Comparison of Compact and Decentralized Urban Development Pathways for Flood Mitigation in Urbanizing Deltas—Guangzhou in the Pearl River Delta as a Case Study

Weibin Lin, Yimin Sun () and Steffen Nijhuis ()
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Weibin Lin: School of Architecture and Art, Hunan Provincial Key Laboratory of Low Carbon Healthy Building, Central South University, Changsha 410083, China
Yimin Sun: School of Architecture, State Key Laboratory of Subtropical Building and Urban Science, South China University of Technology, Guangzhou 510641, China
Steffen Nijhuis: Faculty of Architecture and the Built Environment, Department of Urbanism, Delft University of Technology (TU Delft), Julianalaan 134, 2628 BL Delft, The Netherlands

Land, 2024, vol. 13, issue 3, 1-22

Abstract: Floods are common and inevitable natural disasters. Achieve Sustainable Development Goal (SDG) 11.5 is a critical challenge for coastal cities, especially those in deltaic lowlands such as in the case of Guangzhou, China. Regarding the spatial planning and design of such urban regions, it is crucial to study the impacts of flooding in compact or decentralized spatial development pathways. This reinforces the understanding of the relationship between strategic decisions for spatial planning and flood mitigation. However, the lack of a computer model to assess spatial evolution paths is a significant limitation. The non-dominated Sorting Genetic Algorithm II (NSGA-II) explores the possibility of a compact built-up land layout in 2030. The results showed that, concerning the 2030 decentralized scenario, the 2030 compact scenario presents a large increase in the integrated fitness function value from 0.618 to 0.771 (the increase is equivalent to 0.153 or about 24.75%). In addition, different development scenarios were constructed by setting different target weights. Compared to the decentralized scenario results, the fitness function values of the optimization results of each scenario showed better results at different levels. They could also serve as a reference for other similar coastal areas to achieve SDG 11.5 by 2030.

Keywords: spatial evolution path; Guangzhou estuary area; multi-objective optimization; flood disaster; SDG 11.5 (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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