Föreläsning på Grundvattendagarna 2013

1. Hydrogeological classification as a tool to support
regional scale groundwater assessment and
modelling
Roland Barthel 1 , Luis E. Samaniego 2 , Rohini Kumar 2 , Deliang Chen 1 , Andras Bardossy 3
1 Department
of Earth Sciences, University of Gothenburg, Gothenburg, Sweden.
2 Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany.
3 Institute for Modelling Hydraulic and Environmental Systems, Universitaet Stuttgart, Stuttgart,
Germany.
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
1

2. Starting point and motivation
•
Why the regional scale?
–
Integrated water resources management
–
European Water Framework Directive
–
Climate Change impact assessment
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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3. Starting point and motivation
•
Problems with regional scale hydrogeology:
–
Groundwater observations wells provide very local
information at distinct points and are usually scarce and/or
clustered
–
It is often difficult to decide how representative a groundwater
observation well is
–
It is often difficult to decide if changes in groundwater
observations are the result of natural or anthropogenic
sources
–
Groundwater models are needed but require detailed
representative data for parameterization and calibration
everywhere
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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4. Summary of the challenges at the regional scale:
 High demand for regional scale groundwater assessment and
modeling; but the available “raw” data does often not support
this task
•
Is it possible to make predictions and assessments on the regional
scale without using complex numerical models?
•
Can we improve numerical models using “unconventional”
information?
•
How can we make better use of the existing information, of all the
groundwater data we find in our archives?
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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5. Example data set: Upper Danube Catchment (Germany)
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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6. Data availability and spatial distribution
Upper Danube Catchment, Southern Germany,
80,000 km2, ~2000 Groundwater observation wells
>10years, at least weekly measurements
Shallow
alluvial aquifer
Obs. well
River
Regional unconfined aquifer
?
Regional, confined aquifer
?
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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7. Research Question
• Is it possible to fill these “white spaces” using
hydrogeological classification?
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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8. Groundwater “behavior” (time series of groundwater observations): Southern Germany
GlowaID: 373
GlowaID: 324
GlowaID: 233
4
4
2
2
2
0
-2
-4
1979
GWL
6
GWL
6
4
GWL
6
0
-2
1983
1987
1991
1995
1999
2003
2007
-4
1979
0
-2
1983
GlowaID: 260
1987
1991
1995
1999
2003
-4
1979
2007
1995
1999
2003
2007
1999
2003
2007
1999
2003
2007
2
2
0
-4
1979
GWL
4
2
-2
0
-2
1983
1987
1991
1995
1999
2003
2007
-4
1979
0
-2
1983
GlowaID: 1285
1987
1991
1995
1999
2003
-4
1979
2007
1983
GlowaID: 1252
1987
1991
1995
GlowaID: 95
6
4
4
4
2
2
2
0
GWL
6
GWL
6
GWL
1991
6
4
GWL
GWL
6
4
0
-2
-2
-4
1979
-4
1979
1983
1987
1991
1995
1999
2003
2007
0
-2
1983
GlowaID: 1693
1987
1991
1995
1999
2003
-4
1979
2007
1983
GlowaID: 1714
1987
1991
1995
GlowaID: 2454
6
4
4
2
2
2
0
-2
-4
1979
GWL
6
4
GWL
6
GWL
1987
GlowaID: 1440
6
0
-2
1983
1987
1991
1995
1999
2003
2007
-4
1979
0
-2
1983
GlowaID: 2563
1987
1991
1995
1999
2003
-4
1979
2007
1983
GlowaID: 1618
1987
1991
1995
1999
2003
2007
1999
2003
4
2
2
2
0
-2
-4
1979
GWL
6
4
GWL
6
4
All time series are 30 years
long and normalized so that
mean = 0 and standard
deviation = 1
2007
GlowaID: 4417
6
GWL
1983
GlowaID: 564
0
-2
1983
1987
1991
Barthel et al.
1995
1999
2003
2007
-4
1979
0
-2
1983
1987
1991
1995
1999
2003
2007
-4
1979
1983
1987
1991
1995
Grundvattendagarna 16-17 oktober 2013 i Lund
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9. Classification of time series
GlowaID: 373
GlowaID: 324
GlowaID: 233
4
4
2
2
2
0
-2
-4
1979
GWL
6
GWL
6
4
GWL
6
0
-2
1983
1987
1991
1995
1999
2003
2007
-4
1979
0
-2
1983
GlowaID: 260
1987
1991
1995
1999
2003
-4
1979
2007
1995
1999
2003
2007
1999
2003
2007
1999
2003
2007
2
2
0
-4
1979
GWL
4
2
-2
0
-2
1983
1987
1991
1995
1999
2003
2007
-4
1979
0
-2
1983
GlowaID: 1285
1987
1991
1995
1999
2003
-4
1979
2007
1983
GlowaID: 1252
1987
1991
1995
GlowaID: 95
6
4
4
4
2
2
2
0
GWL
6
GWL
6
GWL
1991
6
4
GWL
GWL
6
4
0
-2
-2
-4
1979
-4
1979
1983
1987
1991
1995
1999
2003
2007
0
-2
1983
GlowaID: 1693
1987
1991
1995
1999
2003
-4
1979
2007
1983
GlowaID: 1714
1987
1991
1995
GlowaID: 2454
6
4
4
2
2
2
0
GWL
6
4
GWL
6
GWL
1987
GlowaID: 1440
6
0
-2
-2
-4
1979
-4
1979
1983
1987
1991
1995
1999
2003
2007
0
-2
1983
GlowaID: 2563
1987
1991
1995
1999
2003
-4
1979
2007
1983
GlowaID: 1618
1987
1991
1995
1999
2003
2007
1999
2003
4
2
2
2
0
-2
-4
1979
GWL
6
4
GWL
6
4
7 main groups of
different behavior based
on spectral analysis
2007
GlowaID: 4417
6
GWL
1983
GlowaID: 564
0
-2
1983
1987
1991
Barthel et al.
1995
1999
2003
2007
-4
1979
0
-2
1983
1987
1991
1995
1999
2003
2007
-4
1979
1983
1987
1991
1995
Grundvattendagarna 16-17 oktober 2013 i Lund
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10. Why are some time series more similar than others?
1. Often, but not always, similar time series are from observation wells
which are close to each other
2. Very often, similar time series are from observation wells which are
located in similar hydrogeological settings
 Similar hydrogeological settings  similar behavior, similar time
series
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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11. How can classification help?
Classified
Input Type:
Recharge
Classified
Groundwater System Type
Classifiable / Predictable
Response Type:
Groundwater Level
6
1
GWL
4
0
Jan
Dec
unconfined
shallow
2
0
-2
-4
1979
1983
1987
1991
1995
1999
2003
2007
long term time series (30 years)
1
6
0
GWL
4
Jan
Dec
2
0
-2
-4
1979
1983
1987
1991
1995
1999
2003
2007
unconfined
deep
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
11

