1. POTENTIAL AND CONSTRAINTS TO IMPROVE EARLY WARNING
IN THE UPPER NIGER BASIN USING THE PREDICTION OF FLOOD VOLUME FROM MONTHLY TO SEASONAL WEATHER FORECAST IN A HYDROLOGICAL MODEL
Authors
AUTHORS: Fournet Samuel1, Aich V.1, Liersch S.1, Dutra E.2, Koné B.3, Pappenberg F.2, Hattermann F. F.1
AFFILIATIONS: 1 Potsdam Institute for Climate Impact Research
v CONTACT v European Centre for Medium-Range Weather Forecasts
3 Wetlands International
Figure 2 & 3: Observed, simulated and
Forecasted* daily discharge** at Koulikouro
Top: ENS in 2008 starting for 13 different weeks
Down: SEAS in 1984 starting the 1st of July***
Figure 5: How reliable is the forecast* at Koulikouro ?
Reliability diagram** to discharge forecast against against monitoring WFD−EI simulation
1. Introduction: Upper Niger Basin
The Upper Niger basin experiences a high seasonal and interrannual climate variability with severe dry episods affecting regional food security and socio-economic development as well as the conservation of wetlands and semi-arid ecosystems. It results in increasing competition and conflicts for water and natural ressources between vulnerable local stakeholders (rainfed and semi-controlled irrigation farming, nomadic pastoralism, traditional fisheries) and steers national investments with the construction of dams and diversion channels for the development of hydropower energy and fully governed irrigated agriculture (Fig.1).
2. Materials and Methods
This study aims at presenting an experimental hydrological forecast model using the Soil and Water Integrated Model with retrospective monthly to seasonal re-forecast from the European Centre for Medium-Range Weather Forecast (Tab.1). Calibrated and validated with Watch Forcing Data, SWIM forecasts discharge up to 32 (Fig.2) or 215 days (Fig.3) ahead incorporating main operational water managements of the river basin (reservoirs and irrigation schemes in Fig.1).
3. Results
Using different global atmospheric reanalysis as hydrologic initial conditions (Tab.1), the confidence, the reliability and the skills (Fig. 4, 5, 6) for different lead time and starting date to report cumulative discharge anomalies at a referenced gauge, Koulikouro, is investigated to assess the constraints for a potential integration in a operational early warning system.
* ENS with WFD-EI as initial conditions;
** Each point referred to threshold alarms settings
*** Forecast
Figure 1: The Upper Niger Basin
Table 2: Principles of ROC diagram
Koulikouro gauge
* forecast readjusted to initial monitored discharge keeping absolute change; ** with WFD-EI as initial conditions;
*** day1 is shifted to 1st of May for SEAS
Figure 6: How good is the forecast* skill to warn discharge anomalies** at Koulikouro ?
4. Conclusion
The potential to detect cumulative discharge anomalies coupling ENS and SEAS re-forecasts from ECMWF to the eco-hydrological model SWIM were assessed.
Bias between observed and simulated discharge creating gaps at the initial dates and in the settings of alarm threshold and similar bias carried by weather forecast, climate prediction and the referenced reanalysis product can be improved to enhance forecast .
5. Aknowledgement
This work was achieved under the fp7 project: Improved Early Warning and
FORecasting to strengthen
Preparedness and adaptation
to Droughts in Africa
ROC DIAGRAM
*ENS with WFD-EI as initial conditions **quantiles applied to daily mean discharge were calculated for each starting date independently for forecast, simulated and monitored discharge to be used as threshold alarms
Table 1: Forecast product characteristics
Figure 4: How confident* is the forecast* to predict discharge at Koulikouro ?
* Percent of forecast having a reasonable error in predicting the difference of daily mean discharge from intial to forecasted date (reasonnable error being set as less than 10% of the initial observed discharge)
** ENS with WFD-EI as initial conditions
* 0 to 15 = medium range ** with WFD-EI, WFD-E4 and EI
WFD= Watch Forcing Data; E4= ERA-40; EI=ERA-Interim