Community Water Watch
Location Dar Es Salaam - Financed by Dutch Ministry of Economic Affairs and Climate
Dar Es Salaam is frequently hit by floods. In particular informal settlements exhibit a high vulnerability to floods, as settlements are unplanned, have to cope with very limited infrastructure and solid waste frequently clogs the already limited capacity of the drainage system. This causes more severe flooding and direct and indirect consequences.
The authorities lack the information they need in the flood response phase to reduce the impacts of floods effectively. This applies to prevention measures as well as disaster response. They cannot allocate resources in a timely and effective manner. Also, the citizens of Dar es Salaam cannot prepare themselves without any warning, which increases the impact of floods. Ultimately this leads to loss of lives, properties damaged and lost, untimely or uncoordinated aid or other non-effectuating actions.
To forecast and monitor very local floods in Dar Es Salaam, a consortium of Deltares, TU Delft, Red Cross and FloodTags, developed a local flood warning service together with local stakeholders. The service is called "Community Water Watch", or briefly CWW. It helps the stakeholders in better preparing and responding to floods, reducing the impact of floods on daily life.
For the CWW, FloodTags delivers media data to combine with hydrometeorological data. As additional feature, the software also includes direct messages sent by Red Cross volunteers. With these ground observations, the CWW can provide a hyperlocal forecast and monitoring.
The system is now operational with the Tanzanian Red Cross and shared with the other stakeholders, including Dar es Salaam Multi Agency Emergency Response Team (DarMAERT), Disaster management department and Bus Rapid Transport Company. Plans are ahead to distribute the data to the wards via WhatsApp, for increased situational awareness.
A large number of cities around the world have similar urban flood problems. By using ground-observations from the media and chats, flood models can be developed and validated that are much finer grained. With it, disaster response and citizen actions can be taken, with a minimised flood impact as result.