Modelling residential habitability and human displacement for tsunami scenarios in Christchurch, New Zealand

International Journal of Disaster Risk Reduction (2019)

Finn Scheele Thomas Wilson Emily M. Lane Kate Crowley Matthew W. Hughes Tim Davies Nick Horspool James H. Williams Lina Le S.R. Uma Biljana Luković Marion R. Schoenfeld James Westfall Thompson

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Abstract:

Understanding the potential impacts of a large tsunami on a coastal region enables better planning of disaster management strategies. Potential housing damage, habitability, human displacement and sheltering needs are key concerns for emergency managers following tsunami events. This article presents a novel approach to address these requirements. We first review available literature on factors influencing residential habitability, human displacement and sheltering needs following disasters. Existing models are reviewed to identify lessons, gaps and opportunities that can inform the development of a new model. We then present a new model for estimating habitability, displacement and sheltering needs for tsunami (HDS-T). The model uses an additive scoring system incorporating both physical and demographic factors, weighted according to their relative influence. We demonstrate application of HDS-T through the case study of three tsunami scenarios affecting the coastal city of Christchurch, New Zealand. The results are time-varying, reflecting the response and early recovery phase of the tsunami events. For the largest scenario, 14,695 residents are displaced on the first day, with 1795 displaced residents requiring sheltering assistance. The number of displaced residents reduces to 9014 on Day 4, 7131 on Day 7, and 4366 at the time point of one month. HDS-T is designed to be adaptable to other natural hazards and contexts, such as earthquakes.

Keywords:

Habitability

Natural hazard

Topics:

Disaster Management and Resilience

Climate Change, Adaptation, Migration

Flood Risk Assessment and Management

10.1016/j.ijdrr.2019.101403

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The effect of natural disasters on FDI attraction: a sector-based analysis over time and space

Natural Hazards (2021)

Thomas Neise Franziska Sohns Moritz Breul Javier Revilla Diez

Abstract Extensive research has addressed the question of why some countries are able to attract a large amount of foreign direct investment (FDI), while others are not. Until now, this research mostly neglected natural disasters as a business risk. In the realm of natural disaster research, some studies have investigated the effect of natural disasters on FDI inflow. However, this research remains overly simplistic and conceals the complexities of the underlying relationship. As such, this article aims to provide a more deciphered perspective by considering variations across economic sectors and the dynamic effect of natural disasters. We apply hybrid panel regressions to a dataset of 181 countries over a period of 13 years across four different economic sectors. The analysis shows that the effect of natural disasters on FDI inflow varies among economic sectors. From a longitudinal perspective, the study finds a positive relationship between exposure to natural disasters and the inflow of FDI within countries 3 and 5 years after an event. Overall, the findings highlight the complex nature of the relationship between natural disasters and FDI and warn against using too simplistic approaches.

Natural hazard

Inflow

Realm

10.1007/s11069-021-04976-3

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Does natural disaster influence people's risk preference and trust? An experiment from cyclone prone coast of Bangladesh

International Journal of Disaster Risk Science (2014)

Dewan Ahsan

Natural hazard

Storm Surge

Risk Perception