3. Background
Morphometric characteristics of Morphometric characteristics of
Boura catchment Binaba catchment
Surface area (km²) : 155.3 Surface area (km²): 11.8
Perimeter (m) : 59.6 Perimeter (m) : 14.6
Compactness index : 1.34 Compactness index : 1.2
Mean elevation (m) : 300 Mean elevation (m) : 225
Specific elevation(m) : 37.24 Specific elevation (m) : 23.80
Mean slope (m/km) : 3.4% Mean slope (m/km) : 0.35%
Global slope index(m/km) : 4 Global slope index (m/km) : 6.9
Andes • Ganges • Limpopo • Mekong • Nile • Volta
4. Background Objectives
× No hydrological monitoring Physical and hydrological
– Boura and Binaba watersheds characterization of watersheds of
are ungauged both sites
• No records of streamflow, Building of the monthly
evaporation, water level etc streamflow time series
• Difficult to calibrate a Establish the water budget of
hydrological model in the each reservoir
basin at a small watershed
Determine the heat balance of
without these records
the reservoir
× Management (allocation) of
Model GW‐SW interactions
water has not been streamlined
especially for the dry season
Andes • Ganges • Limpopo • Mekong • Nile • Volta
5. 2IE TU‐Delft
Developing a Hydrological model Evaporation and seepage losses
(Yates, GIRARD & GR2M) in lakes in the Volta basin using
Developing a water allocation water and heat balance
model using WEAP at a smaller Detailed study in Binaba &
watershed level (Boura and (Boura?)
Binaba) using the water balance Regionalising for the basin using
remote sensing (Images through
Water Use
the TIGER project)
Other components of the water
Groundwater surface water
balance i.e Runoff, P,ET, etc
interactions (natural Isotopes)
Andes • Ganges • Limpopo • Mekong • Nile • Volta
7. Water budget of the reservoir
Boura only
?
?
?
Andes • Ganges • Limpopo • Mekong • Nile • Volta
8. Getting the water balance right ..1
gauge plates
Rain gauge
Evaporation pan
DTS Monitoring well
EC
Andes • Ganges • Limpopo • Mekong • Nile • Volta
9. Getting the water balance right …2
Thalimedes
Water Sampling Points
for Isotope analyses
Rainfall Sampling
Andes • Ganges • Limpopo • Mekong • Nile • Volta
10. Modelling Diagnostic
Analyses of
Users/Typologies
(Uses)
Model Output
from ZonAgri
Evaporation &
Seepage Losses
model output
Output from
other
hydrological
models
Andes • Ganges • Limpopo • Mekong • Nile • Volta
11. Some initial results
Seasonal flows in Boura
Andes • Ganges • Limpopo • Mekong • Nile • Volta
12. Some initial results
Annual flows
Andes • Ganges • Limpopo • Mekong • Nile • Volta
13. Some initial results
Maximum monthly flows per year
Andes • Ganges • Limpopo • Mekong • Nile • Volta
14. Some initial results
Modèle GR2M Yates Girard
Lame écoulée annuelle 36.02 31.6 34.79
moyenne (mm)
Lame écoulée annuelle
34.21 28.4 35.3
médiane(mm)
Ecart‐type (mm) 16.84 17.6 20.85
Coefficient Variation (%) 46.77 57.74 59.92
Coefficient d'écoulement 3.94 4.66 5.56
annuel moyen (%)
Maximum monthly flows per year
Andes • Ganges • Limpopo • Mekong • Nile • Volta
15. Some initial results
Isotope Analysis
Andes • Ganges • Limpopo • Mekong • Nile • Volta
16. Some initial results
Water Temperature at bottom of lake
35 700
30 600
25 500
Temperature (oC)
Water level (m)
20 400
15 300
10 200
5 100
0 0
Date/Time
Binaba reservoir
Andes • Ganges • Limpopo • Mekong • Nile • Volta
17. Way Forward
More data collection
Calibration and verification of models
Scenario building (climate change,
water uses, cropping pattern)
Andes • Ganges • Limpopo • Mekong • Nile • Volta
18. Thank you for
your attention
Andes • Ganges • Limpopo • Mekong • Nile • Volta