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Software Development And Time Series Analysis Of Keetch-Byram Drought Indexs At Kudat, Sabah


Citation

Mohd Yusof, Mohd Saidy (2006) Software Development And Time Series Analysis Of Keetch-Byram Drought Indexs At Kudat, Sabah. Masters thesis, Universiti Putra Malaysia.

Abstract

Forest fire has causes ecosystem disturbances and cause air pollution. In order to reduce the impact there is a need to have an early warning system for fire prevention controlling measures. One of the early warning systems is Keetch-Byram Drought Index (KBDI). A study has been conducted t develop and use the software to analyse temporal variations in Kudat, Sabah. The KBDI daily values where then model and forecast using Autoregressive Moving Average Model (ARMA). The software was developed using Microsoft Visual Basic Version 6.0 with Microsoft Excel (*.xls) supported format with 3 column entry for dates, rainfall and maksimum temperature. Data from Kudat, Sabah were used to calculate the KBDI using the software. The daily KBDI were then analysed using ARMA in the PEST software. The results showed that the mean percentage error is very high because of the error of prediction given in May, July, August and September, calculated the value of 50.04%, 44.69%,44.08 and 61.35% respectively but other months has given in small prediction error, range from 3% to 40%. An error is occurred because of the averaged measurement and the El-Nino phenomenon. Previous studies on the model which related to weather prediction given a problem in accuracy when El-Nino occurred. To reduce an error of prediction model caused by El-Nino, it is suggested to add more data in current calculation


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Additional Metadata

Item Type: Thesis (Masters)
Subject: Drought forecasting - Computer software - Development - Sabah - Kudat - Case studies
Call Number: FH 2006 6
Chairman Supervisor: Associate Professor Ahmad Ainuddin Nuruddin, PhD
Divisions: Faculty of Forestry
Depositing User: Nurul Hayatie Hashim
Date Deposited: 06 Apr 2010 00:57
Last Modified: 27 May 2013 07:20
URI: http://psasir.upm.edu.my/id/eprint/5063
Statistic Details: View Download Statistic

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