTRODUCTION 1.1 Back...More »
Item Type: Project Material | 51 pages | 10,849 engagements |