Multivariate Analysis of Rainfall Spatial Distribution and Its Effect on Stormwater Magnitudes

The response to flood disasters is of great importance to protect people’s lives. Proper recognition of the factors affecting floods will lead to the prevention of negative consequences. In this study, three types of Archimedean copulas, including Clayton, Gumbel, and Frank, have been applied to the depth and duration variables of maximum annual precipitation in four rain gauges’ data sets (eight variables) throughout the primarily urban eastern catchment of Tehran, Iran. The results indicated that the Gumbel copula is the most suitable function of the Archimedean copulas. The average depth of rainfalls produced by the selected copula increased up to 24% compared with different varieties of single-station scenarios. Also, the average duration of produced rainfalls differed up to 14% difference compared with the single-station scenarios. Finally, the average volume of surface flooding varied between +54% and −154% with respect to the single-station scenarios. As a result, taking into account spatial distribution in rainfall will have a significant impact on the generation of runoff. The overall distribution pattern of runoff is significantly influenced by several factors. Firstly, the simultaneous impact of four rain gauge stations on synthetic runoffs plays a crucial role. The second factor is the spatial distribution of precipitation within the catchment, which is influenced by the distribution of rain gauge stations and the interpolation technique used. Additionally, the routing of synthetic surface runoff through the channel system also contributes to the overall distribution pattern of runoff.