Current Status on Flood Forecasting and Early Warning in Africa

An overview of the current state of flood forecasting and early warning in Africa is provided in order to identify future user needs and research. Information was collected by reviewing previously published research in the scientific literature and from institutional websites. This information was supplemented by data collected from a questionnaire sent to hydrological and meteorological institutions that were identified as potentially dealing with flood management issues in Africa. Results show that there are a significant number of institutional flood forecasting initiatives ongoing in Africa, but information regarding many of these initiatives is not easily accessible. Second, there is a clear need for improved flood forecasting and early warning in Africa. Third, the dissemination of existing flood forecasts and warnings to end-users and the public could be improved. It should be noted, however, that due to the difficulty in obtaining information regarding flood forecasting in Africa, the overview presented by the authors might be an underestimation of the current situation. Finally, the authors demonstrate the importance of developing a complementary flood forecasting and early warning system

A pan-African medium-range ensemble flood forecast system

The <i>African Flood Forecasting System</i> (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

Rainfall characteristics and their implications for rain-fed agriculture: a case study in the Upper Zambezi River Basin

This study investigates rainfall characteristics in the Upper Zambezi River Basin and implications for rain-fed agriculture. Seventeen indices describing the character of each rainy season were calculated using a bias-corrected version of TRMM-B42 v6 rainfall estimate for 1998–2010. These were correlated with maize yields obtained by applying a SVATmodel. Finally, a self-organizing map (SOM) was trained to examine multivariate relationships. The results reveal a significant spatio‐temporal variability of rainfall indices and yields, with a gradient from north to south. Yields greater than 1 t/ha are found to be only achievable with rainy seasons longer than 160 days. For shorter durations, the interplay of total rainfall, dry spell frequency and maximum dry/wet spell durations determines agricultural success. Using total rainfall alone or wet day frequency as estimators for yields is insufficient. Alternating wet and dry spells affect yields most negatively. The results have significance in the context of agricultural planning under changing climatic conditions and agricultural planning, as well as for the development of forecasting mechanisms

Rainfall characteristics and their implications for rain-fed agriculture: a case study in the Upper Zambezi River Basin

This study investigates rainfall characteristics in the Upper Zambezi River Basin and implications for rain-fed agriculture. Seventeen indices describing the character of each rainy season were calculated using a bias-corrected version of TRMM-B42 v6 rainfall estimate for 1998–2010. These were correlated with maize yields obtained by applying a SVATmodel. Finally, a self-organizing map (SOM) was trained to examine multivariate relationships. The results reveal a significant spatio‐temporal variability of rainfall indices and yields, with a gradient from north to south. Yields greater than 1 t/ha are found to be only achievable with rainy seasons longer than 160 days. For shorter durations, the interplay of total rainfall, dry spell frequency and maximum dry/wet spell durations determines agricultural success. Using total rainfall alone or wet day frequency as estimators for yields is insufficient. Alternating wet and dry spells affect yields most negatively. The results have significance in the context of agricultural planning under changing climatic conditions and agricultural planning, as well as for the development of forecasting mechanisms