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MINIMALLY INVASIVE MONITORING OF SOIL-
PLANT INTERACTIONS:
NEW PERSPECTIVES
Giorgio Cassiani
Dipartimento di Geoscienze, U...
SUMMARY
q  Soil-plant-atmosphere interactions
q  Characterization of the Earth’s critical zone: the role of
non-invasive...
SUMMARY
q  Soil-plant-atmosphere interactions
q  Characterization of the Earth’s critical zone: the role of
non-invasive...
The Earth’s Critical Zone
Na#onal	
  Research	
  Council	
  (2001)	
  
The Earth’s Critical Zone (CZ) is the thin outer
ve...
Soil-plant-atmosphere interactions are important
Pe
Pi
P
ET
Atmospheric
Input
Atmospheric
Output
Incoming
Runoff
Outgoing
...
vegetated
soil
Soil moisture dynamics in vegetated and bare soils
Volpeetal.,2013
bare
soil
courtesy:	
  M.	
  Marani	
  
Transpiration
and Photosynthesis
courtesy:	
  M.	
  Marani	
  
Importance of root
distribution (li) in determining
overall resistance to flow.
courtesy:	
  M.	
  Marani	
  
Geophysical techniques, combined with flow and
transport models, can provide a major step
forward in the ECZ characterizat...
SUMMARY
q  Soil-plant-atmosphere interactions
q  Characterization of the Earth’s critical zone: the role of
non-invasive...
water table
aquifer confining layer
impermeable
bedrock
small scalelarge scale
What geophysical methods can help define
q...
water table
spring
evapo-transpiration
water table
aquifer confining layer
impermeable
bedrock
small scalelarge scale
q  ...
Geophysical
measurements
Physical
model
(e.g hydrologic)
physical
parameters
(e.g. hydraulic
conductivity)
dynamics
(fluid...
SUMMARY
q  Soil-plant-atmosphere interactions
q  Characterization of the Earth’s critical zone: the role of
non-invasive...
Digital Soil Mapping
Bregonze Hills
Bregonze project description
Goal: characterize hydrological response of
a small hill catchment in the Vene...
Bregonze catchment
Small, self-contained primary catchment,
with mild slope and grass cover
Only the stream bed is populat...
18/08/2014
creek
Frequency-Domain
Electro-Magnetics
Resistivity map obtained
using a GF Instrument
CMD 1 sonde:
max invest...
02/09/2014
Frequency-Domain
Electro-Magnetics
Resistivity map obtained
using a GF Instrument
CMD 1 sonde:
max investigatio...
22/09/2014
Frequency-Domain
Electro-Magnetics
Resistivity map obtained
using a GF Instrument
CMD 1 sonde:
max investigatio...
10/10/2014
Frequency-Domain
Electro-Magnetics
Resistivity map obtained
using a GF Instrument
CMD 1 sonde:
max investigatio...
Matching model predictions and EM data
Monitoring over time and space
the soil moisture conditions
(e.g. via FDEM) can giv...
AGRIS San Michele experimental farm - Ussana - Sardinia
field 21
field 11
FP7 EU
collaborative project
Digital soil mapping using frequency-domain EM
Soil texture pattern effect - ECa
Electrical conductivity
(mS/m)
Soil texture pattern effect – gamma ray spectrometry
doserate
[mG/hr]
508700 508750 508800 508850 508900 508950
Easting (m)
May 18, 2009
4362500
4362550
4362600
4362650
4362700
4362750
Northin...
508650 508700 508750 508800 508850 508900 508950 509000
UTM easting (m)
total dose rate (nG/h)
4362450
4362500
4362550
436...
508700 508750 508800 508850 508900 508950
Easting (m)
May 18, 2009
4362500
4362550
4362600
4362650
4362700
4362750
Northin...
508700 508750 508800 508850 508900 508950
Easting (m)
June 15, 2009
4362500
4362550
4362600
4362650
4362700
4362750
Northi...
508700 508750 508800 508850 508900 508950
Easting (m)
March 31, 2010
4362500
4362550
4362600
4362650
4362700
4362750
North...
508700 508750 508800 508850 508900 508950
Easting (m)
May 19, 2010
4362500
4362550
4362600
4362650
4362700
4362750
Northin...
508700 508750 508800 508850 508900 508950
Easting (m)
February 3, 2011
4362500
4362550
4362600
4362650
4362700
4362750
Nor...
Time-lapse EM results
508700 508750 508800 508850 508900 508950
Easting (m)
May 19, 2010
4362500
4362550
4362600
4362650
4...
bare soil
bare soil
vegetated
soil
vegetated soil
a 507900 507950 508000 508050 508100 508150
UTM easting (m)
total dose r...
Fallow plotCultivated plot
alfalfa (Medicago sativa L.)
Field 11 – May 18 2010 – before irrigation
508015 508020 508025 508030 508035 508040 508045 508050 508055 508060 508065 50...
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...
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...
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...
moisture	
  	
  
content	
  
(-­‐)	
  
