A COMPARISON OF SPATIAL RAINFALL ESTIMATION TECHNIQUES: A CASE STUDY OF NYANDO RIVER BASIN KENYA

Abstract

Many hydrological models for watershed management and planning require rainfall as an input in a continuous format. This study analyzed four different rainfall interpolation techniques in Nyando river basin, Kenya. Interpolation was done for a period of 30 days using 19 rainfall stations. Two geostatistical interpolation techniques (kriging and cokriging) were evaluated against inverse distance weighted (IDW) and global polynomial interpolation (GPI). Of the four spatial interpolators, kriging and cokriging produced results with the least root mean square error (RMSE). A digital elevation model (DEM) was introduced into the cokriging method and this improved the results considerably. The results demonstrate that for low‐resolution rain gauge networks, geostatistical interpolation methods perform better than other techniques that ignore spatial dependence patterns. The use of secondary information improved the prediction results, as demonstrated by the inclusion of the DEM in this study.