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1 Lawrence Berkeley National Laboratory, University of California, Earth Sciences Division 2 University of Oslo, Department of Geophysics,

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Presentation on theme: "1 Lawrence Berkeley National Laboratory, University of California, Earth Sciences Division 2 University of Oslo, Department of Geophysics,"— Presentation transcript:

1 1 Lawrence Berkeley National Laboratory, University of California, Earth Sciences Division 2 University of Oslo, Department of Geophysics, nilsotto@geofysikk.uio.no Simulating Unsaturated Flow Fields Based on Ground Penetrating Radar and Saturation Measurements Stefan Finsterle 1 andNils-Otto Kitterød 2

2 Purpose: Estimate unsaturated flow velocities by inverse modelling of flow parameters conditioned on soil moisture content and Ground Penetrating Radar Why soil moisture? Why unsaturated flow? Why inverse modelling? Why Ground Penetrating Radar? Why do a tracer test?

3 Why unsaturated flow? Protection of groundwater resources The Gardermoen airport

4 The Moreppen research station Oslo Airport Gardermoen 4 km 2 km

5 Residence time? On the runways (acetate, formeate) On the airplanes (glycol) Consumption of ~ 400 mill. liter/year Deicing chemical Jet fuel Main problem: Good remediation potential in the unsaturated zone (oxygen is the best electron acceptor) However:

6 Why Ground Penetrating Radar? Electromagnetic Wave Propagation  2 = j  (  + j  )  Soil moisture content,  :  = f(  ) Sedimentological heterogeneities Most important in unsaturated zone

7 Oslo Airport Gardermoen railway runways utm-E utm-N 616 000618 000 6672500 6674500 6676500 Moreppen research site 10m N Moreppen research site 615,750615,800 6,677,740 6,677,760 6,677,780 6,677,800 6,677,820 6,677,840 p42 p44 p46 p48 p33 p41 p43 p45 p47 p35

8 p47 Delta topset Delta foreset What did we see?Cross section of a delta Delta bottomset Iso-crones Delta foreset Delta topset Sea level (~10.000 BP)

9 p47 p45 p43 p41 GPR profiles p41 p43 p45 p47 Moreppen N 10 m

10 Why GPR? geological architecture  depth [m] 0 2 4 02040 West- East position [m] Significance of heterogeneities to flow? soil moisture content, because  = f(  )   inverse modeling

11 Why soil moisture? easy  high resolution in space  continuous in time  (compared to other variables) satellite radar  GPR profiles p41 p43 p45 p47 Moreppen N 10 m N12 N10 N18 N20 N34 N32 N30 N40 N38 N36 N46 N44 N42 N12 N10 N18 N20 N34 N32 N30 N40 N38 N36 N46 N44 N42 GPR(44)GPR(46) GPR(47) GPR(45) 5 m

12 soil moisture content 0.2 m below the surface Moreppen, delta topset May 11. 1995 vol% H 2 O 3.0 29.8 interpolation in 3D

13 soil moisture content 0.3 m below the surface Moreppen, delta topset May 11. 1995 vol% H 2 O 3.0 29.8

14 soil moisture content 0.5 m below the surface Moreppen, delta topset May 11. 1995 vol% H 2 O 3.0 29.8

15 soil moisture content 1.0 m below the surface Moreppen, delta topset May 11. 1995 vol% H 2 O 3.0 29.8

16 soil moisture content 1.5 m below the surface Moreppen, delta topset May 11. 1995 vol% H 2 O 3.0 29.8

17 soil moisture content 2.0 m below the surface Moreppen, delta topset May 11. 1995 vol% H 2 O 3.0 29.8

18 soil moisture content 2.5 m below the surface Moreppen, delta foreset May 11. 1995 vol% H 2 O 3.0 29.8

19 soil moisture content 3.0 m below the surface Moreppen, delta foreset May 11. 1995 vol% H 2 O 3.0 29.8

20 soil moisture content 3.5 m below the surface Moreppen, delta foreset May 11. 1995 vol% H 2 O 3.0 29.8

21 soil moisture content 3.7 m below the surface Moreppen, below groundwater table May 11. 1995 vol% H 2 O 3.0 29.8

22 soil moisture content Moreppen, fence diagram May 11. 1995 vol% H 2 O 3.0 29.8

23 Why inverse modeling? honor observations  include a priori information  consistent homogenization  question of scale!!

24 find model parameters that minimize | cal. – obs. | Inverse modeling: k abs,S r, 1/ , n |  calc –  obs |

25 depth (m) 0 -2 -3 2 4 6 8 10 12 depth (m) 0 -2 -3 2 4 6 8 10 12 top1 top2 dip1 dip2 dry saturated ~ 0.5 sat. depth (m) 0 -2 -3 2 4 6 8 10 12 c11c16

26 top1 top2 dip1 dip2 observed most likely with uncertanty c11 and c16 are the conditioning wells

27  obs –  calc for the whole flow domain

28 Why do a tracer test? validate model parameters by independent observations  Primary observations is reproduced are we able to reproduce (or make forecasts) of non-observed variables?, but

29 GPR profiles p41 p43 p45 p47 Moreppen N 10 m GPR profiles p41 p43 p45 p47 Moreppen N 10 m

30 Lysimeter trench GPR profiles p41 p43 p45 p47 Moreppen N 10 m Prenart probe

31 3.5 m 6 m 2.3 m Background, 48 mm/day, through the dripper lines Bromide (Br) Tritiated water (HTO)

32

33 depth (m) 0 -2 -3 0 -2 -3 2 4 6 8 10 12 0 -2 -3 day 1 day 2 day 3

34 0.00 0.20 0.40 0.60 0.80 1.00 F(x) for [Br] and [HTO] 0.005.0010.0015.0020.0025.0030.00 time Søvik and Alfnes et al. (2001) Moreppen tracer test -1.82 m (Br) -1.83 m (Br) -2.95 m (Br) -3.09 m (Br) -3.30 m (Br) -1.78 m (HTO) -2.49 m (HTO) -2.95 m (HTO) -3.09 m (HTO) -3.30 m (HTO) 1.8 m iso 2.8 m iso 3.3 m iso 1.8 m ani 2.8 m ani 3.3 m ani

35 Future work 1) Preferential flow How much ? How fast? 0.0 0.2 0.4 0.6 0.8 1.0 F(x) for [Br] and [HTO] 051015202530 time -2.48 m (Br) -2.84 m (Br) 2)Effective parameters

36 0 -2 -3 2 4 6 8 10 12 homogeneous anisotropic heterogeneous isotropic

37 c a b

38 breakthrough curves (42 mm/d infiltration) time (days) 789 101112 number of particles 10 15 5 heterogeneous isotropic (case a) pressure (all) pressure and saturation saturation (no dip2) pressure (no dip2) homogeneous anisotropic saturation (all)


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