The improvement of precipitation estimation with the use of radar-raingauge rainfall merging techniques is influenced by several factors, such as topography, storm types, raingauge network density for adjustment, data quality and the rainfall accumulation time. However, the influence of the raingauge network configuration on the performance of radar-raingauge merging methods is often ignored. The aim of this study is to compare and evaluate the performance of different radar-raingauge merging methods on various densities of raingauge network and raingauge network configurations. The analysis of the effect of the raingauge network density shows that the performance of Kriging merging methods increases with the increase of raingauge network density. The results also showed that the influence of raingauge network configuration on the spatial distribution of precipitation of the merged products is relatively smaller for the Kriging with radar-based error correction (KRE) and Kriging with external drift (KED) methods than for the ordinary Kriging method. This indicates that the inclusion of radar data in the KRE and KED methods helps to maintain the spatial distribution of precipitation on an hourly timescale. According to the statistical performance indicators and visual inspection of the merged rainfall fields, the KED outperforms the other radar-raingauge merging techniques, regardless of raingauge network density and configuration.
- precipitation estimation
- weather radar
- First received 20 December 2013.
- Accepted in revised form 3 November 2014.
- © IWA Publishing 2015