Scaling Characteristics of Storm-Centered ARF Using Radar Rainfall

In the hydraulic design practices, it is necessary to apply areal reduction factor to convert the point rainfall into the areal rainfall in the reference area. The fixed-area ARF (ARFf), which is commonly used, can be considered unrealistic because it is estimated through independent frequency analysis of the point rainfall and the areal rainfall. In this study, storm-centred ARF (ARFs) was estimated using radar rainfall data to reflect the spatial distribution characteristics of storm events effectively. ARFs representing the duration and the return period was extracted by 95% non-exceedance probability of the Weibull distribution to derive envelope covering all values from various storm events. ARFs has a correlation with not only the reference area but also the duration and the return period. Their relationships are defined as the scaling factors. A new ARFs equation that reflects the spatio-temporal characteristics of actual rainfall is presented.

On the use of radar reflectivity for estimation of the areal reduction factor

In order to estimate the rainfall fields over an entire basin raingauge, pointwise measurements need to be interpolated and the small-scale variability of rainfall fields can lead to biases in the rain rate estimation over an entire basin, above all for small or medium size mountainous and urban catchments. For these reasons, several raingauges should be installed in different places in order to determine the spatial rainfall distribution during the evolution of the natural phenomena over the selected area. In technical applications, many empirical relations are used in order to deduce heavy areal rainfall, when just one raingauge is available. In this work, we studied the areal reduction factor (ARF) using radar reflectivity maps collected with the Polar 55C, a C-band Doppler dual polarized coherent weather radar with polarization agility and with a 0.9° beamwidth. The radar rainfall estimates, for an area of 1 km2, were integrated for heavy rainfall with an upscaling process, until we had rainfall estimate for an area of 900 km2. The results obtained for a significant amount of data by using this technique are compared with the most important relations of the areal reduction factor reported in the literature.