Predictive Dynamics of Channel Pattern Changing Trends at Arial Khan River (1977-2018), Bangladesh
Rathindra Nath Biswas, Md. Juel Mia and M. Nazrul Islam
DOI : 10.3844/ajgsp.2018.1.13
Current Research in Geoscience
Volume 8, 2018
Arial Khan River is right bank distributary of Ganges-Padma River systems flowing southwest region of Bangladesh. It is morphologically very dynamic meandering river: where the delta-building process is more active than other distributaries of Ganges-Brahmaputra-Meghna (GBM) River basin. This study analyzes, morphological variables- channel length, valley length, channel area and channel patterns of Arial Khan River. A major portion of this river divided into 8 reaches from starting point Faridpur to outlet point Barisal district in order to measure channel pattern changing trends. For the proper accomplishment of the findings section of this research, time-series satellite images (Landsat MMS, Landsat TM, Landsat ETM+ and OLI) of the year 1977 to 2018 has been taken for delineation of the morphological parameters using GIS and RS techniques. In this research, sinuosity ratio index technique has been applied to analyze the morphological parameter- channel pattern and its changing trends. From the satellite images analysis results over time span, it is observed that significant morphological changes have been occurred in the river length, valley length, river area and its channel patterns. Likewise, the hydro-morphological parameters of this river (e.g., discharge, flow velocity, the river depth, width and pattern) also significantly changed due to combined massive sediment deposition from Ganges-Padma and Brahmaputra-Jamuna River systems. These hydro-morphological changes increased flood hazard vulnerability, bank erosion and sand carpeting; which badly impacted on ecological diversity, agriculture system, rural settlements and transportation networks.
© 2018 Rathindra Nath Biswas, Md. Juel Mia and M. Nazrul Islam. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.