Climatological Calibration of Z-R Relationship for Pahang River Basin

Abstract

Flood disaster due to prolonged heavy rainfall had caused millions ringgit of property losses, infrastructure damages and numerous deaths in the east coast region of Peninsular Malaysia. One of the efforts taken to improve disaster preparedness in this region is by enhancing the flood forecasting and warning system (FFWS) using rainfall input from weather radar. Weather radar has the advantage of its ability to provide good spatial and temporal resolution of rainfall estimates but comes with inherent associated errors. In this study, the radar rainfall estimates were improved by climatological calibration of reflectivity-rain (Z-R) relationships for Pahang river basin. The reflectivity data for period of one year from Kuantan radar station and the hourly rainfall depths at 67 rainfall stations located in the basin for the same periods were used. Correlation analysis between radar and gauged rainfall indicates that the further the distance from the radar, the weaker the R2 coefficient value. Two Z-R equations were derived using optimization method for distance (1) 0-100 km and (2) above 100 km from Kuantan radar. The results in the form of Z = 24R1.7 and Z =5R1.6 represents the average relationship for Kuantan radar for distance (1) and (2). The radar rainfall estimates using the newly derived climatological Z-R equations enhanced the FFWS for Pahang river basin.

Subang Radar Cappi Data Processing and Z-R Optimization for Quantitative Precipitation Estimates (Qpe) Over Langat River Basin

“…Figure 9 provides the bar graph of areal rainfall comparison which shows higher radar QPE values during certain event as compared to the gauged rainfall. The findings are different from other studies done in the country where the radar QPE had underestimated the gauged rainfall [14,15].…”

“…This situation can influence the correlation and estimation accuracy of radar rainfall estimates, thus increasing errors as the distance from radar increases. Studies by [14,15,22] also found that the inaccuracy of radar rainfall estimates increase as it gets further away from the radar. Figure 7 shows the scatter plots of radar QPE versus gauged rainfall for each rainfall station with lines of discrepancy ratio (DR).…”

“…The use of radar rainfall estimates as input to hydrological model is getting more attention by the authorities in Malaysia, especially for enhancing the national flood forecasting and warning system [14,15]. Since the past 15 years, researchers in the country have explored the use of radar QPE and have expanded its application [16,17].…”

Enhanced Technique for Prediction of Z-R Relationship in Tropical Region

“…In the past, it has been common to use Marshall and Palmer Z-R relationship for all categories of rain. However, many studies have demonstrated that parameters 𝑎 varies widely according to region and much lower values are identified as suitable for use especially in tropical region [4][5][6][7][8]. Since Malaysia is one of the tropical countries that experience heavy rainfall rate throughout the year, the selection of suitable Z-R relationship is crucial.…”

Mean Field Bias Correction to Radar QPE as Input to Flood Modeling for Malaysian River Basins

“…Mean Field Bias (MFB) merging technique will be employed in this study using static and dynamic calibration steps to improve the radar QPEs. An innovation in this study compared to the previous studies for NaFFWS project is the use of composite radars for the generation of QPEs instead of a single radar as the data source for QPE derivation [16], [17].…”