Jamba-Journal of Disaster Risk Studies最新文献

Households in developing countries have established various informal mechanisms to cope with unanticipated disasters such as droughts. Understanding these strategies in the context of climate change will enhance the design of locally applicable adaptation mechanisms. This study aimed to investigate a South African rural community's adaptive mechanisms during- and ex-post-drought. Questionnaires were administered to 200 household heads, and five focus group discussions were held with selected community members. An index was computed to establish each adaptive mechanism's importance (termed the rank order) relative to its use in the study area. During droughts, borrowing from neighbours was the most commonly used mechanism by households with no savings, while sharecropping was the second most used mechanism. Ex-post-droughts, using savings was the primary strategy for community members who had savings, followed by seeking employment as the second most used strategy.

Contribution: Findings from the study suggest that the community is highly vulnerable to droughts and disaster risks because of poor adaptive mechanisms, overreliance on water-dependent activities and lack of adequate support from different stakeholders. Community members use different mechanisms during- and ex-post-drought, depending on the stage or severity of the drought. The government and stakeholders should promote community awareness and early warning systems for droughts to mitigate disaster risks. These initiatives should ideally be combined with strengthening existing response measures and educating communities to adequately prepare for droughts and their aftermath.

The increase in climate-related disasters makes it necessary to address the spread of false information for effective disaster management. While social media can speed up disaster information, false information causes anxiety, fear, and poor decision-making, which affect preparedness and resilience. This study describes how local capacity building can address false information in community-based disaster risk management. The research uses a qualitative approach with secondary data analysis and an integrative literature review. The findings of this study show that there is a need to strengthen local capacity building to prevent the spread of false disaster information to communities and interested parties. The current response to misinformation in disaster situations includes digital literacy and media literacy education to help individuals assess news sources and verify information. It also includes community-based training programmes focusing on disaster preparedness, response, and communication, aiming to reduce the impact of misinformation. Establishing local communication networks, such as community radio stations or messaging groups for reliable alternatives to social media, is also critical to address misinformation. The study also found that trusted local leaders and influencers ensure accuracy, and transparent official channels promote public trust. Furthermore, simulated drills and workshops teach information verification practices, preparing communities to manage misinformation during crises. These efforts, along with local capacity building, are essential in strengthening community resilience and improving disaster management practices.

Contribution: This study contributed to improving disaster management communication with local communities. It strengthened the coordination of disaster information and improved partnerships among stakeholders. It also enhanced collaboration and addressed communication gaps in disaster response.

Climate variability is expected to have a negative impact on agricultural production, particularly in sub-Saharan Africa, including Malawi, where the agricultural sector is a crucial part of the economy. This study focusses on increasing our understanding on the ability of smallholder farmers in Karonga, Malawi, to adapt to climate variability. To achieve this, an integrated framework was used to assess the factors that influence the adaptive capacity of smallholder farming systems in Karonga. The integrated indicator-based framework was used to assess financial, social, human assets, knowledge and information, institutions and entitlements, flexible and forward-looking decision-making, gender and power dynamics, natural assets, physical assets and the frequency of floods. Data were collected through face-to-face interviews, focus group discussions and observations. A total of 38 indicators from literature and observations in the study area were entered and analysed in SPSS and Excel using principal component analysis. The survey results indicate that the aggregate adaptive capacity of respondents is low. Component indicators, such as ownership of livestock, support from the community, livelihood diversification and gender of the decision maker, as well as access to a mobile phone and inorganic fertiliser, and share of more productive land, increased the adaptive capacity of smallholder farmers. On the other hand, component indicators such as less productive land, deforestation, capital exclusion from food for work, age of household head, financial assets and gross annual income reduced the adaptive capacity of smallholder farmers to climate change.

Contribution: The article presents an integrated framework that considers both biophysical and socio-economic factors for assessing adaptive capacity. This framework offers a better understanding of the adaptive capacity of farming systems at the smallholder farmer level. The study's findings provide insights into the dynamic nature of adaptive capacity and identify factors that either enable or constrain adaptive capacity at various levels.

The advancement of artificial intelligence (AI) technology presents promising opportunities to improve disaster management's effectiveness and efficiency, particularly with the rising risk of natural hazards globally. This study used the Scopus database to offer a bibliometric review of AI applications in disaster management. Publications were chosen based on research scope (natural hazards), source type (journals and conference proceedings), document type (articles, conference papers and reviews) and language (English). VOSviewer and Biblioshiny were utilised to analyse trends and scientific mapping from 848 publications. The finding shows a rapid increase in AI studies for disaster management, with an annual growth rate of 15.61%. The leading source was the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. Amir Mosavi was the most prolific author, with 10 documents. The analysis reveals that China was the most productive country, while the United States was the most cited. Six research clusters were identified through keyword network mapping: (1) disaster monitoring and prediction using IoT networks, (2) AI-based geospatial technology for risk management, (3) decision support systems for disaster emergency management, (4) social media analysis for emergency response, (5) machine learning algorithms for disaster risk reduction, and (6) big data and deep learning for disaster management.

Contribution: This research contributes by mapping the application of AI technology in disaster management based on peer-reviewed literature. This helps identify major developments, research hotspots, and gaps.

