Browsing by Author "Rahman, Munshi Khaledur"
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- Coastal Erosion and Human Perceptions of Revetment Protection in the Lower Meghna Estuary of BangladeshCrawford, Thomas W.; Islam, Md Sariful; Rahman, Munshi Khaledur; Paul, Bimal Kanti; Curtis, Scott; Miah, Md. Giashuddin; Islam, Mohammad Rafiqul (MDPI, 2020-09-22)This study investigates coastal erosion, revetment as a shoreline protection strategy, and human perceptions of revetments in the Lower Meghna estuary of the Bangladesh where new revetments were recently constructed. Questions addressed were: (1) How do rates of shoreline change vary over the period 2011–2019? (2) Did new revetments effectively halt erosion and what were the magnitudes of erosion change? (3) How have erosion rates changed for shorelines within 1 km of revetments, and (4) How do households perceive revetments? High-resolution Planet Lab imagery was used to quantify shoreline change rates. Analysis of household survey data assessed human perceptions of the revetment’s desirability and efficacy. Results revealed high rates of erosion for 2011–2019 with declining erosion after 2013. New revetments effectively halted erosion for protected shorelines. Significant spatial trends for erosion rates existed for shorelines adjacent to revetments. Survey respondents overwhelmingly had positive attitudes about a desire for revetment protection; however, upstream respondents expressed a strong majority perception that revetment acts to make erosion worse. Highlights of the research include integration of remote sensing with social science methods, the timing of the social survey shortly after revetment construction, and results showing significant erosion change upstream and downstream of new revetments.
- Household Migration and Intentions for Future Migration in the Climate Change Vulnerable Lower Meghna Estuary of Coastal BangladeshPaul, Bimal Kanti; Rahman, Munshi Khaledur; Lu, Max; Crawford, Thomas W. (MDPI, 2022-04-14)Coastal residents of Bangladesh are now confronted with the increased incidence, variability, and severity of weather-related hazards and disasters due to climate change-induced sea level rise (SLR). Many researchers hold the view that as a consequence residents of such area have either already migrated to inland locations or intend to so in the near future. We examine the migration of households following a flash flood event that took place in August 2020 and address intentions for future migration in the Lower Meghna Estuary of coastal Bangladesh. The data obtained for this study include 310 household surveys, field observations, and informal discussions with respondents and local people. Based on the analysis of the field data, this empirical research found one household migrated to other district within one year after the event. When the respondents were asked about their future migration intensions, only a tiny proportion, namely 21 (6.77%) households, likely will leave the study area to settle in other districts while the remaining 289 households likely will stay in the Lakshmipur district. This finding challenges the existing narratives about vulnerability to environmentally induced migration. Moreover, it provides evidence of non-migration, which is a new as well as thriving area of investigation in relation to coastal Bangladesh.
- A Hydroclimatological Analysis of Precipitation in the Ganges–Brahmaputra–Meghna River BasinCurtis, Scott; Crawford, Thomas W.; Rahman, Munshi Khaledur; Paul, Bimal Kanti; Miah, Md. Giashuddin; Islam, Md Sariful; Patel, Mohin (MDPI, 2018-09-29)Understanding seasonal precipitation input into river basins is important for linking large-scale climate drivers with societal water resources and the occurrence of hydrologic hazards such as floods and riverbank erosion. Using satellite data at 0.25-degree resolution, spatial patterns of monsoon (June-July-August-September) precipitation variability between 1983 and 2015 within the Ganges–Brahmaputra–Meghna (GBM) river basin are analyzed with Principal Component (PC) analysis and the first three modes (PC1, PC2 and PC3) are related to global atmospheric-oceanic fields. PC1 explains 88.7% of the variance in monsoonal precipitation and resembles climatology with the center of action over Bangladesh. The eigenvector coefficients show a downward trend consistent with studies reporting a recent decline in monsoon rainfall, but little interannual variability. PC2 explains 2.9% of the variance and shows rainfall maxima to the far western and eastern portions of the basin. PC2 has an apparent decadal cycle and surface and upper-air atmospheric height fields suggest the pattern could be forced by tropical South Atlantic heating and a Rossby wave train stemming from the North Atlantic, consistent with previous studies. Finally, PC3 explains 1.5% of the variance and has high spatial variability. The distribution of precipitation is somewhat zonal, with highest values at the southern border and at the Himalayan ridge. There is strong interannual variability associated with PC3, related to the El Nino/Southern Oscillation (ENSO). Next, we perform a hydroclimatological downscaling, as precipitation attributed to the three PCs was averaged over the Pfafstetter level-04 sub-basins obtained from the World Wildlife Fund (Gland, Switzerland). While PC1 was the principal contributor of rainfall for all sub-basins, PC2 contributed the most to rainfall in the western Ganges sub-basin (4524) and PC3 contributed the most to the rainfall in the northern Brahmaputra (4529). Monsoon rainfall within these two sub-basins were the only ones to show a significant relationship (negative) with ENSO, whereas four of the eight sub-basins had a significant relationship (positive) with sea surface temperature (SST) anomalies in the tropical South Atlantic. This work demonstrates a geographic dependence on climate teleconnections in the GBM that deserves further study.
