Abstract
Abstract. The African Flood Forecasting System (AFFS) is a probabilistic flood forecast system for medium- to large-scale African river basins, with lead times of up to 15 days. The key components are the hydrological model LISFLOOD, the African GIS database, the meteorological ensemble predictions by the ECMWF (European Centre for Medium-Ranged Weather Forecasts) and critical hydrological thresholds. In this paper, the predictive capability is investigated in a hindcast mode, by reproducing hydrological predictions for the year 2003 when important floods were observed. Results were verified by ground measurements of 36 sub-catchments as well as by reports of various flood archives. Results showed that AFFS detected around 70 % of the reported flood events correctly. In particular, the system showed good performance in predicting riverine flood events of long duration (> 1 week) and large affected areas (> 10 000 km2) well in advance, whereas AFFS showed limitations for small-scale and short duration flood events. The case study for the flood event in March 2003 in the Sabi Basin (Zimbabwe) illustrated the good performance of AFFS in forecasting timing and severity of the floods, gave an example of the clear and concise output products, and showed that the system is capable of producing flood warnings even in ungauged river basins. Hence, from a technical perspective, AFFS shows a large potential as an operational pan-African flood forecasting system, although issues related to the practical implication will still need to be investigated.
Highlights
Riverine floods rank as the second highest death-causing natural disaster in Africa, surpassed only by droughts (Vos et al, 2009)
The aim of this study is to investigate the capability of African Flood Forecasting System (AFFS) to predict flood events, in order to derive its potential as an operational flood forecasting system that could in future contribute to the reduction of flood-related losses by providing national and international aid organizations with timely crucial flood forecast information
The flow during the few years for which data were available was relatively low in comparison to the one in the validation period, the calibration did not cover the full range of flow conditions, which surely contributes to a suboptimal calibration
Summary
Riverine floods rank as the second highest death-causing natural disaster in Africa, surpassed only by droughts (Vos et al, 2009). Flood risk management in Africa has recently gained increased attention in the political and scientific environment (Portuguese Space Office, 2007). Both the Hyogo Framework (United Nations, 2005) and Rio+20 (UNCSD Secretariat, 2012) promote the strengthening of the resilience of African nations to withstand and recover quickly from impacts caused by events of hydrometeorological origin. The substantial reduction of disaster losses, in lives as well as in social, economic and environmental assets, is of prime focus. The development of effective early warning systems is fundamental
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
