Minimally invasive monitoring of soil-plant interactions: new perspectives

1. MINIMALLY INVASIVE MONITORING OF SOIL-
PLANT INTERACTIONS:
NEW PERSPECTIVES
Giorgio Cassiani
Dipartimento di Geoscienze, Università di Padova, Italy
giorgio.cassiani@unipd.it

2. SUMMARY
q Soil-plant-atmosphere interactions
q Characterization of the Earth’s critical zone: the role of
non-invasive monitoring
q Large-scale monitoring
q Small-scale monitoring
q Outlook: assimilate data and models, with a vision
q Conclusions

3. SUMMARY
q Soil-plant-atmosphere interactions
q Characterization of the Earth’s critical zone: the role of
non-invasive monitoring
q Large-scale monitoring
q Small-scale monitoring
q Soil – plant interaction modelling
q Conclusions and outlook

4. The Earth’s Critical Zone
Na#onal
Research
Council
(2001)
The Earth’s Critical Zone (CZ) is the thin outer
veneer of our planet from the top of the tree
canopy to the bottom of our drinking water aquifers.
The CZ supports almost all human activity.
Understanding, predicting and managing
intensification of land use and associated economic
services, while mitigating and adapting to rapid
climate change and biodiversity decline, is now one
of the most pressing societal challenges of the 21st
century.
Particular attention shall be devoted to the soil-
plant-atmosphere (SPA) interactions.
mass
energy

5. Soil-plant-atmosphere interactions are important
Pe
Pi
P
ET
Atmospheric
Input
Atmospheric
Output
Incoming
Runoff
Outgoing
Runoff
Study Region
Global water cycle
Regional water recycling
Terrestrial
Carbon
cycle
Crop responses to… courtesy:
M.
Marani

6. vegetated
soil
Soil moisture dynamics in vegetated and bare soils
Volpeetal.,2013
bare
soil
courtesy:
M.
Marani

7. Transpiration
and Photosynthesis
courtesy:
M.
Marani

8. Importance of root
distribution (li) in determining
overall resistance to flow.
courtesy:
M.
Marani

9. Geophysical techniques, combined with flow and
transport models, can provide a major step
forward in the ECZ characterization
Key idea

10. SUMMARY
q Soil-plant-atmosphere interactions
q Characterization of the Earth’s critical zone: the role of
non-invasive monitoring
q Large-scale monitoring
q Small-scale monitoring
q Outlook: assimilate data and models, with a vision
q Conclusions

11. water table
aquifer confining layer
impermeable
bedrock
small scalelarge scale
What geophysical methods can help define
q structure / texture

12. water table
spring
evapo-transpiration
water table
aquifer confining layer
impermeable
bedrock
small scalelarge scale
q structure / texture
q fluid-dynamics
What geophysical methods can help define

13. Geophysical
measurements
Physical
model
(e.g hydrologic)
physical
parameters
(e.g. hydraulic
conductivity)
dynamics
(fluids,
temperature)
structure
(geometry,
geology)
Integrate measurements and physical models that explain the space-
time evolution of state variables (e.g. moisture content, solute
concentration and temperature) that affect the space-time changes
of geophysical response.
GOAL

14. SUMMARY
q Soil-plant-atmosphere interactions
q Characterization of the Earth’s critical zone: the role of
non-invasive monitoring
q Large-scale monitoring
q Small-scale monitoring
q Outlook: assimilate data and models, with a vision
q Conclusions

15. Digital Soil Mapping

16. Bregonze Hills
Bregonze project description
Goal: characterize hydrological response of
a small hill catchment in the Veneto pre-Alps
Geology:
altered volcanic rocks
(basalts, tuffs, breccias)
catchment boundaries

17. Bregonze catchment
Small, self-contained primary catchment,
with mild slope and grass cover
Only the stream bed is populated by high
trees and dense vegetation.
April
April
Frequency-domain
electromagnetics

18. 18/08/2014
creek
Frequency-Domain
Electro-Magnetics
Resistivity map obtained
using a GF Instrument
CMD 1 sonde:
max investigation depth
0.75 m

