Using Big Data in Early Warning System of Flash Floods in Mauritius

Located in the tropics, the Republic of Mauritius is exposed to a number of natural disasters such as cyclones and torrential rains commonly causing flash floods. The World Risk report 2016 ranked Mauritius 7^th on the list of countries that are more exposed to natural hazards. Early warning systems (EWS) are recognized in both the Hyogo Framework for Disaster Reduction (2005-2015) and the Sendai Framework for Disaster Risk Reduction (2015-2030) as an important element of disaster risk reduction. When disasters strike, first responders need to understand new situations on the ground. They require timely, validated information that can be integrated into information products for efficient communication, situational understanding, and ultimately for better decision-making. Communication technology play an important role in disaster management, especially in the preparedness phase. This study assesses the status of EWS of floods in Mauritius, key gaps and challenges, and will propose a framework for a people centered early warning system using big data for flash floods in the country. The study is useful to professionals and policy makers involved in disaster management at all levels in applying early warning information for use in disaster management and mitigation. Currently, real time warning does not exist for flash floods in Mauritius. This research would be significant in enhancing awareness about incorporating big data generated from mobile phones for real time evaluation of the situation and importance of spatial data infrastructure.