hydrogeological classification roland barthel

Grundvattendagarna 16-17 oktober 2013 i LundBarthel et al. 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.


Starting point and motivation

• Why the regional scale?

– Integrated water resources management

– European Water Framework Directive

– Climate Change impact assessment


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


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?


Example data set: Upper Danube Catchment (Germany)


Data availability and spatial distribution

Upper Danube Catchment, Southern Germany, 80,000 km2, ~2000 Groundwater observation wells >10years, at least weekly measurements

Regional, confined aquifer

Obs. well

River

Shallow alluvial aquifer

Regional unconfined aquifer

?

?


Research Question

• Is it possible to fill these “white spaces” using

hydrogeological classification?


Groundwater “behavior” (time series of groundwater observations): Southern Germany

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1285

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1252

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 95

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1693

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1714

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 2454

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 2563

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1618

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 4417

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 373

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 324

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 233

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 260

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 564

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1440

All time series are 30 years long and normalized so that mean = 0 and standard deviation = 1


Classification of time series

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1285

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1252

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 95

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1693

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1714

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 2454

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 2563

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1618

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 4417

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 373

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 324

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 233

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 260

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 564

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1440

7 main groups of different behavior based on spectral analysis


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 arelocated in similar hydrogeological settings

Similar hydrogeological settings similar behavior, similar time series


How can classification help?

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

unconfinedshallow

Classified Groundwater System Type

Classifiable / Predictable Response Type: Groundwater Level

Classified Input Type: Recharge

1

0Jan Dec

1

0Jan Dec

unconfineddeep

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

long term time series (30 years)


Groundwater “behavior” (time series of groundwater observations): Southern Germany

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1285

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1252

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 95

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1693

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1714

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 2454

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 2563

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1618

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 4417

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 373

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 324

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 233

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 260

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 564

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1440



Is all this particular to the data sets from Southern Germany?

?



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


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


Making use of existing classification schemes

Stejmar-Eklund, H., 2002

Hydrogeological type settings


Predictions of behavior based on classification hydrogeological settings

Swedish National Atlas, Volume12,Berg och Jord, SNA, 2009


2628303234363840424446

567.0567.5568.0568.5569.0569.5570.0570.5571.0571.5572.0

NO3 (mg/l) groundwaterlevel (m a.s.l)

25

30

35

40

45

50

55

1990 1992 1994 1996 1998 1999 2001 2003 2005 2007time

579.0

579.5

580.0

580.5

581.0

581.5

582.0

NO3 (mg/l)groundwaterlevel (m a.s.l)

NO3 (mg/l) GWS (m ü. NN)

Correlation between NO3- and groundwater level

Groundwater chemistry as additional information

0

10

20

30

40

50

60

70

80

90

1990 1992 1994 1996 1998 1999 2001 2003 2005 2007212.0

213.0

214.0

215.0

216.0

217.0

218.0

219.0

NO3 (mg/l) groundwaterlevel (m a.s.l)

NO3 (mg/l) GWS (m ü. NN)


Groundwater chemistry: additional information to classify groundwater observations

-4

-2

0

2

4

6

1990 1994 1998 2002 2006

NO3, EC , O

2

Time [Date]

StationID: 5154

-4

-2

0

2

4

6

1990 1994 1998 2002 2006

NO3, EC , O

2

Time [Date]

StationID: 16839

-4

-2

0

2

4

6

1990 1994 1998 2002 2006

NO3, EC , O

2

Time [Date]

StationID: 7196

All positively correlated - only two out of three correlated etc.

NitrateDissolved OxygenElectric Conductivity


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)


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!


How to deal with anthropogenic influences

-4

-2

0

2

4

1979 1983 1987 1991 1995 1999 2003

GWL

GlowaID: 81

-4

-2

0

2

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 179

-6

-4

-2

0

2

4

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 183

-6

-4

-2

0

2

4

1967 1971 1975 1979 1983 1987 1991 1995 1999

GWL

GlowaID: 376

-2

0

2

4

6

8

1988 1992 1996 2000 2004

GWL

GlowaID: 677

-2

0

2

4

6

1973 1977 1981 1985 1989 1993 1997 2001 2005

GWL

GlowaID: 1717

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 284

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1939

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 797

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 1667

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 765

-4

-2

0

2

4

6

1979 1983 1987 1991 1995 1999 2003 2007

GWL

GlowaID: 530

Changes of variance

Quasi-continuously

Dis-continuously


Factors controlling the transient response and dependencies of parameters

?

Z

X

hydrogeological classification roland barthel

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