19. 02/09/2014
Frequency-Domain
Electro-Magnetics
Resistivity map obtained
using a GF Instrument
CMD 1 sonde:
max investigation depth
0.75 m
creek

20. 22/09/2014
Frequency-Domain
Electro-Magnetics
Resistivity map obtained
using a GF Instrument
CMD 1 sonde:
max investigation depth
0.75 m
creek

21. 10/10/2014
Frequency-Domain
Electro-Magnetics
Resistivity map obtained
using a GF Instrument
CMD 1 sonde:
max investigation depth
0.75 m
creek

22. Matching model predictions and EM data
Monitoring over time and space
the soil moisture conditions
(e.g. via FDEM) can give
critical information for model calibration
Full scale 3D catchment model
(CATHY)

23. AGRIS San Michele experimental farm - Ussana - Sardinia
field 21
field 11
FP7 EU
collaborative project

24. Digital soil mapping using frequency-domain EM

25. Soil texture pattern effect - ECa
Electrical conductivity
(mS/m)

26. Soil texture pattern effect – gamma ray spectrometry
doserate
[mG/hr]

27. 508700 508750 508800 508850 508900 508950
Easting (m)
May 18, 2009
4362500
4362550
4362600
4362650
4362700
4362750
Northing(m)
0
5
10
15
20
25
30
35
40
45
50
electrical
conductivity
mS/m
Soil texture

28. 508650 508700 508750 508800 508850 508900 508950 509000
UTM easting (m)
total dose rate (nG/h)
4362450
4362500
4362550
4362600
4362650
4362700
4362750
4362800
UTMnorthing(m)
15
20
25
30
35
40
45
50
55
60
65
70
75
field 21
508975, 4362850
508585, 4362460
+
+
508650 508700 508750 508800 508850 508900 508950 509000
UTM easting (m)
CaCO3 %
4362450
4362500
4362550
4362600
4362650
4362700
4362750
4362800
UTMnorthing(m)
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
32
34

29. 508700 508750 508800 508850 508900 508950
Easting (m)
May 18, 2009
4362500
4362550
4362600
4362650
4362700
4362750
Northing(m)
0
5
10
15
20
25
30
35
40
45
50
electrical
conductivity
mS/m
Field 21 – May 18, 2009

30. 508700 508750 508800 508850 508900 508950
Easting (m)
June 15, 2009
4362500
4362550
4362600
4362650
4362700
4362750
Northing(m)
0
5
10
15
20
25
30
35
40
45
50
electrical
conductivity
mS/m
Field 21 – June 15, 2009

31. 508700 508750 508800 508850 508900 508950
Easting (m)
March 31, 2010
4362500
4362550
4362600
4362650
4362700
4362750
Northing(m)
0
5
10
15
20
25
30
35
40
45
50
electrical
conductivity
mS/m
Field 21 – March 31, 2010

32. 508700 508750 508800 508850 508900 508950
Easting (m)
May 19, 2010
4362500
4362550
4362600
4362650
4362700
4362750
Northing(m)
0
5
10
15
20
25
30
35
40
45
50
electrical
conductivity
mS/m
Field 21 – May 19, 2010

33. 508700 508750 508800 508850 508900 508950
Easting (m)
February 3, 2011
4362500
4362550
4362600
4362650
4362700
4362750
Northing(m)
0
5
10
15
20
25
30
35
40
45
50
electrical
conductivity
mS/m
Field 21 – Feb 3, 2011

34. Time-lapse EM results
508700 508750 508800 508850 508900 508950
Easting (m)
May 19, 2010
4362500
4362550
4362600
4362650
4362700
4362750
Northing(m)
0
5
10
15
20
25
30
35
40
45
50
electrical
conductivity
mS/m
508700 508750 508800 508850 508900 508950
Easting (m)
May 18, 2009
4362500
4362550
4362600
4362650
4362700
4362750
Northing(m)
0
5
10
15
20
25
30
35
40
45
50
electrical
conductivity
mS/m
508700 508750 508800 508850 508900 508950
Easting (m)
May 19, 2010
4362500
4362550
4362600
4362650
4362700
4362750
Northing(m)
0
5
10
15
20
25
30
35
40
45
50
electrical
conductivity
mS/m
This area is considerably drier than the bare soil
area planted
with wheat
in January 2010

