This document summarizes a study that modeled water yield, sedimentation, and flood dynamics in two sub-basins in the Volta River Basin in Ghana. The study: 1) Used a hydrological model to simulate water and sediment yields in the Zebilla catchment and estimate the average annual water yield is 1.4 billion cubic meters, with 0.16 billion cubic meters generated within the basin. 2) Estimated the average annual sediment yield for the Zebilla catchment is 3.4 tons/hectare per year, with cropland and woodland contributing 4.7 tons/hectare per year. 3) Calculated the average sediment yield deposited in

1. Modelling Water Yield, Sedimentation, and Flood
Dynamics in 2 sub‐basins of the Volta Basin
Emmanuel Obuobie, Fred Kizito, Christophe Le Page and Jean
Philippe Venot

2. Location and background

3. Social aspects of IWRM
‐ Tool: Companion modeling
‐ Methodology: Stakeholders identify a collective challenge and use
conceptual frameworks to identify their systems in a play fashion
‐ Collective identification of social and ecological dynamics
‐ Outcome: Identification of a shared representation of issues at stake
(actors, resources, dynamics and relationships) through local
stakeholder consultation

4. Conceptual System setup
Flood
vulnerability and
land use planning
4

5. Modeling Water/Sediment Yields
‐ Study catchment in Ghana (Zebilla: 1,695 km2) ‐
‐ Modeling conducted to include
upstream inputs to‐ and downstream sinks
from study area

6. Model Calibration and Validation
Calibration results 16
Simulated Measured R2=0.84
Annual Total Water Yield (mm)
for Yakala 14
NSE=0.77
12 PBIAS= 6.3%
10
8
6
4
2
Conditions for successful calib. 0
R2 > 0.6 1980 1981 1982 1983 1984 1985
NSE > 0.50 Year
PBIAS is + 25%
(Santhi et al., 2001; Moriasi et al., 2007) 8 R2=0.72
Simulated Measured NSE=0.68
Monthly Total Water Yield (mm)
7 PBIAS= 12.6%
6
5
4
3
2
1
0
janv.‐80 janv.‐81 janv.‐82 janv.‐83 janv.‐84 janv.‐85
Calibration Years
6

7. Model Calibration and Validation
70 R2=0.83
Simulated Measured NSE=0.82
Monthly Total Water Yield (mm)
60
PBIAS= 4.4%
50
40
30
20
10
Calibration and 0
validation results
for Nawuni Calibration Months
70
R2=0.82
Monthly Total Water Yield (mm)
60 Simulated Measured NSE=0.78
PBIAS= 15.5%
50
40
30
20
10
0
Validation Months
7

8. Key water Yield Results
Methodology: Simulated discharge in ‘cms’ was converted to ‘cmy’
Outcome: Estimate of water fluxes that can be imported into WEAP
for allocation to the different water users in the basin
Mean annual water yield: 1.4 Billion m3 of which 0.16 Billion m3 is generated
within the basin. The remaining 90% is generated upstream of the basin.
4500 900
Zebila water yield Total water yield
4000 800
Annual Water Yield (Mm3)
3500 700
Total Water Yield (Mm3)
3000 600
2500 500
2000 400
1500 300
1000 200
500 100
0 0
1971 1976 1981 1986 1991 1996 2001

9. Sediment Yield Estimation
‐ Methodology: Empirical relationship between water discharge and sediment
concentration yields sediment discharge.
‐ Sediment discharge is used to simulate and calibrate sediment transport (t/day)
in the catchment; yield is computed as a function of study area t/ha
‐ Outcome: Estimate of sediment yields permits scenarios for interventions to
mitigate problem e.g. grass strips
Calibration and
validation
Results for
Nawuni

10. Sediment Yield Estimation
‐ Average annual sediment yield for Zebila catchment: 3.4 t/ha/yr
‐ Sediment yield by land use type: Cropland/woodland, Savanna
Land use Cropland/woodland Savanna
Sediment (t/ha/yr) 4.7 2.1
Contribution to sedimentation (%) 69 31
‐ Average sediment yield in reservoirs in Zebila catchment: 0.012 t/ha/yr (2035 t/yr)
‐ Global average sediment yield: 15 t/ha/yr
‐ Average for Africa: 9 t/ha/yr

11. Flood Hazard Assessment
GEO‐SFM Model
Small reservoirs
Hydrograph

12. Characterizing Flood Risk
Produce a
Generate Daily synthetic
Historical Rainfall streamflow record
(1961-2003) by reanalysis
Determine locations
where bankfull storage
Is exceeded
?
Compute Bankfull
storage

13. Next Steps
Sediment modeling
o Model scenarios of interventions e.g., introducing grass
strips to ascertain impacts on erosion and sedimentation
Flood modeling
o Conduct data processing module, water balance routines
and flow routing modules
o Generate flood hazard map

14. Concluding Remarks
‐ Modeling tools are useful for studying sedimentation/erosion and
flooding dynamics within the framework of Integrated Water
Resources Management (IWRM)
‐ Estimates indicate that 90% of the sub‐basin water resources are from
upstream sources which signifies implications for upstream‐
downstream collaboration on IWRM issues
‐ Sedimentation control through interventions ensures that:
‐ Reservoirs are not subjected to uncontrollable siltation levels
‐ Storage capacity of reservoirs is lengthened and they are used
more productively which
‐ Enhances community water provision and livelihoods in the Basin

15. Concluding Remarks‐ 2
‐ Flood hazard modeling is far advanced. When completed the
generated hazard maps will inform decision making regarding land use
planning in the study catchment. This will help reduce vulnerability to
flooding disasters.
‐ Results from sedimentation and flood modeling feed into multi‐
stakeholder platform for policy and IWRM interventions

16. Thank you