Evaluation of Three Geostatistical Interpolation Methods for the Estimation of Average Daily Rainfall
Asian Journal of Environment & Ecology · pp. 1–9 · Published 10 Jun 2017
10.9734/AJEE/2017/34002Abstract
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 Dep 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.
Cited by 2
Tiny Mananoma, Yosua A. Ratu, Frederiko Marchiano Imanuel Moningka · Open Civil Engineering Journal · 2024
Yaling Zhang, Chuan Liang, Lu Zhao · Stochastic environmental research and risk assessment (Print) · 2021
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