Evaluation of Three Geostatistical Interpolation Methods for the Estimation of Average Daily Rainfall

Daffi, R. E. and Wamyil, F. B. (2020) Evaluation of Three Geostatistical Interpolation Methods for the Estimation of Average Daily Rainfall. In: Current Perspectives to Environment and Climate Change Vol. 3. B P International, pp. 42-50. ISBN 978-93-89562-77-4

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Abstract

This study focuses on evaluating the results from three geostatistical interpolation methods used for
the estimation of average daily rainfall in ILWIS 3.7. Rainfall data from nine (9) gauging points over
the Upper Deep River Basin, North Central Nigeria were used.The total catchment area is 6076 km2.
The moving average method, ordinary kriging technique and nearest point or Thiessen method were
used for the interpolation. The rainfall values used were for five (5) days in the same month where
rainfall data for at least six (6) of the nine (9) gauging points were recorded, since rain did not fall on
the whole the catchment on the same day. The results obtained from the different geostatistical
methods used were different but closely similar with the moving average method recording the highest
rainfall values for all interpolations. The techniques behind the methods were evaluated and
discussed based on the results obtained. From the results it was observed that the moving average
method calculated half of the maximum rainfall within the catchment and assigned that value for the
average rainfall while in the Thiessen polygon method, the results obtained were similar to the
arithmetic average of the rainfall values with all zero points counted as one point. The work
demonstrated that remote sensing and GIS techniques are fast in the estimation of average rainfall
over a catchment area and the estimated rainfall data for any point within the catchment can be
obtained from the output raster maps. It is recommended for GIS users to choose the geostatistical
method that best suits their purpose.

Item Type: Book Section
Subjects: Apsci Archives > Geological Science
Depositing User: Unnamed user with email support@apsciarchives.com
Date Deposited: 23 Nov 2023 05:58
Last Modified: 23 Nov 2023 05:58
URI: http://eprints.go2submission.com/id/eprint/2290

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