GUOXin-yu,YANGJing-wei,LIZhi-cheng,et al.Waterlogging Risk Assessment Based on Subjective and Objective Combination Weight-TOPSIS-k-means++[J].China Water & Wastewater,2024,40(5):130-136.
Waterlogging Risk Assessment Based on Subjective and Objective Combination Weight-TOPSIS-k-means++
China Water & Wastewater[ISSN:1000-4062/CN:12-1073/TU]
volume:
第40卷
Number:
第5期
Page:
130-136
Column:
Date of publication:
2024-03-01
- Keywords:
- waterlogging risk assessment; TOPSIS; entropy weight method; analytic hierarchy process; k-means++
- Abstract:
- Most towns are facing high risk of waterlogging in China. The risk and vulnerability indicators of a risk-potential environment in a tidal town area were quantified by using grid analysis and neighborhood analysis of geographic information system (GIS), and the layers were overlaid by using GIS spatial connection function based on the calculation results of one-dimensional and two-dimensional coupling model of storm sewer system-river established by InfoWorks ICM. The combination weights of each index were calculated by coupling entropy weight method and analytic hierarchy process, and the weights of waterlogging depth, waterlogging velocity, distance to kindergarten, distance to hospital, GDP density and population density were 0.365, 0.177, 0.084, 0.088, 0.084 and 0.202, respectively. A waterlogging risk assessment model based on subjective and objective combination weight-TOPSIS-k-means++ was constructed, and its calculation results were compared with those of subjective and objective combination weight-weighted score-k-means++ method, which verified the effectiveness of the research method. The application of k-means++ method to cluster the risk level based on comprehensive consideration of risk and vulnerability indicators provides a comprehensive scientific basis for the design of rainwater pipelines and the remediation of waterlogging points in the area.
Last Update:
2024-03-01