Contents -- Preface -- Introduction -- 1. Drought Disaster in Asia -- 2. Global Landslides Risk Case Study -- 3. Storm Surges in Coastal Areas -- 4. Natural Disaster Risks in Sri Lanka: Mapping Hazards and Risk Hotspots -- 5. Multihazard Risks in Caracas, República Bolivariana de Venezuela -- 6. Reducing the Impacts of Floods through Early Warning and Preparedness: A Pilot Study for Kenya -- Tables -- Table 2.1 Description of variables -- Table 2.2. Classification of slope factor "Sr" for evaluation of susceptibility -- Table 2.3. Classification of lithology factor "Sl" for evaluation of susceptibility -- Table 2.4. Classification of soil moisture factor "Sh" for evaluation of susceptibility -- Table 2.5. Classification of precipitation trigger indicator "Tp" -- Table 2.6. Classification of seismicity trigger indicator "Ts" -- Table 2.7. Classification of landslide hazard potential based on the computed hazard index originally suggested by Mora and Vahrson (1994) -- Table 2.8. Classification of landslide hazard potential based on the computed hazard index used in this study -- Table 2.9. Classification of slope factor "Sr" for snow avalanche susceptibility -- Table 2.10. Classification of precipitation factor "Tp" for avalanche hazard evaluation -- Table 2.11. Classification of temperature factor "Tt" for avalanche hazard analysis -- Table 2.12. Classification of snow avalanche hazard potential -- Table 2.13. Annual frequency of occurrence and typical return period (in years) for different classes of landslide and avalanche hazard -- Table 2.A.1. Classes of frequencies -- Table 2.A.2. Vulnerability indicators -- Table 2.A.3. Exponent and p-value for landslide multiple regression -- Table 2.A.4. Other exponents and p-values for landslide multiple regression.

Table 3.1. Hurricane characteristics and indicative surge magnitudes based on the Saffir-Simpson scale -- Table 3.2. Some major coastal cities and human-induced subsidence during the 20th century -- Table 3.3. Generic approaches to hazard reduction based on purposeful adjustment. -- Table 3.4. Regional contributions to coastal flooding in 1990 and the 2020s based on the analysis of Nicholls (2004). -- Table 3.5. The range of scenarios used by Nicholls (2004) -- Table 3.6. Estimates of the global exposure and incidence of flooding under the four SRES scenarios in the 2080s, plus 1990 estimates as a reference -- Table 3.7. Global-mean sea-level rise scenarios (cm) used by Nicholls (2004) (referenced to 1990), including the IS92a GGa1 scenario as a reference -- Table 3.8. The SRES Socioeconomic Scenarios for the 2080s: A Global Summary -- Table 3.9. Deaths associated with major hurricanes, cyclones, and typhoons (MC) and extra-tropical storm (ETS) disasters (>1,000 deaths) since 1700. -- Table 3.10. Deaths in storm surges around the North Sea from the 11th to the 18th centuries. All surges were due to extra-tropical storms -- Table 3.11. An expert synthesis of storm surge hotspots around the world. -- Table 3.12. Potential and actual hotspots vulnerable to flooding by the storm surge. -- Table 5.1. Critical Facilities and Systems (Categories and Definitions) -- Table 5.2. Studio estimates for the order of magnitude of losses for a generic city whose assets are valued at US 100 billion. -- Table 6.1. Flood scenarios for a worst case and a moderate case -- Table 6.2. Characteristics of the different livelihood zones analyzed -- Table 6.3. Percentage of livestock contribution to cash income and food consumption of the livelihood zones analyzed -- Figures -- Figure 1.1. Total Annual Precipitation, in millimeters.

Figure 1.2. Total number of drought disasters for all Asian countries with geo-referenced boundaries available -- Figure 1.3. Number of drought disasters with month specified, for all countries listed in the Asia category in EM-DAT -- Figure 1.4. Number of drought disasters for Asia and the maritime continent, summed by year and over all countries in the region -- Figure 1.5. Number of drought disasters with months specified for Asia and the maritime continent -- Figure 1.6. Number of drought disasters for non-Asia countries in the EM-DAT database -- Figure 1.7. Precipitation anomalies for the 1999-2001 period, divided by yearly standard deviation to facilitate comparison over diverse climate regimes -- Figure 1.8. Reported drought disasters, 1999-2001 -- Figure 1.9. Match between drought disaster and climatic measure of drought (3 consecutive months with precipitation deficits meeting a set threshold). -- Figure 1.10. Match between drought disaster and climatic measure of drought (4 out of 6 months with precipitation deficits meeting a set threshold). -- Figure 1.11. Match between drought disaster and climatic measure of drought (12-month average of Weighted Anomaly of Standardized Precipitation (WASP). -- Figure 1.12. Number of matches for 12-month WASP compared to the total number of drought disaster reports (with monthly data). -- Figure 1.13. Correlation between the 12-month WASP calculated from two different precipitation data sets: the University of East Anglia (UEA) precipitation data and the CPC's Merged Analysis of Precipitation (CMAP). -- Figure 1.14. Time series of drought disasters and climatic drought events (based on 12-month WASP) -- Figure 1.15. Climate anomalies (12-month WASP) for two periods: 1982-1983 (red) and 1999-2000 (blue).