35. bare soil
bare soil
vegetated
soil
vegetated soil
a 507900 507950 508000 508050 508100 508150
UTM easting (m)
total dose rate (nG/h)
4362400
4362450
4362500
4362550
4362600
UTMnorthing(m)
95
97
99
101
103
105
107
109
b
c d
field 23 508265, 4362675
507935, 4362375
+
+

36. Fallow plotCultivated plot
alfalfa (Medicago sativa L.)

37. Field 11 – May 18 2010 – before irrigation
508015 508020 508025 508030 508035 508040 508045 508050 508055 508060 508065 508070
Easting (m)
Twin fields - background - May 18 2010
4362515
4362520
4362525
4362530
4362535
4362540
4362545
4362550
4362555
4362560
4362565Northing(m)
0
5
10
15
20
25
30
35
40
45
50
0
5
10
15
20
25
30
35
40
45
50
bare (fallow) soil
vegetated soil
508700 508750 508800 508850 508900 508950
Easting (m)
May 19, 2010
4362500
4362550
4362600
4362650
4362700
4362750
Northing(m)
0
5
10
15
20
25
30
35
40
45
50
electrical
conductivity
mS/m
ERT line 2
TDR probes
ERT line 1

38. 0.5 1 1.5 2 2.5 3 3.5 4 4.5
P0
-0.5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
0.5 1 1.5 2 2.5 3 3.5 4 4.5
P1
-0.5
0.5 1 1.5 2 2.5 3 3.5 4 4.5
P2
-0.5
0.5 1 1.5 2 2.5 3 3.5 4 4.5
P5
-0.5
0.5 1 1.5 2 2.5 3 3.5 4 4.5
P12
-0.5
0.5 1 1.5 2 2.5 3 3.5 4 4.5
NA0
-0.5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
0.5 1 1.5 2 2.5 3 3.5 4 4.5
NA1
-0.5
0.5 1 1.5 2 2.5 3 3.5 4 4.5
NA2
-0.5
0.5 1 1.5 2 2.5 3 3.5 4 4.5
NA5
-0.5
0.5 1 1.5 2 2.5 3 3.5 4 4.5
NA12
-0.5
0.5 1 1.5 2 2.5 3 3.5 4 4.5
NA0
-0.5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
0.5 1 1.5 2 2.5 3 3.5 4 4.5
NA1
-0.5
0.5 1 1.5 2 2.5 3 3.5 4 4.5
NA2
-0.5
0.5 1 1.5 2 2.5 3 3.5 4 4.5
NA5
-0.5
0.5 1 1.5 2 2.5 3 3.5 4 4.5
NA12
-0.5
electrical
resis#vity
(Ohm
m)
May
24
15:30
May
19
17:30
May
20
9:30
42
mm
irriga#on
during
night
13
mm
rainfall
during
night
May
20
12:30
May
21
10:30
line
2
bare
soil
line
1
vegetated
soil
meters
meters
meters
meters
meters
meters
meters
meters
meters
meters
meters
meters
meters
meters
meters
Vegetation changes the distribution of moisture content
and also the soil structure and its hydraulic properties

39. 0.12 0.16 0.2 0.24 0.28 0.32
theta (-)
-1
-0.8
-0.6
-0.4
-0.2
0
depth(m)
TDRs on May 19
TDRs on May 24
TRASE on May 19
ERT calibrated on May 19
ERT calibrated on May 24
Calibration of electrical resistivity tomography
inversion results against in situ time domain
reflectometry measurements of moisture content
over the vegetated plot.
The curves of moisture content as a function of
depth are obtained taking the horizontal averages
of the line 1 electrical resistivity tomography
resistivity images, transforming resistivity into
moisture content values using a Waxman and Smits
(1968) formulation.
0.1 1
saturation (-)
1
10
100
1000
resistivity(Ohmm)
Laboratory data on soil samples from the
San Michele farm (diamonds) compared against
the field-calibrated Waxman and Smits
relationship

