Rainfall Data Generation For Samaru, Zaria Using Statistical Parameters

Project and Seminar Material for Agricultural Economics and Extension

Rainfall Data Generation For Samaru, Zaria Using Statistical Parameters


Abstract


Estimation of rainfall for a desired return period is one of the pre-requisites for any design purpose at a particular site, which can be achieved by probabilistic approach. This study is aimed at using the statistical parameters of long-term observed rainfall data to generate monthly rainfall depth and estimate rainfall values at different return periods for hydrological and agricultural planning purposes. The daily rainfall data of 60 years from 1953 to 2012 were collected from the meteorological station situated at the Institute for Agricultural Research (IAR), Ahmadu Bello University (ABU) Zaria. In this work, the expected number of observations was 720.However, a sample size of 431 being the months with rainfall amounts was used for the study.

Three probability distributions functions viz: normal, log normal and exponential distribution were used for rainfall generation. The data was processed to estimate the statistical parameters of the distributions for Probability Density Functions (PDFs) selected. The two types of parameters estimated using the methods of maximum likelihood via the statistical package called EasyFitXL5.6 are the scale and location parameters. The parameters‟ estimates were further used in various PDFs equations to generate new sets of rainfall amounts. Five statistical goodness of fit test were used in order to select the best fit probability distribution and are; Anderson-Darling, Chi-square and Kolmogorov-Smirnov, ANOVA and Student t test. From the analysis of the data, it was discovered that the normal PDF predicts correctly the monthly amount of rainfall and specific return periods rainfall values followed by the log-normal and exponential PDF, the least predictor.

After carefully observing and testing the three PDFs, it was discovered that the normal PDF estimated closely the monthly amounts of rainfall compared with the log-normal and exponential PDFs when considered generally for monthly and return periods rainfall values estimation. Nevertheless, the normal PDFs have been found to predict well the daily rainfall amounts in Samaru. This work should be made available to local and immediate environments to Samaru through local and regional experts on climatic information dissemination for use in planning and management of specific rainfed crop(s) production.


Chapter One


Introduction

1.1. Background of the Study

Synthetically generated daily or monthly rainfall data are frequently necessary in data scarce environments as input into the planning and design of water resources and soil conservation projects; simulation studies of crop growth and yield; farming systems and field farm operations scheduling ( Jamaludin and Jemain 2007). Rainfall is the principal phenomenon driving many hydrological extremes such as floods, droughts, landslides, debris and mud-flows; its analysis and modelling are typical problems in applied hydrometeorology. Rainfall exhibits a strong variability in time and space. Hence, its stochastic modeling is not an easy task (De Michele and Bernardara, 2005).

A good understanding of the pattern and distribution of rainfall is important for water resource management of an area. Knowledge of rainfall characteristics, its temporal and spatial distribution play a major role in the design and operation of agricultural systems, telecommunications, runoff control, erosion control, as well as water quality systems. Generated weather is needed to supplement existing weather data, provide alternative weather realizations for a particular historical record, or identify possible weather sequences for a seasonal climate forecast (Walpole and Mayers, 1989)


Rainfall Data Generation For Samaru, Zaria Using Statistical Parameters


Project Material Download

3,000 Naira


The complete material will be sent to you in just 2 steps.

Quick & Simple…


Step One Purchase

Make payment of ₦3,000: through USSD Transfer, Bank Mobile App, ATM Transfer, or POS Transfer to:

Access Bank PlcAccount No.: 0811003731
Name: Samphina Academy
Account Type: Current

Or Click Here to pay with Debit Card

FOR CLIENTS OUTSIDE NIGERIA:
Click Here to pay with Debit Card ($15)
GHANA – Make Payment of 60 GHS to MTN MoMo, 0553978005, Douglas Osabutey 

  PAY WITH CRYPTOCURRENCY


Step Two Purchase

Send the following details through Text Message or WhatsApp Messenger | +234-8143831497

  • Payment Details 
  • Email Address 
  • Rainfall Data Generation For Samaru, Zaria Using Statistical Parameters

The complete material will be sent to your email address after receiving your payment information | T & C Apply


  Contact Our Help Desk


You may also like:

⚠️ Need a different topic? Perform a quick search



Get A Complete Business Plan For Any Business In Nigeria

Business Plan for Businesses in Nigeria

  Business Plans in Nigeria


Rainfall Data Generation For Samaru, Zaria Using Statistical Parameters


Disclaimer

This research material “Rainfall Data Generation For Samaru, Zaria Using Statistical Parameters” is for research purposes and should be used as a guide in developing your research project / seminar work. For no reason should you copy word for word (verbatim) as samphina.com.ng will not be liable for any who copied the material.

The aim of providing this material is to reduce the stress of moving from one school library to another all in the name of searching for research materials. This service is legal because, all institutions permit their students to read previous projects, books, articles or papers while developing their own works. According to Austin Kleon “All creative work builds on what came before”.

samphina.com.ng is only providing this material “Rainfall Data Generation For Samaru, Zaria Using Statistical Parameters” as a reference for your research. The paper should be used as a guide or framework for your own paper. The contents of this paper should be able to help you in generating new ideas and thoughts for your own research. Use it as a guidance purpose only.


How to defend your research work


This is a general guide on how to defend your research work:

1. Prepare For Questions:

If you are preparing for questions that may be asked during your defense, then your answers will flow smoothly and effectively. This will prove your knowledge on the subject e.g “Rainfall Data Generation For Samaru, Zaria Using Statistical Parameters“, and strengthening your argument. Ask friends and family, read your work for them to listen to your presentation, and write down questions. You may be lucky the panel will ask you those you have already prepared on.

2. Strong Summary:

Summarizing your chapters will help keep your audience focused because it is easy for a mind to drift, so providing summaries will ensure your panel will follow along, even if they lose focus for a brief moment. Visual aides, such as graphs and power-point presentations can be very helpful. If you are going to use these, make sure you will practice your presentation with them.

3. Be Confident in Your Research Work:

Not knowing your topic “Rainfall Data Generation For Samaru, Zaria Using Statistical Parameters” inside out will cause you to struggle and ultimately fail with your defense. You need to know the subject from every angle to ensure you are fully prepared for any question that may come your way.

4. Conclusion:

Reinforce your findings to conclude your defense. The finale of your presentation should focus on proving the work that has been done. You may need to recap on what has changed and remained unchanged, if is necessary.

5 . Listen:

Before you get defensive or recite a particular answer, make sure you truly understand the question being asked. Being a good listener is an important quality, because providing an inaccurate or off-topic answer will also weaken the validity of your paper.

Samphina Academy

Samphina Academy is an Online Educational Resource Center that is aimed at providing students with quality information and materials to aid them in succeeding in their academic pursuit.