12. Groundwater “behavior” (time series of groundwater observations): Southern Germany
GlowaID: 373
GlowaID: 324
GlowaID: 233
4
4
2
2
2
0
-2
-4
1979
GWL
6
GWL
6
4
GWL
6
0
-2
1983
1987
1991
1995
1999
2003
2007
-4
1979
0
-2
1983
GlowaID: 260
1987
1991
1995
1999
2003
-4
1979
2007
1995
1999
2003
2007
1999
2003
2007
1999
2003
2007
2
2
0
-4
1979
GWL
4
2
-2
0
-2
1983
1987
1991
1995
1999
2003
2007
-4
1979
0
-2
1983
GlowaID: 1285
1987
1991
1995
1999
2003
-4
1979
2007
1983
GlowaID: 1252
1987
1991
1995
GlowaID: 95
6
4
4
4
2
2
2
0
GWL
6
GWL
6
GWL
1991
6
4
GWL
GWL
6
4
0
-2
-2
-4
1979
-4
1979
1983
1987
1991
1995
1999
2003
2007
0
-2
1983
GlowaID: 1693
1987
1991
1995
1999
2003
-4
1979
2007
1983
GlowaID: 1714
1987
1991
1995
GlowaID: 2454
6
4
4
2
2
2
0
-2
-4
1979
GWL
6
4
GWL
6
GWL
1987
GlowaID: 1440
6
0
-2
1983
1987
1991
1995
1999
2003
2007
-4
1979
0
-2
1983
GlowaID: 2563
1987
1991
1995
1999
2003
-4
1979
2007
1983
GlowaID: 1618
1987
1991
1995
1999
2003
2007
1999
2003
4
2
2
2
0
-2
-4
1979
GWL
6
4
GWL
6
4
All time series are 30 years
long and normalized so that
mean = 0 and standard
deviation = 1
2007
GlowaID: 4417
6
GWL
1983
GlowaID: 564
0
-2
1983
1987
1991
Barthel et al.
1995
1999
2003
2007
-4
1979
0
-2
1983
1987
1991
1995
1999
2003
2007
-4
1979
1983
1987
1991
1995
Grundvattendagarna 16-17 oktober 2013 i Lund
12

13. Is all this particular to the data sets from Southern Germany?
?
All time series are 30
years long and
normalized so that mean
= 0 and standard
deviation = 1
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
13

14. Summary
1. It becomes obvious that many groundwater observation wells
show similar behavior, so that we can form groups of
groundwater observation wells that behave the same way.
2. The similarity of the behavior can be related to a similarity of the
hydrogeological setting
 Similar hydrogeology creates similar behavior  knowing this
allows us to predict the behavior of groundwater at a location
with known hydrogeology but no observations
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
14

15. Workflow of our proposed research approach:
1. Comparative analysis and classification of groundwater
time series  group groundwater observations together
based on their similarity
2. Classification of groundwater systems  group
hydrogeological settings based on the similarity of the
hydrogeological situation
3. Determine the dependencies between the resulting
groups
4. Predict the behavior of locations with no observations
based on the found dependencies
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
15

