David Stone, IPILPS Workshop

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Diurnal Cycle Observations of Stable Water
Isotopes in the Biosphere

• David Stone, IPILPS Workshop
• ANSTO 18-22 April 2005

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IPILPS isotopes at the land surface

• Scientific Hypothesis
• Observation and analysis of the diurnal fluxes of
  H218O and HDO between the soil, plants and
  atmosphere can accurately determine the
  partitioning of precipitation into transpiration,
  evaporation and total runoff.
• Method
• Three ecosystems were selected as study areas
• Tropical forest, such as the Amazon Basin, Sth
  America
• Cool, humid temperate forest, such as Central
  Europe, or Nth America
• Warm, dry temperate forest, such as SE Australia
• Exploit stable water isotopes H218O and HDO to
  investigate the hypothesis.
• Observations would be required at Tumbarumba
• Field data expected to be available for the
  Amazon, Europe and America

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IPILPS Stable Isotope data needs

• Data expected to be available include
• precipitation
• atmospheric vapour
• plant (stem and leaf) water
• soilwater
• groundwater ( not expected to vary significantly)
• riverwater
• The data will be used within IPILPS to evaluate
  isotope enabled LSS output

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Overview of presentation

• Expected ranges of values
• the precipitation input at the three ecosystems
• vapourltstemltleaf order of enrichment
• Data sets examined
• Amazon Manaus, Santarem and Trinidad
• Central Europe Munich, other German sites
• North America temperate and semi-arid
• others

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Variation in del 18O ()
Leafwater 3 to10
THE WATER CYCLE
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Expected isotope ratios for SE Australia
(Tumbarumba)
Leaves
GMWL
rainwater
Surface water
Root zone water stem water transpired water
9-10
Surface evaporate
LEL
Local vapour
9-10
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10 depletion
Mean rainfall
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Precipitation Input Signal 3 sites
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Munich Vapour and Precipitation
Vapour and precipitation lie along a single MWL
data source W. Stichler, unpublished
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Munich vapour/precipitation equilibrium
Regression r2 0.7 Delta 18O(p-v) 8.5
data source W. Stichler, unpublished
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IPILPS data requirements and sources

• Water isotopologues
• del H218O and 1H2H16O () both desired
• Comparison of LSS
• By output, and against real data
• Real field data required at appropriate time
  scales, monthly, daily, hourly
• Prefer data at diurnal timescale
• BASIN database (Ehleringer), Americas
• CarboEuroflux (various), Europe

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Data collection methods

• Towers fitted with tubing for cryogenic vapour
  trapping, water kept frozen
• Soil and Leaf samples sealed in exetainers
  distilled cryogenically before analysis
• del D and del O-18 performed by IR-MS

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Tropical Rainforest data Manaus, Amazon
Trinidad
LBA BASIN sites
Manaus
Santarem
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data source Matsui et al,1983, Acta Amazonica,
13, 307-68
10 enrichment
15
am
pm
Enrichment increases during day
10.4 average enrichment
Data source LBAdatabase (Ometto) submitted for
publication
Canopy Leaves enriched
11
Understory Leaves less enriched
9
16
11
9
Data source LBA (Ometto) unpublished
Dry season vapour, leaf and stem water more
enriched
11
7
17
Data source LBA (Ometto) unpublished
12- 14
Inter-annual differences possible?
6
11
Much less leaf enrichment than in previous year
18
Data source LBA (Ometto) unpublished
10- 12
8
8
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Data source LBA (Ometto) unpublished
10- 13
10
Dry season vapour, leaf and stem water more
enriched
9
Much less leaf enrichment than in previous year
5
20
Data source LBA (Ometto) unpublished
Vapour less enriched mid-morning, but more
enriched in afternoon
5 difference in canopy
12
8
21
Vapour more enriched midday, but less enriched in
afternoon
5-10 difference in canopy
Data source LBA (Ometto) unpublished
small difference between vapour and stems!!
12
8
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Amazon Forest Vapour daytime variation, June 2000
Data source LBA (Ometto) unpublished
Vapour less enriched mid-morning, but more
enriched in afternoon
Vapour more enriched midday, but less enriched in
afternoon
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Amazon Forest Vapour Keeling Plot analysis, June
1995
Data source Leo Sternberg, IAEA 2004
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Amazon Forest Vapour Keeling Plot analysis, May -
Dec 1995
Data source Leo Sternberg, IAEA 2004
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Average precip, calc
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Conclusions

• Amazon
• Leaf enrichment increases during day
• Canopy Leaves enriched, understory much less so
• Stem water enriches slightly in dry season
• Dry season vapour, leaf stem water more
  enriched
• VapourltStemltLeaf enrichment close to optimum
• Keeling plot analysis, 18O, indicates
  transpiration predominant flux of return vapour
  to atmosphere

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Cool Temperate Munich, Germany
Jena and Dresden
CarboEuroFlux sites
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data source W. Stichler, unpublished
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data source W. Stichler, unpublished
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data source W. Stichler, unpublished
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Munich Vapour and Precipitation
data source W. Stichler, unpublished
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Samples taken in evening 1900-2300
Leaf water depletes overnight
Stem and soilwater little variation
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Leaf water depletes summer to winter
Stem and soilwater show little variation
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Leaf water depletes summer to winter
Stem and soilwater show little variation
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Cool Temperate Ottawa and Oregon
BASIN sites
Ottawa
Oregon sites
Oklahoma
Arizona
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10 enrichment
data source Flanagan, L.B. and Varney, G.T.
1995, Oecologia 10137-44
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Leafwater enriched during daytime
10 enrichment
Average precip, calc
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Average precip, calc
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Shallow soilwater
deeper soilwater
Average precip, calc
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13 enrichment
Average precip, calc
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Conclusions

• Europe
• Leaf enrichment decreases during evening (6-11pm)
• Stem, roots, soil and litter show small
  variations, but little systematic seasonal change
• VapourltStemltLeaf enrichment less than optimum
• Humid North America
• Soilwater data have a large variation
• Forest stemltleaf enrichment at optimum
• Grassland stemltleaf enrichment at optimum
• Forest and Grassland vapourltstem enrichment less
  than optimum ( Summer data only available)

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Warm Temperate - semi arid regions
Israel, Arizona
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Average precip
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Depletion during daytime
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GMWL
LEL
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Conclusions

• Semi-arid Israel and North America
• Israel vapourltstemltleaf enrichment at optimum
• Arizona vapour became depleted during the day
• Keeling plot analysis, using both 2H and 18O
  indicates transpiration predominant flux of
  return vapour to atmosphere

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