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Article

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

1
School of Earth, Atmospheric and Life Science, University of Wollongong, Wollongong, NSW 2522, Australia
2
Department of Geography, University of Babylon, Ministry of Higher Education and Scientific Research, Hillah 51001, Iraq
3
Department of Applied Geography, University of Karbala, Ministry of Higher Education and Scientific Research, Karbala 56001, Iraq
4
Department of Geography, Environment and Spatial Sciences, Michigan State University, East Lansing, MI 48808, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Carlos Pinto-Gomes and Mauro Raposo
Received: 31 March 2021 / Revised: 11 May 2021 / Accepted: 12 May 2021 / Published: 18 May 2021
(This article belongs to the Special Issue Dynamic of Vegetation and Climate Change)
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. View Full-Text
Keywords: sea-level rise; GIS environment; remote sensing applications; data errors propagation modelling; inundation model (bathtub) sea-level rise; GIS environment; remote sensing applications; data errors propagation modelling; inundation model (bathtub)
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MDPI and ACS Style

Al-Nasrawi, A.K.M.; Kadhim, A.A.; Shortridge, A.M.; Jones, B.G. Accounting for DEM Error in Sea Level Rise Assessment within Riverine Regions; Case Study from the Shatt Al-Arab River Region. Environments 2021, 8, 46. https://0-doi-org.brum.beds.ac.uk/10.3390/environments8050046

AMA Style

Al-Nasrawi AKM, Kadhim AA, Shortridge AM, Jones BG. Accounting for DEM Error in Sea Level Rise Assessment within Riverine Regions; Case Study from the Shatt Al-Arab River Region. Environments. 2021; 8(5):46. https://0-doi-org.brum.beds.ac.uk/10.3390/environments8050046

Chicago/Turabian Style

Al-Nasrawi, Ali K.M., Ameen A. Kadhim, Ashton M. Shortridge, and Brian G. Jones 2021. "Accounting for DEM Error in Sea Level Rise Assessment within Riverine Regions; Case Study from the Shatt Al-Arab River Region" Environments 8, no. 5: 46. https://0-doi-org.brum.beds.ac.uk/10.3390/environments8050046

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