Accounting for DEM Error in Sea Level Rise Assessment within Riverine Regions; Case Study from the Shatt Al-Arab River Region

被引:6
作者
Al-Nasrawi, Ali K. M. [1 ,2 ]
Kadhim, Ameen A. [3 ,4 ]
Shortridge, Ashton M. [4 ]
Jones, Brian G. [1 ]
机构
[1] Univ Wollongong, Sch Earth Atmospher & Life Sci, Wollongong, NSW 2522, Australia
[2] Univ Babylon, Dept Geog, Minist Higher Educ & Sci Res, Hillah 51001, Iraq
[3] Univ Karbala, Dept Appl Geog, Minist Higher Educ & Sci Res, Karbala 56001, Iraq
[4] Michigan State Univ, Dept Geog Environm & Spatial Sci, E Lansing, MI 48808 USA
关键词
sea-level rise; GIS environment; remote sensing applications; data errors propagation modelling; inundation model (bathtub); FRACTIONAL VEGETATION COVER; TOPOGRAPHY MISSION; SHUTTLE RADAR; ELEVATIONS; ATLANTIC; MODELS;
D O I
10.3390/environments8050046
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Global elevation datasets such as the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) are the best available terrain data in many parts of the world. Consequently, SRTM is widely used for understanding the risk of coastal inundation due to climate change-induced sea level rise. However, SRTM elevations are prone to error, giving rise to uncertainty in the quality of the inundation projections. This study investigated the error propagation model for the Shatt al-Arab River region (SARR) to understand the impact of DEM error on an inundation model in this sensitive, low-lying coastal region. The analysis involved three stages. First, a multiple regression model, parameterized from the Mississippi River delta region, was used to generate an expected DEM error surface for the SARR. This surface was subtracted from the SRTM DEM for the SARR to adjust it. Second, residuals from this model were simulated for the SARR. Modelled residuals were subtracted from the adjusted SRTM to produce 50 DEM realizations capturing potential elevation variation. Third, the DEM realizations were each used in a geospatial "bathtub" inundation model to estimate flooding area in the region given 1 m of sea level rise. Across all realizations, the area predicted to flood covered about 50% of the entire region, while predicted flooding using the raw SRTM covered only about 28%, indicating substantial underprediction of the affected area when error was not accounted for. This study can be an applicable approach within such environments worldwide.
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页数:14
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