Assessment of Social Vulnerability to Floods in the Floodplain of Northern Italy

Practices for reducing the impacts of floods are becoming more and more advanced, centered on communities and reaching out to vulnerable populations. Vulnerable individuals are characterized by social and economic attributes and by societal dynamics rooted in each community. These indicators can magnify the negative impacts of disasters together with the capacity of each individual to cope with these events. The Social Vulnerability Index (SoVI) provides an empirical basis to compare social differences in various spatial scenarios and for specific environmental hazards. This research shows the application of the SoVI to the floodplain of northern Italy, based on the use of 15 census variables. The chosen study area is of particular interest for the high occurrence of flood events coupled with a high level of human activity, landscape transformations, and an elevated concentration of assets and people. The analysis identified a positive spatial autocorrelation across the floodplain that translates into the spatial detection of vulnerable groups, those that are likely to suffer the most from floods. In a second stage, the output of the index was superimposed on the flood hazard map of the study area to analyze the resulting risk. The Piemonte and Veneto regions contain the main areas prone to flood \u201csocial\u201d risk, highlighting the need for a cohesive management approach at all levels to recognize local capacities and increase communication, awareness, and preparedness to mitigate the undesirable effects of such events

A flood vulnerability index for coastal cities and its use in assessing climate change impacts

Worldwide, there is a need to enhance our understanding of vulnerability and to develop methodologies and tools to assess vulnerability. One of the most important goals of assessing coastal flood vulnerability, in particular, is to create a readily understandable link between the theoretical concepts of flood vulnerability and the day-to-day decision-making process and to encapsulate this link in an easily accessible tool. This article focuses on developing a Coastal City Flood Vulnerability Index (CCFVI) based on exposure, susceptibility and resilience to coastal flooding. It is applied to nine cities around the world, each with different kinds of exposure. With the aid of this index, it is demonstrated which cities are most vulnerable to coastal flooding with regard to the system's components, that is, hydro-geological, socio-economic and politico-administrative. The index gives a number from 0 to 1, indicating comparatively low or high coastal flood vulnerability, which shows which cities are most in need of further, more detailed investigation for decision-makers. Once its use to compare the vulnerability of a range of cities under current conditions has been demonstrated, it is used to study the impact of climate change on the vulnerability of these cities over a longer timescale. The results show that CCFVI provides a means of obtaining a broad overview of flood vulnerability and the effect of possible adaptation options. This, in turn, will allow for the direction of resources to more in-depth investigation of the most promising strategies

Flash Flood Early Warning Research in China

Along with global climate change, extreme rainfall causes severe flash flood disasters, especially in mountainous areas. As about 67% of the terrestrial part of the whole country is mountain area with frequent heavy rainfall, China suffers from flash flood disasters throughout its history. As flash floods are distributed extensively and its influence sphere highly concentrated, it is unreasonable and uneconomical to prevent flash flood disasters mainly via engineering measures. Then, China starts exploring about flash flood early warning, which is optimal for developing country with dense populations, since the 1990s. Based on the literature research, a systematic framework for Chinese flash flood early warning research has been developed. In this frame, flash flood early warning is classified into long-term warning and real-time warning. This chapter presents the Chinese achievements in analysis methods for long-term warning, computational methods for real-time warning indicators, improving data sources used for real-time warnings and the information construction of real-time warning systems. In addition, the suggestions for future study are presented

Remote sensing and optimized neural networks for landslide risk assessment: Paving the way for mitigating Afghanistan landslide damage

Landslides caused by mega earthquakes and other extreme climate change pose a major threat to lives and infrastructure. However, the lack of a detailed and timely landslide inventory and relevant risk assessment attributable to ongoing conflicts limits the effective prevention measures in Afghanistan. This study presents the first landslide inventory covering the whole nation of Afghanistan from 2015 to the present utilizing Google Earth Pro imagery and manual interpretation. Based on this inventory of 3,260 mapped landslides, we analyzed the distributional characteristics of landslides in Afghanistan and conducted a risk assessment that included landslide susceptibility and hazard, and vulnerability of the bearing areas. The existing regional studies attest to the accuracy and reliability of the inventory, and the results of the risk assessment using the optimized neural network method in this study are well validated. This study can provide a good database for the Afghan government to carry out relevant pre-disaster warnings and post-disaster reconstruction, which can help to delineate hotspots where landslides may occur, and reduce potential economic losses and human casualties from future landslides

