Over 2,000 residents in Fellowship, Portland are expected to benefit from the installation of a comprehensive flood early warning system to assist the community in managing potential flood-related disasters. The equipment was received at a handover ceremony on October 31, 2018 at the Fellowship Baptist Church.
The community is vulnerable to flooding caused by several factors such as high stream and river flow during heavy rainfall, and blockage of river course and other waterways by landslide debris. Grant assistance valued at USD $45,000 provided by the USAID-funded Ja REEACH II project has enabled the installation of the early warning system. The equipment has been installed at strategic sections throughout the mid-Rio Grande Valley through partnership with the Water Resources Authority (WRA). The handover ceremony also included an information session led by the WRA, and the Office of Disaster Preparedness and Emergency Management.
The community participated in a series of risk assessment and planning workshops conducted by Ja REEACH which identified the need for a comprehensive flood early warning system to respond efficiently to future incidences of flooding.
“I am glad that the system is now in place to give us enough time as a community to take action whenever it rains so that it can lessen the impact of the flooding in the community”. Icema Swire, flood victim, and community member. Previously, flood waters have risen as high as 23 feet surrounding Mrs. Swire’s home.
Deputy Managing Director of the WRA, Peter Clarke, highlighted the significance of the early warning system for the community. “Fellowship has a history of flooding and history of loss. We have an obligation to try and keep all our citizens as safe as we can. There are communities that are extremely vulnerable Fellowship is one of those extremely vulnerable community and such it is natural that it is one of the first that would have been chosen for this project.”
The WRA is currently collecting real-time rainfall and river flow data for developing a flood prediction model for the Rio Grande Valley.
