Assessing catchment scale flood resilience of urban areas using a grid cell based metric.

Urban flooding has become a global issue due to climate change, urbanization and limitation in the capacity of urban drainage infrastructures. To tackle the growing threats, it is crucial to understand urban surface flood resilience, i.e., how urban drainage catchments can resist against and recover from flooding. This study proposes a grid cell based resilience metric to assess urban surface flood resilience at the urban drainage catchment scale. The new metric is defined as the ratio of the number of unflooded grid cells to the total grid cell number in an urban drainage catchment. A two-dimensional Cellular Automata based model CADDIES is used to simulate urban surface flooding. This methodology is demonstrated using a case study in Dalian, China, which is divided into 31 urban drainage catchments for flood resilience analysis. Results show the high resolution resilience assessment identifies vulnerable catchments and helps develop effective adaptation strategies to enhance urban surface flood resilience. Comparison of the new metric with an existing metric reveals that new metric has the advantage of fully reflecting the changing process of system performance. Effectiveness of adaptation strategies for enhancing urban surface flood resilience is discussed for different catchments. This study provides a new way to characterize urban flood resilience and an in-depth understanding of flood resilience for urban drainage catchments of different characteristics, and thus help develop effective intervention strategies for sustainable sponge city development.

Wang Y ，Meng F ，Liu H ，Zhang C ，Fu G ... -  《-》

Urban flooding resilience evaluation with coupled rainfall and flooding models: a small area in Kunming City, China as an example.

Xu T ，Xie Z ，Jiang F ，Yang S ，Deng Z ，Zhao L ，Wen G ，Du Q ... -  《WATER SCIENCE AND TECHNOLOGY》

Exploring the relationship between urban flood risk and resilience at a high-resolution grid cell scale.

The assessment of flood risk and resilience has become increasingly important in recent years for effective urban flood management. While flood resilience and risk are two distinct concepts with unique assessment metrics, there is lack of quantitative analysis and understanding of the relationship between them. This study aims to investigate this relationship at the grid cell level in urban areas. To assess flood resilience for high-resolution grid cells, this study proposes a performance-based flood resilience metric, which is calculated using the system performance curve based on flood duration and magnitude. Flood risk is calculated as the product of maximum flood depth and probability, considering multiple storm events. The case study of Waterloo in London, UK is analyzed using a two-dimensional cellular automata-based model CADDIES, which consists of 2.7 million grid cells (5 m × 5 m). The results indicate that over 2 % of grid cells have risk values exceeding 1. Furthermore, there is a 5 % difference in resilience values below 0.8 between the 200-year and 2000-year design rainfall events, specifically 4 % for the former and 9 % for the latter. Additionally, the results reveal a complex relationship between flood risk and resilience, though decreasing flood resilience generally leads to increasing flood risk. However, this relationship varies depending on the land cover type, with building, green land, and water body cells showing higher resilience for the same level of flood risk compared to other land uses such as roads and railways. Classifying urban areas into four categories, including high risk vs. low resilience, high risk vs. high resilience, low risk vs. low resilience, and low risk vs. high resilience, is crucial in identifying flood hotspots for intervention development. In conclusion, this study provides an in-depth understanding of the relationship between risk and resilience in urban flooding, which could help improve urban flood management. The proposed performance-based flood resilience metric and the findings from the case study of Waterloo in London could be valuable for decision-makers in developing effective flood management strategies in urban areas.

Wang Y ，Zhang C ，Chen AS ，Wang G ，Fu G ... -  《-》

Cellular automata based framework for evaluating mitigation strategies of sponge city.

Urban surface water flooding is increasing because of climate change and urbanization, and brings great challenges to urban sustainable development. It is, therefore, most important to develop urban flood management approaches to alleviate the consequences of floods. China is implementing a "sponge city" initiative to tackle urban surface water flooding and improve urban water management. There is, however, limited cost-effectiveness evaluation to support the choice of economically efficient mitigation strategies. To address this gap, this study developed an evaluation framework based on cellular automata and cost-benefit analysis to assess the performance of mitigation strategies in sponge city construction. This approach is demonstrated with a case study of Siergou (Dalian, China), which has a total area of 10.1 km2. The mitigation measures of green roofs, permeable pavements and bio-retention were used to generate mitigation scenarios. A two-dimensional cellular automata-based model was used to simulate urban surface water flooding. The results obtained from the case study indicate that the framework can achieve cost-effective mitigation strategies for sponge city construction, which can support robust decision making. The distribution of mitigation strategies has great impacts on the effectiveness of alleviating urban flood risk. This study provides new insight into the development of cost-effective mitigation strategies for sponge city construction.

Wang Y ，Liu Z ，Wang G ，Xue W ... -  《-》

Assessing flood resilience of urban drainage system based on a 'do-nothing' benchmark.

To deal with the threat of urban flooding, it is necessary to assess the flood resilience of urban drainage systems at the planning and design stage. This study proposes a system resilience assessment methodology based on a 'do-nothing' benchmark. In this new benchmark, the number of flooded nodes used in computation of mean flood duration in the system is that observed under a 'do-nothing' scenario (i.e. with no intervention), irrespective of the scenario under evaluation. This methodology is demonstrated using a case study in Chizhou city, China, a simple stormwater drainage network with seven subcatchments. Schemes of interventions (with distributed storage tanks) that aim to mitigate flooding are then produced by zero-one integer programming and schemes sampling. The results show that the proposed method can compute the mean flood duration and system resilience reasonably and helps identify effective intervention schemes. Compared with traditional methods, this resilience assessment method based on a 'do-nothing' scenario can correctly indicate the change in trend of system resilience provided by different schemes, and aids understanding of different interventions to improve system resilience to urban flooding. This study also provides a new way to test different interventions and to explore which provide the greatest improvement in system resilience.

Wang M ，Fang Y ，Sweetapple C 《-》