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Modeling of rainfall intensity in port harcourt metropolis using dimensional analysis and statistical method

 

Table Of Contents


Project Abstract

Abstract
Rainfall intensity is a critical parameter in hydrological studies and urban planning to mitigate flooding and manage stormwater runoff. In Port Harcourt metropolis, the variability in rainfall intensity poses significant challenges for infrastructure development and environmental management. This research aims to model rainfall intensity in Port Harcourt using dimensional analysis and statistical methods to provide insights for sustainable urban development. The study utilizes dimensional analysis to identify the key parameters influencing rainfall intensity in the region. By considering factors such as rainfall duration, intensity, and spatial distribution, a dimensionless formula is developed to characterize rainfall patterns in Port Harcourt. This approach allows for a comprehensive analysis of the complex interactions between various meteorological variables affecting rainfall intensity. Statistical methods are employed to analyze historical rainfall data collected from different stations within the Port Harcourt metropolis. The data is used to develop regression models that capture the relationship between rainfall intensity and meteorological variables such as temperature, humidity, and wind speed. By statistically analyzing the data, the research aims to identify significant predictors of rainfall intensity and assess their impact on urban hydrology. The integration of dimensional analysis and statistical methods provides a holistic approach to modeling rainfall intensity in Port Harcourt. The developed models offer valuable insights for urban planners, engineers, and policymakers to design resilient infrastructure and implement effective stormwater management strategies. By understanding the factors influencing rainfall intensity, stakeholders can make informed decisions to enhance the city's resilience to extreme weather events. Furthermore, the research contributes to the existing body of knowledge on rainfall modeling in urban areas, particularly in regions with high rainfall variability like Port Harcourt. The findings of this study can serve as a basis for future research on climate change adaptation and sustainable urban development in similar tropical regions. Ultimately, the proposed modeling approach aims to support evidence-based decision-making to address the challenges of urban flooding and climate change in Port Harcourt metropolis. In conclusion, this research employs a multidisciplinary approach combining dimensional analysis and statistical methods to model rainfall intensity in Port Harcourt metropolis. The study aims to provide practical tools and insights for managing urban hydrology and enhancing the resilience of the city to extreme weather events.

Project Overview

INTRODUCTION
1.1         BACKGROUND OF STUDY

Port Harcourt is the capital and biggest City of Rivers State, Nigeria. Its lies down the Bonny River, and is situated at latitude 40 461 3811 N and longitude of 70001 4811 E. Port Harcourt climate is surrounded by the sub-equatorial climate belt. Temperature and humidity are high all through the year, the area is patent by two separate seasons, the wet and the dry seasons with 70% of the annual rains diminishing between April and August while 22% is spread in the three months of September to November and the driest months are from December to March.A lot of attention has been aimed attowards modeling of rainfall intensity in various parts of Nigeria. Sadly, information of the quantity of monthly or yearly rainfall does not in any way present information on the frequency of monthly or yearly rainfall.

Dimensional analysis constitutes the starting point for the design and operation of physical scale models which are used to predict the behavior of their full-sized equivalent called prototypes. Such models, which are generally geometrically similar to the prototype, are used in the design of pumps, spillways, river and estuary engineering works, etc. Mathematical modeling techniques have advanced speedily due to the arrival of high-speed digital computers, enabling equations of motion brace with semi-empirical relationships to be solved for complicated situations. (Featherstone and Nalluri, 1998). Without the technique of dimensional analysis, experimental and computational progress in fluid mechanics would have been considerably delayed. The starting point of dimensional analysis is to decrease the number of separate variables involved in a particular type of physical system into a smaller number of nondimensional groups of the variables. The arrangement of the variables in the groups is generally chosen so that each group has a physical importance. All physical parameters can be precise in terms of a number of basic dimensions. In engineering, the basic dimensions, mass (M), length (L) and time (T) are adequate for this purpose (Featherstone and Nalluri, 1998).

