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Climate uncertainty and vulnerability of urban flooding associated with regional risk using multi-criteria analysis in Mumbai, India.
Yadav, Nilesh; Wu, Jianping; Banerjee, Abhishek; Pathak, Shray; Garg, R D; Yao, Shenjun.
Afiliação
  • Yadav N; Key Laboratory of Geographic Information Science (Ministry of Education) and School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Shanghai, 200241, China.
  • Wu J; Key Laboratory of Geographic Information Science (Ministry of Education) and School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Shanghai, 200241, China. Electronic address: jpwu@geo.ecnu.edu.cn.
  • Banerjee A; State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-environment and Resources, Chinese Academy of Sciences, Donggang, West RD. 318, Lanzhou, 730000, China.
  • Pathak S; Department of Civil Engineering, Indian Institute of Technology Ropar, Rupnagar, Punjab, 140001, India.
  • Garg RD; Geomatics Engineering Group, Indian Institute of Technology Roorkee, Roorkee, 247667, India.
  • Yao S; Key Laboratory of Geographic Information Science (Ministry of Education) and School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Shanghai, 200241, China.
Environ Res ; 244: 117962, 2024 Mar 01.
Article em En | MEDLINE | ID: mdl-38123049
ABSTRACT
The study made a comprehensive effort to examine climatic uncertainties at both yearly and monthly scales, along with mapping flood risks based on different land use categories. Recent studies have progressively been engrossed in demonstrating regional climate variations and associated flood probability to maintain the geo-ecological balance at micro to macro-regions. To carry out this investigation, various historical remote sensing record, reanalyzed and in-situ data sets were acquired with a high level of spatial precision using the Google Earth Engine (GEE) web-based remote sensing platform. Non-parametric techniques and multi-layer integration methods were then employed to illustrate the fluctuations in climate factors alongside creating maps indicating the susceptibility to floods. The study reveals an increased pattern in LST (Land Surface Temperature) (0.03 °C/year), albeit marginal declined in southern coastal regions (-0.15 °C/year) along with uneven rainfall patterns (1.42 mm/year). Moreover, long-term LULC change estimation divulges increased trends of urbanization (16.4 km2/year) together with vegetation growth (8.7 km2/year) from 2002 to 2022. Furthermore, this inquiry involves numerous environmental factors that influence the situation (elevation data, topographic wetness index, drainage density, proximity to water bodies, slope, and soil properties) as well as socio-economic attributes (population) to assess flood risk areas through the utilization of Analytical Hierarchy Process and overlay methods with assigned weights. The outcomes reveal nearly 55 percent of urban land is susceptible to flood in 2022, which were 45 and 37 percent in 2012 and 2002 separately. Additionally, 106 km2 of urban area is highly susceptible to inundation, whereas vegetation also occupies a significant proportion (52 km2). This thorough exploration offers a significant chance to formulate flood management and mitigation strategies tailored to specific regions during the era of climate change.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Urbanização / Inundações País/Região como assunto: Asia Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Urbanização / Inundações País/Região como assunto: Asia Idioma: En Ano de publicação: 2024 Tipo de documento: Article