Abstract

With rapid urbanization and extreme rainstorm events associated with climate change, urban waterlogging has become one of the most frequent and severe disasters globally. In this study, a multi-dimensional and multi-process index system based on the Pressure-State-Response (PSR) framework was developed to measure the level of urban waterlogging resilience (UWR). The spatial distribution of UWR on a block scale was explored based on the entropy weight method with the natural breakpoint method (EWM-NBM) in the central district of Wuhan City, China. In addition, the effects of the runoff control facilities and early warning measures on UWR were also quantified. Further, the Geodetector was used to investigate the main driving factors of UWR and their interactions. Results showed that the constructed index system for UWR based on the PSR framework performed reasonably, and the EWM-NBM was validated to be effective in the integrated assessment. In terms of the validation results, 82.72 % of the recorded waterlogging points belonged to high and very-high risk levels. The spatial heterogeneity of UWR was significant in the study area where the higher-level UWR mainly appears in the areas near the undeveloped suburban and water bodies (lakes and rivers), and the lower-level UWR was concentrated in central urban areas with more impervious surfaces. There was a clear increasing trend in UWR after the implementation of runoff control facilities and early warning measures, but its spatial distribution remained almost invariant. Among all the indexes, the impervious surface percentage had the strongest (69.58 %) explanatory ability for the UWR, and mean annual precipitation (15.51 %), GDP (14.03 %), and population density (11.98 %) also demanded attention. Most driving factors of UWR showed nonlinear interactions. This research could provide a benchmark for urban planning to enhance UWR to mitigate the waterlogging within the main urban area.

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