Reclassifying historical disasters: From single to multi-hazards.

Multi-hazard events, characterized by the simultaneous, cascading, or cumulative occurrence of multiple natural hazards, pose a significant threat to human lives and assets. This is primarily due to the cumulative and cascading effects arising from the interplay of various natural hazards across space and time. However, their identification is challenging, which is attributable to the complex nature of natural hazard interactions and the limited availability of multi-hazard observations. This study presents an approach for identifying multi-hazard events during the past 123 years (1900-2023) using the EM-DAT global disaster database. Leveraging the 'associated hazard' information in EM-DAT, multi-hazard events are detected and assessed in relation to their frequency, impact on human lives and assets, and reporting trends. The interactions between various combinations of natural hazard pairs are explored, reclassifying them into four categories: preconditioned/triggering, multivariate, temporally compounding, and spatially compounding multi-hazard events. The results show, globally, approximately 19 % of the 16,535 disasters recorded in EM-DAT can be classified as multi-hazard events. However, the multi-hazard events recorded in EM-DAT are disproportionately responsible for nearly 59 % of the estimated global economic losses. Conversely, single hazard events resulted in higher fatalities compared to multi-hazard events. The largest proportion of multi-hazard events are associated with floods, storms, and earthquakes. Landslides emerge as the predominant secondary hazards within multi-hazard pairs, primarily triggered by floods, storms, and earthquakes, with the majority of multi-hazard events exhibiting preconditioned/triggering and multivariate characteristics. There is a higher prevalence of multi-hazard events in Asia and North America, whilst temporal overlaps of multiple hazards predominate in Europe. These results can be used to increase the integration of multi-hazard thinking in risk assessments, emergency management response plans and mitigation policies at both national and international levels.

A novel framework for addressing uncertainties in machine learning-based geospatial approaches for flood prediction.

Globally, many studies on machine learning (ML)-based flood susceptibility modeling have been carried out in recent years. While majority of those models produce reasonably accurate flood predictions, the outcomes are subject to uncertainty since flood susceptibility models (FSMs) may produce varying spatial predictions. However, there have not been many attempts to address these uncertainties because identifying spatial agreement in flood projections is a complex process. This study presents a framework for reducing spatial disagreement among four standalone and hybridized ML-based FSMs: random forest (RF), k-nearest neighbor (KNN), multilayer perceptron (MLP), and hybridized genetic algorithm-gaussian radial basis function-support vector regression (GA-RBF-SVR). Besides, an optimized model was developed combining the outcomes of those four models. The southwest coastal region of Bangladesh was selected as the case area. A comparable percentage of flood potential area (approximately 60% of the total land areas) was produced by all ML-based models. Despite achieving high prediction accuracy, spatial discrepancy in the model outcomes was observed, with pixel-wise correlation coefficients across different models ranging from 0.62 to 0.91. The optimized model exhibited high prediction accuracy and improved spatial agreement by reducing the number of classification errors. The framework presented in this study might aid in the formulation of risk-based development plans and enhancement of current early warning systems.

Vulnerability of Australia to heatwaves: A systematic review on influencing factors, impacts, and mitigation options.

BACKGROUND: Heatwaves have received major attention globally due to their detrimental effects on human health and the environment. The frequency, duration, and severity of heatwaves have increased recently due to changes in climatic conditions, anthropogenic forcing, and rapid urbanization. Australia is highly vulnerable to this hazard. Although there have been an increasing number of studies conducted in Australia related to the heatwave phenomena, a systematic review of heatwave vulnerability has rarely been reported in the literature. OBJECTIVES: This study aims to provide a systematic and overarching review of the different components of heatwave vulnerability (e.g., exposure, sensitivity, and adaptive capacity) in Australia. METHODS: A systematic review was conducted using the PRISMA protocol. Peer-reviewed English language articles published between January 2000 and December 2021 were selected using a combination of search keywords in Web of Science, Scopus, and PubMed. Articles were critically analyzed based on three specific heatwave vulnerability components: exposure, sensitivity, and adaptive capacity. RESULTS AND DISCUSSION: A total of 107 articles meeting all search criteria were chosen. Although there has been an increasing trend of heat-related studies in Australia, most of these studies have concentrated on exposure and adaptive capacity components. Evidence suggests that the frequency, severity, and duration of heatwaves in Australian cities has been increasing, and that this is likely to continue under current climate change scenarios. This study noted that heatwave vulnerability is associated with geographical and climatic factors, space, time, socioeconomic and demographic factors, as well as the physiological condition of people. Various heat mitigation and adaptation measures implemented around the globe have proven to be efficient in reducing the impacts of heatwaves. CONCLUSION: This study provides increased clarity regarding the various drivers of heatwave vulnerability in Australia. Such knowledge is crucial in informing extreme heat adaptation and mitigation planning.