- Rohingya Refugee Crisis and Forest Cover Change in Teknaf, BangladeshHassan, Mohammad Mehedy; Smith, Audrey Culver; Walker, Katherine; Rahman, Munshi Khaledur; Southworth, Jane (MDPI, 2018-04-30)Following a targeted campaign of violence by Myanmar military, police, and local militias, more than half a million Rohingya refugees have fled to neighboring Bangladesh since August 2017, joining thousands of others living in overcrowded settlement camps in Teknaf. To accommodate this mass influx of refugees, forestland is razed to build spontaneous settlements, resulting in an enormous threat to wildlife habitats, biodiversity, and entire ecosystems in the region. Although reports indicate that this rapid and vast expansion of refugee camps in Teknaf is causing large scale environmental destruction and degradation of forestlands, no study to date has quantified the camp expansion extent or forest cover loss. Using remotely sensed Sentinel-2A and -2B imagery and a random forest (RF) machine learning algorithm with ground observation data, we quantified the territorial expansion of refugee settlements and resulting degradation of the ecological resources surrounding the three largest concentrations of refugee camps—Kutupalong–Balukhali, Nayapara–Leda and Unchiprang—that developed between pre- and post-August of 2017. Employing RF as an image classification approach for this study with a cross-validation technique, we obtained a high overall classification accuracy of 94.53% and 95.14% for 2016 and 2017 land cover maps, respectively, with overall Kappa statistics of 0.93 and 0.94. The producer and user accuracy for forest cover ranged between 92.98–98.21% and 96.49–92.98%, respectively. Results derived from the thematic maps indicate a substantial expansion of refugee settlements in the three refugee camp study sites, with an increase of 175 to 1530 hectares between 2016 and 2017, and a net growth rate of 774%. The greatest camp expansion is observed in the Kutupalong–Balukhali site, growing from 146 ha to 1365 ha with a net increase of 1219 ha (total growth rate of 835%) in the same time period. While the refugee camps’ occupancy expanded at a rapid rate, this gain mostly occurred by replacing the forested land, degrading the forest cover surrounding the three camps by 2283 ha. Such rapid degradation of forested land has already triggered ecological problems and disturbed wildlife habitats in the area since many of these makeshift resettlement camps were set up in or near corridors for wild elephants, causing the death of several Rohingyas by elephant trampling. Hence, the findings of this study may motivate the Bangladesh government and international humanitarian organizations to develop better plans to protect the ecologically sensitive forested land and wildlife habitats surrounding the refugee camps, enable more informed management of the settlements, and assist in more sustainable resource mobilization for the Rohingya refugees.
- Shoreline Change Analysis along Rivers and Deltas: A Systematic Review and Bibliometric Analysis of the Shoreline Study Literature from 2000 to 2021Rahman, Munshi Khaledur; Crawford, Thomas W.; Islam, Md. Sariful (MDPI, 2022-11-08)Globally, coastal zones, rivers and riverine areas, and deltas carry enormous values for ecosystems, socio-economic, and environmental perspectives. These often highly populated areas are generally significantly different from interior hinterlands in terms of population density, economic activities, and geophysical and ecological processes. Geospatial technologies are widely used by scholars from multiple disciplines to understand the dynamic nature of shoreline changes globally. In this paper, we conduct a systematic literature review to identify and interpret research patterns and themes related to shoreline change detection from 2000 to 2021. Two databases, Web of Science and Scopus, were used to identify articles that investigate shoreline change analysis using geospatial technique such as remote sensing and GIS analysis capabilities (e.g., the Digital Shoreline Analysis System (DSAS). Between the years 2000 and 2021, we initially found 1622 articles, which were inspected for suitability, leading to a final set of 905 articles for bibliometric analysis. For systematic analysis, we used Rayyan—a web-based platform used for screening literature. For bibliometric network analysis, we used the CiteSpace, Rayyan, and VOSviewer software. The findings of this study indicate that the majority of the literature originated in the USA, followed by India. Given the importance of protecting the communities living in the riverine areas, coastal zones, and delta regions, it is necessary to ask new research questions and apply cutting-edge tools and technology, such as machine learning approach and GeoAI, to fill the research gaps on shoreline change analysis. Such approaches could include, but are not limited to, centimeter level accuracy with high-resolution satellite imagery, the use of unmanned aerial vehicles (UAV), and point cloud data for both local and global level shoreline change and analysis.