Naimur Rahman

Climate change intensification has led countries worldwide to encounter more frequent disasters. Community resilience development requires adaptive governance because it enables organizations to remain flexible and build partnerships with multiple stakeholders to achieve continuous learning. However, insufficient investigations exist to understand how governance systems use resilience principles to manage climate-based combination disasters. This study explores the features of adaptive governance systems that enhance community resilience during combined climate-related disaster management. The research adopts a systematic approach to published articles indexed in the Web of Science, Scopus, and Google Scholar over the last decade by following PRISMA-ScR guidelines. The evaluation uses 51 research studies to analyze various geographic areas and intellectual environments. The evaluation focuses on two main areas of analysis based on multilevel governance structures alongside stakeholder cooperation for indigenous knowledge integration and adaptable framework deployment. Despite the successful implementation of adaptive governance models, existing studies lack evaluations of effective adaptation processes for compound disasters. The usefulness of adaptive management for enhancing resilience faces resistance because of organizational hesitation, insufficient feedback from agencies, and limited community-based access points. New methods to handle complex disaster conditions require the establishment of mechanisms for adaptable learning. The adaptive governance framework is the best possible strategy for building community resilience against deteriorating climate dynamics that generate severe disasters. However, system deployment requires fixing various operational and institutional barriers to succeed. Research-based analytical work must develop unified governance systems that handle changes to disaster-related hazards when they occur unpredictably. The analyses from research studies present vital data to governmental decision-makers, disaster response personnel, and community leadership institutions regarding the implementation of governance systems that facilitate inclusive adaptation approaches to climate change threats.

Community resilience is increasingly central to climate adaptation policy, yet household‐level evidence from riverine island (char) settings remains limited. This study assessed household flood resilience in riverine island communities of northern Bangladesh and developed a context‐specific Flood Resilience Index ( FRI ) using targeted literature review, expert consultation, and repeated char field engagement (pilot interviews and village focus group discussions). We conducted a cross‐sectional household survey ( n = 384) in six villages across Ulipur Upazila and Chilmari Upazila, Kurigram District, Bangladesh, during July–September 2023 to populate the index. The FRI was constructed from 48 indicators grouped into eight components and three capacities (anticipatory, absorptive, adaptive) using min–max normalization and equal (unit) weights; capacity and overall scores were obtained via arithmetic aggregation across the 3A structure, and radar/spider plots were used to visualize and compare capacity/component profiles across upazilas. The overall flood resilience index was 0.326, indicating that char dwellers are less resilient against recurrent floods irrespective of where they live. The anticipatory, absorptive, and adaptive capacity indices were 0.333, 0.289, and 0.339, indicating generally low flood resilience; households closer to the mainland were more resilient than those farther away, reflecting better communication, services, and livelihood opportunities. Policy priorities include improving access to food and healthcare, income diversification, actionable early warning and risk information, and resilient connectivity/infrastructure through coordinated local government action, NGO participation, and public–private partnerships.

This study examines the factors influencing food security and dietary diversity among rural farming households in Bangladesh, focusing on strategies small farmers can adopt to tackle food security challenges. Using data from a survey of 399 households, food insecurity is evaluated through the Dietary Diversity Score (DDS) and the Household Food Insecurity Access Scale (HFIAS). These measures are crucial for assessing the food security of small‐scale farmers. The study shows how DDS captures food quality beyond calories, and how HFIAS reflects hunger experiences and food insecurity severity beyond production. The findings reveal that 61% of households are food‐secured, while 39% experience varying levels of food insecurity. The average DDS score of 6.2 indicates diverse diets. Positive factors influencing DDS include income diversification, crop diversification, and farm size, while larger household size and distance to markets negatively affect food security. Crop diversification and access to agricultural information reduce food insecurity, as shown by HFIAS. Regression analysis confirms that higher income diversification, larger farm size, and smaller household size promote food security, while larger household size and greater market distance worsen it. This study calls for policies targeting food security and dietary diversity improvements among small farming households in rural Bangladesh.