40. 0.5 1 1.5 2 2.5 3 3.5 4 4.5
P12
-0.5
0.5 1 1.5 2 2.5 3 3.5 4 4.5
P12 entire sintetico
-0.5
0.5 1 1.5 2 2.5 3 3.5 4 4.5
P12 65 cm sintetico
-0.5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
Line
1:
synthe<c
(b)
May
24
15:30
Line
1:
measured
May
24
15:30
Line
1:
synthe<c
(a)
May
24
15:30
12 16 20 24 28
resistivity (Ohm m)
-2
-1.6
-1.2
-0.8
-0.4
0
depth(m)
synthetic (a):
extrapolated inverted profile
synthetic (b):
higher resistivity below 0.63 m
Sensitivity analysis with respect to the actual resistivity profile below 0.6 m,
that is, the depth down to which the electrical resistivity tomography inversion
is considered reliable.

41. moisture
content
(-­‐)
May
19
17:30
May
20
9:30
May
20
12:30
May
21
10:30
May
24
15:30
13
mm
precipita#on
during
night
42
mm
irriga#on
during
night
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
P0
-0.5
meters
0
0.025
0.05
0.075
0.1
0.125
0.15
0.175
0.2
0.225
0.25
0.275
0.3
4 4.5
0
0.025
0.05
0.075
0.1
0.125
0.15
0.175
0.2
0.225
0.25
0.275
0.3
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
P1
-0.5meters
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
P2
-0.5
meters
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
P5
-0.5
meters
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
P12
-0.5
meters
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
NA0
-0.5
meters
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
NA1
-0.5
meters
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
NA2
-0.5
meters
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
NA5
-0.5
meters
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
NA12
-0.5
meters
line
2
bare
soil
line
1
vegetated
soil

42. 33.544.5
%
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
125
% resistivity change w.r.t. background
(19/05/10)
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
line NA: 24/05/10 15:35
-0.5
meters
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
line NA: 23/05/10 9:40
-0.5
meters
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
line NA: 22/05/10 10:30
-0.5
meters
0.5 1 1.5 2 2.5 3 3.5 4 4.5
meters
line NA: 20/05/10 9:40
-0.5
meters
line
2:
bare
soil
(fallow
plot)
Complex behavior seems to call into play
important pore water salinity
(and old vs new water) issues

43. SUMMARY
q Soil-plant-atmosphere interactions
q Characterization of the Earth’s critical zone: the role of
non-invasive monitoring
q Large-scale monitoring
q Small-scale monitoring
q Outlook: assimilate data and models, with a vision
q Conclusions

44. TIME LAPSE MICRO-ERT in the Venice Lagoon

45. Aim:
are marsh
plants able to
induced a
permanent
aerated layer
when flooded ?
Marani et al.
2006, WRR
- 24 buried electrodes + 24 surface elect.
- 0.1 m spacing
- Time-lapse skip0 dip-dip (pre, during and
after flooding)
- 6 Tensiometers in depth
TIME LAPSE MICRO-ERT in the Venice Lagoon

46. July 2012 experiment: resistivity ratio with respect to background
at 3 time steps during marsh flooding
Dryer zone at
roots depthBoaga et al. 2014, GRL
TIME LAPSE MICRO-ERT in the Venice Lagoon

47. Dryer zone at
30-40 cm
depth
Water level
Confirmed by
tensiometers
TIME LAPSE MICRO-ERT in the Venice Lagoon
Boaga et al. 2014, GRL

48. Dryer zone at
roots depth
TIME LAPSE MICRO-ERT in the Venice Lagoon
Boaga et al. 2014, GRL

49. CLES, val di Non, Trentino
Noce catchment
apple orchard

50. sandy-silty soil with no clay

51. 4 PVC tubes
Length =120 cm;
Ø= 1 inch
Totally internal wiring
Built with 10 cm water-tight
segments to allow internal link
operability
Stainless steel circular
electrodes with
height of 3 cm
Construction of the micro ERT cross-borehole system

52. Resistivimeter
SYSCAL pro 72 channels
(48 in boreholes,
24 on surface)
Field deployment
- Installation without
pre dig for the max
electrode-soil coupling
- Selected an
apple tree
already
monitored
- by other means
- ( d i e l e c t r i c
probes)

