An Alternative Risk Assessment Model of Urban Waterlogging: A Case Study of Ningbo City

Zhou, Meiling; Feng, Xiuli; Liu, Kaikai; Zhang, Chi; Xie, Lijian; Wu, Xiaohe

doi:10.3390/su13020826

Cited by 14 publications

(6 citation statements)

References 38 publications

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“…However, the multi-layer network theory uses nodes and edges to describe the structure and the function of the research object [22]. On this basis, it abstracts the risk carrier of the objective world into a multi-layer random network structure, and then the coupling relationship between urban waterlogging risk elements are described mathematically, which lays the foundation for the subsequent quantitative discussion [23].…”

Section: Urban Waterlogging Risk Simulation Methodsmentioning

confidence: 99%

What Causes Waterlogging?—Explore the Urban Waterlogging Control Scheme through System Dynamics Simulation

et al. 2021

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It is a common phenomenon in cities that waterlogging affects people’s normal life. It is of great significance for targeted transformation and upgrading to identify the risk factors of urban waterlogging. This paper collected the waterlogging data of Tianjin in China, analyzed the coupling mechanism among waterlogging risk factors of urban drainage systems, and then selected the system dynamics theory and the Vensim software as the analysis tools due to the mixing characteristic and the limited availability of data. After that, the sensitive factors were identified by model simulation and sensitivity analysis, and the prominent impact of urban expansion on waterlogging risk was discussed. Then, through the comparison of the three simulation scenarios, it was found that, compared with the urban development focus shifting strategy, the strategies of sponge city reconstruction and management optimization could achieve the risk control goal within a shorter time. On this basis, two kinds of governance schemes with strong operability were put forward, which were the data governance strategy and the sponge city reconstruction strategy of giving priority to old urban areas. According to the simulation results, a city can reverse the increasing trend of waterlogging risk within ten years under the appropriate scheme. Furthermore, the paper puts forward the strategic reimagining of the rural revitalization strategy and the ecological restoration strategy for the long-term sustainable development transformation of Tianjin.

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Section: Urban Waterlogging Risk Simulation Methodsmentioning

confidence: 99%

What Causes Waterlogging?—Explore the Urban Waterlogging Control Scheme through System Dynamics Simulation

et al. 2021

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“…In China, the economic losses that accompany flood disasters have also increased over the past several decades [1,2]. Floods are the result of the interaction between human activities and the natural environment, and are closely related to land [3]. On the one hand, land characteristics affect the risk of floods [4,5]; while on the other hand, the floods can seriously affect the efficiency of land use [6,7].…”

Section: Introductionmentioning

confidence: 99%

The Effect of Flood Risk on Residential Land Prices

Wei

Zhao

2022

Land

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Floods are one of the most frequent natural disasters today. Hence, it is highly important to explore the effect of flood risk on residential land prices to promote the rational allocation of land resources and incorporate climate change risk control into territorial spatial planning. This paper takes the primary urban area of Hangzhou as an example, based upon data from 424 residential land plots. With spatial autocorrelation analysis and the Spatial Durbin Model (SDM) approach, the spatial effect of flood risk on residential transaction land price was investigated. The results show that, ceteris paribus, plots with high risk of flooding suffer a price discount of 8.62%. The unique mechanism of the way flood risk affects land prices was discussed further from the perspectives of land ownership and land price systems in China. Furthermore, when the land price in surrounding areas increases one percent, the land price in the area will increase 14.32%. The spatial spillover effects of land price were analyzed with the flood information disclosure system and the stakeholders’ considerations in land price comparison. The effect of flooding on residential land prices in Hangzhou is the result of government regulations and market allocations, which are fundamentally different from those of the free market allocations in many western countries. Interestingly, the risk of flooding is capitalized into the price, whether it is determined by government or market pricing. Integrating flood risk into land price determination can help promote the optimal allocation of land resources and minimize depreciation attributable to flood disasters.

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“…From 18 to 20 July 2021, Zhengzhou, a megalopolis in central China, suffered a rare and sustained heavy rainfall, which killed 292 people, affected about 1.89 million people, collapsed 52,800 houses, and caused direct economic losses of 53.2 billion yuan. Thus, the series of problems caused by urban rainstorm waterlogging has become a research focus and received more and more attention [4][5][6][7][8] .…”

Section: Introductionmentioning

confidence: 99%

Multi-dimensional dynamic simulation of rainstorm waterlogging in urban communities

2022

Dis Prev Res

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One major threat to cities at present is the increasing rainstorm waterlogging hazards due to climate change and accelerated urbanization. This paper explores the mechanism of rainstorm waterlogging and enables the fine simulation of surface water propagation over complex urban terrain. A novel community-scale waterlogging modeling scheme is presented by loosely coupling a one-dimensional sewer model with a two-dimensional overland model under an open-source framework. The coupled model was applied to Waigaoqiao Free Trade Zone located in Pudong New Area of Shanghai. To quantify the influence of rainfall intensity and drainage conditions on the waterlogging, 12 scenarios were constructed by combining four rainfall return periods (3, 5, 10, and 20 a) and three startup water depths (1.5, 2.0, and 2.5 m) of pump stations. The multi-scenario simulation results show that the waterlogging risk increases from north to south in the study area, and that risk zones with water depth above 0.3 m are mostly concentrated in the southwest and southeast corners of the site. The longer the rainfall return period, the larger the submerged area, and the spatial distribution of surface water accumulation is affected by local topography and drainage system. In addition, reducing the startup water depth of pump stations has an obvious effect on inhibiting the severity of water accumulation. The results provide insights into overland flow across an urban area with densely populated buildings and help to reduce the risk of rainstorm-induced waterlogging disasters.

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An Alternative Risk Assessment Model of Urban Waterlogging: A Case Study of Ningbo City

Cited by 14 publications

References 38 publications

What Causes Waterlogging?—Explore the Urban Waterlogging Control Scheme through System Dynamics Simulation

What Causes Waterlogging?—Explore the Urban Waterlogging Control Scheme through System Dynamics Simulation

The Effect of Flood Risk on Residential Land Prices

Multi-dimensional dynamic simulation of rainstorm waterlogging in urban communities

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