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

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.

• Publication year

  2015

• Venue

  Advances in Meteorology

• Publication date

  2015-03-19

• Fields of study

  Geography, Environmental Science

• Identifiers
  DOI 10.1155/2015/380404
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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