The danger of mapping risk from multiple natural hazards

In recent decades, society has been greatly affected by natural disasters (e.g. floods, droughts, earthquakes), losses and effects caused by these disasters have been increasing. Conventionally, risk assessment focuses on individual hazards, but the importance of addressing multiple hazards is now recognised. Two approaches exist to assess risk from multiple-hazards; the risk index (addressing hazards, and the exposure and vulnerability of people or property at risk) and the mathematical statistics method (which integrates observations of past losses attributed to each hazard type). These approaches have not previously been compared. Our application of both to China clearly illustrates their inconsistency. For example, from 31 Chinese provinces assessed for multi-hazard risk, Gansu and Sichuan provinces are at low risk of life loss with the risk index approach, but high risk using the mathematical statistics approach. Similarly, Tibet is identified as being at almost the highest risk of economic loss using the risk index, but lowest risk under the mathematical statistics approach. Such inconsistency should be recognised if risk is to be managed effectively, whilst the practice of multi-hazard risk assessment needs to incorporate the relative advantages of both approaches

Disaster Risks Research and Assessment to Promote Risk Reduction and Management

Natural hazard events lead to disasters when the events interact with exposed and vulnerable physical and social systems. Despite significant progress in scientific understanding of physical phenomena leading to natural hazards as well as of vulnerability and exposure, disaster losses due to natural events do not show a tendency to decrease. This tendency is associated with many factors including increase in populations and assets at risk as well as in frequency and/or magnitude of natural events, especially those related to hydro-meteorological and climatic hazards. But essentially disaster losses increase because some of the elements of the multidimensional dynamic disaster risk system are not accounted for risk assessments. A comprehensive integrated system analysis and periodic assessment of disaster risks at any scale, from local to global, based on knowledge and data/information accumulated so far, are essential scientific tools that can assist in recognition and reduction of disaster risks. This paper reviews and synthesizes the knowledge of natural hazards, vulnerabilities, and disaster risks and aims to highlight potential contributions of science to disaster risk reduction (DRR) in order to provide policy-makers with the knowledge necessary to assist disaster risk mitigation and disaster risk management (DRM)

The analysis of the spatial patterns and controls governing the global occurrence of fatal landslides

In the research presented here, a global inventory of fatal landslides has been generated allowing the investigation of the spatial distribution and temporal occurrence of mass movement events. There are important regional differences within these data with Asian fatalities being characterised by high frequency, low magnitude landslide events. In comparison, high magnitude events were found to be responsible for the high fatality totals in the Americas. This research has demonstrated that the spatial distribution of fatal landslides is best explained by a combination of physical and social factors and has yielded some interesting results.87% of the fatal landslide events recorded within the database were triggered by high intensity of prolonged rainfall events associated with tropical cyclones or monsoon rainfall that are compounded in areas of high relief associated with tectonically active mountain belts. Increasing landslide impacts are often associated with less developed countries, where there is rising population density, rural to urban migration, growth of megacities, and severe land degradation. However, the results indicate that the occurrence of landslide fatalities are not simply a function of level of development of a country or population density but that fatalities predominantly occur within middle income countries and rural areas which are increasingly vulnerable to landslide disasters. This can be attributed to changes in physical systems, most notably climate variation

Climate Change and the Future Impacts of Storm-Surge Disasters in Developing Countries

As the climate changes during the 21st century, larger cyclonic storm surges and growing populations may collide in disasters of unprecedented size. As conditions worsen, variations in coastal morphology will magnify the effects in some areas, while largely insulating others. In this paper, we explore the implications for 84 developing countries and 577 of their cyclone-vulnerable coastal cities with populations greater than 100,000. Combining the most recent scientific and demographic information, we estimate the future impact of climate change on storm surges that will strike coastal populations, economies and ecosystems. We focus on the distribution of heightened impacts, because we believe that greater knowledge of their probable variation will be useful for local and national planners, as well as international donors. Our results suggest gross inequality in the heightened impact of future disasters, with the most severe effects limited to a small number of countries and a small cluster of large cities.climate change; developing countries; disasters; coastal cities; storm surges; coastal populations; economic activity