Sylhet flood 2022 has created a devastating impact on all the sectors of economy. Sylhet and Sunamganj district had undergone tremendous damage and loss consequences. This study tends to determine the monetary value of damage and loss in those areas. Economic Commission for Latin America and the Caribbean (ECLAC) methodology for damage and loss assessment and Damage and Loss Assessment Form (D-Form) have been used partially in this study to calculate the damage and loss. Some emerging concept and methodology have been introduced here as well e.g., incorporation of recovery period to calculate loss, introducing sector-wise different equation to calculate sectoral damage and loss, and so on. Samples from four wards of Sylhet City Corporation under Sylhet district and four wards from two unions of Chatak upazila under Sunamganj district have been taken. Samples were collected by Sample Random Sampling method through a questionnaire survey. Total 176 samples had been taken, among them 87 were from the urban area, and 89 were from the rural area. 90% percent confidence level has been considered with 10% margin of error. In this study, damage and loss have been broken into several sectors and those sectors were further classified into several sub-sectors. The results show that damage and loss in the rural area is higher than the urban area. Agricultural sector and housing sector mostly contribute to the damage and loss in rural area. On the other hand, housing sector and private business sector mostly contribute to the damage and loss in urban area. Lower and lower-middle income people had undergone serious damage and loss compare to the higher income people. The people dwell in katcha or semi-pucca house faced the majority portion of damage and loss. As this study analyses the damage and loss into several sectors, it can identify the spatial vulnerability of the rural and the urban people. It can also identify the necessity of the vulnerable people. The outcome of the study will help the government and the policy makers to create a sustainable recovery, social protection and rehabilitation.

For towns and organizations worldwide, managing flood risk is a crucial concern. A successful flood risk management strategy must include accurate flood hazard mapping, vulnerability assessment, and quantification of probable flood impacts. To determine the risk of the study region and places more vulnerable to flooding, is necessary to evaluate the flood hazard in the study area. Sylhet, a major city in Bangladesh, is highly vulnerable to flooding due to its low-lying topography and its location in the Brahmaputra River basin. Floods in Sylhet can cause significant damage to property and infrastructure and displace thousands of people. Earth observation (EO) techniques can be used to assess flood risk impacts in Sylhet in several ways. EO data can also be used to develop flood forecasting models and to monitor flood events in real-time. This study presents a methodology for assessing flood risk impacts in Sylhet using EO techniques. The methodology is based on the integration of satellite imagery, flood forecasting models, and ground-based data. From this study, flood impacts and loss scenarios based on loss and impact databases from the past can also be created, which strengthens the defenses of the exposed areas and is helpful for the future.

Adaptive Social Protection (ASP) helps develop resilience of poor and vulnerable households through investing in their capacity to prepare for, cope with, and adapt to shocks, in order to prevent them from falling into poverty. In the short run, shock-responsive social protection (SRSP) help absorb climate-induced shocks while ASP promotes climate resilience through an inclusive social protection system. Idiosyncratic and covariate shocks generated by climatic events impact adversely on various stages of life cycle of the affected communities, viz. early childhood, school age, youth, working age and old age. Gender-specific adverse shocks of climatic events have non-trivial impacts on the poor and vulnerable people that substantially reduce their welfare in the absence of effective adaptive and shock-responsive social protection system. Social protection policies and programs in Bangladesh include support and assistance to individuals and households facing various risks and vulnerabilities. The country is exposed to increased incidence of large and frequent climatic events, such as cyclone, floods, droughts and salinity. Climate change will be a major driver of strategy and resource use in social protection in the country in the backdrop of increased frequency of disasters leading to non-trivial damage & loss, vulnerability with the focus on effective short-term response and long-term recovery-resilience. Given this context, the present paper aims to assess the global practice of ASP and SRSP, review the policies and plans of the Government of Bangladesh, analyze the budget allocation and use in ASP and SRSP, and suggest an outline of a shock-responsive and adaptive social protection system in Bangladesh. Finally it elaborates the seven steps of the framework that include identifying shocks; assessing vulnerability, damage & loss; designing and modifying social protection programs; financing & implementing interventions; monitoring & evaluation; scaling up; and coordination & collaboration.

