Implementing Forecast-based Financing in disaster management in Kenya
Currently, many predictable extreme events such as floods and drought, result in disasters and suffering. This is aggravated by climate change. The impact of these events can be reduced or avoided if weather and climate forecasts are systematically used for early action to prepare for disaster. However, forecasts are not always used to take early action, with governments and humanitarian organisations often starting their response operations after a disaster has taken place. A number of reasons have been cited for this reactive rather that anticipatory actions including the lack of plans and early financing to take early action. If a Forecast-based Financing system is in place, this could reduce climate-related risks to vulnerable people and save valuable time and money in humanitarian response.
Forecast-based Financing (FbF) is an anticipatory mechanism to enable access to funding before a disaster, to implement early action based on credible forecasts and in depth risk analysis. FbF was inspired by index insurance which offers automatic insurance payments to farmers when an extreme hydrological event happens.
· Key national level institutions who are important in the implementation of FbF exist and have shown interest and willingness to engage with FbF
· Humanitarian and disaster management institutions desire to use forecasts to plan for early action, with thinking of who will potentially be affected and cost implications
· The National Meteorological Services wants to have greater impacts, which presents an opportunity to develop forecasts designed to trigger early action
· The policy context is currently favourable for supporting early action, demonstrated by the recently approved NDRM policy and the NDRM Bill that is currently under discussion
· A number of data sources on vulnerability exists
· Lack of a Disaster Management Law
· A national scale flood early warning system (FEWS) does not exist
· Overlapping disaster management among key government institutions
· The timeliness of data, for example, the livelihoods area assessment which is a key tool for many actors, including WFP being updated for the last time in 2010
· Inadequate technical and bureaucratic data sharing infrastructure
· Difficulty in obtaining granular data from key stakeholders such as the Kenya National Bureau of Statistics