Characterizing the Indian Ocean sea level changes and potential coastal flooding impacts under global warming

被引:26
|
作者
Carvalho, K. S. [1 ]
Wang, S. [1 ]
机构
[1] Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Flooding; Indian Ocean; Interpolation; Inundation mapping; Sea level; CLIMATE-CHANGE; INTERPOLATION; VARIABILITY; INFERENCE; MOTION; RISE;
D O I
10.1016/j.jhydrol.2018.11.072
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The Indian Ocean which is home to many islands and the low-lying coastal zones have attracted considerable attention due to regional sea level changes. In this study, we examine regional changes in sea level of the Indian Ocean and potential coastal flooding impacts by using tide gauge data. Various interpolation methods are evaluated to predict values at locations where data is unavailable. Based on the cross-validation analysis, the radial basis function is identified as the most optimal interpolation method and is used to analyze the spatial patterns of sea level changes. The analysis reveals that Bangladesh, Seychelles, and Cocos (Keeling) Islands have relatively high rates of sea level rise. These regions would thus be highly vulnerable to coastal flooding induced by the accelerating sea level rise in future decades, posing significant threats to coastal communities and ecosystems. Flooding impacts are examined through inundation mapping in a geographic information system (GIS) environment. In addition, relationships between regional factors (sea surface temperature, air temperature, and vertical land motions) affecting sea level rise are investigated. Our findings indicate that vertical land motion is an important factor affecting sea level changes for the regions of Seychelles and Cocos Islands. There is a strong relationship between air temperature and sea level rise for all studied regions. This study is a first attempt to examine regional changes in sea level of the Indian Ocean and potential coastal flooding impacts by using tide gauge data. The methods used in this study can be applied to other coastal regions around the world.
引用
收藏
页码:373 / 386
页数:14
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