53. Acquisition
scheme
A complete skip-0 dipole-dipole scheme
with reciprocal was used for all
acquisitions.

54. ERT inversion
Using the ERT code R3T (A.Binley,
Lancaster University)

55. Date
Note
15/10/10
Installation and Measurement 1
14/01/11
Measurement 2
04/04/11
Measurement 3
28/04/11
Measurement 4
18/05/11
Measurement 5
06/07/11
Measurement 6
04/08/11
Measurement 7 + Irrigation TEST
07/09/11
Measurement 8
05/10/11
Measurement 9
03/05/12
Measurement 10 + Irrigation TEST
04/11/12
Measurement 11 + Irrigation TEST
Repeated (seasonal) measurements
Irrigation
tests

56. Three irrigation tests:
August 2011, May 2012, November 2012
August 2011: irrigation performed via two drippers on the ground surface: total
flow rate =2.4 l/h for six hours, following a long dry period.
May 2012: widespread irrigation performed with a sprinkler ; total water volume
= 500 l over 2.5 hours, at the top of growing season.
November 2012: widespread irrigation performed with a sprinkler ; total water
volume = 500 l over 5 hours, wet period following apple harvest (low ET).

57. August 2011 experiment: resistivity ratio with respect to background
at four time steps.
The iso-surface equal to 60 % of the background resistivity does not
penetrate any deeper than 30-40 cm below ground surface.

58. May 2012 experiment: resistivity ratio with respect to background at
four time steps shown on the horizontal slice at 30 cm depth.
Moisture content measured by TDR in the top 32 cm.
The moisture content was already high at the start of the experiment.

59. May 2012 experiment: resistivity ratio with respect to background at
30 cm depth and at 8.5 hours after start of irrigation
%
0
Resistivity ratio
w.r.t. background
100
200
30030 cm
depth
root
suction
zone ?

60. November 2012 experiment: resistivity ratio with respect to
background at four time steps.
Moisture content measured by TDR in the top 32 cm.
The initial moisture content is higher than other experiments, low ET

61. May 2012 experiment: resistivity ratio with respect to background
averaged over horizontal slices
0.5 h after irrigation start irrigation end at 2.5 h
root
suction
Zone
?

62. May 2012 experiment: resistivity changes
converted into saturation changes and
averaged along horizontal planes.
0.5 h after irrigation start irrigation end at 2.5 h
Archie’s law
from lab
root
suction
Zone
?
Rho
Sw

63. November 2012 experiment: resistivity ratio with respect to
background averaged over horizontal slices
0.5 h after irrigation start 2.5 h after irrigation start
?

64. May 2012 experiment: mass balance issue from 3D ERT
Note that the total irrigated water amounts to 500 liters

65. We applied the CATHY (CATchment HYdrology) model
[Bixio et al, 2000; Camporese et al., 2010], a physically-
based 3D distributed model which uses Richards’ equation
to describe variably saturated flow in porous media.
We used the following parameters:
Ks = 6x10-5 m/s
Van Genuchten n = 1.35
Porosity = 0.5
θr = 8x10-2
ψa = -0.7
Sw
ψ

66. Time = 2 hours
tracking of particle
motion starting
from the surface
May 2012 experiment
Volume of interest
Pseudo-color
Var-saturation
Depthm
m

67. Time = 3 hours
tracking of particle
motion starting
from the surface
May 2012 experiment
Pseudo-color
Var-saturation
Depthm
m
Volume of interest

68. Time = 5 hours
tracking of particle
motion starting
from the surface
May 2012 experiment
Pseudo-color
Var-saturation
Depthm
m
Volume of interest

69. Time = 3 hours
May 2012 experiment
Pseudo-color
Var-saturation
Depthm
m
Volume of interest

70. Time = 3 hours
November and May
irrigation
experiment
Depthm
m
(240 μS/cm)
Pseudo-color
Var-saturation
Piston effect ?
Again:
important pore water salinity
(and old vs new water) issues

