Migrating rivers, consequent paleochannels: The unlikely partners and hotspots of flooding

被引:17
作者
Sajinkumar, K. S. [1 ,2 ]
Arya, A. [1 ,3 ]
Rajaneesh, A. [1 ]
Oommen, T. [2 ]
Yunus, Ali P. [4 ]
Rani, V. R. [5 ]
Avatar, Ram [6 ]
Thrivikramji, K. P. [7 ]
机构
[1] Univ Kerala, Dept Geol, Thiruvananthapuram 695581, Kerala, India
[2] Michigan Technol Univ, Dept Geol & Min Engn & Sci, 1400 Townsend Dr, Houghton, MI 49931 USA
[3] Pondicherry Univ, Port Blair 744103, Andaman & Nicob, India
[4] Natl Inst Environm Studies, Ctr Climate Change Adaptat, Tsukuba, Ibaraki 3058506, Japan
[5] Cent Groundwater Board, Thiruvananthapuram 695004, Kerala, India
[6] Hokkaido Univ, Fac Environm Earth Sci, Grad Sch Environm Sci, Sapporo, Hokkaido 0600810, Japan
[7] Ctr Environm & Dev, Thiruvananthapuram 695013, Kerala, India
关键词
2018 Kerala flood; Paleochannel; River migration; Object Oriented Analysis; Principal Component Analysis; INDIA; TECTONICS; KERALA; BASIN; INFORMATION; GROUNDWATER; MIDDLE;
D O I
10.1016/j.scitotenv.2021.150842
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Furious floods have become an omnipresent reality with the dawn of climate change and its transition to adult-hood. Since climate change has now become an accepted reality, analysing the factors that favour or disfavour floods are an urgent requirement. Here we showcase the role of paleochannels, a product of migrating rivers, in a catastrophic flood in the south-western part of the Indian Peninsula. This study exposes whether these geo-morphic features facilitate or impede floods. For the purpose of extracting paleochannels and floodwater map-ping, we utilized multiple satellite datasets and took advantage of diversified feature selection algorithms. Paleochannels were demarcated viz., initial identification of a few paleochannels from literature and confirma-tion through high-resolution Google Earth (GE) images, followed by Principal Component Analysis (PCA) of Sentinel-2 images using Google Earth Engine (GEE), and a supervised classification of the principal bands 1, 2, and 3. False-positives were eliminated using Object-Oriented Analysis (OOA), which reduced the 964,254 poly-gons to 23,254. These polygons were visually affirmed using GE images that resulted in 115 paleochannels as the final collection. A few locations were verified through Vertical Electrical Sounding (VES) using the Schlumberger method. The features were analysed with the floodwaters of the 2018 catastrophic flood, extracted from Syn-thetic Aperture Radar (SAR) data, which was delineated for different temporal limits including the day of peak flood of August 17, 2018. During the peak flood, the inundation of the study area extended to 534.86 km2 with all the paleochannels getting immersed in floodwater. After 44 days of peak flood, the post-flood analysis revealed that when the floodwater receded 50%, the paleochannels emptied 87.39%, with the midland paleochannels discharging more than those of lowlands. Thus, such geomorphic features can be flood hotspots, but can be considered for discharging floodwater to mitigate flood risk in case of unprecedented rain. (c) 2021 Elsevier B.V. All rights reserved.
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页数:13
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