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Infrared temperature to assess plant transpiration reduction
EGU General Assembly, April 3-8, 2011, Vienna, Austria
HS 8.3 Subsurface Hydrology - Unsaturated Zone
HS 8.3.1: Soil-plant interactions from the rhizosphere to field scale
Angelica Durigon1*, Quirijn de Jong van Lier1 and Klaas Metselaar
1Department
University of São Paulo
of Biosystems Engineering, ESALQ-University of São Paulo, Brazil. *[email protected]
2Department of Environmental Sciences, Wageningen University and Research Centre, The Netherlands.
Introduction
Objective
Theoretical Aspects of Crop Water Stress
• Resistances in the soil-plant-atmosphere pathway determine
transpiration rate. Stomatal conductance can be changed by
the plant in a reaction to environmental conditions, e.g. a dry
soil or a dry atmosphere.
Study the physical mechanisms and the interaction between
factors related to soil and atmosphere that lead to crop water
stress.
• A direct effect of stomata closure is increased stomatal
resistance leading to reduced transpiration and CO2-uptake
rate. Indirect consequences are a reduction in energy
dissipation and photosynthesis and an increase in leaf
temperature.
• Identify plant water stress occurrence using canopy temperature
Tcanopy.
• Leaf temperature can be used to evaluate plant water status
and transpiration reduction.
• Transpiration rate is determined by stomatal conductance and microclimatic elements,
as VPD (Vapor Pressure Deficit) → CO2 Assimilation model (Jacobs et al., 1996)
How to identify plant water stress?
• Determine how pressure head h, ∆Tcanopy-air and vapor pressure
deficit VPD in field conditions are related with plant water stress.
• Relationship ∆Tcanopy-air x VPD: linear when there is enough water supply to plants.
• Use mechanistic models of root water extraction and CO2
assimilation by leaves to determine which part (soil and/or
atmosphere) is responsible for plant water stress occurrence.
• Comparison between Tcanopy x wet-bulb temperature Twb: if resistances in healthy
plants are low, Tcanopy must be constantly higher than Twb; as soon as plant resistance to
transpiration increases, Tcanopy become even higher than Twb.
Field Experiment
• Difference of ∆Tcanopy-air between irrigated and non irrigated plot.
Identifying Plant Water Stress
• ∆Tcanopy-air x VPD (02-Aug to 02-Sep)
8
Area: 990 m2 (22 m x 45 m)
Two plots: 22 m x 22,5 m (one
irrigated)
Campaign observations:
• Root density: 3 times each plot.
• Stomatal resistance and transpiration rate: 11 days at midday.
• Leaf Area Index (LAI): 5 times with a ceptometer.
Next steps
• Simulate the dry period with the root water extraction model of De Jong
van Lier et al. (2008):
• Data of root density, matric flux potential M and soil hydraulic
parameters.
• Simulate the dry period with the CO2 assimilation model of Jacobs et al.
(1996) to identify the midday depression in photosynthesis in plants of both
plots:
• Meteorological data.
• Data of Ds (specific humidity difference between atmosphere and
leaves) and LAI.
-4
10
(DTcanopy-air)nir - (DTcanopy-air)ir
8
5 - Even with a high VPD
difference in 25-Aug, water
stress reduced as soil water
content increased.
6
4
VPDnir - VPDir
2
0
15
30
45
VPD, hPa
8
4
∆Tcanopy-air , °C
4 - Water stress decreased in
16-Aug as VPD reduced.
12
2 - Plants of irrigated plot
were not water stressed
(linear relationship).
-12
Dry period: 02-Aug to 02-Sep
Continuous observations (every 30 minutes):
• Pressure head h (Polymer Tensiometers measuring till -1.6 MPa):
2 observation points each plot at 0.05, 0.15 and 0.30 m depth.
• Tair and RH: 1 observation point each plot.
• Tcanopy: 1 observation point each plot (infrared thermometry).
0
1 - Plants of non irrigated plot
were water stressed.
-8
3 - Water stress started on 5-Aug
(comparing both plots and
considering plants in irrigated
plot were non water stressed).
