Modeling the Risks of Climate Change and Global Warming to Humans Settled in Low Elevation Coastal Zones in Louisiana, USA

• 作者: Caroline O. Akinrinwoye Edmund C. Merem John B. Namwamba Joshua Tate Kamran Abdollahi Kellyn LaCour-Conant Olipa S. Mwakimi Onyumbe E. Ben Lukongo Ronald Okwemba Tomas Ayala-Silva Yaw A. Twumasi
• 来源期刊: 大气和气候科学(英文)
• 学科: 地球科学
• 关键词: Coastal Flooding Climate Change Sea Level Rise ELEVATION Global Warming GIS POPULATION Regression Analysis LOUISIANA
• 年，卷（期）: dqhqhkxyw_2020,（3）
• 页码范围: 298-318
• 页数: 21页
• 分类号: P73

摘要

This paper seeks to identify high risk areas that are prone to flooding, caused by sea level rise because of high impacts of global climate change resulting from global warming and human settlements in low-lying coastal elevation areas in Louisiana, and model and understand the ramifications of predicted sea-level rise. To accomplish these objectives, the study made use of accessible public datasets to assess the potential risk faced by residents of coastal lowlands of Southern Louisiana in the United States. Elevation data was obtained from the Louisiana Statewide Light Detection and Ranging (LiDAR) with resolution of 16.4 feet (5 m) distributed by Atlas. The data was downloaded from Atlas website and imported into Environmental Systems Research Institute’s (ESRI’s) ArcMap software to create a single mosaic elevation image map of the study area. After mosaicking the elevation data in ArcMap, Spatial Analyst extension software was used to classify areas with low and high elevation. Also, data was derived from United States Geological Survey (USGS) Digital Elevation Model (DEM) and absolute sea level rise data covering the period 1880 to 2015 was acquired from United States Environmental Protection Agency (EPA) website. In addition, population data from U.S. Census Bureau was obtained and coupled with elevation data for assessing the risks of the population residing in low lying areas. Models of population trend and cumulative sea level rise were developed using statistical methods and software were applied to reveal the national trends and local deviations from the trends. The trends of population changes with respect to sea level rise and time in years were modeled for the low land coastal parishes of Louisiana. The expected years for the populations in the study area to be at risk due to rising sea level were estimated by models. The geographic information systems (GIS) results indicate that areas of low elevation were mostly located along the coastal Parishes in the study area. Further results of the study