2005年-世界发展银行全球_Natural_Disaster_Hotspots__A_Global_Risk_Analysis_148页_29mb

Natural Disaster Hotspots: A Global Risk Analysis Summary

Core Content

This document, Natural Disaster Hotspots: A Global Risk Analysis, presents a comprehensive assessment of natural disaster risks across the globe, focusing on identifying areas most vulnerable to multiple hazards. It is part of a series on disaster risk management and was published by the World Bank in 2005. The analysis uses a combination of hazard exposure data and vulnerability indicators to classify regions as "disaster risk hotspots."

Main Points

• Objective: To provide a global perspective on disaster risk, emphasizing the overlap of multiple hazards and their impact on populations and economies.
• Scope: The analysis covers six major natural hazards: earthquakes, volcanoes, landslides, floods, drought, and cyclones.
• Methodology: The project combines hazard exposure with historical vulnerability data to calculate risk levels at the subnational level using gridded population and GDP per unit area as indicators.
• Key Findings:
  • Approximately 25 million square kilometers (about 19% of the Earth's land area) and 3.4 billion people are relatively highly exposed to at least one natural hazard.
  • Some 3.8 million square kilometers and 790 million people are highly exposed to at least two hazards.
  • About 0.5 million square kilometers and 105 million people are exposed to three or more hazards.
  • Many of these high-risk areas are densely populated and developed, increasing the potential for casualties and economic losses.
  • There are significant interactions between different hazards, such as landslides triggered by cyclones and flooding, or earthquakes damaging infrastructure critical for flood and drought protection.

Project Approach

• The project uses a risk assessment framework to evaluate both mortality risk and economic loss risk.
• Data Sources include historical disaster records from the EM-DAT database and various global datasets such as GDP and population data.
• Global Hotspots Classification is based on ranking grid cells into deciles according to their exposure and vulnerability levels.
• The analysis distinguishes between single-hazard exposure and multihazard exposure, using a simple multihazard index and population-weighted multihazard index to highlight areas with the highest combined risk.

Multihazard Risk Assessment

• Vulnerability Coefficients are derived from historical loss data and are used to assess the potential impact of hazards.
• Single-hazard risk assessment results are summarized in the document, showing the distribution of risk for each hazard type.
• Multihazard risk assessment results reveal the combined risk from multiple hazards, with areas in East and South Asia and Central America showing the highest risk.
• The multihazard risk map is constructed by weighting each hazard index by incidence frequency data and by relief expenditure data.

Case Studies

• The document includes case studies that explore specific hazards and localized areas in greater detail.
• These case studies use the same theoretical framework as the global analysis and provide real-world insights into disaster risk management.
• Some case studies focus on storm surge hotspots, flood-prone regions, and landslide-prone areas, offering practical examples of how the global findings apply at a local level.
• The case studies also highlight the importance of integrating risk assessments into development planning to minimize disaster impacts.

Key Information

• Data Limitations: The global analysis is constrained by the scale of data and its quality, with some hazards having only 15- to 25-year records.
• Policy Implications: The report emphasizes the need to mainstream disaster risk management into development activities, as natural disaster risks are increasingly recognized as a development issue.
• Support and Collaboration: The project was developed in collaboration with several international organizations, including the United Nations, Columbia University, and the Norwegian Geotechnical Institute.
• Funding and Support: The project received support from the UK Department for International Development (DFID) and the Norwegian Ministry of Foreign Affairs, as well as complementary funding from the Earth Institute and Lamont-Doherty Earth Observatory.

Conclusion and Way Forward

• The report concludes that disaster risk management is essential for development and that information development is critical for effective risk reduction.
• It encourages development agencies and policymakers to use the findings to plan ahead for disasters and minimize their impacts.
• The project highlights the importance of affordable technologies and risk-based strategies in reducing the devastating effects of natural disasters, especially in low-income countries.
• Future work includes a more detailed analysis of tsunami-related risks, which were not included in this initial study due to data limitations.

Key Tables and Figures

• Table 1.1: Lists countries most exposed to multiple hazards, showing the percentage of land and population exposed, and the maximum number of hazards in each country.
• Table 1.2: Highlights countries at relatively high mortality risk from multiple hazards.
• Table 3.1: Ranks major natural hazards by the number of deaths reported in EM-DAT.
• Table 8.1: Summarizes the case studies and their contributors.
• Table 8.2: Provides an expert synthesis of storm surge hotspots globally.
• Table 8.3: Maps potential and actual hotspots vulnerable to flooding by storm surge.
• Figure 1.1: Shows the global distribution of areas highly exposed to one or more hazards, by hazard type.
• Figure 1.2: Displays the types of hazards associated with the top three deciles of the global risk distribution for mortality and economic losses.
• Figure 5.1: Illustrates the global distribution of areas significantly exposed to one or more hazards, by the number of hazards.
• Figure 7.1: Represents the global distribution of disaster risk hotspots for all hazards.
• Figure 8.7: A multihazard risk map constructed by weighting each hazard index by incidence frequency data.
• Figure 8.8: A multihazard risk map based on relief expenditure data.

Authors and Contributors

• Maxx Dilley, Robert S. Chen, Uwe Deichmann, Arthur L. Lerner-Lam, and Margaret Arnold are the primary authors.
• Jonathan Agwe, Piet Buys, Oddvar Kjekstad, Bradfield Lyon, and Gregory Yetman are also contributors.
• The project was supported by the World Bank, Columbia University, and several other international institutions.