The rapid expansion of urban areas and their significant effects on carbon emissions and the urban heat landscape have become major research subjects in Bangladesh. The primary aim of this study was to analyse the changes in land use and land cover (LULC) and land surface temperature (LST) from 2003 to 2023 and project them to 2043 for Gazipur, Bangladesh. Additionally, spatiotemporal variations in carbon emissions during summer and winter and their relationships with the LST were explored. A support vector machine (SVM) was used to evaluate changes in LULC. Furthermore, Cellular Automata‐Artificial Neural Network (CA‐ANN) models were utilised to investigate the future dynamics of LST and LULC. The findings of the study include urban expansion from 3% in 2003 to 18% in 2023, and its projected value indicates an expansion of 315 km ² in 2043 from 52 km ² in 2003. Therefore, the projected LST results indicate a notable increase of 10°C for the winter season in 2043. The correlation between LST and carbon emissions showed strong R ² values for both summer and winter. Specifically, the R ² values were 0.93 and 0.97 for summer and 0.91 and 0.94 for winter in 2013 and 2019, respectively. This investigation has the potential to offer novel insights into prospective urban development, effective management of thermal environments and strategies for mitigating carbon emissions.

Because of their increasing frequency and severity, communities must be prepared for and anticipate natural hazards. Education plays a crucial role in building resilience and improving disaster preparedness. Despite the importance of disaster preparation, education policy and administration do not systematically incorporate disaster preparedness. This study addresses ‘what can be done to increase resilience in the face of natural hazards by effectively integrating disaster preparedness into education policy and management?’ Thus, this study identifies strategies for integrating disaster preparedness into education policy. A mixed-methods approach comprised a systematic review using PRISMA and thematic analysis. This study reveals notable shortcomings in existing education policies and management practices concerning disaster preparation, particularly in areas prone to natural disasters. The lack of a comprehensive disaster preparedness curriculum, insufficient teacher training, and underrresource allocation contribute to these shortcomings. The assessment also focused on the benefits of disaster preparedness in education, including improved disaster response and recovery, increased community resilience, and improved knowledge and skills among students and teachers. Additionally, this study identified several cases demonstrating effective approaches and tactics for successfully integrating disaster preparation into education. This study argues that education policy and administration must prioritize disaster readiness, especially in areas at risk from natural hazards. With appropriate strategies and resources, disaster preparation can be effectively integrated into education with noticeable advantages. Educators must receive thorough training on disaster preparedness, and sufficient resources must be allocated. This study indicates that more research is needed to determine how disaster preparation can be integrated into education and measure the impact of such integration on community resilience and outcomes after disasters.

This study investigates the ecological environment quality within Bangladesh's Jamuna River Basin from 2003 to 2023, using Landsat imagery analysed through Google Earth Engine (GEE) to create the Remote Sensing Ecological Index (RSEI) for the districts of Kurigram, Sirajganj and Tangail. The analysis reveals significant spatial and temporal variations in ecological health, driven by both anthropogenic and natural factors. The findings show that whilst Kurigram's ecological quality fluctuates between good and moderate states, Sirajganj has experienced a continuous decline, and Tangail shows marked ecological degradation, especially in urban areas. The study demonstrates that the integration of RSEI with spatial autocorrelation techniques, such as Moran's I and Local Indicator of Spatial Autocorrelation (LISA), effectively captures spatial clustering of ecological quality. The clustering patterns indicate that ecological degradation is unevenly distributed, influenced by both human activities and natural processes. These results emphasise the importance of sustainable land management practices to mitigate further ecological decline and provide a foundation for targeted conservation efforts. The study's use of geospatial tools offers a scalable approach for assessing ecological health in other river basins and regions facing environmental pressures. This research underscores the critical role of monitoring long‐term ecological changes to inform policy interventions and promote sustainable development in vulnerable ecosystems.