Jute (Corchorus sp.) is a naturally occurring bast fibre producing crop. It has long, silky fiber which are biodegradable. This lignocellulosic, strong and environmentally favorable fibre has great demand worldwide. Jute products hold the potential to reduce the widespread usage of plastic bags which have negative impact on ecosystem and environment. Plastic bags and other synthetic products are threatening for environment as they cause pollution of water and soil. Lignin is a major component of jute cell wall. Presence of higher amount of lignin causes degradation of fiber quality. To lower lignin content in fiber and enhance the quality, a genome wide investigation of gene families involved in the lignin production pathway can help to target candidate genes for knockout experiments and investigate to make the fiber finer ones. Caffeoyl-CoA 3-O-methyltransferase (CCoAOMT) is one of the most significant gene families involved in the lignin biosynthesis. In this study, an extensive characterization of the CCoAOMT gene family was carried out in two jute species (C. capsularis and C. olitoroius) by analyzing their structural, functional, molecular and evolutionary characteristics. 6 CCoAOMT gene members were identified in each of the two species. Furthermore, considerable alteration of CCoAOMT transcripts in different tissues was observed by expression profiling using qPCR and candidate genes were chosen for knockout experiment using CRISPR-Cas9 technique. Vector constructs were developed through modular cloning technology with a view to lower the lignin content and improve quality of this golden fibre.

Cottage, micro, small, and medium enterprises (CMSMEs) play a vital role in advancing economies, alleviating poverty, and promoting sustainability, even as they grapple with resource constraints and innovation challenges. This is particularly crucial in the context of sustainable agriculture, and Bangladesh is no exception. Despite its remarkable achievements in feeding a large population with limited land, the environmental impact of CMSMEs in the Bangladeshi agriculture sector remains understudied. Environmental life cycle assessment (ELCA) can offer valuable insights into the sector's environmental footprint, which is imperative for informed policymaking. The study indicates that certain fresh food items, such as potato, tomato, banana, mango, ruhi fish, silver carp, beef, and mutton, have high environmental footprints, posing risks to human health and ecosystems. These impacts are especially significant in terms of land use, terrestrial eco-toxicity, global warming, human non-carcinogenic toxicity, terrestrial acidification, and human carcinogenic toxicity. This leads to adverse effects on human health (Disability Adjusted Life Years - DALY) and species loss (Species Loss per Year - Species.year), primarily driven by the value chains of these items. The analysis also highlights that animal-based food items have a greater environmental impact compared to plant-based ones. To ensure sustainable agriculture, a pragmatic strategy is needed, including facilitating CMSME involvement. However, challenges like access to finance and technology hinder the adoption of sustainable practices by CMSMEs. In alignment with the National Adaptation Plan (NAP) for 2023-2050, which emphasizes climate-resilient agriculture and private sector engagement, agriculture governance in Bangladesh must prioritize sustainability and strengthen regulatory enforcement, particularly in rural areas. Incentivizing sustainable practices and acknowledging the limitations and needs of small businesses is essential. The establishment of specific environmental targets and regular measurement and analysis of agriculture's environmental footprints are key steps in this pursuit while recognizing the commercial constraints of "going green."

