With rapid urbanization, floods that occur are more frequently associated with non-riverine, urban flooding. Reliable and efficient simulation of rainstorm inundation in an urban environment is profound for risk analysis and sustainable development. Although sophisticated hydrodynamic models are now available to simulate the urban flooding processes with a high accuracy, the complexity and heavy computation requirement render these models difficult to apply. Moreover, a large number of input data describing the complex urban underlying surfaces is required to setup the models, which are typically unavailable in reality. In this paper, a simple and efficient urban rainstorm inundation simulation method, named URIS, was developed based on a geographic information system (GIS) with limited input data. The URIS method is a simplified distributed hydrological model, integrating three components of the soil conservation service (SCS) module, surface flow module, and drainage flow module. Cumulative rainfall-runoff, output from the SCS model, feeds the surface flow model, while the drainage flow module is an important waterlogging mitigation measure. The central urban area of Shanghai in China was selected as a study case to calibrate and verify the method. It was demonstrated that the URIS is capable of characterizing the spatiotemporal dynamic processes of urban inundation and drainage under a range of scenarios, such as different rainstorm patterns with varying return periods and different alterations of drainage diameters. URIS is therefore characterized with high efficiency, reasonable data input, and low hardware requirements and should be an alternative to hydrodynamic models. It is useful for urgent urban flood inundation estimation and is applicable for other cities in supporting emergency rescue and sustainable urban planning.

Green infrastructure (GI) plays a fundamental role in achieving urban pluvial flood management, mitigating urban heat island effect, and improving living suitability. Residents’ participation is the main driving force of GI implementation. Based on semi-structured interviews, GIS spatial analysis, and multiple regression, we investigated residents’ willingness to participate in the implementation of GI in public and private space and identified the influence factors in Shanghai, China. The results show that, compared with private space, residents prefer to implement GI in public space, where they have different preferences of GI measures. On urban scale, residents’ willingness to participate in the implementation of GI in private space is characterized as “high in the inner city, low in the suburban areas”, while the spatial difference is insignificant for public space. In addition, the factors affecting residents’ willingness to participate in the implementation of GI are different in private and public space. The deterministic factors of GI participation are gender, education level, and floor for private space, while only include building age for public space, in addition to the common factors of free time, cognition of GI, perception of pluvial flood risk, supportive factors, and environment-improving factors that can influence both private and public space GI participation. Our analysis therefore provides valuable information for policymakers concerning nature-based solutions to climate change adaptation and urban sustainability.

Extreme flooding usually causes huge losses of residential buildings and household properties, which is critical to flood risk analysis and flood resilience building in Shanghai. We developed a scenario-based multidisciplinary approach to analyze the exposure, losses and risks of residential buildings and household properties, and their spatial patterns at the neighborhood committee level in Shanghai, based on extreme storm flood scenarios of 1/200, 1/500, 1/1000 and 1/5000-year. Our findings show that the inundation area of the residential buildings caused by a 1/200-year storm flood reaches 24.9 km², and the total loss of residential buildings and household properties is 29.7 billion CNY (Chinese Yuan) (or 4.4 billion USD), while the inundation area of residential buildings and the total loss increases up to 162.4 km² and 366.0 billion CNY (or 54.2 billion USD), respectively for a 1/5000-year storm flood. The estimated average annual loss (AAL) of residential buildings and household properties for Shanghai is 590 million CNY/year (or 87.4 million USD/year), with several hot spots distributed around the main urban area and on the bank of the Hangzhou Bay. Among sixteen districts, Pudong has the highest exposure and annual expected loss, while the inner city is also subject to extreme flooding with an AAL up to near half of the total. An analysis of flood risk in each of 209 subdistricts/towns finds that those most vulnerable to storm flooding are concentrated in Pudong, Jiading, Baoshan Districts and the inner city. Our work can provide meaningful information for risk-sensitive urban planning and resilience building in Shanghai. The methodology can also be used for risk analysis in other coastal cities facing the threat of storm flooding.

The impact of flooding on cities is becoming increasingly significant in the context of climate change and rapid urbanization. Based on the analysis of the land use changes and rainstorm waterlogging inundation scenarios of Jiangqiao Town from 1980 to 2020, a scenario analysis was conducted to simulate and assess the rainstorm waterlogging disaster risk in 2040 under three land use scenarios (a natural development scenario, Scenario ND; an economic growth scenario, Scenario EG; and an ecological development priority scenario, Scenario EP) and three rainstorm scenarios with return periods of 10, 50, and 100 years. The following results were found: (1) Land use change is a significant factor in the risk of urban rainstorm waterlogging disaster caused by surface runoff and inundation depth change. In particular, the resultant increase in impermeable surfaces such as residential land and industrial land and the decrease in farmland during urbanization would lead to an increase in urban rainstorm waterlogging disaster risk. (2) Under three rainstorm scenarios, the future land use exposure elements and losses are consistent in terms of spatial distribution; from 10-year to 100-year return periods, they manifest as an expansion from the south to the surroundings, especially to the central region of the study area. The locations at risk are mainly distributed in the central and southern regions of Jiangqiao Town. (3) The economic losses are different in different land use scenarios and rainstorm scenarios. In the context of rainstorm scenarios with return periods of 10, 50, and 100 years, the total losses in land use scenario ND are CNY 560 million, CNY 890 million, and CNY 1.07 billion; those in land use scenario EG are CNY 630 million, CNY 980 million, and CNY 1.19 billion; and those in land use scenario EP are CNY 480 million, CNY 750 million, and CNY 910 million. The total losses of land use EP are the lowest by comparison. So, the influence of land use change on the rainstorm waterlogging disaster risk shows obvious differences among different rainstorm scenarios. This study has important reference value for decision making on land use management and flood disaster risk management in rapidly urbanizing areas.

The integration of nature-based solutions into land use optimization has become a central focus of current research, primarily due to its effectiveness in mitigating flooding impacts and promoting sustainable development in both urban and rural areas. Taking Shanghai’s Pujiang Country Park as a case study, this paper conducts a simulation analysis to assess the flood mitigation effectiveness of three distinct land use patterns (Natural scenario, Scenario N; Complete urbanization scenario, Scenario U; Country Park Planning scenario, Scenario P) under five stormwater scenarios with return periods of 2, 5, 10, 20, and 50 years. The findings reveal that Scenario P exhibits superior flood mitigation performance, particularly under stormwater scenarios with a return period of less than 50 years. Building upon these results, the paper proposes recommendations for optimizing land use to mitigate the impact of flooding. This study is crucial for understanding the mechanisms involved in urban stormwater logging mitigation through land use methods and holds significance for decision-making in land use and planning at the micro level.

The integration of nature-based solutions into land use optimization has emerged as a focal point of current research, primarily due to its efficacy in mitigating flooding impacts and fostering sus-tainable development in both urban and rural areas. Utilizing Shanghai Pujiang Country Park as a case study, this paper conducts a simulation analysis to assess the flood mitigation effectiveness of three distinct land use patterns (Natural scenario, Scenario N; Complete urbanization scenario, Scenario U; Country Park Planning scenario, Scenario P) under five stormwater scenarios with re-turn periods of 2, 5, 10, 20, and 50 years. The findings reveal that Scenario P exhibits superior flood mitigation performance, particularly under stormwater scenarios with a return period of less than 50 years. Building upon these results, the paper proposes recommendations for optimizing land use with a focus on mitigating the impact of flooding. This study is crucial for comprehending the mechanisms involved in urban stormwater logging mitigation through land use methods and holds significance for decision-making in land use and planning at the micro level.