71. The Bulgherano – Lentini field site
Orange
trees
Lentini (SR)
•
October
2013:
meas.
living
plant,
irriga#on
test
•
June
2014:
meas.
dead
plant;

72. Eddy
covariance
tower
Sap flow
probes
The Bulgherano – Lentini field site

73. Surface
electrodes
Borehole
electrodes
Sap
flow
probes

74. Surface
electrodes
Borehole
electrodes
3D ERT monitoring scheme
• 24 superficial electrodes covering a 1.3x1.3 m2 area
• 48 borehole electrodes, 12 in each of the 4 micro-boreholes
• Acquisition using a complete skip-0 dipole-dipole scheme with reciprocal
was used for all acquisitions.
• Inversion using the ERT code R3t (A.Binley, Lancaster University)
1.3
m
1.3
m
1.2
m
ORANGE TREE

75. 0-­‐40
cm:
Dry
region
influenced
by
root
water
uptake
Resistivity (Ω m)
Irrigation test: background conditions

76. Clouds
Transpiration
z
ABL
Free Atmosphere
sunrise mid-morning
SoilPlantAtmosphere
mid-afternoon
courtesy:
M.
Marani

77. hours
Time-lapse monitoring during irrigation
(4 liters/min per dripper, 4 drippers per tree – spaced 1 m)
October 2-3, 2013
eddy covariance
sap flow

78. Convert resistivity into moisture content
laboratory tests
(with due care to pore water electrical conductivity,
water extracted in situ via suction cups)
θ =
4.703
ρ1.12
Archie’s law (1942)

79. Resistivity ratio
with respect to background(%)
June 2014 irrigation test (the orange tree is dead)
Indipendent calibration of unsaturated flow model
(in absence of tree transpiration) for in situ
saturated hydraulic conductivity Ks = 0.002 m/h
From laboratory experiments: pressure –saturation
parameters: residual moisture content θr = 0., porosity
θs=0.54, α = 0.12 1/m, n = 1.6.

80. We know the total water
extracted by the tree
(sap flow measurements)
We have to estimate
the fraction extracted
from this square meter, i.e.
the radius of the root water
uptake area.
irrigation and rainfall (input)
1 m
1 m
0.4 m root
water
uptake
(output)
Conceptual scheme of 1D infiltration modelling
1 m
drippersorange trees TDR

81. 0 0.2 0.4 0.6
soil moisture content (-)
-2
-1.6
-1.2
-0.8
-0.4
0
depthbelowground(m)
real data: 12:00 noon
October 2, 2013
initial conditions (1/1/2013)
1.75 m2
1.50 m2
1.25 m2
2.00 m2
2.25 m2
Results of 1D infiltration modelling
radius ≈ 0.75 m

82. 0.300
0.320
0.340
0.360
0.380
0.400
0.420
0.440
27/09/2013
28/09/2013
29/09/2013
30/09/2013
01/10/2013
02/10/2013
03/10/2013
04/10/2013
05/10/2013
06/10/2013
07/10/2013
08/10/2013
Soilmoisturecontent(-­‐)
TDR
at
20
cm
depth
TDR
at
35
cm
depth
TDR
at
45
cm
depth
1 m
dripperstrees TDR
The TDR data
provide
independent
supporting
evidence that the
root water uptake
zone has a radius
smaller than the
distance between
the TDR probes
and the orange
tree trunk
(about 0.75 m).

83. SUMMARY
q Soil-plant-atmosphere interactions
q Characterization of the Earth’s critical zone: the role of
non-invasive monitoring
q Large-scale monitoring
q Small-scale monitoring
q Outlook: assimilate data and models, with a vision
q Conclusions

84. “I believe that the spatiotemporal linkage between the hydrologic and
ecologic dynamics will be one of the most exciting frontiers of the
future.”
(Ignacio Rodriguez-Iturbe, 2000).
“A radicle may be compared with a burrowing mole, which wishes to
penetrate perpendicularly into the ground. By continually moving its
head from side to side, or circumnutating, he will feel a stone or other
obstacle as well as any difference in the hardness of the soil, and he
will turn from that side; if the earth is damper on one than the other
side he will turn thitherward as a better hunting ground.
Nevertheless, after each interruption, guided by the sense of gravity,
he will be able to recover his downward course and burrow to a
greater depth.”
(Charles Darwin, The Power of Movement in Plants, 1881).