Figure 1.16. WASP estimate of climatic drought (shaded brown curve) and drought disaster declarations (red bars) for Central -- Figure 1.17. WASP estimate of climatic drought (shaded brown curve) and drought disaster declarations (red bars) for Laos and India. -- Figure 1.A.1. Persistent deficit of precipitation -- Figure 2.1. General approach for landslide hazard and risk evaluation -- Figure 2.2. Global soil moisture index: 1961-1990 -- Figure 2.3. Expected monthly extreme values for a 100-years event. -- Figure 2.4. Expected PGA with a return period of 475 years -- Figure 2.5. Variation of slope factor, Sr, in Tajikistan and its neighboring regions -- Figure 2.6. Variation of lithology factor, Sl, in Tajikistan and its neighboring regions -- Figure 2.7. Variation of seismic trigger indicator, Ts, in Tajikistan and its neighboring regions -- Figure 2.8. Variation of soil moisture factor, Sh, in Tajikistan and its neighboring regions -- Figure 2.9. Landslide hazard zonation map obtained for Tajikistan and its neighboring regions -- Figure 2.10. Example landslide hazard map for Central American and Caribbean countries -- Figure 2.11. Example landslide risk map for parts of Central and South America -- Figure 2.12. Historical rock avalanche events in Møre & Romsdal and Sogn & Fjordane Counties extracted from Norway's historical database (NGU/Astor Furseth) -- Figure 2.13. Regional hazard zonation in Møre & Romsdal County in western Norway. -- Figure 2.14. Landslide hazard map (landslide and rock fall hazards) for the western part of Norway based on the simplified model -- Figure 2.15. Snow avalanche hazard zones for Norway based on the avalanche hazard model -- Figure 2.16. Map of Armenia -- Figure 2.17. Comparison of global landslide hazard mapping in Armenia using NGI model with the GEORISK landslide inventory.

Figure 2.18. Major landslide events in Nepal during a 30-year time period (1971-2000) -- Figure 2.19. Landslide hazard in Nepal predicted by the NGI model in this study -- Figure 2.20. Population density map of Nepal in 1995. -- Figure 2.21. Landslide hazard in Georgia predicted by the model developed in this study -- Figure 2.22. Snow avalanche hazard in Georgia predicted by the model developed in this study -- Figure 2.23. Observed landslides in Sri Lanka between 1947 and 2003 and prediction of landslide hazard in Sri Lanka by the model developed in this study. -- Figure 2.24. Historical landslide data in Jamaica -- Figure 2.25. Prediction of landslide hazard in Jamaica with the model developed in this study -- Figure 2.26. Global hotspot landslide hazard zonation for the world -- Figure 2.27. Global hotspot landslide hazard zonation for Central Asia and the Middle East -- Figure 2.28. Global hotspot landslide hazard zonation for Central American and Caribbean countries -- Figure 2.29. Hotspot landslide risk zonation for Central America and Jamaica -- Figure 2.30. Hotspot landslide risk zonation for Central Asia -- Figure 2.31. Global hotspot snow avalanche hazard zonation for Central Asia -- Figure 2.A.1. Distribution of risk utilizing a vulnerability proxy in Central America -- Figure 2.A.2. Distribution of risk using a vulnerability proxy in South America -- Figure 2.A.3. Distribution of risk utilizing a vulnerability proxy in Central Asia -- Figure 2.A.4. Transformation for variables ranging between 0 and 1 -- Figure 2.A.5. Predicted killed versus observed for landslide -- Figure 3.1. Areas in the southwest Netherlands flooded by the 1953 storm surge, February 1, 1953 (from Edwards 1953) -- Figure 3.2. A simplified reconstruction of the November 1970 storm surge in Bangladesh.

Figure 3.3. Areas in Tokyo that are below normal high-water and surge levels with and without a 1-m rise in sea level.