Abstract
The regular occurrence of flash floods over the region of Jeddah, Saudi Arabia in the past decade has highlighted the serious need for the development of early warning systems. Radar stations have been installed in Jeddah in the last decade whose active radius covers the Middle Western area of the country. Therefore, radar information and the associated the rainfall estimates are potentially useful components of an effective early warning system. Weather radar can potentially provide high-resolution spatial and temporal rainfall estimates that bring more accuracy to flood warnings as well as having applications in areas with insufficient rainfall stations coverage. Weather radar does not measure rainfall depth directly. An empirical relationship between reflectivity (Z) and rainfall rate (R), called the Z-R relationship (Z = ARb), is generally used to assess the rainfall depth. In this study, the rainfall events during August-September 2007 were analyzed to develop a Z-R relationship using the Spatial Probability Technique (SPT). This technique is based on a basic GIS function and the probability matching method. Using this technique, the Z-R pairs can be analyzed for both linear and empirical power relationships. It is found that the empirical power function is more appropriate to describe Z-R relationship than a linear function for the studied area. The method is applied with some success to the flooding event of November 25, 2009. However, the investigation of the Z-R relationship is only one step in the development of a warning system; further study of other parameters relevant to rainfall and flash flood occurrence is needed.
Highlights
Recent advances achieved in radar technology and in methods for processing radar data are leading to increasing confidence in the use of radar-based rainfall estimates in hydrologic analyses and simulations
The main goal of this paper is to examine rainfall amounts associated with flash flood occurrences over Jeddah on 25 November, 2009 using radar data and the Z-R relationship
The aim of this study is to find new Z-R relationships suitable for this area; the resulting relationships will be used to improve radar estimates of rainfall
Summary
Recent advances achieved in radar technology and in methods for processing radar data are leading to increasing confidence in the use of radar-based rainfall estimates in hydrologic analyses and simulations. Based on the Z-R relationship (Z = aRb), rainfall rate can be estimated from radar reflectivity. Research showed that while average optimal constants in the relation Z = aRb could be found, more appropriate values vary depending on location and weather type [9] [10]. These variations in the parameters are caused by microphysical and kinematical processes that affect the drop-size distribution and fall speeds [9] [11] [12]. Numerous methods have been proposed to correct for one or more of these errors [11] [13]-[15]. [16] Created an algorithm that makes corrections for many of these errors by defining adjustment parameters for each type of error individually
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