Authors: Max Martin, Department of Life Sciences, Christ University, Bengaluru; visiting research fellow, School of Glob-al Studies, University of Sussex, UK The study examines how traditional fishers in Thiruvananthapuram, southwestern India, respond to early warning systems (EWS) in the context of increased risks due to climate change and extreme weather. The region is home to […]
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,
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, 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 »
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 »
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 »
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 »
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
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 »
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 »