Modelling rainfall patterns in Meru and Embu regions using generalized linear models and series models/ (Record no. 86766)

MARC details
000 -LEADER
fixed length control field 02379nam a22002057a 4500
003 - CONTROL NUMBER IDENTIFIER
control field KE-MeUCS
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200305100409.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200305b xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
Source
040 ## - CATALOGING SOURCE
Transcribing agency KE-MeUCS
Modifying agency KE-MeUCS
050 ## - LIBRARY OF CONGRESS CALL NUMBER
Classification number QC926.2.C4 2019
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Chepkoech, Carllen
245 ## - TITLE STATEMENT
Title Modelling rainfall patterns in Meru and Embu regions using generalized linear models and series models/
Statement of responsibility, etc Carllen Chepkoech
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Meru:
Name of publisher, distributor, etc Carllen Chepkoech,
Date of publication, distribution, etc 2019.
300 ## - PHYSICAL DESCRIPTION
Extent xii, 49pg:.
500 ## - GENERAL NOTE
General note Includes Reference
520 ## - SUMMARY, ETC.
Summary, etc Rainfall is the meteorological phenomenon that is useful for human activities.Majority of population depend on rainfall water for agriculture and domestic use. Since Meru and Embu regions are agricultural zones relying heavily on rainfed agriculture , it is important for farmers to know rainfall patterns prevailing in their regions. The main objective of this study was to model rainfall patterns in Meru and Embu regions. Stationarity and unit root for data were tested, time series model was developed and fitted to the historical data using Box- Jenkins (BJ) Methodology and rainfall in the regions were forecasted for five years. Monthly and yearly rainfall and temperature data obtained from Kenya meteorological department for the period 1976-2015 was used in the study. This information can be used in planning and management of water for domestic and agricultural use in the regions. Rainfall data was found to be seasonally and non-stationary and hence differencing and seasonal differencing was applied to achieve stationarity.Rainfall in both regions has short rains in the months of October to December (OND) and long rains in the moths of March to May (MAM). The model that best fitted rainfall data was ARIMA (1,1,1)(0,1,1)12. This model was used to forecast monthly rainfall patterns for five years and found that future rainfall patterns will not change with time. Negative binomial model was found to be the best model since it had a lower Akaike Information Criterion (AIC).After fitting the data to this model the mean amount of rainfall was found to change with slight change in the temperature in both regions. It was recommended that, future researchers should consinder zoning regions and apply developed ARIMA model and negative binomial to homogeneous zones.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Thesis
Cataloguer
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Cataloger Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Library of Congress Classification     Meru University Meru University Short Loan 05/03/2020       QC926.2.C4 2019 19-32926 05/03/2020 05/03/2020 Thesis

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