Indigenous knowledge plays a crucial role in predicting hazardous events, particularly for rural communities who are not reached by conventional early warning systems. Historical knowledge of hazard occurrence stored in the repository of these communities combined with their ability to observe environmental indicators, enhances their preparedness for, response to, and recovery from disasters. This study sought to gain insights into the Indigenous indicators used by rural communities in the Joe Morolong Local Municipality, Northern Cape, South Africa, to predict natural hazards, and explores how these indicators could complement meteorological seasonal climate and weather forecasts. The study was conducted in Joe Morolong Local Municipality, Northern Cape, South Africa. A phenomenological approach, which is a form of qualitative research design, was employed, with data collected through focus group discussions and virtual interviews with key informants, involving 109 participants. The findings reveal that communities rely on various environmental signs, including changes in vegetation, lunar cycles, cloud formations, bird behaviors, and wind speed and direction, to predict and anticipate hazardous events. These traditional methods, refined over generations, provide localised, trusted, and contextually relevant early warning systems that enhance disaster preparedness. By recognising and integrating these Indigenous indicators with meteorological forecasts, disaster risk management efforts can be strengthened, ensuring that rural communities have more comprehensive and effective tools for mitigating the risks and impacts of natural hazards.

Contribution: This study emphasises the value of Indigenous knowledge as a vital resource for enhancing disaster and climate resilience, as well as improving early warning systems.

This article reviewed bodies of existing local and international literature to provide multi-level insights into Africa's readiness to standardise the adoption of social media and associated technologies in managing the numerous climate-related disasters in Africa, including storms, floods and droughts. Social media is making serious inroads in disaster management globally, except in Africa, with countries such as the United States of America, Japan, Haiti, Australia and so on, effectively deploying social media technologies in different cycles of disaster management, particularly since 2010. To encourage disaster management stakeholders in Africa to mainstream the involvement of social media in disaster management, this study examined Africa's prospects using force-field analysis that assessed the social, financial, policy, technological and other factors that inspire or restrain the effective and comprehensive adoption of social media technologies in disaster management. The force-field analysis demonstrated that disaster management stakeholders in Africa have all the tools and conditions to adopt social media technologies in climate-related disaster management on the continent.

Contribution: Driving forces such as the steady Internet access and penetration in Africa, fast-growing social media penetration and adoption of mobile technology, Africa having four of the top 10 countries that spend the most time on social media globally, growing investments in Internet infrastructure and communalistic nature of African societies, among others, are pointers of Africa's readiness to mainstream social media technologies in climate change-related disaster management.

This study examined trends in disaster preparedness literature, identified key current issues, and discovered future research avenues. This research adopts bibliometric analysis, VOSviewer 16.20 version and Biblioshiny. The results indicated some notable findings related to the development of disaster preparedness studies. This study successfully identified the most prominent trends in the literature of disaster preparedness, including the most commonly discussed and collaborative work among researchers in this discipline through the bibliometric approach. This research also highlighted that there has been a shifting focus in disaster preparedness studies over time, with an emphasis on aspects such as disaster risk mitigation and disaster risk reduction advocacy. In addition, this study seeks to identify the gaps in the research that has already been undertaken and provide possible issues for future research to fill these gaps and enhance the understanding of disaster preparedness. Because of the comprehensive nature of bibliometric analysis, this study could help scholars gain a broad view of relevant issues, while identifying prominent publications that are worthy of reference. The analysis provides insights into developments and innovations in disaster preparedness studies and identifies research gaps that require further exploration.

Contribution: This study reveals trends and gaps and provides possible issues for future research in disaster preparedness, providing essential guideposts for future research and policy.

This research used descriptive statistics to analyse rainfall trends in the Cuvelai- Etosha Basin (Namibia) over a 50-year historical period (1968 to 2018). The results revealed that rainfall fell over a period of 6 months between the months of November and April. Rainfall amounts were also observed to be higher in the first 3 months of each year, and annual levels ranged between 200 mm and 700 mm. The trend revealed that rainfall levels between 1977 and 1992 were consistently below the calculated average of 410 mm, and the rainfall amounts, and rain season were observed to have significantly shortened between the years 2009 and 2018. The rainfall trend observed over the 50-year period did not provide a definitive indication of whether the pattern followed a specific trajectory. The trend line's position was below the average line for many seasons, and it indicated that many of the seasons experienced rainfall levels below the annual average; however, an increase was observed from the years 2008 -2012 and the year 2018 wherein the rainfall received was above average and fell intensely over a brief period and these are the years where flooding was reported.

Contribution: An epileptic pattern was observed that could not be used to definitively define a trend but was useful to highlight that there was an occurrence of episodes of heavy rainfall being experienced in the months of January through March and any resilience efforts need to be prioritised during this time.

Malawi faces severe climate change impacts, with 30 climate-related disasters recorded in 20 years, causing over 4000 deaths, affecting 2.6 million people and resulting in economic losses of over $1 billion. The southern region, especially Chikwawa District, is hit the hardest, experiencing 40% of these disasters. In light of this, the study aimed to assess organisations' capacity and obstacles to collaborative approaches for adapting and building resilience to climate change-induced extreme weather events. Primary data were collected through a questionnaire distributed among 25 organisations, involving 325 participants. Thematic analysis was employed for qualitative data analysis, and the analytical hierarchy processing (AHP) method was applied to analyse intra-organisational challenges or obstacles to adopting climate resilience strategies. Alarmingly, 90% of organisations suspended operations because of climate-related disasters, with only 5% engaged in flood mitigation approaches. About 67% lacked flood abatement measures, and only 4% had conducted risk assessments. Most enterprises relied on government (80%) and Non-governmental organisations (NGOs) (70%) for resilience. Additionally, 85% of the organisations did not act collectively during extreme weather events, facing challenges such as lack of planning, adaptive capacity, leadership and funding. The results of this research offer a baseline for the organisations within the study area to map the way forward in making sure that the relentless impact of climate change-induced hazards should not always turn into disasters for their livelihoods and also the community at large.

Contribution: This study provides a methodology for the identification of barriers to fostering a culture of proactive organisational adaptation to the escalating impacts of climate change for safeguarding lives and livelihood within a neighbourhood.