Spatial Pattern and Land Surface Features Associated with Cloud-to-Ground Lightning in Bangladesh: An Exploratory Study.

Severe weather events such as lightning appear to be a significant threat to humans and property in South Asia, an area known for intense convective activity directly related to the tropical climate of these areas. The current study was conducted in Bangladesh and examined the association between cloud-to-ground (CG) lightning and ground surface properties, with the aim of improving existing knowledge regarding this phenomenon. GLD360 data from 2015 to 2020 were used to describe the seasonal lightning climatology. Elevation, land use and land cover, vegetation and surface heat flux data were used to examine all land surface features possibly associated with CG lightning occurrence. Hot and cold spot spatial patterning was calculated using local indicators of spatial association. Results indicated a strong CG lightning seasonality. CG stroke density varied considerably across seasons with the pre-monsoon exhibiting the highest density. This was followed by occurrences in the monsoon season. The March-June period experienced 73% of the total observed. Elevation appeared to influence the post-monsoon CG stroke, however, its role in the other seasons was more difficult to define. The land cover/lightning index indicated that waterbodies and herbaceous wetlands had more influence than other land cover types, both during the day and at night, and it appeared that latent heat flux played a major role. The CG stroke hot and cold spot locations varied diurnally. The findings suggest that large-scale irrigation practices, especially during the pre-monsoon months, can influence the observed spatiotemporal pattern. The production of hotspot maps could be an initial step in the development of a reliable lightning monitoring system and play a part in increasing public awareness of this issue. Supplementary Information: The online version contains supplementary material available at 10.1007/s41748-022-00310-4.

The potential of Tidal River Management for flood alleviation in South Western Bangladesh.

Reduced sediment deposition, land subsidence, channel siltation, and salinity intrusion has been an unintended consequence of the construction of polders in the south western delta of Bangladesh in the 1960s. Tidal River Management (TRM) is a process that is intended to temporarily reverse these processes and restore sediment deposition and land elevation at the low-lying sites, known as 'beels', where TRM is carried out. However, there is limited evidence to prioritise sites for TRM on the basis of its potential effectiveness at alleviating flooding. In this study, the south western delta of Bangladesh was classified according to different flood susceptible zones. In south western Bangladesh, the major portion of agricultural and aquaculture land is located within flood susceptible zones (65% and 81%, respectively). 44.5% of the total population in embanked regions live in areas classified as being flood susceptible. This study identified 106 'beels' suitable for TRM. Modelling of potential sediment deposition predicted that the consequent increase in land elevation could be up to 1.4 m in five years, which would alleviate land subsidence and modify several geomorphological factors such as aspect, slope, curvature, and Stream Power Index (SPI). Implementation of TRM at these sites could potentially reduce the probability of annual flooding from 0.86 (on average) to 0.57 (on average). Therefore, TRM could lower the flood susceptible area by 35% in suitable 'beels'. Whilst during the implementation of TRM agriculture has to cease for a few years, a systematic programme of TRM could result in a long-term increase in agricultural production by reducing flood susceptibility of agricultural lands in delta regions.

Have coastal embankments reduced flooding in Bangladesh?

From the 1960s, embankments have been constructed in south western coastal region of Bangladesh to provide protection against flooding, but the success of the polder programme is disputed. We present analysis of floods during the years 1988-2012, diagnosing whether the floods were attributable to monsoonal precipitation (pluvial flooding), high upstream river discharge into the tidal delta (fluvio-tidal flooding), or cyclone-induced storm surges. We find that pluvial flooding was the most frequent, but typically resulted in less flooded area (11.44% of the region on average) compared with the other forms of flooding. The greatest area of inundation (48% of total area) occurring in 2001 as a consequence of fluvio-tidal and surge flooding, whilst cyclone Sidr in 2007 flooded 35% of the area. We modelled these different forms of inundation to estimate what flooding might have been had the polders not been constructed. For the 'no embankment' counter-factual scenario, our model demonstrated that because of a combination of subsidence and inadequate drainage, construction of the polders has increased the pluvial flooded area by 6.5% on average (334 km2). However, during the 1998 fluvio-tidal flood, the embankments protected an estimated 54% of the area from flooding. During the cyclone Sidr storm surge event, embankment failure in several polders and pluvial inundation resulted in 35% area inundation, otherwise, the total inundation would have been 18% area. We conclude that whilst polders have provided protection against storm surges and fluvio-tidal events of moderate severity, they have exacerbated more frequent pluvial flooding and promoted potential flooding impacts during the most extreme storm surges.