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disaster risk management

Rebuilding communities after disasters – four and a half lessons learned

Abhas Jha's picture

Rebuilding after Cyclone Idai. (Photo: Denis Onyodi / IFRC/DRK/Climate Centre via Flickr CC)

The death toll from Cyclone Idai that ripped into Mozambique, Zimbabwe, and Malawi in March 2019 is now above 1,000, with damages estimated at $2 billion. In 2018, more than 10,000 people lost their lives in disasters (with $225 billion of economic losses). Approximately 79 percent of fatalities occurred in the Asia Pacific region, including the catastrophic earthquake and tsunami in Indonesia’s Sulawesi Island. In fact, 2017 and 2018 have been estimated as the most expensive back-to-back years for weather disasters, totaling $653 billion of losses.

Cyclone Idai: Building climate and disaster resilience in Mozambique and beyond

Ede Ijjasz-Vasquez's picture
Mozambique after Cyclone Idai. Photo by Denis Onyodi / IFRC / DRK / Climate Centre via Flickr CC

Cyclone Idai is one of the most devastating storms to ever hit Africa, causing catastrophic damage in Mozambique, Malawi, and Zimbabwe.
 
Starting off in early March 2019 as a tropical depression, the storm rapidly evolved into a cyclone, affecting over 2 million people and killing close to 1,000 in the three countries affected. The port city of Beira, Mozambique – the hardest hit – is struggling to reemerge from the rubble.

#BuildBetterBefore to save lives and strengthen economies

Ede Ijjasz-Vasquez's picture
 

For those of us who have family and friends living in earthquake and hurricane prone areas, the 1.3 million people that have died in disasters in the last 25 years are more than a staggering statistic. It’s personal.

In this video, Luis Triveno (@luis_triveno), Urban Specialist, sits down with Ede Ijjasz-Vasquez (@Ede_WBG), Senior Director, to discuss what the World Bank is doing to make homes safer – before it’s too late.

Changing impact of weather and climate services in response to changing climate

Anna-Maria Bogdanova's picture
Image credit: Elena11 / Shutterstock
Have you ever wondered what your national meteorological agency actually does? I suppose it wouldn’t be inaccurate to say that they can help you decide how to dress, whether or not to carry an umbrella, or water the garden. But their purpose is so much bigger than that.

National meteorological and hydrological services (NMHSs) are responsible for helping people understand, predict and warn of weather- and water-related hazards such as storms, floods, and hurricanes.

The road to recovery: Rebuilding the transport sector after a disaster

Melody Benavidez's picture
Transport and disaster recovery

In the Paradise, California fires of November 2018, a range of factors coalesced leaving 86 people dead and over 13,900 homes destroyed. Fueling the fires were gale-force winds that when combined with the area’s institutional and infrastructural challenges led to one of the deadliest fires in California history.

When Paradise was developed, the road network was built to maximize buildable space for homes. However, as the Paradise fires demonstrated, in the event of a large-scale disaster, the road network inhibited community-wide evacuation. Paradise featured nearly 100 miles of private roads that dead-ended on narrow overlooks with few connector streets. As wind rapidly accelerated the fire throughout the community, residents trying to flee found themselves on roads paralyzed by traffic for hours on end. Evacuation routes turned into fire traps. Local officials went on to say that the miracle of the tragedy was how many people escaped.

The Paradise example demonstrates the importance of transport networks for allowing swift evacuation during the response phase, and also hints at how important effective recovery of the transport network will be in Paradise, California. In the aftermath of any significant disaster event, it is the roads, railways and ports that underpin the restoration of economic activity and the reconstruction of critical infrastructure after a disaster. In the aftermath of devastating floods, earthquakes, landslides, or typhoons, roads may be rendered unusable, making it more expensive to transport goods and services as well as preventing people from earning income. As such, having multiple ways to get from point A to point B, by modality and by route, is critical to continued connectivity. The recovery phase can be the impetus to reexamine vulnerable links in the transport network and address those deficiencies to help reduce future risks and strengthen the economic and physical resilience of people and infrastructure assets.