16. Workflow of our proposed research approach:
1. Comparative analysis and classification of groundwater
time series  group groundwater observations together
based on their similarity
2. Classification of groundwater systems  group
hydrogeological settings based on the similarity of the
hydrogeological situation
3. Determine the dependencies between the resulting
groups
4. Predict the behavior of locations with no observations
based on the found dependencies
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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17. Making use of existing classification schemes
Hydrogeological type settings
Stejmar-Eklund, H., 2002
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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18. Predictions of behavior based on classification hydrogeological settings
Swedish National Atlas, Volume12,
Berg och Jord, SNA, 2009
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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19. Groundwater chemistry as additional information
Correlation between NO3- and groundwater level
GWS (m ü. NN)
NO3 (mg/l)
46
44
42
40
38
36
34
32
30
28
26
NO3 (mg/l)
NO3 (mg/l)
55
90
50
80
70
45
60
40
50
40
35
30
30
20
groundwaterlevel (m a.s.l)
572.0
571.5
571.0
570.5
570.0
569.5
569.0
568.5
568.0
567.5
567.0
GWS (m ü. NN) 582.0
219.0
581.5
218.0
581.0
217.0
580.5
216.0
215.0
580.0
214.0
579.5
NO3 (mg/l)
213.0
groundwaterlevel (m a.s.l)
10
579.0
25
NO3 (mg/l)
groundwaterlevel (m a.s.l)
0
1990 1992 1994 1996 1998 1999 2001 2003 2005 2007 212.0
1990 1992 1994 1996 1998 e
tim1999 2001 2003 2005 2007
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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20. Groundwater chemistry: additional information to classify groundwater observations
StationID: 5154
6
NO3, EC , O2
4
Nitrate
Dissolved Oxygen
Electric Conductivity
2
0
-2
-4
1990
1994
1998
2002
2006
Time [Date]
StationID: 7196
StationID: 16839
4
NO3, EC , O2
6
4
NO3, EC , O2
6
2
0
2
0
-2
-2
-4
1990
-4
1990
1994
1998
Time [Date]
2002
2006
1994
1998
2002
2006
Time [Date]
All positively correlated - only two out of three correlated etc.
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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21. Conclusions
•
Hydrogeological classification is possible, and can be based on existing
concepts
•
What is new, is the combination of hydrogeological classification with
the classification of the dynamic behavior (quantity and chemistry)
•
It requires both:
– Advanced statistical tools
– And “traditional” geological expertise
•
Classification of groundwater systems and systematic use of similarity
of groundwater observations:
– Might help to replace complex numerical models where they are not feasible
– Can provide tools for the improvement and validation of numerical models
•
A wide range of applications in regional hydrogeology is possible, e.g.
– Prediction of climate change impacts
– Separation of natural and human impacts
– Assessment of regional planning instruments (RBMs, WFD)
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
21

22. Hydrogeological classification as a tool to support regional scale
groundwater assessment and modelling
Roland Barthel 1 , Luis E. Samaniego 2 , Rohini Kumar 2 , Deliang Chen 1 , Andras Bardossy 3
1 Department
of Earth Sciences, University of Gothenburg, Gothenburg, Sweden.
2 Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany.
3 Institute for Modelling Hydraulic and Environmental Systems, Universitaet Stuttgart, Stuttgart,
Germany.
Thank you for your attention!
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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23. How to deal with anthropogenic influences
GlowaID: 81
GlowaID: 179
4
GlowaID: 183
4
2
2
2
0
GWL
GWL
GWL
0
-2
-2
-4
1979
-2
-4
1983
1987
1991
1995
1999
-4
1979
2003
1983
1987
GlowaID: 376
1991
1995
1999
2003
-6
1979
2007
4
-2
-4
2
-2
1988
1999
2003
2007
2
0
1992
GlowaID: 284
1996
2000
-2
1973 1977 1981 1985 1989 1993 1997 2001 2005
2004
GlowaID: 797
GlowaID: 1667
6
4
4
4
2
2
2
0
-2
-4
1979
GWL
6
GWL
6
GWL
1995
4
0
-6
1967 1971 1975 1979 1983 1987 1991 1995 1999
1991
6
GWL
GWL
6
0
1987
GlowaID: 1717
8
2
0
-2
1983
1987
1991
1995
1999
2003
-4
1979
2007
Quasi-continuously
0
-2
1983
GlowaID: 1939
1987
1991
1995
1999
2003
-4
1979
2007
1983
GlowaID: 765
1987
1991
1995
1999
2003
2007
GlowaID: 530
6
4
4
2
2
Changes of
variance
4
2
0
-2
-4
1979
GWL
6
GWL
6
GWL
1983
GlowaID: 677
4
GWL
0
0
-2
1983
1987
1991
Barthel et al.
1995
1999
2003
2007
-4
1979
0
Dis-continuously
-2
1983
1987
1991
1995
1999
2003
2007
-4
1979
1983
1987
1991
1995
Grundvattendagarna 16-17 oktober 2013 i Lund
1999
2003
2007
23

24. Factors controlling the transient response and dependencies of parameters
Z
?
X
Barthel et al.
Grundvattendagarna 16-17 oktober 2013 i Lund
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