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评估沙特阿拉伯王国吉达省沿海地区对海平面上升的脆弱性及土地利用情况。

Assessing coastal vulnerability and land use to sea level rise in Jeddah province, Kingdom of Saudi Arabia.

作者信息

Almaliki Abdulrazak H, Zerouali Bilel, Santos Celso Augusto Guimarães, Almaliki Abdulrhman A, Silva Richarde Marques da, Ghoneim Sherif S M, Ali Enas

机构信息

Department of Civil Engineering, College of Engineering, Taif University, P.O. BOX 11099, Taif 21944, Saudi Arabia.

Vegetal Chemistry-Water-Energy Laboratory, Department of Hydraulic, Faculty of Civil Engineering and Architecture, Hassiba Benbouali, University of Chlef, B.P. 78C, Ouled Fares, 02180, Chlef, Algeria.

出版信息

Heliyon. 2023 Jul 23;9(8):e18508. doi: 10.1016/j.heliyon.2023.e18508. eCollection 2023 Aug.

DOI:10.1016/j.heliyon.2023.e18508
PMID:37576270
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10415659/
Abstract

Sea level rise is one of the most serious outcomes of increasing temperatures, leading to coastal flooding, beach erosion, freshwater contamination, loss of coastal habitats, increased soil salinity, and risk of damage to coastal infrastructures. This study estimates the vulnerability to inundation for 2100 in coastal zones in Jeddah Province, Kingdom of Saudi Arabia, under various sea level rise (SLR) scenarios of 1, 2, 5, and 10 m. The predicted flooding was estimated using a combination of factors, including SLR, the bathtub model, digital elevation model, climate scenarios, and land use and land cover. The climate scenarios used were Representative Concentration Pathway (RCP) scenarios 1.9, 2.6, 4.5, and 8.5. The results of the SLR scenarios of 1, 2, 5, and 10 m revealed that 1.6, 4.7, 14.9, and 30.6% (or 88, 214, 679, 1398 km) of the study area's coast could be classified as inundated areas. The various SLR scenarios can inundate 3.3 to 34% of the road area/length. The inundated built-up and road areas were estimated to range between 0.31 and 0.79 km, accounting respectively for 1.18 to 3.01% of the total class areas for 1-meter and 2-meter SLR scenarios. In contrast, the inundated area will be significant in the situation of 5 and 10 m SLR scenarios. Regarding the case of a 10-meter SLR scenario, the inundation will negatively impact the built-up and road infrastructure areas, inundating 8.9 km, with industrial infrastructures affected by inundation estimated at 0.21 km, followed by green space infrastructures at 0.013 km. The spatial information based on various SLR scenario impact mapping for Jeddah Province can be highly valuable for decision-makers to better plan future civil engineering structures within the framework of sustainable development.

摘要

海平面上升是气温升高最严重的后果之一,会导致沿海地区洪水泛滥、海滩侵蚀、淡水污染、沿海栖息地丧失、土壤盐度增加以及沿海基础设施受损风险。本研究估算了沙特阿拉伯王国吉达省沿海地区在1米、2米、5米和10米等不同海平面上升(SLR)情景下到2100年的淹没脆弱性。预测洪水时综合考虑了多种因素,包括海平面上升、浴缸模型、数字高程模型、气候情景以及土地利用和土地覆盖。所使用的气候情景为代表性浓度路径(RCP)情景1.9、2.6、4.5和8.5。1米、2米、5米和10米海平面上升情景的结果显示,研究区域海岸分别有1.6%、4.7%、14.9%和30.6%(即88、214、679、1398平方公里)可被归类为淹没区域。不同海平面上升情景下,道路区域/长度的淹没比例在3.3%至34%之间。估算的淹没建成区和道路区域在0.31至0.79平方公里之间,在1米和2米海平面上升情景下分别占总类别面积的1.18%至3.01%。相比之下,在5米和10米海平面上升情景下淹没面积将非常可观。以10米海平面上升情景为例,淹没将对建成区和道路基础设施区域产生负面影响,淹没面积达8.9平方公里,受淹没影响的工业基础设施估计为0.21平方公里,其次是绿地基础设施为0.013平方公里。基于吉达省不同海平面上升情景影响图的空间信息对于决策者在可持续发展框架内更好地规划未来土木工程结构具有极高价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/d73278003450/gr13.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/d73278003450/gr13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/2e7c3cd38e18/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/226fc3ba7417/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/678130d77cef/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/60ed7220c88f/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/1d3d4c0961e4/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/b046db762892/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/69958c6b238b/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/d05f7f21f32a/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/5f34980779c7/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/83482ebd743e/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/495d589c0d3c/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/d4aa52aaf81c/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/eccddea42ae6/gr12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be26/10415659/d73278003450/gr13.jpg

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