Practitioner Community

Hurricane / Typhoon / Cyclone

Factors Influencing Accessibility and Actionability of Risk Reduction Measures in Last Mile Communities: Insights from the Northern Philippines

Author: Rhomir Yanquiling, University of Melbourne This research explores the factors influencing the accessibility and actionability of early warning systems (EWS) and risk reduction measures in last-mile communities in Northern Philippines. The study focuses on two vulnerable communities, Mapita and Cabalitian, that were affected by Super Typhoon Mangkhut. Utilizing a mixed-methods approach, including surveys, interviews, […]

Factors Influencing Accessibility and Actionability of Risk Reduction Measures in Last Mile Communities: Insights from the Northern Philippines Read More »

Dominica Building Resilience Through Community Early Warning Systems

Setting the Scene ​​​​​Dominica is highly vulnerable to the effects of climate change, the impacts of which have already been experienced when the island suffered a direct hit by category five Hurricane Maria in September 2017, which wiped out 226% of its gross domestic product. Two years later, Tropical Storm Erika passed over the island

Dominica Building Resilience Through Community Early Warning Systems Read More »

Cyclone Mocha Case Study

Cyclone Mocha, a Category 5 storm, made landfall in Myanmar on May 14, 2023, causing significant damage in coastal areas of Bangladesh and Myanmar. Despite the challenges, Bangladesh’s disaster management efforts, led by the Cyclone Preparedness Programme, successfully evacuated over 700,000 people, with no reported loss of life. This case study highlights the effectiveness of

Cyclone Mocha Case Study Read More »

Predicting hurricane evacuation decisions with interpretable machine learning methods

The present study proposed a novel interpretable machine learning approach to predict household-level evacuation decisions by leveraging easily accessible demographic and resource-related predictors, compared to existing models that mainly rely on psychological factors. An enhanced logistic regression model (that is, an interpretable machine learning approach) was developed for accurate predictions by automatically accounting for nonlinearities

Predicting hurricane evacuation decisions with interpretable machine learning methods Read More »

Climate crises Q&A: Why have some recent storms gained so much strength, so quickly?

Leave a Comment /

Warming oceans and the El Nino phenomenon have caused some storms to gain strength far more rapidly than predicted. When communities are caught off-guard, the results can be devastating. More investment in forecasting, early warning, preparation — and an assist from artificial intelligence — are parts of the solution. An interview with Juan Bazo, climate

Climate crises Q&A: Why have some recent storms gained so much strength, so quickly? Read More »

Putting communities in the driver seat: Good practices from the Philippines

In the spirit of the localization agenda, the flood resilience project of the Philippine Red Cross accompanies, enables, and connects communities to become more resilient to floods and other hazards. We facilitated a participatory whole-of-community process to design evidence-based and risk-informed community resilience building interventions. In this process, community members could voice their needs and

Putting communities in the driver seat: Good practices from the Philippines Read More »

Translating Warnings into Action – How we can Improve Early Warning Systems to Protect Communities

Early warnings for hazards are essential for living safely and minimizing economic losses.  For many hazards, it is possible to give advance notice and accurate information to help communities prepare and respond.  However, issuance of the warning itself is not enough for a warning system to be effective, as the effectiveness of warnings is determined

Translating Warnings into Action – How we can Improve Early Warning Systems to Protect Communities Read More »

Flood Resilience Alliance: Honduras Informe Nacional

Honduras se encuentra entre los primeros cinco países más vulnerables del planeta, según el índice de Riesgo Climático (IRC) que elabora cada año Germanwatch. Los efectos de los desastres impactan negativamente el desarrollo e incrementan la pobreza. En las dos últimas décadas, los desastres han ocasionado pérdidas y daños al país equivalentes a 5592 millones

Flood Resilience Alliance: Honduras Informe Nacional Read More »

Flood Resilience Alliance: Costa Rica Informe Nacional

En Costa Rica las condiciones de vulnerabilidad, como el incremento de población sin planificación, la mala distribución y uso del suelo, y el terreno montañoso y con pendientes pronunciadas, han provocado desequilibrios ecológicos de gran magnitud, en donde una de las consecuencias son las inundaciones devastadoras con desbordamientos súbitos. Los ríos La Estrella, Limoncito, Banano,

Flood Resilience Alliance: Costa Rica Informe Nacional Read More »

Flood Resilience Alliance: Costa Rica Country Briefing

In Costa Rica, drivers of vulnerability such as unplanned population growth, poor distribution and use of land, and the mountainous and steeply sloping terrain have led to great ecological imbalances. One of the consequences is devastating flooding with sudden overflows. The La Estrella, Limoncito, Banano, Reventazón, Matina, and Pacuare rivers, in the Limón province, and

Flood Resilience Alliance: Costa Rica Country Briefing Read More »

Start typing and press enter to search

Scroll to Top