Oilseed Brassicas are the 3^rd largest edible oil source in the world. Despite being so, their fatty acid profiles have shown high levels of erucic acid content which is detrimental for human health. Erucic acid can cause myocardial damage and muscle lesions in the heart if taken frequently. This issue prevents the worldwide use of mustard oil as an ideal edible oil and its global commercial export. Genome editing technology have been a pioneer in producing smart varieties of crop which are either adaptable to the current changing climate or capable of ensuring public health. Previous reports show that, the Fatty Acyl CoA Elongase 1 (FAE1) gene is the key gene for the synthesis of erucic acid. The product of which is 3-ketoacyl-CoA synthase, one of the four enzyme complexes involved in the synthesis of erucic acid from oleic acid. Brassica rapa has two functional homologues of this gene on its A08 and C03 chromosomes. By using CRISPR (Clustered Regularly Interspaced Palindromic Repeats) associated protein Cas9 genome editing technology it is possible to knockout the expression of this gene and to produce low erucic acid producing novel B. rapa plants. To do so, analysis of fatty acid profile of the local Tori-7 variety of B. rapa has been done along with in-silico analysis and molecular characterization of the said genotype. SgRNAs have been designed to target our two homologues of the FAE1 gene and integrated into the pAGM8031_fae1 vector via modular cloning method. Through Agrobacterium-mediated genetic transformation method, novel mutant lines are being developed with the goal to conduct molecular analysis on the transgenic lines for our desired mutation and establishing a homozygous line of genome edited, low erucic acid producing B. rapa plants which can ensure safety of public health if released commercially.

Bangladesh experiences annual flooding due to its geographical location in the delta of significant rivers, combined with climatic factors like heavy monsoon rains and the effects of climate change, which lead to increased flood risks. In the Northeastern part of Bangladesh, Sunamganj and Sylhet regions are particularly vulnerable, experiencing recurrent monsoon floods that inflict substantial economic losses, impacting agriculture, infrastructure, and livelihoods, incurring millions of dollars in damages. This study aimed to analyze the flooding situation for the Flash Flood of 2022 by creating classified flood extent and susceptibility maps to asses affected land use land cover. For result validation, a comparison was made between the results obtained and the flood map available at the secondary data source of the Flood Forecasting and Early Warning (FFWC) website, Bangladesh. In this study, Sentinel-1A SAR images were used to analyze flood extent using SNAP, and Sentinel 2A images were assessed using Google Earth Engine and ERDAS Imagine for land use land cover information. Flood susceptibility analysis was done with ArcGIS software and based on factors such as topographic wetness index, elevation, slope, rainfall, soil type, land use/land cover, drainage density, and distance from the river. Three risk zones were identified for this study area: low-risk, moderate-risk, and high-risk. The land use land cover classification was validated with primary ground-truthing data. The classes of agricultural land, vegetative cover, built environment, barren land, and dry haor land were identified, and their flooded and non-flooded areas in hectares were calculated. The flood extent maps were validated with the FFWC flood map which showed 81% accuracy. For the Sylhet district, 56% of the total district's area of 2,76,755 hectares was inundated, and for the Sunamganj district, 66% of the total district's area of 1,57,719 hectares. This research produced a quick, efficient, and cost-effective flood analysis technique for analysing flood extent, susceptibility, and impact on land use. It can aid disaster management stakeholders in formulating proactive rescue, recovery, and future mitigation strategy development initiatives.

Potato (Solanum tuberosum L.) occupies a significant position as the third most-consumed global food crop, underscoring its crucial role in agriculture due to its nutritional value, adaptability, and industrial applications. However, the cultivation of this crop faces numerous challenges due to its complex genetics, including traits such as heterozygosity, self-incompatibility, and tetraploid nature. In response to drought-induced stress, plants produce abscisic acid (ABA), which triggers drought-related genes and encourages the closure of stomata to endure water scarcity. In the case of potatoes, an excessive breakdown of ABA by ABA 8’-hydroxylase, a cytochrome P450 monoxygenase, enhances their ability to withstand drought. The primary objective of this research is to enhance potato's resilience to drought using CRISPR-Cas9 technology to modify ABA catabolic genes, thereby reducing the breakdown of ABA. Previous research in rice has identified three homologous genes, OsABA8ox1, OsABA8ox2, and OsABA8ox3, which encode ABA 8’-hydroxylase and have a notable impact on drought sensitivity. Lowering the expression of OsABA8ox3 has proven to increase rice's ability to withstand severe drought. Similarly, in the context of potatoes, we pinpointed two orthologous genes closely related to Arabidopsis CYP707A as potential targets for precise genome editing, with the goal of enhancing drought resistance. By making precise edits to ABA catabolic genes through CRISPR-Cas9 technology, our aim is to fine-tune ABA catabolism in potato plants, thus amplifying their capacity to endure drought. These newly engineered potato varieties are anticipated to exhibit enhanced resilience to drought, a quality of paramount importance in the face of climate change. As global temperatures rise and weather patterns become increasingly erratic, the imperative to enhance the drought resilience of staple crops such as potatoes becomes evident. This advancement promises to bolster food security and contribute significantly to global efforts aimed at addressing hunger and promoting sustainable agriculture amid the challenges posed by climate change.

