Presentation by Laurene Bouaziz (Delft University of technology) at the Symposium on catchment hydrology and WFlow, during Delft Software Days - Edition 2017. Tuesday, 24 October 2017, Delft.

1. The value of additional data to
design the hydrological model of
the Meuse
Laurène Bouaziz
24 oct 2017

2. Currently: HBV model
• Developed for Sweden
• Works well for high
discharges
• Models as tools

3. Meuse model
• Models as hypothesis
• How should the model look like?

4. Available data
• Historical timeseries (P, T, Q, E) – 45 basins
• Satellite based soil moisture
– VanderSat
– 100m resolution
• Piezometer levels (ADES, PIEZ’EAU)
• Landuse, elevation, geology

5. What I’ll show:
1 Historical series of P,E,Q
& the Budyko framework
Loss term
2 Satellite based soil moisture Summer and
winter processes
& constrain the
parameter beta
3 Satellite based soil moisture
& groundwater levels
Different model
concepts for
different parts of
the landscape

6. 1. Plotting the long term water
balance
Andréassian and Perrin 2012

7. 1. Plotting the long term water
balance
Andréassian and Perrin 2012
Ea = 0.97 * Ep

8. 1. Estimating Ea with Budyko
Budyko 1974, Gentine 2012
Ea = 0.88 * Ep

9. 1. Consequences for the model
• Deep percolation losses
– Karstification of limestone, chalk
• Abstractions

10. 2. Satellite based soil moisture
• VanderSat
• 100 m resolution
• Almost daily 2015-2017

11. 2. Previous work
• Van Dijk et al. used Microwave and MODIS
(5x5km)
• Worked good in natural rivers (monthly
timestep) but no good signal in rivers in
western Europe

12. 2. Soil moisture based rating curve

13. 2. Predict discharges using soil
moisture
Separate
rating curve
for summer
and winter
One rating
curve for
entire period

14. 2. Constraining the beta parameter
𝑅
𝑃
=
𝑆𝑢
𝑆𝑢𝑚𝑎𝑥
𝑏𝑒𝑡𝑎

15. 3. Groundwater and soil moisture

16. 3. Consequences for the model
• Coupled soil moisture and
groundwater schematization
• Different model concept for
the riparian zones

17. Summary
1 Historical series of P,E,Q
& the Budyko framework
Loss term
2 Satellite based soil moisture Summer and
winter processes
& constrain the
parameter beta
3 Satellite based soil moisture
& groundwater levels
Different model
concepts for
different parts of
the landscape

18. Conclusion
• Additional sources of data and creative use
of data may help to define the model
structure and/or constrain the model
parameters
• Shift the focus from parameter fitting
towards process understanding

19. Merci