Risk Management for Tsunami-Related Disasters
|Dedication||1 – 2 hours per week|
Certificate $ 50
|Institution||World Federation of Engineers Organizations
Peruvian Engineers Association
December 26th 2004 at 00:58:53 UTC, the world was overwhelmed to see in near-real time the shocking images of the big Indian Ocean earthquake and tsunami effects. It took more than 270,000 lives and caused loss of property and infrastructure along large coastal zones of Indonesia, India, Sri Lanka and Thailand. This quite unexpected event reminded us that nature could give bad surprises if we are not aware of the actual level of risk, wherever we are. About 30 events with total death toll of 150,000 had already occurred during the 20th century.
Tsunamis are defined as a series of large waves of extremely long wavelength and period usually generated by a violent, impulsive undersea disturbance or activity near the coast or in the ocean. They are usually associated with earthquake faulting of the sea floor, but may also be related to submarine landslides and volcanic activity.
Although the great progress achieved, and that tsunami early warning systems exist now for the most hazardous areas of the world, we are far from being fully prepared and resilient. Besides the 2004 Indian Ocean event, since the dawn of this 21st century, several other tsunamis have devastate coastal regions showing that there is still large room for improvement on tsunami-related disaster risk management.
In that context, the Committee on Disaster Risk Management of the World Federation of Engineering Organizations (CDRM-WFEO) seeks to contribute in the reduction of potential losses of life and property in tsunami prone areas through this first course aimed to strength capacities in DRM.
To recognize the elements conferring a given tsunami hazard level to a study area or population, considering the regional framework of risk.
Learn the modern techniques for quick assessment of damage in affected areas useful for timely response and first aid.
To understand the basis of artificial intelligence using big data to support decisions during the phases of early warning and response.
This course is intended for chief and operating officers of management/preparedness agencies, government authorities, engineers, and urban planners. Advanced students and professionals with fundamental skills in physics and natural sciences are also welcome.
Certification as participant will be delivered to those having visited the platform and attended the lectures. Meanwhile, the mention of “has approved the course” will be given to those who fulfill the exercises and take the final exam.
The course is cost-free. Only the certification needs the payment of US$ 50.=
Additional information through the platform or write to:
Dr José Macharé Ordoñez (WFEO-CDRM member)
How can I ask questions or request clarifications?
You can ask your questions via the forums and messaging tool, as well as by emailing your course tutor
Who can I contact if I have technical difficulties?
For technical assistance, our support team is ready and available to help you 24 hours a day, 7 days a week. You can contact us at INDES-HELP; please be ready to explain in detail the problem you’re encountering.
What background knowledge is necessary?
Do I need to take the courses in a specific order?
- Lectures 6
- Quizzes 0
- Duration 6 semanas
- Language English (Subtitulado en español)
- Students 101
- Assessments Yes
Unit 1 - Lessons from the past tsunami events and future perspectives
- We revisit the lessons of the past catastrophic tsunami events, e.g. the 2011 Japan and 2004 Indian Ocean, specifically on the response and impact, and discuss the paradigm shift of tsunami disaster management policies and the perspectives for future tsunami disaster mitigation. Revisiting the modern histories of Tohoku tsunami disasters and pre-2011 tsunami countermeasures, we clarify how Japan’s coastal communities have prepared for tsunami. The discussion mainly focuses on structural measures such as seawalls and breakwaters and non-structural measures of hazard map and evacuation. The responses to the 2011 event are discussed specifically on the tsunami warning system and efforts to identify the tsunami impacts. The post tsunami survey results shed the light on the mechanisms of structural destruction, tsunami loads, and structural vulnerability to inform structural rehabilitation measures and land use planning.
Unit 2 - Tsunamis: modeling technology and its application for tsunami warning
- This lecture gives an overview of tsunami modeling and its application on monitoring and warning systems which are arranged to five sections: 1) Tsunami generation mechanism, 2) Numerical approach, 3) Tsunami monitoring system, 4) Tsunami warning system and 5) Lessons from recent tsunamis. Audiences of this lecture will understand limitation of the current tsunami modeling and warning system and be able to understand or convey proper tsunami warning message as well as perform safer evacuation related actions.
Unit 3 - Tsunami Effects on Infrastructure
- Extreme coastal floods such as the 2004 Indian Ocean Tsunami, the 2010 Chile Tsunami or the 2011 Tohoku Tsunami, as well as by the 2005 Katrina and 2012 Sandy hurricanes have shown that, hydrodynamic and debris loading are major contributors to the extreme damage experienced by coastal infrastructure. The course will provide an overview of the effects of tsunamis on coastal infrastructure and of the world’s first design standard for tsunami resistant structures. The new ASCE-7 Tsunami Loads and Effects Committee (of which Prof. Nistor is a Voting Member) has recognized the significant importance of tsunami-induced hydrodynamic and debris loading and proposed a comprehensive document (ASCE7 Chapter 6) for the design of critical infrastructure.
Unit 4 - Artificial Intelligence and Remote sensing technology for tsunami damage
- The focus of this lecture is on the application of artificial intelligence and Earth observation technologies for extracting tsunami-induced damage in urban areas. We will learn how the advance of machine learning framework together with multisource remote sensing imagery enables rapid and accurate damage recognition soon after tsunami disasters. Here, some of the state-of-the-art algorithms used for damage mapping will be explored. Finally, we will see examples of applications in previous disaster events such as the 2018 Sulawesi Tsunami in Indonesia.
Unit 5 - Modeling tsunami evacuations
- This course lecture presents the methodologies for assessing tsunami evacuation trough simulation and modeling. The discussion focuses on the use of agent based modeling (ABM) as a tool to assess the evacuation behavior and contribute to tsunami risk reduction. The lecture presents several cases of tsunami evacuation studies and applications to evacuation planning. In addition, an open-source agent based platform is presented and the steps to develop, modify and use it for evacuation simulation are briefly discussed. The lecture aims on giving a short introduction to the use of ABM in disaster research, and in particular, tsunami evacuation research.