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Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
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Urban Flood Resilience Evaluation Based on Heterogeneous Data and Group Decision-Making
Xiang He1, Yanzhu Hu1, Xiaojun Yang2
1School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Entropy (Basel, Switzerland)
|September 27, 2024
Summary
Urban flood resilience in China is improving, showing a 14.1% increase from 2017-2021. This study introduces a new hybrid method to assess and enhance urban flood resilience using complex data and decision-making techniques.
Area of Science:
- Environmental Science
- Urban Planning
- Decision Science
Background:
- Urban floods are increasingly frequent in China, necessitating enhanced urban flood resilience.
- Existing assessment methods struggle with heterogeneous data and group decision-making complexities.
- The Pressure-State-Response-Social-Economic-Natural Complex Ecosystem (PSR-SENCE) model provides a framework for understanding urban flood resilience.
Purpose of the Study:
- To develop a hybrid multi-criteria group decision-making method for assessing urban flood resilience.
- To integrate heterogeneous data sources and address uncertainties in the assessment process.
- To provide a theoretical foundation and practical guidance for improving urban flood resilience.
Main Methods:
- A hybrid approach combining group decision-making, PSR-SENCE model, and heterogeneous data analysis.
- Development of a qualitative and quantitative indicator system based on the PSR-SENCE model.
- Introduction of Synthesis Weighting-Group Analytic Hierarchy Process (SW-GAHP) for indicator weighting and Extensional Group Decision-Making Technology (EGDMT) for qualitative data evaluation.
- Utilizing Flexible Parameterized Mapping Function (FPMF) for quantitative indicators and the normal cloud model for uncertainty management.
Main Results:
- The proposed method was applied to Beijing from 2017 to 2021, demonstrating a consistent annual improvement in urban flood resilience.
- A notable 14.1% increase in urban flood resilience was observed over the evaluation period.
- Optimization recommendations were provided for both favorable and unfavorable indicators, including flood risk and population density.
Conclusions:
- The developed hybrid method effectively assesses urban flood resilience using heterogeneous data and group decision-making.
- The method offers a robust and superior approach compared to existing techniques, as shown by comparative and sensitivity analyses.
- The findings provide a valuable theoretical basis and practical decision-making guide for enhancing urban flood resilience in cities.
Keywords:
group decision-makingheterogeneous dataindicator systemnormal cloud modelurban flood resilienceMore Related Videos
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