Demystifying machine learning for disaster risk management

Giuseppe Molinario's picture

To some, artificial intelligence is a mysterious term that sparks thoughts of robots and supercomputers. But the truth is machine learning algorithms and their applications, while potentially mathematically complex, are relatively simple to understand. Disaster risk management (DRM) and resilience professionals are, in fact, increasingly using machine learning algorithms to collect better data about risk and vulnerability, make more informed decisions, and, ultimately, save lives.

Artificial intelligence (AI) and machine learning (ML) are used synonymously, but there are broader implications to artificial intelligence than to machine learning. Artificial (General) Intelligence evokes images of Terminator-like dystopian futures, but in reality, what we have now and will have for a long time is simply computers learning from data in autonomous or semi-autonomous ways, in a process known as machine learning.

The Global Facility for Disaster Reduction and Recovery (GFDRR)’s Machine Learning for Disaster Risk Management Guidance Note clarifies and demystifies the confusion around concepts of machine learning and artificial intelligence. Some specific case-studies showing the applications of ML for DRM are illustrated and emphasized. The Guidance Note is useful across the board to a variety of stakeholders, ranging from disaster risk management practitioners in the field to risk data specialists to anyone else curious about this field of computer science.

Machine learning in the field

In one case study, drone and street-level imagery were fed to machine learning algorithms to automatically detect “soft-story” buildings or those most likely to collapse in an earthquake. The project was developed by the World Bank’s Geospatial Operations Support Team (GOST) in Guatemala City, and is just one of many applications where large amounts of data, processed with machine learning, can have very tangible and consequential impacts on saving lives and property in disasters.

The map above illustrates the “Rapid Housing Quality Assessment”, in which the agreement between ML-identified soft-story buildings, and those identified by experts is shown (Sarah Antos/GOST).

What if we could use nature to prevent disasters?

Brenden Jongman's picture
 

Heavy rain and severe flooding brought the city of Colombo, Sri Lanka, to its knees. In China’s Yangtze River Basin, rivers spilled their banks, inundating towns and villages. In Mobile Bay, Alabama, strong ocean waves carried away valuable coastline.

In each of these locations, disasters caused by natural hazards seemed beyond human control. But instead of focusing only on building more drains, seawalls and dams, these governments turned to nature for protection from the disasters. Several years later, the urban wetlands, oyster reefs and flood plains they helped establish are now keeping their citizens safe while nourishing the local economies.

Securing sustainable livelihoods for waste pickers

Amal Faltas's picture

Today on Global Waste Picker Day, we explore the problem of solid waste management in the Gaza Strip and how it is compounded by poverty, unemployment, and severe restrictions imposed on residents
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With a high unemployment rate in Gaza (53.7 percent), and every second person in Gaza living below the poverty line, residents of the Gaza Strip also face greater technical, environmental, social, institutional and financial challenges, due in large part to restricted access to goods and services. Frequent border closures cause considerable delays for the entry and servicing of waste management equipment and these delays contribute to a fragmented and poorly managed waste collection and disposal system - exacerbating public health and environmental concerns.

How are we approaching the intersection of fragility, conflict and violence, and disaster risk?

Ede Ijjasz-Vasquez's picture
 

We are facing an unprecedented era of increasingly complex crises. A growing number of countries are affected by both recurring disasters caused by natural hazards and protracted crises associated with fragility, conflict and violence (FCV). Violent conflict has spiked dramatically since 2010 and the fragility landscape is becoming more complex. Two billion people now live in countries affected by FCV. By 2020, it is estimated that between 43% and 60% of the world’s extreme poor will live in FCV countries.

Resilient housing challenges in Eastern Europe and Central Asia

Ede Ijjasz-Vasquez's picture
 

As the World Bank expands its engagement in the housing sector with countries in Eastern Europe and Central Asia (ECA), two major challenges have emerged. At one extreme of the housing spectrum is the potential seismic risk posed by certain multifamily buildings built before the 1990s. At the other end is the exposure of poor communities living in informal settlements to frequent natural hazards. In this video blog, Senior Director Ede Jorge Ijjasz-Vasquez and Senior Urban Development Specialist Ashna Mathema discuss how both issues need to be urgently addressed.

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