Performance assessment of coupled green-grey-blue systems for Sponge City construction

Wang

et al. 2020

IJERPH

Nanjing city is taken as a case in this urban rainstorm disaster risk research. Using the data of meteorology and social-economy statistics of Nanjing area, the paper selected ten indicators to establish the risk assessment system of urban rainstorm disaster from the aspects of the vulnerability of hazard-affected body, the fragility of disaster-pregnant environment, and the danger of hazard factors. Multi-layer weighted principal component analysis (MLWPCA) is an extension of the principal component analysis (PCA). The MLWPCA is based on factor analysis for the division subsystem. Then the PCA is used to analyze the indicators in each subsystem and weighted to synthesize. ArcGIS is used to describe regional differences in the urban rainstorm disaster risk. Results show that the MLWPCA is more targeted and discriminatory than principal component analysis in the risk assessment of urban rainstorm disaster. Hazard-affected body and disaster-pregnant environment have greater impacts on the risk assessment of rainstorm disaster in Nanjing, but the influence of hazard factors is few. Spatially, there is a large gap in the rainstorm disaster risk in Nanjing. The areas with high-risk rainstorm disaster are mainly concentrated in the central part of Nanjing, and the areas with low-risk rainstorm disaster are in the south and north of the city.

Section: Resultsmentioning

confidence: 99%

Risk Assessment of Urban Rainstorm Disaster Based on Multi-Layer Weighted Principal Component Analysis: A Case Study of Nanjing, China

Wang

et al. 2020

IJERPH

“…between which water pollution is the first priority (Leng et al 2020). were considered less important for SC planning.…”

Section: The Construction Of Priority Index Modelmentioning

confidence: 99%

Prioritizing Sponge City Sites in Rapidly Urbanizing Watersheds Using Multi-Criteria Decision Model

Zhang

Zhang

et al. 2021

Preprint

Spatial planning is crucial for Sponge City (SC) construction; however, prioritizing SC sites at the watershed scale has not been fully explored. In this study, a multi-criteria decision model, considering demand and suitability of SC construction, was established by monitoring, model simulation and index calculation. This new model was then tested in a rapidly urbanizing watershed, Beijing, China and the priority of SC construction at both grid scale (1km 1km) and subwatershed scale was ranked. The results showed that the highest priority was found in emerging regions where urbanization is ongoing, and followed by urban core areas. In addition, six indexes were identified by clustering heatmaps as key factors affecting the priority of SC planning, including topographic index, water pollution index, pollution rate based on the state standard of surface water environment quality, urbanization planning, urban levels, and vegetation index, which could guide SC planning in data-lacking regions. The approach and findings in this study can not only provide helpful references for watershed managers and urban planners but also can be easily used in other regions.

“…The results of W-C showed that surface water quality was the most important indicator with a weight of 0.3784, followed by runoff control indicator with a weight of 0.3441. This result could be explained by the fact that urban water management, integrating water pollution and runoff floods, is the priority target of SC construction (Li et al 2019, Lin et al 2020, between which water pollution is the first priority (Leng et al 2020). The next most important indicator was site suitability with a weight of 0.1477, which determines the effectiveness of SC facilities.…”

Section: The Construction Of Priority Index Modelmentioning

confidence: 99%

“…Besides, hydrologically sensitive areas (HSAs) were employed to identify priority sites for LID implementation in a watershed with a geographic information system (GIS)-based framework and indicated 16% and 17% reductions in nutrient and sediment loads into receiving waters (Martin-Mikle et al 2015). Scholars have also explored the optimal spatial scheme for facilities based on multi-objective models, including information on facility efficiency and cost (Hou et al 2020a, Leng et al 2020.…”

Section: Introductionmentioning

confidence: 99%

Prioritizing sponge city sites in rapidly urbanizing watersheds using multi-criteria decision model

Zhang

Meng

et al. 2021

Environ Sci Pollut Res

Spatial planning is crucial for Sponge City (SC) construction; however, prioritizing SC sites at the watershed scale has not been fully explored. In this study, a multi-criteria decision model, considering demand and suitability of SC construction, was established by monitoring, model simulation and index calculation. This new model was then tested in a rapidly urbanizing watershed, Beijing, China and the priority of SC construction at both grid scale (1km×1km) and subwatershed scale was ranked.The results showed that the highest priority was found in emerging regions where urbanization is ongoing, and followed by urban core areas. In addition, six indexes were identified by clustering heatmaps as key factors affecting the priority of SC planning, including topographic index, water pollution index, pollution rate based on the state standard of surface water environment quality, urbanization planning, urban levels, and vegetation index, which could guide SC planning in data-lacking regions. The approach and findings in this study can not only provide helpful references for watershed managers and urban planners but also can be easily used in other regions.