The document presents BReach, a methodology for assessing data consistency in rating curve data. BReach involves: 1) selecting a rating curve model, 2) sampling the parameter space, 3) assessing a quality measure, 4) assigning tolerance degrees, 5) assessing bidirectional reaches, and 6) identifying consistent data periods. The methodology was validated using synthetic and observational data and was found to be robust with little subjective input. BReach can help identify temporal variability in rating curves and dependency on variables. Future work includes applying BReach to additional stations and models.

1. BReach: a methodology for the
assessment of data consistency
(in rating curve data)
Katrien Van Eerdenbrugh
Ghent University
Laboratory of Hydrology and Water Management

2. Data consistency in rating curve data
Objective
method?

3. BReach (Bidirectional Reach)
1. Model selection
2. Sampling of the parameter space
3. Assessment of a quality measure
4. Assignment of tolerance degrees
5. Assessment of bidirectional reach
6. Identification of consistent data periods
BReach
Validation

4. 𝑄 ≅ 𝑐(ℎ − ℎ0) 𝑛
1. Model selection (rating curve)
steady state conditions
uniform flow
constant roughness
simplified cross section
If

5. 2. Sampling of the parameter space
𝑸 ≅ 𝒄(𝒉 − 𝒉 𝟎) 𝒏

6. Pappenberger et al., 2006
3. Assessment of a quality measure

7. 3. Assessment of a quality measure
40 41 42 43 … 97 98 99 100 101
1 0 0 0 0 … 0 0.67 0.67 1 0
2 0 0 0 1 … 0 0 0 0 0
3 0 0 0.5 1 … 1 1 1 1 1
… … … … … … … … … … …
1200000 0 0 0 1 … 0 0 0 0 0.17
1200001 1 1 0.83 1 … 1 1 1 1 1
1200002 0 0.83 1 1 … 1 1 1 1 1
Pappenberger et al., 2006
Sorted h-Q data points
ParametersetsParametersets

8. 40 41 42 43 … 97 98 99 100 101
1 0 0 0 0 … 0 0.67 0.67 1 0
2 0 0 0 1 … 0 0 0 0 0
3 0 0 0.5 1 … 1 1 1 1 1
… … … … … … … … … … …
1200000 0 0 0 1 … 0 0 0 0 0.17
1200001 1 1 0.83 1 … 1 1 1 1 1
1200002 0 0.83 1 1 … 1 1 1 1 1
4. Assignment of tolerance degrees
Sorted h-Q data points
Parametersets
10%
data points
allowed
with
quality=0
• Model structural uncertainty
• Data outliers

9. 5. Assessment of bidirectional reach
40 41 42 43 … 97 98 99 100 101
1 0 0 0 0 … 0 0.67 0.67 1 0
2 0 0 0 1 … 0 0 0 0 0
3 0 0 0.5 1 … 1 1 1 1 1
… … … … … … … … … … …
1200000 0 0 0 1 … 0 0 0 0 0.17
1200001 1 1 0.83 1 … 1 1 1 1 1
1200002 0 0.83 1 1 … 1 1 1 1 1
40 41 42 43 … 97 98 99 100 101
1 0 0 0 0 … 0 0.67 0.67 1 0
2 0 0 0 1 … 0 0 0 0 0
3 0 0 0.5 1 … 1 1 1 1 1
… … … … … … … … … … …
1200000 0 0 0 1 … 0 0 0 0 0.17
1200001 1 1 0.83 1 … 1 1 1 1 1
1200002 0 0.83 1 1 … 1 1 1 1 1
40 41 42 43 … 97 98 99 100 101
1 0 0 0 0 … 0 0.67 0.67 1 0
2 0 0 0 1 … 0 0 0 0 0
3 0 0 0.5 1 … 1 1 1 1 1
… … … … … … … … … … …
1200000 0 0 0 1 … 0 0 0 0 0.17
1200001 1 1 0.83 1 … 1 1 1 1 1
1200002 0 0.83 1 1 … 1 1 1 1 1
Left reach
98
40 41 42 43 … 97 98 99 100 101
1 0 0 0 0 … 0 0.67 0.67 1 0
2 0 0 0 1 … 0 0 0 0 0
3 0 0 0.5 1 … 1 1 1 1 1
… … … … … … … … … … …
1200000 0 0 0 1 … 0 0 0 0 0.17
1200001 1 1 0.83 1 … 1 1 1 1 1
1200002 0 0.83 1 1 … 1 1 1 1 1
Left reach
98
-
40 41 42 43 … 97 98 99 100 101
1 0 0 0 0 … 0 0.67 0.67 1 0
2 0 0 0 1 … 0 0 0 0 0
3 0 0 0.5 1 … 1 1 1 1 1
… … … … … … … … … … …
1200000 0 0 0 1 … 0 0 0 0 0.17
1200001 1 1 0.83 1 … 1 1 1 1 1
1200002 0 0.83 1 1 … 1 1 1 1 1
Left reach
98
-
42
…
-
27
30
Sorted h-Q data points
Parametersets
10%
data points
allowed
with
quality=0

10. • Model structural uncertainty
• Data outliers
10%
data points
allowed
with
quality=0
4. Assignment of tolerance degrees

11. 6. Identification of consistent data periods

12. -1 m
-1 m
+2 m
Validation: synthetic data
• Simulation with hydrodynamic model: 2 geometries
• Selection of (random) transition date
• Selection of Q/h results before and after transition
• Add noise (observational uncertainty)
 Capability to detect transition point?

13. Validation: synthetic data

14. Validation: observational uncertainty
Pappenberger et al., 2006

15. Validation: observ. Uncertainty (4x σ)

16. Validation: model deficiency

17. BReach: conclusions
Robust methodology
• Validated
• Little dependency of subjective choices
• Flexibility
Possible applications:
• Temporal variability
• Dependency of a variable
• NO assessment of parameter values

18. (near) future
BReach(t) – BReach(h):
• Variety of Q stations (Flanders, UK, Sweden)
Other models:
• Hydrological
• Hydraulic

19. Questions
Are there any questions/remarks?
Locations for BReach analysis in Belgium?