Livelihood Vulnerability of Char Land Communities to Climate Change and Natural Hazards in Bangladesh: An Application of Livelihood Vulnerability Index

Bangladesh is one of the most vulnerable countries to climate change in the world. In general, Charland (Riverine Island) communities are frequently affected by floods, riverbank erosion, and other climatic hazards, which cause many to lose their sources of livelihoods and properties and making them more vulnerable. Using survey data of 262 rural households, this study investigates the extent of livelihood vulnerability to climate change and natural hazards of the Charland communities by applying the climate change vulnerability index (CVI) (i.e. UN-IPCC vulnerability framework) and the livelihood vulnerability index (LVI) to develop context-specific interventions for building climate and livelihood resilience. The two approaches of vulnerability assessment were modified to incorporate local contexts and indigenous knowledge into 41 sub-components. The result shows that LVI and CVI values are different between Charland communities. The LVI index shows that households in Char Jotindro-Narayan (0.148) are more vulnerable than Char Kulaghat (0.139). The CVI values for Char Jotindro-Narayan (0.633) are slightly lower than for Char Kulaghat (0.639). The major vulnerability factors were identified as the social networks, food self-sufficiency, natural disasters, and climatic variability. The study also indicates that flood, riverbank erosion, unemployment, and access to communication, market, and basic service opportunities are the major biophysical and socioeconomic factors determining livelihood vulnerability. The context-specific sustainable policies and development initiatives are required to improve the adaptive capacity of Charland communities across Bangladesh and thereby building their climate and livelihood resilience.

Estimation and Prediction of Riverbank Erosion Susceptibility and Shifting Rate Using DSAS, BEHI, and REBVI Models: Evidence from the Lower Ganga River in India

The process of riverbank erosion (RE) is often accelerated by natural events and anthropogenic activities leading to the transformation of this natural process to natural hazard. The present study aims to estimate bank erosion rate and prediction of the lower Ganga River in India using digital shoreline analysis system (DSAS) model. The prediction of RE susceptibility mapping has been generated using three ensemble models such as DSAS, bank erosion hazard index (BEHI), and river embankment breaching vulnerability index (REBVI). For the study satellite images and field data (bank materials, geotechnical parameters, embankment structure, hydraulic pressure etc.) have been used to recognize the river bank position and BEHI and REBVI scores. During 1973-2020, the average bank erosion and accretion rate was found 0.059 km/y and 0.022 km/y at the left bank while 0.026 km/y and 0.046 at the right bank respectively. The prediction results illustrated that the very high vulnerable condition of 06 villages and 21 villages for high vulnerable due to left bank erosion. BEHI and REBVI scores have been the significant performance of understanding and identification of RE vulnerable areas. The long-term (2020-2045) average erosion and deposition rate was predicted at 0.135 km/y and 0.024 km/y at the left bank and 0.043 km/y and 0.045 km/y at the right bank respectively. The prediction accuracy and validation of models were measures by statistical techniques such as student’s t-test, RMSE, and R2 values. This study would be help planners and decision makers the spatial guidelines to understanding future trends of bank erosion and shifting rate for land-use planning and management strategies to protect riverbank.

MEASURING THE DETERMINANTS OF ADAPTIVE CAPACITY TO UNDERSTAND THE VULNERABILITY RISK AMONG THE RIVERBANK EROSION AFFECTED HOUSEHOLDS IN BANGLADESH: A STRUCTURAL EQUATION MODELING (SEM) APPROACH

Bangladesh is one of the most disaster-prone countries in the world. In particular, its riverine dwellers face continuous riverbank erosion, frequent flooding, and other adverse effects of climate change which makes the life of people more vulnerable. In order to assess adaptive capacity, understanding of how different households comprehend climate change is crucial. This paper aims to measure the determinants of adaptive capacityto understand the vulnerability risk among the riverbank erosion affected households. An integrated model was proposed with the constructs derived from Awareness-Ability-Action (AAA) and Socioeconomic-Sociopolitical and Institutional-Socioecological (SSS) model. A structured questionnaire survey was used to collect data from 300 participants who were affected by natural disaster specifically river erosion. The proposed research model was tested using the partial least-squares (PLS) method, a statistical analysis technique based upon structural equation modeling (SEM).The results show that the loss of farming land and all levels of riparian households impacted severely by riverbank erosion and forced into a low livelihood status, strong adaptive capacity would reduce vulnerability risk in the affected areas, community-level vulnerability measurement enhances communities understandings, build capacity, make aware, and allow them to identify appropriate locally adaptation strategies, and local level adaptation strategies may reduce the impact of such hazards on all sorts of vulnerability risk among rural households. The nature of this study may restrict its generalizability to other research settings. Future research may be necessary to validate the findings by applying this model in the vulnerability context in other developing countries. This research method and results would generate new insights with respect to planning the sustainable development goal and provide a reference for decision-making.

