Characteristics, drivers, and predictability of flood events in the Tana River Basin, Kenya

Flood-related impacts and losses are rising. Therefore, understanding flood characteristics, drivers, and predictability is critical for informed decisions in the ongoing flood early warning (FldEWS) projects. This study presents an in-depth analysis of hydro-meteorological, Sentinel Mission (SM), and ensemble hydrological model datasets. The authors examine flood characteristics using observed hydro-meteorological and SM datasets, followed by statistical analysis of climate drivers of flood events at inter-annual and sub-seasonal (S2S) time scales. Finally, reforecasts from Global Flood Awareness System (GloFAS) are assessed against observed river flows.

The results of the study suggest that there is good potential for GloFAS to complement existing forecasting and FldEWS across the region, operated by national and the regional forecasting agencies. As emphasized elsewhere, realizing this opportunity likely requires closer collaboration between the relevant agencies, and the at-risk populations; improved evidence on the most effective communication channels and use of forecasts; enhanced coherence and coordination in flood risk governance arrangements; all supported by appropriate investment and capacity enhancement across actors.