Abdur Rahim Hamidi

Flood disasters in the Himalayan–Indus Basin are increasing in frequency, scale, and impact, driven by glacial melt, erratic monsoons, and changing land-use patterns. Yet their effects are unevenly distributed, and their causes extend beyond climatic or environmental factors. Using the 2022 Pakistan floods as a case study, this paper argues that such disasters are not isolated anomalies but emerge from the intersection of climate extremes, systemic risk, social vulnerability, and governance failure. Drawing on interdisciplinary scholarship in disaster studies, hydropolitics, and critical development, this study employs a qualitative, exploratory research design, analysing published papers, technical and policy reports, and grey literature. A critical social science perspective frames the analysis, highlighting how historical and political processes—including colonial-era infrastructure, socio-political exclusion, and institutional dysfunction—have produced and distributed systemic flood risk in Pakistan. We argue that flood crises stem not only from climate extremes but are systemically produced by historical and political processes, shaped by intersecting hierarchies of social, economic, and political marginalization. The paper critiques dominant hazard-centric and technocratic responses and calls for reimagining resilience as a transformative process—one that involves overhauling governance, dismantling exclusion, rebuilding socio-ecological relations, and embedding equity and justice in disaster risk strategies. The paper advocates for just, participatory, and ecologically grounded approaches to resilience. While focused on Pakistan, the findings offer broader insights for understanding and addressing systemic flood risk across the Himalayan–Indus region and comparable climate-vulnerable contexts. The paper contributes to ongoing debates on disaster governance and resilience in climate-vulnerable regions.

Social vulnerability plays a critical role in shaping the impacts of flooding, yet the ways in which it is measured remain inconsistent and often disconnected from local realities. As climate-related flood events intensify globally, there is an urgent need to understand how social vulnerability is conceptualized and assessed to inform more equitable and effective risk reduction strategies. This paper reports the results of a systematic literature review on indicators and indexes used to assess social vulnerability to floods. Utilizing the PRISMA methodology, we identified and screened 1621 studies published between 2013 and 2023, selecting 36 peer-reviewed publications for examining how social vulnerability indices have been conceptualized, constructed, and applied, as well as the range of indicators, and methodological approaches used. We identified 78 indicator sets across 22 thematic domains. Results indicate that most attention has been given to a small set of indicators focusing on at-risk populations, socioeconomic factors, housing, and employment, while other factors such as health conditions, disaster preparedness, social connectedness, gender minorities, and sexuality are consistently underrepresented. Many studies rely on established frameworks without adapting them to local socio-cultural contexts and use census and secondary data sources, providing limited household-level and qualitative insights. Lack of methodological transparency, particularly regarding normalization and weighting, is common as is insufficient validation and ground-truthing. Greater attention to these issues, along with empirical case studies, is needed to provide in-depth insights into the root causes of social vulnerability and inform policies better tailored to local realities. This review highlights significant conceptual and methodological gaps, calling for more context-sensitive, mixed-method, and empirically validated approaches to improve the robustness and local relevance of social vulnerability assessments in flood-prone areas.

The Arctic is undergoing unprecedented transformations with implications for regional ecosystems, Indigenous communities, and global climate systems. Ocean heat transport, permafrost thawing, and ice–albedo interactions are some of the feedback mechanisms that contribute to the increase in average temperatures in the Arctic. These processes increase the risks associated with climate change globally by speeding up the loss of sea ice, changes in biodiversity, and greenhouse gas emissions. This review synthesises recent advances in Arctic climate science, focusing on the drivers and feedback mechanisms of Arctic amplification, its cascading impacts on ecosystems and socioeconomic systems, and emerging governance challenges. It highlights critical knowledge gaps, specifically regarding the importance of Indigenous knowledge and interdisciplinary approaches in climate adaptation strategies. This study emphasises the need for inclusive, transformative, and collaborative approaches by analysing governance frameworks, climate policies, and community resilience initiatives. Innovative adaptation strategies are suggested, such as ecosystem-based adaptations, climate-resilient infrastructure, and the switch to renewable energy to address these issues. Arctic-specific governance recommendations are proposed to develop sustainable solutions that preserve its ecology while reducing its global effects by filling research gaps and promoting international collaboration. The future of the Arctic is not merely a regional issue but also a global one, requiring swift and coordinated action to address climate challenges.

In recent years, social vulnerability has gained much importance in academic studies. However, social indices are rarely combined and validated with exposure and resilience components. This study provides an integrated analysis of the flood exposure and social vulnerability of rural households in a case area of Charsadda District, Khyber Pakhtunkhwa, Pakistan. A conceptual framework was designed (based on the MOVE framework) as a guideline and key indicators were identified. For the exposure component, parameters such as elevation, flooded locations, and distance from the river were endorsed to understand flood mechanisms. For populating socioeconomic variables, questionnaire-based interviews were conducted with 210 households. The results were presented through ArcGIS-generated maps. The most significant indicators interplaying with high vulnerability were exposure-related indicators. The findings showed that the southern areas, including Agra, Daulat Pura, and Hisar Yasinzai were highly vulnerable due to having the highest number of flood locations, lowest elevations, and shortest distances from rivers, as well as larger household sizes, more elderly, children and women, illiteracy rates, and weak financial capacity. Understanding such dominant indicators and areas where high social vulnerability and high exposure converge can inform the authorities in mitigating both social and physical flood vulnerability.

Floods are threats seriously affecting people’s lives and property globally. Risk analysis such as flood susceptibility assessment is one of the critical approaches to mitigate flood impacts. However, the inadequate field survey and lack of data might hinder the mapping of flood susceptibility. The emergence of user-generated content (UGC) in the era of big data provides new opportunities for flood risk management. This research proposed a flood susceptibility assessment model using UGC as a potential data source and conducted empirical research in Ji’an County in China to make up for the lack of ground survey data in mountainous-hilly areas. This article used python crawlers to obtain the geographic location of the floods in Ji’an City from 2016 to 2019 from social media, and the state-of-the-art MaxEnt algorithm was adopted to obtain the flood occurrence map. The map was verified by the flood data crawled from reliable official media, which achieved an average AUC of 0.857% and an overall accuracy of 93.1%. Several novel indicators were used to evaluate the importance of conditioning factors from different perspectives. Land use, slope, and distance from the river were found to contribute most to the occurrence of floods. Our findings have shown that the proposed historical UG C-based model is practical and has good flood-risk-mapping performance. The importance of the conditioning factors to the occurrence of floods can also be ranked. The reports from stakeholders are a great supplement to the insufficient field survey data and tend to be valuable resources for flood disaster preparation and mitigation in the future. Finally, the limitations and future development directions of UGC as a data source for flood risk assessment are discussed.