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Flood-Watch

Flooding is a natural disaster that is oftentimes hard to predict and can cause major economic and environmental losses. In Romania, in recent years, floods have affected communities, agriculture, and infrastructure. In 2019, the Ministry of the Environment, Waters and Forests (MMAP), together with the National Administration "Romanian Waters" (ANAR) and the National Institute of Hydrology and Water Management (INHGA) implemented the EU Floods Directive on the territory of Romania. They defined "Areas of Potential Significant Flood Risk" (APSFR), which documents the areas of flood risk in Romania. Current Romanian systems that are available to the public rely on static maps, and they do not provide automated real-time analysis, which can hinder the reaction time of citizens and authorities.

The FloodWatch application aims to offer a smart solution for detecting early signs of floods and to predict a possible inundation in Romania. The platform uses artificial intelligence to analyze satellite image data to classify land regions (water, vegetation, urban, etc.), topographic elevation maps, and real-time precipitation forecast maps in order to identify areas at high risk of river overflow. It will monitor some of the regions from the the 526 Areas of Potential Significant Risk (APSFR) that are scattered around the river courses within Romanian territory. The system can estimate the likelihood of flooding 6 to 24 hours in advance, displaying vulnerable regions on an interactive map and generating alerts for users.

By working with multiple data sources, the system aims to monitor hydrologic behavior and to accurately predict river flooding. The solution is targeted especially at farmers that could lose a lot of revenue in case of an untimely announced flood and it aims at contributing to reduced economic losses and increased public safety. The platform provides both real-time monitoring and historical analysis of hydrological behavior, which is highly relevant in the context of climate change.

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Detecting early signs of floods by using real-time satelite data

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