Abstract
Abstract. Kenya is mostly affected by floods during the March-April-May (MAM) and October-November-December (OND) rainfall. This often occurs along river basins such as the Tana river basin, leading to disruption of people’s livelihoods, loss of lives, infrastructure destruction and interruption of economic activities. This study used openly available data on flood exposure, vulnerability, lack of coping capacity, flood impacts and observed satellite rainfall to analyse and predict forecast-based impacts in Tana river. Earth observation satellites including LANDSAT, sentinel 1 and 2 were acquired based on credible flood event dates to validate flood exposure and flood events. The community risk assessment (CRA) approach was used to delineate communities at high risk of floods using combination of data on vulnerability, flood exposure and lack of coping capacity. Using an ordinary least squares (OLS) predictive model, observed satellite rainfall was used as a covariate in order to predict flood impacts on communities with high flood risk scores in Tana river. Weighted scores from the CRA dimensions were summed up with forecasted hazards from the OLS model in order to derive a flood impact-based forecast. The flood impact information is to be used in forecast-based action through early warning, early action protocols thereby reducing impacts of potential floods in communities living in high flood risk areas based on the flood risk map.
Highlights
IntroductionPredictable extreme weather events such as floods lead to disasters that are often intensified by climate change
1.1 Forecast-based financingPredictable extreme weather events such as floods lead to disasters that are often intensified by climate change
This paper aims to obtain and analyze credible reports on flood events and impacts in Tana river, to collate information on temporal river gauge levels and observed rainfall derived from satellites for both Tana river and the upper catchment areas, to investigate linear relationship between flood impacts and observed rainfall and river gauge levels and to predict flood impacts using a predictive model
Summary
Predictable extreme weather events such as floods lead to disasters that are often intensified by climate change. The impacts of these events can be mitigated if climate forecasts are thoroughly utilised for early action in order to prepare for disasters. There exists a window of opportunity between when a forecast issued and when the hazardous event occurs, where early actions can be taken to cushion the most vulnerable from the impacts of a flood Recognizing this window of opportunity and taking advantage of advances in science, data and technology, humanitarian organisations such as the Red Cross Red Crescent Movement have developed and piloted an approach known as Forecastbased early Action (FbA), in partnership with meteorological and hydrological services and other humanitarian agencies. Coughlan de Perez defines FbA as when a forecast states that an agreed-upon probability threshold will be exceeded for a hazard of a designated magnitude, an action with an associated cost must be taken that has a desired effect and is carried out by a designated organization (Coughlan de Perez et al, 2015)
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