• Login
    View Item 
    •   Repository
    • Journal Articles
    • Articles: Department of Water and Agricultural Resources Management
    • View Item
    •   Repository
    • Journal Articles
    • Articles: Department of Water and Agricultural Resources Management
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Rainfall Variability, Drought Characterization, and Efficacy of Rainfall Data Reconstruction: Case of Eastern Kenya

    Thumbnail
    View/Open
    Full text (2.631Mb)
    Date
    2014-08
    Author
    Kisaka, Oscar M.
    Mucheru-Muna, Monicah
    Ngetich, F.K.
    Mugwe, Jayne
    Mugendi, Daniel N.
    Mairura, F.
    Metadata
    Show full item record
    Abstract
    This study examined the extent of seasonal rainfall variability, drought occurrence, and the efficacy of interpolation techniques in eastern Kenya. Analyses of rainfall variability utilized rainfall anomaly index, coefficients of variance, and probability analyses. Spline, Kriging, and inverse distance weighting interpolation techniques were assessed using daily rainfall data and digital elevation model using ArcGIS. Validation of these interpolation methods was evaluated by comparing the modelled/generated rainfall values and the observed daily rainfall data using root mean square errors and mean absolute errors statistics. Results showed 90% chance of below cropping threshold rainfall (500 mm) exceeding 258.1 mm during short rains in Embu for one year return period. Rainfall variability was found to be high in seasonal amounts (CV = 0.56, 0.47, and 0.59) and in number of rainy days (CV = 0.88, 0.49, and 0.53) in Machang’a, Kiritiri, and Kindaruma, respectively. Monthly rainfall variability was found to be equally high during April and November (CV = 0.48, 0.49, and 0.76) with high probabilities (0.67) of droughts exceeding 15 days in Machang’a and Kindaruma. Dry-spell probabilities within growing months were high, (91%, 93%, 81%, and 60%) in Kiambere, Kindaruma, Machang’a, and Embu, respectively. Kriging interpolation method emerged as the most appropriate geostatistical interpolation technique suitable for spatial rainfall maps generation for the study region.
    URI
    http://hdl.handle.net/123456789/282
    Collections
    • Articles: Department of Water and Agricultural Resources Management [200]

    University of Embu copyright ©  2021
    Contact us | Send Feedback
    Library ER 
    Atmire NV
     

     

    Browse

    All of RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    University of Embu copyright ©  2021
    Contact us | Send Feedback
    Library ER 
    Atmire NV