Rainfall intensity is a function that can as well be expressed in terms of basic dimensions. Its unit of mm/hr can be used to determine that its formula is also expressed to be dimensionally compatible to the basic units of length and time. That is the objective of this work. Different characteristics of rainfall are important to specialists in various fields and therefore the number of ways of analyzing rainfall data is quite limitless. The method chosen rely upon the nature of the available data and the intention of the study. At most stations, only daily totals of rainfall are measured. These totals may refer to various storms during a day or to a part of one storm that bridges two measuring periods. In this case the records are a somewhat artificial and inaccurate description of precipitation. The only characteristics of rainfall that can be procure from such data are those pertaining to specified period of time, such as days, months, seasons, or years. A relatively small amount of rainfall-measuring stations are equipped with continuous recording gauges, which yield data on the characteristics of individual storms such as duration and intensity as well as total amount (Thomas and Luna, 1978). Another process in choosing appropriate methods of analysis is the particular planning problem for which a description of the rainfall regime is required. Ecologists and Agronomists may be interested explicitly in seasonal totals, the frequency of small amounts of rain or the likelihood of droughts for their studies of crops or natural plant populations.

Civil engineers focus on the intensity, duration and areal range of the large, infrequent storms that dispute the design of their structures (Thomas and Luna, 1978). The major difficulty faced by engineers and hydrologists in planning and design of water resources structures in the developing nations such as Nigeria is the unavailability of the required long term rainfall data. While rainfall records of many years and subsequently, rainfall frequency atlas are commonly available in developing countries such as United States of America. The engineering application of rainfall intensity is mainly in the process of design discharge for flood control structures. With the recent devastations caused by flood, this study becomes very vital because most drainage structures have been built without the actual rainfall intensity values.

Rainfall intensity is a climate parameter that affects the way and manner man lives. It affects every facet of the ecological system; hence the study of rainfall intensity is important and cannot be over emphasized. Aside the beneficial aspect of rainfall, it can also be destructive in nature; natural disaster like floods and landslides are caused by rain. This project considers modeling rainfall intensity, using the dimensional analysis techniques.

1.2         STATEMENT OF PROBLEM

The insufficient representation of the hydrological data has being a major problem today, because it can lead to over flooding and environmental pollution in rainfall catchments areas, drainages basins or watershed. The flow of liquid water transport hazardous waste materials across the globe, it also involve the reshaping of the geological features of the earth through processes including erosion and sedimentation. For instance, when water flows it evaporates and takes up energy from its surroundings and cools the environment, when it condenses, it releases energy and warms the environment, these heat exchange influences the climate; with such a problem, a model plays an important role in controlling such cases using mathematical analysis.

1.3         OBJECTIVES OF STUDY

The objectives of this study are:

  1. To model rainfall intensity and make predictions using statistical analysis.
  2. To determine the predictions of rainfall intensity data using dimensional       analysis.

iii.           To verify and validate the model to check for accuracy.

1.4         SIGNIFICANCE OF STUDY

The determinationof rainfall intensity models is very vital, particularly for areas that always experience flooding, because with the model, flooding can be controlled and also predictions of catchments response to change, such as land use change, climate change and water quality can be investigated i.e., it plays a great role in water resource management, as it helps in determining the water quality. Also, the study plays a vital role in the meteorological sector as it helps in weather forecasting and rainfall data collection. Hence, with this researchworkgovernment will have a good insight on how to control flooding and also have a visible model for forecasting.

1.5         JUSTIFICATION OF STUDY

Over flooding and erosion control has been a major problem in our environment, especially areas that has no good drainage system, also human health has been affected due to environmental pollution as a result of poor flooding control and forecasting. Hence, in such a case there is need to develop models for effective control and forecasting.

1.6         LIMITATION OF STUDY

The limitations encountered in this research work were: limited meteorological data for developing the model.



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