Comprehensive Understanding the Disaster-Causing Mechanism, Governance Dilemma and Targeted Countermeasures of Urban Pluvial Flooding in China

Urban pluvial flooding in China has become one of the major challenges for sustainable development. This paper analyzes the impact of climate change, urbanization, and integrated disaster drivers on urban pluvial flooding hazards, starting from the disaster-causing mechanisms of urban pluvial flooding in China. This paper then analyzes the main features and progress of urban pluvial flooding governance in China. In particular, this paper describes the progress of sponge cities in China. On the basis of the above contents, this paper describes three manifestations of the fragmentation dilemma at the level of governance, namely, fragmentation in value integration due to conflicting management orders and service values, fragmentation in resource and power allocation due to the lack of vertical top-level design and blurred horizontal departmental management boundaries, and fragmentation in policy formulation and implementation due to outdated urban flood control standards and interdepartmental information compartmentalization. In response to the fragmentation dilemma in urban pluvial flooding management in China, this paper introduces the concept of holistic governance and clarifies the path of urban waterlogging management, i.e., forming a collaborative and diversified governance subjects, deeply optimizing the organizational structure of urban waterlogging management, creating a mature information-based governance platform, and improving the legal and rule of law construction model. This paper is informative for understanding the governance of urban pluvial flooding in China from a government-led management level.

Determination of Optimal Meshness of Sewer Network Based on a Cost–Benefit Analysis

Urban pluvial flooding occurs when the capacity of sewer networks is surcharged due to large amounts runoff produced during intense rain events. Rapid urbanization processes and changes in climate increase these events frequency. Effective and sustainable approaches for the reduction in urban floods are necessary. Although several gray, green and hybrid measures have been studied, the influence of network structure on flood occurrence has not yet been systematically evaluated. This study focuses on evaluating how different structures of a single urban drainage network affect flood volumes and their associated damages. Furthermore, a cost–benefit analysis is used to determine the best network structure. As a case study, a sewer subnetwork in Dresden, Germany was selected. Scenarios corresponding to different layouts are developed and evaluated using event-wise hydrodynamic simulation. The results indicate that more meshed structures are associated with lower flood volumes and damage. Moreover, all analyzed scenarios were identified as cost-effective, i.e., the benefits in terms of flood damage reduction outweighed the costs related to pipe installation, operation and maintenance. However, a predominantly branched structure was identified as the best scenario. The present approach may provide a new cost-effective solution that can be integrated into the development of different mitigation strategies for flood management.

A Methodological Approach to Municipal Pluvial Flood Risk Assessment Based on a Small City Case Study

Urban flooding caused by heavy rainfall confronts cities worldwide with new challenges. Urban flash floods lead to considerable dangers and risks. In cities and urban areas, the vulnerability to pluvial flooding is particularly high. In order to be able to respond to heavy rainfall events with adaptation strategies and measures in the course of urban development, the spatial hazards, vulnerabilities and risks must first be determined and evaluated. This article shows a new, universally applicable methodical approach of a municipal pluvial flood risk assessment for small and medium-sized cities. We follow the common approaches to risk and vulnerability analyses and take into account current research approaches to heavy rainfall and urban pluvial flooding. Based on the intersection of the hazard with the vulnerability, the pluvial flood risk is determined. The aim of the present pluvial flood risk assessment was to identify particularly affected areas in the event of heavy rainfall in the small German city of Olfen. The research procedure and the results have been coordinated with the city’s administration within the framework of a real laboratory. In the course of the science–policy cooperation, it was ensured that the results could be applied appropriately in urban developments.

Mitigation of Urban Pluvial Flooding: What Drives Residents’ Willingness to Implement Green or Grey Stormwater Infrastructures on Their Property?

As a consequence of climate change, the impact of pluvial flooding is expected to increase in the next decades. Despite citizens’ poor knowledge, several types of stormwater infrastructure can be implemented to mitigate the impact of future events. This paper focuses on the implementation of green and grey stormwater interventions (i.e., with or without vegetation) on private properties. Framed by the Protection Motivation Theory, a survey-based case study analysis, carried out in a pluvial flooding-prone area of the Veneto Region (Italy), highlights the main factors driving people’s willingness to implement these interventions. The analysis shows that the implementation of grey stormwater infrastructures is driven by the perceived threat and the amount of past pluvial flooding damage (i.e., the direct experience as a proxy of prior knowledge) while the implementation of green stormwater infrastructures is driven also by additional factors (awareness of these interventions, age and education level of the citizens). Based on these results, lack of knowledge on innovative stormwater interventions represents a critical barrier to their implementation on private properties, and it confirms the need for specific dissemination and information activities.

The accuracy of weather radar in heavy rain: a comparative study for Denmark, the Netherlands, Finland and Sweden

Weather radar has become an invaluable tool for monitoring rainfall and studying its link to hydrological response. However, when it comes to accurately measuring small-scale rainfall extremes responsible for urban flooding, many challenges remain. The most important of them is that radar tends to underestimate rainfall compared to gauges. The hope is that by measuring at higher resolutions and making use of dual-polarization radar, these mismatches can be reduced. Each country has developed its own strategy for addressing this issue. However, since there is no common benchmark, improvements are hard to quantify objectively. This study sheds new light on current performances by conducting a multinational assessment of radar's ability to capture heavy rain events at scales of 5 min up to 2 h. The work is performed within the context of the joint experiment framework of project MUFFIN (Multiscale Urban Flood Forecasting), which aims at better understanding the link between rainfall and urban pluvial flooding across scales. In total, six different radar products in Denmark, the Netherlands, Finland and Sweden were considered. The top 50 events in a 10-year database of radar data were used to quantify the overall agreement between radar and gauges as well as the bias affecting the peaks. Results show that the overall agreement in heavy rain is fair (correlation coefficient 0.7–0.9), with apparent multiplicative biases on the order of 1.2–1.8 (17 %–44 % underestimation). However, after taking into account the different sampling volumes of radar and gauges, actual biases could be as low as 10 %. Differences in sampling volumes between radar and gauges play an important role in explaining the bias but are hard to quantify precisely due to the many post-processing steps applied to radar. Despite being adjusted for bias by gauges, five out of six radar products still exhibited a clear conditional bias, with intensities of about 1 %–2 % per mmh−1. As a result, peak rainfall intensities were severely underestimated (factor 1.8–3.0 or 44 %–67 %). The most likely reason for this is the use of a fixed Z–R relationship when estimating rainfall rates (R) from reflectivity (Z), which fails to account for natural variations in raindrop size distribution with intensity. Based on our findings, the easiest way to mitigate the bias in times of heavy rain is to perform frequent (e.g., hourly) bias adjustments with the help of rain gauges, as demonstrated by the Dutch C-band product. An even more promising strategy that does not require any gauge adjustments is to estimate rainfall rates using a combination of reflectivity (Z) and differential phase shift (Kdp), as done in the Finnish OSAPOL product. Both approaches lead to approximately similar performances, with an average bias (at 10 min resolution) of about 30 % and a peak intensity bias of about 45 %.