85. Conceptual plant model indicating mesh
nodes of richards’ equation solver and
the distribution of the plant water flux
paths.
The model is based on an optimality
criterion maximizing plant
transpiration.
Outlook
Soil-plant-atmosphere
continuum model
ΨR
ΨL
CO2
gx
gs
gs
T
H2O
Volpe et al., 2013; Manoli et al., 2014

86. ( ) ( )[ ] xRRLLxLR AzzψgT ⋅+−+⋅−= ψψψ ),(
( ) ( )[ ] riiRRiLRi Azzgq ⋅+−+⋅−= ψψψψ ),(
cwLsLw ALAIVPDgaf ⋅⋅⋅⋅⋅= εψψ )()(
Soil-Plant-Atmosphere continuum model
Leaf-Atmosphere
Xylem-Leaf
Root-Xylem ΨR
ΨL
CO2
gx
gs
gs
T
0=
∂
∂
−
∂
∂
s
w
s
c
g
f
g
f
λ
(Katul et al., 2010)
( )Lsg ψ
( )[ ] ( )Lrs
w
ws qzKK
t
S
t
SS ψψψϕ
ψ
,++∇⋅∇=
∂
∂
+
∂
∂
Variably saturated flow (Cathy):
H2O
(Volpe et al., 2011)
Volpe et al., 2013;
Manoli et al., 2014
(Paniconi and Putti, 1994)

87. RWU RWU
Root Hydraulic Redistribution Root Hydraulic Redistribution
Darcy flow divergence Darcy flow divergence
RootHydraulicRedistributionandspatialinteractions
Manolietal.,2014

88. Soil-Plant-Atmosphere Interactions:
Roots as Optimal Organized Transport Systems
The root systems of corn from J. E. Weaver, F. C.
Jean, J. W. Crist, Development and Activities of
Roots of Crop Plants (Carnegie
Institute,Washington, DC, 1922).
Directional drilling configuration (together with a 3D
seismic cube)
From http://www.dgi.com/earthvision/evmain.html

89. courtesy:
M.
Pu7

90. 12.5
m
8
m
2 m
1.3
m
2.5
m
soil
drain (gravel)
soil
drain (gravel)
12.5
m
12.5
m
5.5m
x
2.5m 5.5m
x
2.5m
5.5m
x
2.5m
2m
x
2.5m
3m
x
2.5m
2m
x
2.5m
3m
x
2.5m
2m
x
2.5m
3m
x
2.5m
schematic plan and side view of the greenhuse. In planar view observe the different sizes of the
lysimeters and a tentative placement of the ERT micro-boreholes (red dots – shown only for some
lysimeters).
Roots as Optimal Organized Transport Systems
Need for full scale controlled experiments

91. q Near surface geophysics is strongly affected by both
static and dynamic soil/subsoil characteristics.
q This fact, if properly recognized, is potentially full of
information on the Critical Zone dynamic behaviour, and
particularly for the root zone.
q Integration with physical modelling is essential to
capture the meaning of space-time signal changes.
q Exciting frontiers will be opened if high resolution
geophysics can monitor processes to prove / disprove
fundamental theories.
Conclusions

92. FUNDING FROM:
- EU FP7 iSOIL
- EU FP7 CLIMB
- EU FP7 GLOBAQUA
- MIUR PRIN 2011 “Innovative methods for water resources management
under hydro-climatic uncertainty scenarios”

93. Acknowledgements
MARCO MARANI, MARTA ALTISSIMO, PAOLO SALANDIN, MATTEO CAMPORESE,
MARIO PUTTI, NADIA URSINO, RITA DEIANA, JACOPO BOAGA, MATTEO ROSSI,
MARIATERESA PERRI
Università di Padova
ALBERTO BELLIN, BRUNO MAJONE
Università di Trento
SIMONA CONSOLI, DANIELA VANELLA
Università di Catania
STEFANO FERRARIS
Università di Torino
ANDREW BINLEY
Lancaster University

94. Thanks for your attention