The Dynamic Improvement Mechanism of Urban Resilience

2 Pages Posted: 15 Jul 2019

See all articles by GuiJun Li

GuiJun Li

Central University of Finance and Economics (CUFE)

Chenhuan Kou

Central University of Finance and Economics (CUFE)

Multiple version iconThere are 2 versions of this paper

Date Written: July 13, 2019

Abstract

Background: Urban resilience is the ability of an urban system maintains or rapidly returns to desired functions in the face of a disturbance. Under the view of safe-to-fail, resilience has become a new way for the sustainable development of the city, which is growing increasingly complex and fragile. Recently, the topic of urban resilience gains widespread attention, especially in the context of global climate change and many scholars equated climate adaptation with resilience. However, disaster-tolerant is only one aspect of urban resilience, focusing on it alone cannot reduce urban vulnerability. Therefore, study authors aim at finding the interaction mechanism and sensitive factors of urban resilience, as well as urban subsystems' resilience, from the viewpoint of system science, in order to improve urban resilience effectively.

Methods: The authors analyze the composition of urban resilience in four aspects and build a system dynamics model by using the technique of rate-variable in-tree. In the proposed model, there is an arithmetic rule between urban generic resilience and subsystems’ specific resilience, as same as the operation law between level variable and flow variable. Taking Beijing City as the case study, a 15-year simulation is carried out, and the simulation data came from Chinese official documents.

Results: The study results will be summarized as the following points: Point one, the growth of urban resilience is categorized into three periods. In the first period (1-2 year), urban resilience has faster growth, and the growth rate exceeds 10%, then the growth rate slows down (<7%) in the second period (3-8 year) and finally increases again (7%~8%) in the third period. Point two, the subsystems’ resilience plays distinct roles in the growth of generic resilience. For example, in the first period, the resilience of energy material network dominates the increasing of urban resilience followed by the resilience of governance network, the resilience of infrastructure network, and the resilience of socio-economic network. But in the second period, the resilience of energy material network slows down while the other subsystems' resilience overgrew. In the third period, the resilience of socio-economic network starts to play a critical role in the increase of urban resilience. Point three, the sensitive factors of population mobility rate and the proportion of education and medical investment dominates the growth of urban resilience, while the proportion of education and medical investment also is the sensitive factor of socio-economic network’s resilience. Besides, the sensitive factor of greenery coverage rate main promotes the growth of the infrastructure network’s resilience, the sensitive factor of wastewater treatment rate main promotes the growth of the energy material network’s resilience and the sensitive factor of employment rate main promotes the growth of the governance network’s resilience.

Conclusions: The specific resilience of four subsystems affects and supports each other, constitutes the urban resilience together. In the different stage of urban development, these subsystems' resilience plays different roles in the growth of urban resilience. The growth of urban resilience and subsystems' resilience is influenced by different sensitive factors.

Keywords: Urban resilience, Subsystems’ resilience, System dynamics, In-tree, Sensitive factor

Suggested Citation

Li, GuiJun and Kou, Chenhuan, The Dynamic Improvement Mechanism of Urban Resilience (July 13, 2019). Abstract Proceedings of 2019 International Conference on Resource Sustainability - Cities (icRS Cities). Available at SSRN: https://ssrn.com/abstract=3419348 or http://dx.doi.org/10.2139/ssrn.3419348

GuiJun Li

Central University of Finance and Economics (CUFE) ( email )

39 South College Road
Haidian District
Beijing, Beijing 100081
China

Chenhuan Kou (Contact Author)

Central University of Finance and Economics (CUFE) ( email )

39 South College Road
Haidian District
Beijing, Beijing 100081
China

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