May	
  19	
  17:30	
  
May	
  20	
  	
  9:30	
  
May	
  20	
  12:30	
  
May	
  21	
...
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...
SUMMARY
q  Soil-plant-atmosphere interactions
q  Characterization of the Earth’s critical zone: the role of
non-invasive...
TIME LAPSE MICRO-ERT in the Venice Lagoon
Aim:
are marsh
plants able to
induced a
permanent
aerated layer
when flooded ?
Marani et al.
2006, WRR
- 24 buried electro...
July 2012 experiment: resistivity ratio with respect to background
at 3 time steps during marsh flooding
Dryer zone at
roo...
Dryer zone at
30-40 cm
depth
Water level
Confirmed by
tensiometers
TIME LAPSE MICRO-ERT in the Venice Lagoon
Boaga et al. ...
Dryer zone at
roots depth
TIME LAPSE MICRO-ERT in the Venice Lagoon
Boaga et al. 2014, GRL
CLES, val di Non, Trentino
Noce catchment
apple orchard
sandy-silty soil with no clay
4 PVC tubes
Length =120 cm;
Ø= 1 inch
Totally internal wiring
Built with 10 cm water-tight
segments to allow internal link...
Resistivimeter
SYSCAL pro 72 channels
(48 in boreholes,
24 on surface)
Field deployment
-  Installation without
pre dig fo...
Acquisition
scheme
A complete skip-0 dipole-dipole scheme
with reciprocal was used for all
acquisitions.
ERT inversion
Using the ERT code R3T (A.Binley,
Lancaster University)
Date	
   Note	
  
15/10/10	
   Installation and Measurement 1	
  
14/01/11	
   Measurement 2	
  
04/04/11	
   Measurement ...
Three irrigation tests:
August 2011, May 2012, November 2012
August 2011: irrigation performed via two drippers on the gro...
August 2011 experiment: resistivity ratio with respect to background
at four time steps.
The iso-surface equal to 60 % of ...
May 2012 experiment: resistivity ratio with respect to background at
four time steps shown on the horizontal slice at 30 c...
May 2012 experiment: resistivity ratio with respect to background at
30 cm depth and at 8.5 hours after start of irrigatio...
November 2012 experiment: resistivity ratio with respect to
background at four time steps.
Moisture content measured by TD...
May 2012 experiment: resistivity ratio with respect to background
averaged over horizontal slices
0.5 h after irrigation s...
May 2012 experiment: resistivity changes
converted into saturation changes and
averaged along horizontal planes.
0.5 h aft...
November 2012 experiment: resistivity ratio with respect to
background averaged over horizontal slices
0.5 h after irrigat...
May 2012 experiment: mass balance issue from 3D ERT
Note that the total irrigated water amounts to 500 liters
We applied the CATHY (CATchment HYdrology) model
[Bixio et al, 2000; Camporese et al., 2010], a physically-
based 3D distr...
Time = 2 hours
tracking of particle
motion starting
from the surface
May 2012 experiment
Volume of interest
Pseudo-color
V...
Time = 3 hours
tracking of particle
motion starting
from the surface
May 2012 experiment
Pseudo-color
Var-saturation
Depth...
Time = 5 hours
tracking of particle
motion starting
from the surface
May 2012 experiment
Pseudo-color
Var-saturation
Depth...
Time = 3 hours
May 2012 experiment
Pseudo-color
Var-saturation
Depthm
m
Volume of interest
Time = 3 hours
November and May
irrigation
experiment
Depthm
m
(240 μS/cm)
Pseudo-color
Var-saturation
Piston effect ?
Aga...
The Bulgherano – Lentini field site
Orange	
  
trees	
  
Lentini (SR)
• 	
  October	
  2013:	
  meas.	
  living	
  plant,	...
Eddy
covariance
tower
Sap flow
probes
The Bulgherano – Lentini field site
Surface	
  electrodes	
  
Borehole	
  electrodes	
  
Sap	
  flow	
  probes	
  
Surface	
  electrodes	
  
Borehole	
  electrodes	
  
3D ERT monitoring scheme
•  24 superficial electrodes covering a 1.3x...
0-­‐40	
  cm:	
  
Dry	
  region	
  influenced	
  
by	
  root	
  water	
  uptake	
  
Resistivity (Ω m)
Irrigation test: back...
Clouds
Transpiration
z
ABL
Free Atmosphere
sunrise mid-morning
SoilPlantAtmosphere
mid-afternoon
courtesy:	
  M.	
  Marani...
hours
Time-lapse monitoring during irrigation
(4 liters/min per dripper, 4 drippers per tree – spaced 1 m)
October 2-3, 20...
Convert resistivity into moisture content
laboratory tests
(with due care to pore water electrical conductivity,
water ext...
Resistivity ratio
with respect to background(%)
June 2014 irrigation test (the orange tree is dead)
Indipendent calibratio...
We know the total water
extracted by the tree
(sap flow measurements)
We have to estimate
the fraction extracted
from this...
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...
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
03/10/20...
SUMMARY
q  Soil-plant-atmosphere interactions
q  Characterization of the Earth’s critical zone: the role of
non-invasive...
“I believe that the spatiotemporal linkage between the hydrologic and
ecologic dynamics will be one of the most exciting f...
Conceptual plant model indicating mesh
nodes of richards’ equation solver and
the distribution of the plant water flux
pat...
( ) ( )[ ] xRRLLxLR AzzψgT ⋅+−+⋅−= ψψψ ),(
( ) ( )[ ] riiRRiLRi Azzgq ⋅+−+⋅−= ψψψψ ),(
cwLsLw ALAIVPDgaf ⋅⋅⋅⋅⋅= εψψ )()(
S...
RWU RWU
Root Hydraulic Redistribution Root Hydraulic Redistribution
Darcy flow divergence Darcy flow divergence
RootHydrau...
Soil-Plant-Atmosphere Interactions:
Roots as Optimal Organized Transport Systems
The root systems of corn from J. E. Weave...
courtesy:	
  M.	
  Pu7	
  
