Presentation by Ruben Imhoff (WUR) at the wflow User Day 2018, during Delft Software Days - Edition 2018. Friday 09 November 2018, Delft.

1. Towards high resolution calibration-free modelling
with seamless large-domain parameter estimates
Ruben Imhoff, Willem van Verseveld, Bart van Osnabrugge, Albrecht Weerts
Delft Software Days - November 9th, 2018
Distributed hydrological modelling with wflow_sbm

2. 8 november 2018
Contents
1. Background and motivation
2. Model parameter estimations – ‘Towards calibration-free modelling
with seamless large domain parameter estimates’
3. Application in the Rhine basin
4. Lessons learned from a intercomparison study in the United
States
a. Reduction of root water uptake
b. Improvements in soil evaporation
5. Wrap-up and outlook

3. Background and motivation
Distributed hydrological models, a
pleasure or a burden?
Transition to distributed models
comes at a price:
• Over-parameterized models
• Patchy parameter maps
• Limits climate and land use
change studies
• Calibration a burden for
operational and policy use
8 november 2018
BackgroundParameter
estimates
Application
Rhine
ApplicationUSOutlook

4. Background and motivation
So what can we do?
• Pedo-transfer functions (PTFs) -
Parameter estimates
• Convenient regionalization techniques,
e.g. Multiscale Parameter Regionalization
(MPR) [Samaniego et al., 2010]. Applied for:
• German model mHM [e.g. Samaniego et al.,
2010; Kumar et al., 2013; Samaniego et al.,
2017]
• VIC [Mizukami et al., 2017]
• Next step: same upscaling procedures,
but no calibration involved
8 november 2018
BackgroundParameter
estimates
Application
Rhine
ApplicationUSOutlook
Samaniego et al., 2010

5. Model parameter estimations
Step 1: High resolution data
• ISRIC SoilGrids 250m – global
soil database [Hengl et al., 2017]
• Forcing, e.g. genRE interpolation
(1200 m, hourly) for Rhine basin
[van Osnabrugge et al., 2017, 2018]
Step 2: Parameter estimates at
original data resolution
Step 3: Convenient upscaling
techniques to model resolution
Step 4: Run your model
1.2 km resolution for the Rhine
Now, 1 km resolution for the US
8 november 2018
Background
Parameter
estimatesApplication
Rhine
ApplicationUSOutlook
Global
parameters for
PTFs(γ)
Geophysical
properties (μ)
Tranfer-functions
β = f(γ,μ)
Upscaling (arithmetic
mean, harmonic mean,
geometric mean, etc.)
Model simulation
Calibration

6. Model parameter estimations
An example of the pedo-transfer functions
8 november 2018
Background
Parameter
estimatesApplication
Rhine
ApplicationUSOutlook
1.2 km 2.4 km 3.6 km 4.8 km

7. Model parameter estimations
• Soil data available at various
depths  wflow_sbm set up
with four soil layers
• All sensitive parameters
estimated (based on sensitivity
analysis)
• Strength of wflow_sbm
• Model does not have to be
calibrated!
• Snow parameters still
uniform and following HBV
8 november 2018
Background
Parameter
estimatesApplication
Rhine
ApplicationUSOutlook

8. Application in the Rhine basin - Results
Discharge simulations
8 november 2018
Background
Parameter
estimates
Application
RhineApplicationUSOutlook

9. Application in the Rhine basin - Results
Evapotranspiration estimates
8 november 2018
Background
Parameter
estimates
Application
RhineApplicationUSOutlook

10. Application in the Rhine basin - Results
Estimates at different resolutions
8 november 2018
Background
Parameter
estimates
Application
RhineApplicationUSOutlook

11. Lessons learned from an intercomparison study in the
United States
Intercomparison study with VIC model – collaboration with National
Center for Atmospheric Research
8 november 2018
Background
Parameter
estimates
Application
Rhine
ApplicationUS
Outlook
34 basins
in the
CONUS
VICreg
semi-
distributed
VICind
semi-
distributed
Wflow_s
bm
distributed

12. Lessons learned from an intercomparison study in the
United States
General overview results
Reached KGE for discharge simulations
wflow_sbm with parameter estimates outperforms VICreg with calibrated
transfer-functions.
Individual basin calibration (VICind) still gives best
performance
8 november 2018
Background
Parameter
estimates
Application
Rhine
ApplicationUS
Outlook

13. Lessons learned from an intercomparison study in the
United States
Improvements in soil
evaporation module
• Soil evaporation could
only take place from
unsaturated zone in upper
layer
• Problem for warm and
humid catchments
• New implementation –
Two-step soil evaporation:
1. Unsaturated zone
2. Saturated zone
• Importance of PET-
estimations
8 november 2018
Background
Parameter
estimates
Application
Rhine
ApplicationUS
Outlook
From
To

14. Lessons learned from an intercomparison study in the
United States
Importance of root water uptake reductions during dry periods:
The benefits of the Feddes transpiration reduction in wflow_sbm
8 november 2018
Background
Parameter
estimates
Application
Rhine
ApplicationUS
Outlook
Feddes et al., 1978

15. Wrap-up and Outlook
Code improvements and lessons learned
• Two-step soil evaporation procedure (available in latest version)
• Importance of transpiration reduction function (available in latest version)
• Pay attention to forcing and in particular PET estimates
Parameter estimates
• Wflow_sbm can be run without further calibration
• Promising results for the Rhine basin
• Improvements to be made in sub-tropical and semi-arid regions (US case)
• For operational use: possibly calibrate one or two parameters only (e.g. M
and Ksat)
8 november 2018
Background
Parameter
estimates
Application
Rhine
ApplicationUS
Outlook

16. Wrap-up and Outlook
Outlook
• Easy model setup
• Calibration an option to further tune model for operational
use  But not always necessary!
• Paper in preparation [Imhoff et al., WRR, 2018]
• Global parameter maps on 1 km will come available soon
>  See presentation by Albrecht Weerts on the CRUCIAL
product for wflow_sbm global
8 november 2018
Background
Parameter
estimates
Application
Rhine
ApplicationUS
Outlook

17. Questions?