Bangladesh is one of the most vulnerable countries in the world in terms of climate change and variability. Introduction. There are numerous studies on climate change vulnerability studies in Bangladesh in various sectors, i.e., livelihood vulnerability, agricultural vulnerability, fisheries vulnerability, vulnerability in the tourism sector, hazard-specific vulnerabilities, etc. This study aims to review the vulnerability studies of Bangladesh in order to know the current status of these studies and identify limitations and gaps of vulnerability studies in Bangladesh for further research potential. The study has followed the PRISMA statement of systematic review using the keywords “Vulnerability assessment” AND Bangladesh, “Climate vulnerability” AND Bangladesh, “Climatic vulnerability” AND Bangladesh, to search for published articles from the Scopus, Web of Science and Google Scholar. The study has identified 1,500 related articles and reviewed a total of 120 articles (after screening, inclusion and exclusion of articles). The study has found that most of the vulnerability assessment studies have been conducted in the coastal areas of Bangladesh which is the most vulnerable area. Other studies focused on the floodplain and haor region that are exposed to flood and river erosion. However, some studies have been conducted in the Barind region, e.g., Rajshahi. The methods used for vulnerability studies are mainly the IPCC 2007 vulnerability study method, livelihood vulnerability index, agricultural vulnerability index, principal component analysis, GIS-based Fuzzy logic method, etc. Both primary and secondary data including geospatial database, government database and household-level survey data were used for this assessment. A majority of the studies used primary-level household data using some selected indicators of exposure, sensitivity and adaptive capacity. Besides there are disaster-specific vulnerability assessment studies, for example, cyclones, floods, droughts, river erosion, etc. This review has provided the scopes, limitations and opportunities of vulnerability studies in Bangladesh and can help in policy planning for sustainable climate change adaptation and resilience building.

Groundwater salinization is considered as a major environmental problem in the coastal areas worldwide influencing ecosystems and human health. In Bangladesh, groundwater quality and quantity in the coastal regions have both significantly degraded as a result of saline water intrusion due to sea-level rise, storm surge flooding and excessive pumping of groundwater over the past few decades. Coastal aquifers are experiencing saltwater intrusion due to the hydraulic connection between groundwater and seawater. However, an accurate prediction of salinity concentration in groundwater remains a challenge due to the complexity of groundwater salinization processes and its influencing factors. In this study, machine learning (ML) algorithms has been performed for predicting groundwater salinity and identifying its influencing factors. This study was conducted in the southwestern coastal zones, i. e., Khulna, Bagerhat, and Satkhira of Bangladesh using geospatial database of 215 groundwater samples and different conditioning factors. Then, the predictive performances of different ML algorithms were compared, i.e., the Artificial Neural Network (ANN), Gaussian Process Regression (GPR), and the Support Vector Machine. The model performance was assessed by using root-mean-square error (RMSE) and coefficient of determination (R²). The results show that the ANN model has the highest performance with R² = 0.92 and RMSE = 56.45 and six of the 10 influencing factors, including distance from shoreline, groundwater level, aquitard thickness, hydraulic conductivity, distance from the river, river salinity are the most important factors for groundwater salinity prediction. The results of the study will provide policy makers with useful information to tackle the issue of elevated salt levels in groundwater in coastal lowlands caused by excessive extraction. Human actions are a significant factor in the escalation of groundwater salinization, making it imperative to take prompt action based on the findings to promote sustainable management of groundwater in the southwestern coastal region.