We examined the quantitative difference in the distribution of tsunami and storm deposits based on numerical simulations of inundation and sediment transport due to tsunami and storm events on the Sendai Plain, Japan. The calculated distance from the shoreline inundated by the 2011 Tohoku-oki tsunami was smaller than that inundated by storm surges from hypothetical typhoon events. Previous studies have assumed that deposits observed farther inland than the possible inundation limit of storm waves and storm surge were tsunami deposits. However, confirming only the extent of inundation is insufficient to distinguish tsunami and storm deposits, because the inundation limit of storm surges may be farther inland than that of tsunamis in the case of gently sloping coastal topography such as on the Sendai Plain. In other locations, where coastal topography is steep, the maximum inland inundation extent of storm surges may be only several hundred meters, so marine-sourced deposits that are distributed several km inland can be identified as tsunami deposits by default. Over both gentle and steep slopes, another difference between tsunami and storm deposits is the total volume deposited, as flow speed over land during a tsunami is faster than during a storm surge. Therefore, the total deposit volume could also be a useful proxy to differentiate tsunami and storm deposits.

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The world is encountering climate change and severe natural disasters. Floods have been one of the most disruptive disasters these decades. The 2011 flood in Thailand affected 13.6 million people and caused damage of USD 46.5 billion, while the 2013 flood in Jakarta, despite its short period, affected more than 45,000 people. This study intends to examine the changes of disaster information preference before and during each disaster. Questionnaire surveys were conducted in July 2013 in Thailand and Indonesia. The results found that the preferences for information increased once the disaster approached, except for preparedness plans and warnings in both cases and waste disposal in the Indonesian case. While most of the information preferences show no significant difference in mean between the two disasters, the results found significant differences in preferences for traffic/transportation infrastructure both before and during the arrival of disasters, availability of food and water, waste disposal before disaster impact, and overall damage information during the impact. The findings are crucial in terms of information gathering and dissemination to maintain the lives and livelihoods of human being during disasters. This study can contribute to both research and practice in terms of disaster information analysis and better preliminary examination of the preference for information needs from similar disasters with different scales and geographies.

@en

The world is encountering climate change and severe natural disasters. Floods have been one of the most disruptive disasters these decades. The 2011 flood in Thailand affected 13.6 million people and caused damage of USD 46.5 billion, while the 2013 flood in Jakarta, despite its short period, affected more than 45,000 people. This study intends to examine the changes of disaster information preference before and during each disaster. Questionnaire surveys were conducted in July 2013 in Thailand and Indonesia. The results found that the preferences for information increased once the disaster approached, except for preparedness plans and warnings in both cases and waste disposal in the Indonesian case. While most of the information preferences show no significant difference in mean between the two disasters, the results found significant differences in preferences for traffic/transportation infrastructure both before and during the arrival of disasters, availability of food and water, waste disposal before disaster impact, and overall damage information during the impact. The findings are crucial in terms of information gathering and dissemination to maintain the lives and livelihoods of human being during disasters. This study can contribute to both research and practice in terms of disaster information analysis and better preliminary examination of the preference for information needs from similar disasters with different scales and geographies.

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In November 2013, Super Typhoon Haiyan (Yolanda) hit the Philippines. It caused heavy loss of lives and extensive damages to buildings and infrastructure. When collapsed buildings are focused on, it is inter-esting to find that these buildings did not collapse for the same reasons after the landfall of the typhoon and storm surge. The objective of this study is to develop a statistical model for building damage due to Super Typhoon Haiyan and its storm surge. The data were collected in collaboration with Tanauan Municipality, the Philippines. The data for the inundation map were ob-tained by field surveys conducted on-site to determine the cause of the damages inferred from satellite data. The maximum wind speed was derived from the Hol-land parametric hurricane model based on the Japan Meteorological Agency (JMA) typhoon track data and the inundation depth of storm surge was calculated using the MIKE model. Multinomial logistic regression was used to develop a model to identify the significant factors influencing the damage to buildings. The result of this work is expected to be used to prepare urban plans for preventing damage from future storms.@en