Evidence map›Paper›PMID 29556796›Full record

ArticleEnvironmental monitoring and assessment2018

Evaluation of climate-induced waterlogging hazards in the south-west coast of Bangladesh using Geoinformatics.

Syed M Tareq, M Tauhid Ur Rahman, A Z M Zahedul Islam, A B M Baddruzzaman, M Ashraf Ali

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Article in Environmental monitoring and assessment, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Syed M TareqClimate Change Lab, Department of Civil Engineering, Military Institute of Science and Technology, Dhaka, 1216, Bangladesh. syedtareq71@gmail.com.
M Tauhid Ur RahmanClimate Change Lab, Department of Civil Engineering, Military Institute of Science and Technology, Dhaka, 1216, Bangladesh.
A Z M Zahedul IslamWater Resources Engineering Laboratory, Space Research and Remote Sensing Organization, Dhaka, 1207, Bangladesh.
A B M BaddruzzamanDepartment of Civil Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh.
M Ashraf AliDepartment of Civil Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Climate-induced waterlogging has been significantly affecting the lives and livelihood of people in the south-west coastal region of Bangladesh for a couple of decades. The objective of this study is to investigate the waterlogging hazards of Tala, a south-western coastal Upazila of Bangladesh by analyzing satellite image. An empirical model based on velocity of flow, depth of flow, and inundation depth has been proposed to assess waterlogging hazard in pre monsoon, monsoon, and post monsoon period. Landsat TM images for the years 1989, 2000, and 2011 were analyzed by using Geoinformatics including GIS and remote sensing techniques to quantify the water hazard. Three dominant land use classes such as "water," "vegetation," and "bare lands and others" were selected to identify the land use land cover change. Both FGD (focus group discussions) and KII (key informant interviews) were also accomplished to assess the waterlogging hazard. It was revealed that 0.7% of the study area (246 ha) was under water in 1989, which increased alarmingly to 34% (11,525 ha) in 2011. There was an increase in 62.9% of water bodies during 1989 to 2000, which was further expanded to 77% during 2000 to 2011. Satellite image analysis between 2011 and 2015 also showed that nearly 89% of the waterlogged area including floodplain is inundated by tidal saline water that supports shrimp cultivation. On the contrary, 11% of the waterlogged area was occupied by trapped rain water. Confirmation of saline water and fresh water was done by measuring electrical conductivity and conducting "mouth taste" during field visit. The decreasing rate of "bare lands and others" category indicates that there is around 69.4% of reduction in this category to accommodate the increasing water covering areas. The hazard model shows that the middle part of the Tala along with the flood plain of the Kabodak River usually have to suffer waterlogged in both pre monsoon and post monsoon period. It was found that low flow in the upstream side, siltation in the Kabodak River, elevated riverbed, and recent increase in total annual rainfall have resulted in waterlogging problem. Combining inputs obtained from FGD, KII, and economic study of drainage, the TRM (tidal river management) followed by re-excavation of silted riverbed may provide a sustainable solution to solve the prolonged waterlogging situation.

Indexed as

Climate ChangeAgricultureBangladeshClimateEnvironmental MonitoringFresh WaterRainRiversBeelsHazardKabodak RiverLand use land cover (LULC)Tidal river management (TRM)

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.