Impact of Spatial Variation and Uncertainty of Rainfall Intensity on Urban Flooding Assessment

An effective urban drainage system (UDS) is crucial for solving urban flooding problems, motivating plenty of studies to design, build and rehabilitate UDSs. However, the existing design and analysis methods usually assume a uniformly spatial distribution of rainfall intensity throughout an urban catchment, while there is an observably spatial variation of rainfall intensity (SVRI) in most practical systems, especially for short-duration storms and/or large-scale catchments. The assumption ignoring SVRI might fully or partially underestimate the runoffs locally and thus increase the partial flooding risks for the UDS designed under uniformly spatial rainfall distribution. To address this issue, this paper proposes an improved framework with two spatially variable rainfall models (SVRMs) to evaluate the impacts of SVRI on urban flooding. In this proposed framework, four aspects of improvements have been implemented: (i) both SVRMs are derived from the spatially uniform hyetographs to ensure the same total precipitation volume; (ii) both SVRMs utilize the density function of truncated two-dimensional Gaussian distribution to approximate the pattern of SVRI; (iii) different characteristics of SVRI are quantified in these two SVRMs respectively, and (iv) the Monte Carlo method is adopted to implement the uncertainty of rainfall intensity in SVRMs. Besides, two real-world UDSs of different configurations and scales are used to demonstrate the effectiveness of the developed framework. The application results show that the SVRI could significantly aggravate urban flooding risk including flooding duration and volume, and the impact patterns may vary with the characteristics of UDSs. The results and findings of this study also indicate the importance of taking SVRI into consideration in UDS design and flooding assessment practice.