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A sustainable model of community-based flood early warning

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Local governments in Nepal are coordinating and investing in disaster preparedness

A sustainable model of community-based flood early warning

The sustainability of risk reduction interventions is always a question when the threat is seasonal and when stakeholders in a shared risk environment are impacted differently. However, upstream and downstream municipalities in Nepal have shown the way forward by creating a basket fund for operation and maintenance of a community-based flood early warning systems (CBFEWS).

After attending the regional hands-on training on CBFEWS organised by by the River Basins and Cryosphere Programme at ICIMOD, the Tilathi Koiladi Rural Municipality (TKRM) in Saptari District, on the Nepal-India border, invested in a CBFEWS to address the flood risk from the Khando Khola. The river is prone to flash floods and poses a constant threat during the monsoon. Further, the Municipality also teamed up with Rupani Rural Municipality, Rajbiraj Municipality and SABAL Nepal to create a basket fund for operation and maintenance of the system.

Typically, flood early warning generated upstream often does not reach downstream communities because of administrative boundaries. The creation of a CBFEWS Sustainability Committee and a basket fund will not only ensure sustainability of the system, but also better communication among stakeholder municipalities and communities.

The CBFEWS system and the cooperation have attracted local government representatives from bordering areas in India who have visited the site to learn from this model. TRKM is also directly connected with and receiving technical support from the equipment manufacturing company. ICIMOD is providing minimal support and it is expected that from 2022 TRKM will be able to fully maintain the system and provide critical flood early warning information.

The creation of a basket fund by upstream and downstream municipalities for operation and maintenance of the early warning system is a major step towards sustainability of the early warning system.

Chapter 1

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