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	...
q  Near surface geophysics is strongly affected by both
static and dynamic soil/subsoil characteristics.
q  This fact, i...
FUNDING FROM:
-  EU FP7 iSOIL
-  EU FP7 CLIMB
-  EU FP7 GLOBAQUA
- MIUR PRIN 2011 “Innovative methods for water resources ...
Acknowledgements
MARCO MARANI, MARTA ALTISSIMO, PAOLO SALANDIN, MATTEO CAMPORESE,
MARIO PUTTI, NADIA URSINO, RITA DEIANA, ...
Thanks for your attention
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Giorgio Cassiani

  1. 1. MINIMALLY INVASIVE MONITORING OF SOIL- PLANT INTERACTIONS: NEW PERSPECTIVES Giorgio Cassiani Dipartimento di Geoscienze, Università di Padova, Italy giorgio.cassiani@unipd.it
  2. 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. 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. 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. 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. 6. vegetated soil Soil moisture dynamics in vegetated and bare soils Volpeetal.,2013 bare soil courtesy:  M.  Marani  
  7. 7. Transpiration and Photosynthesis courtesy:  M.  Marani  
  8. 8. Importance of root distribution (li) in determining overall resistance to flow. courtesy:  M.  Marani  
  9. 9. Geophysical techniques, combined with flow and transport models, can provide a major step forward in the ECZ characterization Key idea
  10. 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. 11. water table aquifer confining layer impermeable bedrock small scalelarge scale What geophysical methods can help define q  structure / texture
  12. 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. 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. 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. 15. Digital Soil Mapping
  16. 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. 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. 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. 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. 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. 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. 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. 23. AGRIS San Michele experimental farm - Ussana - Sardinia field 21 field 11 FP7 EU collaborative project
  24. 24. Digital soil mapping using frequency-domain EM
  25. 25. Soil texture pattern effect - ECa Electrical conductivity (mS/m)
  26. 26. Soil texture pattern effect – gamma ray spectrometry doserate [mG/hr]
  27. 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. 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. 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. 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. 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. 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. 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. 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. 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. 36. Fallow plotCultivated plot alfalfa (Medicago sativa L.)
  37. 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. 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. 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. 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. 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. 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. 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. 44. TIME LAPSE MICRO-ERT in the Venice Lagoon
  45. 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. 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. 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. 48. Dryer zone at roots depth TIME LAPSE MICRO-ERT in the Venice Lagoon Boaga et al. 2014, GRL
  49. 49. CLES, val di Non, Trentino Noce catchment apple orchard
  50. 50. sandy-silty soil with no clay
  51. 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. 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. 53. Acquisition scheme A complete skip-0 dipole-dipole scheme with reciprocal was used for all acquisitions.
  54. 54. ERT inversion Using the ERT code R3T (A.Binley, Lancaster University)
  55. 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. 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. 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. 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. 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. 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. 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. 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. 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. 64. May 2012 experiment: mass balance issue from 3D ERT Note that the total irrigated water amounts to 500 liters
  65. 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. 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. 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. 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. 69. Time = 3 hours May 2012 experiment Pseudo-color Var-saturation Depthm m Volume of interest
  70. 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. 71. The Bulgherano – Lentini field site Orange   trees   Lentini (SR) •   October  2013:  meas.  living  plant,  irriga#on  test   •   June  2014:  meas.  dead    plant;  
  72. 72. Eddy covariance tower Sap flow probes The Bulgherano – Lentini field site
  73. 73. Surface  electrodes   Borehole  electrodes   Sap  flow  probes  
  74. 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. 75. 0-­‐40  cm:   Dry  region  influenced   by  root  water  uptake   Resistivity (Ω m) Irrigation test: background conditions
  76. 76. Clouds Transpiration z ABL Free Atmosphere sunrise mid-morning SoilPlantAtmosphere mid-afternoon courtesy:  M.  Marani  
  77. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 87. RWU RWU Root Hydraulic Redistribution Root Hydraulic Redistribution Darcy flow divergence Darcy flow divergence RootHydraulicRedistributionandspatialinteractions Manolietal.,2014
  88. 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. 89. courtesy:  M.  Pu7  
  90. 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. 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. 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. 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. 94. Thanks for your attention

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