0
-2
Water stress
31-Jul 5-Aug 10-Aug 15-Aug 20-Aug 25-Aug 30-Aug 4-Sep
Fig. 3: Difference of ∆Tcanopy-air and VPD between
non irrigated (nir) and irrigated (ir) plots
• Pressure head h - non irrigated plot
0
100
-4
-8
-12
0
15
30
45
VPD, hPa
Fig. 2: ∆Tcanopy-air x VPD for irrigated plot (above) and
non irrigated plot (below).
100
0.05 m
10
1
0.3 m
0.15 m
0.1
• Tcanopy and Twb
0.05 m
10
0.15 m
1
0.3 m
0.1
31-Jul 5-Aug 10-Aug 15-Aug 20-Aug 25-Aug 30-Aug 4-Sep
31-Jul 5-Aug 10-Aug 15-Aug 20-Aug 25-Aug 30-Aug 4-Sep
Fig. 4: Pressure head h for both observation points of non irrigated plot
20
6 - Tcanopy is higher than Twb for both plots.
16
ΔTcanopy-wb , °C
Fig. 1: Experimental site.
∆Tcanopy-air , °C
BEANS (Phaseolus vulgaris L.)
4
14
Pressure head h, m
19/07/2010
07:00 - 10:30
11:00 - 14:30
15:00 - 18:00
• ∆Tcanopy-air and VPD between plots
Pressure head h, m
• Field experiment was performed in Brazil (UTM 253.300E,
latitude 153.400N) from June/2010 to September/2010.
02/07/2010
• Root water uptake rate is determined by root water uptake dynamic and soil water
content → Root water extraction model (De Jong van Lier et al., 2008)
Non Irrigated
12
8
7 - ΔTcanopy-wb is approximately constant
during whole period for irrigated plot but
increases for non irrigated plot.
4
Irrigated
0
31-Jul 5-Aug 10-Aug 15-Aug 20-Aug 25-Aug 30-Aug 4-Sep
Fig. 5: Difference between Tcanopy and Twb for non
irrigated and irrigated plots.
8 - At the end of the month, Tcanopy of non
irrigated plot becomes even higher than
Twb indicating an increment in stomatal
resistance to transpiration.
9 - Although atmospheric demand was the same for both
plots, hydrological parameters differed significantly between
them.
10 - Pressure head dropped down to -150.0 m in non
irrigated plot and at this time Tcanopy presented its maximum
values (~ 38.0°C).
Preliminar conclusion: Sometimes observed plant water
stress was a combined effect of soil and atmosphere, on other
ocassions it has been a single effect of soil or atmosphere.
Main Bibliographic References
Bakker et al. (2007). New polymer tensiometers: measuring matric pressures down to wilting point. Vadose Z.J., 6, 196-202.
De Jong van Lier et al. (2008) Macroscopic root water uptake distribution using a matric flux potential approach. Vadose Z. J., p. 1065-1078.
Ehrler (1973). Cotton leaf temperatures as related to soil water depletion and meteorological factors. Agron. J., 65, 404-409.
Fucks (1990). Infrared measurement of canopy temperature and detection of plant water stress. Theor. Appl. Climatol., 42, 253-261.
Idso et al. (1981). Normalizing the stress-degree-day parameter for environmental variability. Agricultural Meteorology, 24, 45–55.
Acknowledgements
Jacobs et al. (1996) Stomatal behavior and photosynthetic rate of unstressed grapevines in semi-arid conditions. Agricultural and Forest Meteorology, 2,
111-134.
Shimoda and Oikawa (2006). Temporal and spatial variations of canopy temperature over a C3-C4 mixture grassland. Hydrol. Process., 20, 3503-3516.
Tanner (1963). Plant temperature. Agron. J., 55, 210-211.
Van der Ploeg et al. (2008). Matric potential measurements by polymer tensiometers in cropped lysimeters under water-stressed conditions. Vadose Z.
J., 7, 1048-1054.
CAPES-WUR Agreement (proj. n.° 019/06)
WUR/The Netherlands (proj. n.° 5100184-01)
FAPESP (proj. n.° 2009/02117-7)
University of São Paulo - Post-Graduation Section