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

作　　者：Yaw A. Twumasi Edmund C. Merem John B. Namwamba Tomas Ayala-Silva Ronald Okwemba Olipa S. Mwakimi Kamran Abdollahi Onyumbe E. Ben Lukongo Kellyn LaCour-Conant Joshua Tate Caroline O. Akinrinwoye Yaw A. Twumasi;Edmund C. Merem;John B. Namwamba;Tomas Ayala-Silva;Ronald Okwemba;Olipa S. Mwakimi;Kamran Abdollahi;Onyumbe E. Ben Lukongo;Kellyn LaCour-Conant;Joshua Tate;Caroline O. Akinrinwoye(Department of Urban Forestry and Natural Resources, Southern University and A&M College, Baton Rouge, LA, USA;Department of Urban and Regional Planning, Jackson State University, Jackson, MS, USA;USDA-ARS Tropical Agriculture Research Station, Mayaguez, Puerto Rico;Institute of Resource Assessment, University of Dares Salam, Dares Salam, Tanzania;Department of Public Policy, Southern University and A&M College, Nelson Mandela College of Government and Social Sciences, Baton Rouge, LA, USA)

机构地区：[1]Department of Urban Forestry and Natural Resources, Southern University and A&M College, Baton Rouge, LA, USA [2]Department of Urban and Regional Planning, Jackson State University, Jackson, MS, USA [3]USDA-ARS Tropical Agriculture Research Station, Mayaguez, Puerto Rico [4]Institute of Resource Assessment, University of Dares Salam, Dares Salam, Tanzania [5]Department of Public Policy, Southern University and A&M College, Nelson Mandela College of Government and Social Sciences, Baton Rouge, LA, USA

出　　处：《Atmospheric and Climate Sciences》2020年第3期298-318,共21页大气和气候科学（英文）

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 studyThis 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

关 键 词：Coastal Flooding Climate Change Sea Level Rise ELEVATION Global Warming GIS POPULATION Regression Analysis LOUISIANA 

分 类 号：P73[天文地球—海洋科学]