Floods in Lebanon normally take place during the wet season, generally after a strong storm or at the beginning of the spring with the melting of the snow. During floods, rivers burst their bank causing damage to agricultural lands and farms. The consequences of such events are tragic including annual financial losses, casualties, loss of livestock, and destruction to assets, built-up areas, agricultural lands, and damage to fisheries, boats, and forests, in addition to triggering landslides. The availability of innovative technologies to forecast hydro-meteorological hazards has increased in recent years and can certainly support disaster risk reduction, preparedness, and contingency planning activities with reliable and timely information.
The country experiences 1 to 2 cases of flooding annually, a number that is likely to rise (Flooding is mainly caused by irregularities in rainfall patterns) those floods cause many economic damage, environmental impacts, and loss of livelihoods. In the recent past, Lebanon experienced deviation in rainfall patterns, which has been attributed to increasing temperatures. These changes in rainfall patterns are affecting the frequency of intense rainfall events and altering catchments and drainage basins. Heavy rains measure up to 100 mm per hour during storm events causing damage to property and agricultural lands, and often set off landslides that deposit solid waste into the Mediterranean Sea. Increased winter rainfalls, due to climate change impact, lead to destructive flooding. This situation will be exacerbated by the vulnerability of Lebanese communities to flooding by affecting socio-economic factors such as population growth, urbanization, poverty, and inadequate infrastructure.
Flood Assessment has been initiated by NEWSP through many projects and many flood scenarios were prepared with 0.1 exceedance probability (or return period T=10 years) as a high probability scenario based on the local history of flood events. A 0.02 exceedance probability (or return periods T= 50 years) as a medium probability scenario. And a 0.01 exceedance probability (or return period T=100 years) as a low probability scenario to indicate the worst-case scenario.
Currently, we are working on developing accurate hazard forecasts that can be converted into impact predictions and then easily disseminated in a manner that supports evidence-based action or decision-making, such as alerts concerning the extent, duration, evolution, and impacts of flood events. This information allows life-saving evacuations, and flood response including support to the displaced population. The early warning system that will be set will include emergency alert messages through mobile apps so that local communities receive updated information on ongoing events and future possible evolution based on their position. To this end, mobile apps will display the latest parameters measured by the closest Automated Weather and gauge stations.
The country experiences 1 to 2 cases of flooding annually, a number that is likely to rise (Flooding is mainly caused by irregularities in rainfall patterns) those floods cause many economic damage, environmental impacts, and loss of livelihoods. In the recent past, Lebanon experienced deviation in rainfall patterns, which has been attributed to increasing temperatures. These changes in rainfall patterns are affecting the frequency of intense rainfall events and altering catchments and drainage basins. Heavy rains measure up to 100 mm per hour during storm events causing damage to property and agricultural lands, and often set off landslides that deposit solid waste into the Mediterranean Sea. Increased winter rainfalls, due to climate change impact, lead to destructive flooding. This situation will be exacerbated by the vulnerability of Lebanese communities to flooding by affecting socio-economic factors such as population growth, urbanization, poverty, and inadequate infrastructure.
Flood Assessment has been initiated by NEWSP through many projects and many flood scenarios were prepared with 0.1 exceedance probability (or return period T=10 years) as a high probability scenario based on the local history of flood events. A 0.02 exceedance probability (or return periods T= 50 years) as a medium probability scenario. And a 0.01 exceedance probability (or return period T=100 years) as a low probability scenario to indicate the worst-case scenario.
Currently, we are working on developing accurate hazard forecasts that can be converted into impact predictions and then easily disseminated in a manner that supports evidence-based action or decision-making, such as alerts concerning the extent, duration, evolution, and impacts of flood events. This information allows life-saving evacuations, and flood response including support to the displaced population. The early warning system that will be set will include emergency alert messages through mobile apps so that local communities receive updated information on ongoing events and future possible evolution based on their position. To this end, mobile apps will display the latest parameters measured by the closest Automated Weather and gauge stations.