Your browser doesn't support javascript.
loading
Adaptation capability of rainfall hotspots in water resilient cities using QGIS: a case study of Taichung City in Taiwan.
Cheng, Ming-Jen; Sia, Wei-Liang; Liao, Feng-Chi; Chang, Li-Shin.
Afiliação
  • Cheng MJ; School of Architecture, Feng Chia University, Taichung City 407, Taiwan.
  • Sia WL; Ph.D. Program for Civil Engineering, Water Resources Engineering, and Infrastructure Planning, Xitun District, Feng Chia University, No. 100 Wenhua Road, Taichung City, 407802, Taiwan. prowdesigner@gmail.com.
  • Liao FC; Department of Spatial Design, Kun Shan University, Tainan City 710, Taiwan.
  • Chang LS; School of Architecture, Feng Chia University, Taichung City 407, Taiwan.
Environ Monit Assess ; 194(3): 219, 2022 Feb 24.
Article em En | MEDLINE | ID: mdl-35201445
ABSTRACT
In the context of extreme climate due to global climate transition, rainwater adaptation in resilient cities is a key issue for countries. The purpose of this study is to identify the rainfall hotspots in urban areas and investigate whether these hotspots have environmental conditions for rainfall adaptation. The study site is located in the Taichung area. This study collects rainfall data from rainfall stations at elevations below 500 m, employs QGIS (quantum GIS) to create an inverse distance weighted graphical distribution of rainfall to determine the hotspots where the maximum and minimum rainfalls occur, identifies the topography, green spaces, water areas, and buildings in the catchment, integrates the coverage area in the project, and estimates the amount of rainwater that could be directly absorbed by the land within the catchment. The results of this study show that, among the rainfall stations at an elevation below 100 m where most urban areas are located, the Taichung rainfall station is the area with the highest number of rainfall events from May to August. Without reliance on gully or river drainage, the natural infiltration of the land in the catchment could only adjust to 80 mm of heavy precipitation within 24 h of the rainfall warning level of the Central Weather Bureau.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Chuva / Água País/Região como assunto: Asia Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Chuva / Água País/Região como assunto: Asia Idioma: En Ano de publicação: 2022 Tipo de documento: Article