Climate Bridge Fund: Tackling Climate Migration in Bangladesh by Bridging Stakeholder Gaps

Climate change is already happening. In the Fifth Assessment Report (AR5), the Intergovernmental Panel on Climate Change (IPCC) indicates that about 72 million people will be displaced with 0.5-metre sea level rise if there is no investment in adaptation. In the case of a 2.0-metre rise, that number of people will be pushed to 187 million. IPCC also provides evidence on increased displacement and migration due to floods and droughts in many countries including Bangladesh. It has been reported “22% of households affected by tidal-surge floods and 16% of households that were affected by riverbank erosion moved to urban areas in Bangladesh”

Assessing the Long-Term Planform Dynamics of Ganges-Jamuna Confluence With the Aid of Remote Sensing and GIS

The Ganges-Jamuna-Padma confluence is one of the world's most active confluences. The confluence of two of the world's greatest rivers, the Ganges and the Brahmaputra, makes this a globally significant site. Severe erosion along the banks has been caused by morphological changes in this region. Riverbank erosion is one of Bangladesh's most serious problems, as it necessitates costly intervention. Riverbank erosion in Bangladesh affects millions of people each year as a result of erosion in this confluence zone. As a result, it's critical to comprehend the confluence's morphological changing pattern. This study aims to quantify actual bank shifting around the confluence of the Ganges, Jamuna, and Padma in terms of shifting rate and area during a twenty-five-year period (1990-2015). To conduct this study the collected satellite image were geo-referenced and digitize bank lines from using ArcGIS program. The bank line is the linear structure that divides the river channel's outer border from the flood plains. The distance between the extreme margins of the left and right banks, including mid-channel sandbars, was measured to determine channel width variation. To assess the maturity of change, this time frame is subdivided into five phases, each lasting five years. In addition, the long-term shift from 1972 to 2015 is qualitatively noticeable. This morphological alteration was studied using LANDSAT satellite images. The research gives current and trustworthy information on the Ganga-Jamuna confluence's planform dynamics. This research will be useful in the planning and execution of drainage development plans and erosion control strategies in this critical confluence zone.

Effects of riverbank erosion on mental health of the affected people in Bangladesh

Background In Bangladesh, riverbank erosion is a major problem that regularly displaces millions of people and affects their mental health every year. Objectives The primary objective is to explore the effects of riverbank erosion on mental health problems such as depression, anxiety, and stress in Bangladesh. Methods We conducted a household survey from August 2019 to November 2019 on randomly selected adult respondents from Rajbari District located along the Ganges River and Tangail District located along the Brahmaputra River. The respondents were divided into two groups: exposed and non-exposed to riverbank erosion. All participants were asked to complete self-reported questionnaires on the Depression, Anxiety and Stress Scale-21, and other socio-demographic, economic and riverbanks erosion-related factors. We performed Chi-squared test and multiple logistic regression analysis to explore the significant risk factors (P<0.05) of mental illness (depression, anxiety and stress). Results We surveyed 611 households, of whom 410 were from Rajbari and 201 were from Tangail. Among 611 respondents, 509 (83.31%) were exposed by riverbank erosion whereas 102 (16.69%) were non-exposed. The prevalence of depression, anxiety and stress (DAS) was 38.30%, 76.60%, 32.41%, respectively, and they were significantly higher among the exposed group than the non-exposed group (depression: 45.19% versus 3.92%, P<0.001; anxiety: 82.71% versus 46.08%, P<0.001; stress: 38.11% versus 3.92%, P<0.001). The respondents exposed to river erosion were respectively 8.28, 2.26 and 5.09 times more likely to develop DAS disorder compared to their non-exposed counterparts (ORD = 8.28, 95% CI = 2.75–24.89; ORA = 2.26, 95% CI = 1.31–3.88; ORS = 5.09, 95% CI = 1.64–15.76). Females and those who lost their houses and displaced, were more likely to have DAS disorder compared to their respective counterparts. Conclusions The exposed people were more likely to experience mental health problem and demand some social safety net programs with special focus on female and those who lost houses and displaced.