A time series analysis of the monthly distribution of rainfall in enugu metropolis
Table Of Contents
Chapter ONE
INTRODUCTION
- 1.1Introduction
- 1.2Background of study
- 1.3Problem Statement
- 1.4Objective of study
- 1.5Limitation of study
- 1.6Scope of study
- 1.7Significance of study
- 1.8Structure of the research
- 1.9Definition of terms
Chapter TWO
LITERATURE REVIEW
- 2.1Overview of Time Series Analysis
- 2.2Importance of Rainfall Distribution Studies
- 2.3Previous Studies on Rainfall Distribution
- 2.4Methods Used in Rainfall Time Series Analysis
- 2.5Factors Influencing Monthly Rainfall Patterns
- 2.6Technology and Tools for Rainfall Data Analysis
- 2.7Impact of Climate Change on Rainfall Distribution
- 2.8Statistical Techniques for Analyzing Rainfall Data
- 2.9Challenges in Rainfall Time Series Analysis
- 2.10Future Trends in Rainfall Distribution Studies
Chapter THREE
RESEARCH METHODOLOGY
- 3.1Research Methodology Overview
- 3.2Data Collection Methods
- 3.3Sampling Techniques
- 3.4Data Analysis Procedures
- 3.5Software for Data Analysis
- 3.6Research Design
- 3.7Ethical Considerations
- 3.8Validity and Reliability of Data
Chapter FOUR
DATA PRESENTATION AND ANALYSIS
- 4.1Overview of Findings
- 4.2Analysis of Monthly Rainfall Distribution Patterns
- 4.3Correlation Analysis of Rainfall Data
- 4.4Seasonal Variations in Rainfall Distribution
- 4.5Comparison with Previous Studies
- 4.6Impact of Urbanization on Rainfall Patterns
- 4.7Discussion on Climate Change Effects
- 4.8Implications of Findings for Policy and Planning
Chapter FIVE
SUMMARY, CONCLUSION AND RECOMMENDATIONS
- 5.1Summary of Findings
- 5.2Conclusion
- 5.3Recommendations for Future Research
- 5.4Implications for Practical Applications
- 5.5Contribution to the Field of Rainfall Distribution Studies
Thesis Abstract
It is widely accepted that water supply will be a pressing issue in this century. Thus, position of adequate rainfall in the development of human and natural resources is a worthwhile research work. The data used in this project work was monthly amount of rainfall in Enugu city within the period of (2000 – 2012). A preliminary inspection on the data revealed that the data has no trend but consist of multiplicative seasonal movements. Furthermore, the monthly data was also found to be stationary and serially uncorrelated by the Augmented Dickey Fuller test of unit root and the Autocorrelation test for serial correlation of the error term respectively. The exponential smoothing procedures were adopted for the construction of the best fit model for the prediction of future rainfall pattern in Enugu. This was achieved by algorithms aimed at smoothing out all irregular components inherent in the series. The best fit model parameters were used to predict monthly rainfall distribution for 2013. The result suggested heavy rainfall in general for the year in question with its amplitude in the month of October.
Thesis Overview
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