aWhere Case Study: Flooding in Central African Republic

aWhere Case Study: Flooding in Central African Republic

Recent flooding in the capital city Bangui has uprooted tens of thousands of residents and has turned deadly. In a country that has been recovering from violence for the past few years, these extreme weather events will put development efforts behind. aWhere’s timely weather data, combined with datasets such as population density can help governments get ahead of these risks that cause incredible humanitarian distress and expense.

Weather Insights:

Impacts felt across urban and rural settings

According to a recent article from The New Humanitarian, flooding in the capital city Bangui has uprooted tens of thousands of residents and has turned deadly. In a country that has been recovering from violence for the past few years, these extreme weather events will put development efforts behind. aWhere’s timely weather data, combined with datasets such as population density can help governments get ahead of these risks that cause incredible humanitarian distress and expense. The maps below show the total rainfall for the past month (Oct 8 – Nov 7) as well as the difference in precipitation totals from the long-term normal (average based on 2006-2018 rainfall).


These weekly climate charts for Bangui and M’Baiki illustrate the extreme variability in rainfall over the past year compared to the long-term normal. There were weeks with low or normal rainfall followed by much higher than normal rainfall. The forecast shows that rainfall will be returning to normal which is a welcome site to these heavily populated areas. aWhere’s daily-update content offers timely insights to meet urban and rural needs.

Analytics:

How much of the population is impacted?

aWhere’s agile gridded surface can be easily combined with external datasets such as population (Source: WorldPop 2020 estimate as illustrated below). Drilling down into specific communities shows how many people have been experiencing higher than normal precipitation – in this case ~1.5 million people have experienced over 300 mm more rainfall than normal over the past 30 days (as shown in the pink bars). According to the long-term normal, the majority of the population (~1.3 million people) experiences 175 mm of rainfall during this time period (as shown in blue bars). The analysis of population per aWhere grid cell combined with weather analytics enables prioritization and planning in advance of weather events such as flooding or drought.

Implications and Recommendations

Central African Republic was listed as the most at-risk country on the 2017 Climate Change Vulnerability Index. There is potential here to have at least anticipated and taken appropriate action and investments to reduce the impact of flooding. As erratic climate events become more frequent, early warning systems must be strengthened to support planning and investments to deliver economic resilience to climate change.

aWhere’s weather data and models can help service providers, industry and farmer/producers organizations in Africa and around the world adapt to weather variability by applying accurate observed weather to deliver economic resilience to climate change in agriculture, energy, health, trade (domestic and international) and watershed management.

Contact aWhere for more information: Analytics driving economic resilience.


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