| Autor: |
Bijoy Mitra, Muhammad Muhitur Rahman, Aftab Ahmad Khan, Syed Masiur Rahman |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Heliyon, Vol 10, Iss 12, Pp e33120- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2405-8440 |
| DOI: |
10.1016/j.heliyon.2024.e33120 |
| Popis: |
This research investigates the impact of sea level rise (SLR) on the Indus Delta, a vital ecosystem increasingly vulnerable to climate change repercussions. The objective of this study is to comprehensively assess the flooded areas under various shared socioeconomic pathway (SSP) scenarios based on the Intergovernmental Panel on Climate Change's (IPCC) 6th Assessment Report. The study employs a GIS-based bathtub model, utilizing historical (1995–2014) and IPCC-projected (2020–2150) tide gauge data from Karachi, Kandla, and Okha stations to identify potential inundated areas threatened by coastal flooding. Additionally, it analyzes LANDSAT-derived multispectral images to identify coastal erosion hotspots and changes in the landscape. A supervised random forest classifier is used to classify major landforms and understand alterations in land cover. Furthermore, neural network-based cellular automata simulations are applied to predict future land cover for 2050, 2100, and 2150 at risk of inundation. The results indicate that under different SSP scenarios, the estimated inundated land area varies from 307.36 km2 (5 % confidence on SSP1-1.9) to 7150.8 km2 (95 % confidence on SSP5-8.5). By 2150, the region will lose over 550 km2 of agricultural land and 535 km2 of mangroves (mean SLR projection). This work emphasizes identifying sensitive land cover for SLR-induced coastal flooding. It might fuel future policy and modeling endeavors to reduce SLR uncertainty and build effective coastal inundation mitigation methods. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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