Improving outcomes for socioeconomic variables with coastal vulnerability index under significant sea-level rise: an approach from Mumbai coasts

被引:23
作者
Pramanik, Malay Kumar [1 ,2 ]
Dash, Poli [3 ]
Behal, Dimple [4 ]
机构
[1] Jawaharlal Nehru Univ, New Delhi 110067, India
[2] Asian Inst Technol AIT, Sch Environm Resources & Dev, Dept Dev & Sustainabil, POB 4, Klongluang 12120, Pathum Thani, Thailand
[3] Deshapran Coll Teachers Educ, Purba Medinipur 721427, W Bengal, India
[4] Sch Planning & Architecture, Bhopal 462030, India
关键词
Sea-level rise; Mumbai coast; Geospatial approach; Coastal management; Coastal vulnerability; Climate change; CLIMATE-CHANGE; EAST-COAST; IMPACTS; HAZARDS; INDIA;
D O I
10.1007/s10668-021-01239-w
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Climate change has led to increased sea levels, which are caused by a complex interplay of the physical environment components from coastal areas, causing the rise in storm surge, erosion and flooding. In this scenario, the low-lying topography of the Mumbai region is highly susceptible to sea level-induced flooding and coastal erosion due to the increasing number of economic activities. The unsustainable urbanization, unplanned development, and huge land conversion lead to the destruction of this region lead to the destruction of mangroves and filled waterways with construction debris which makes the region more vulnerable to flooding due to inadequate drainage, overflow and absence of natural protectors. These human-induced factors and their impacts remain unknown. Therefore, the study uses four socioeconomic variables (CVI4) with five geological (CVI5) and three geological variables (CVI8; with integrating CVI5) to assess the role of developmental and socio-economic activities in overall coastal vulnerability (CVI12) analysis. To quantify the importance of the combined variables and understand the response, random forest (RF) model was also used. This study selected four different iterations with integrating the pixel-based differentially weighted rank values of all variables to determine the significant causes behind that have an impact on coastal vulnerability index (CVI). The results show that CVI5 and CVI8 contributed 7.8% and 36.9%, respectively, whereas CVI4 contributed 55.3% to the CVI12. The response curve shows that the influence of these variables is an increasing trend to CVI12 and the results of CVI12 are highly correlated with socioeconomic index variables (r = 0.84, p = 0.001) which indicates the socio-economic variables played a major role towards the coastal vulnerability of the region. It suggests that unsustainable urbanization, unplanned development and coastal erosion increasing pressure make Mumbai and Kurla region more vulnerable to flood. Accordingly, CVI12 results show 55.83 km of the shoreline surveyed, being very low vulnerable, a moderate vulnerability of 60.91 km, while a high vulnerability of 50.75 km is considered to be very high. The results may be used as a guide in formulating policies to mitigate and adjust the Mumbai coast as the rise in sea level is expected to cause more frequent coastal floods, etc.
引用
收藏
页码:13819 / 13853
页数:35
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