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![Page 1: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/1.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Water balance partitioning at the catchment scale:
Hydrosphere-biosphere interactions
Peter Troch, Ciaran Harman and Sally Thompson
2009 Hydrologic Synthesis Reverse Site VisitAugust 20-21 2009
Arlington, VA
2009 Hydrologic Synthesis Reverse Site Visit – Arlington, VA
![Page 2: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/2.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Motivation: another Horton index…
Horton, 1933 (AGU)
H constantV
W V : Growing-season vaporization (E+T)
W : Growing-season wetting (P-S)
“The natural vegetation of a region tends to develop to such an extent that it can utilize the largest possible proportion of the available soil moisture supplied by infiltration” (Horton, 1933, p.455)
![Page 3: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/3.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Horton Index vs. Humidity IndexMean Horton Index Std. Horton Index
53% with Std(H)<0.0674% with Std(H)<0.0783% with Std(H)<0.0893% with Std(H)<0.10
Troch et al., 2009 (HP)
![Page 4: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/4.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Climate Vegetation Geology Topography
The Horton Index
EcosystemProductivity
CatchmentBiogeochemistry
![Page 5: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/5.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
What controls the Horton index?
![Page 6: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/6.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
The Horton Index
Precip
“Fast” runoff
“Slow” runoff
ET
Wetting
Annual Evapotranspiration
Annual WettingHI =
Proportion of available water vaporized
![Page 7: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/7.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
![Page 8: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/8.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Three approaches explain HI
FunctionProcessPattern
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Pre
dic
ted
HI_
50
0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
HI_50
HI
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
... all three predict the mean remarkably well
ProcessFunctionPattern
Uncalibrated
Calibrated
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
HI was predictable based on static or mean catchment properties
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Pre
dic
ted
HI_
50
0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
HI_50
Pattern
HI = f ( )
Humidity index P/EP
Mean Topographic Index<Log (a / tan β)>
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Function
Functional model predicts mean, variance of HI
Wetting potentialFast flow threshold
P
S
U
ET
W
Functional model:
→ S and U have thresholds
→ ET and W have upper limit
…and using a conceptualization of annual partitioning of precip…
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Process ... and using a stochastic model based on filtering of storm events.
Storagecapacity
Calibrated storage capacity
CalibratedUncalibrated
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
We gained insight into controls on HI
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Empirical HI model
HUI
CT
I
0.1
0.2 0
.3
0.4
0.5
0.6
0.7
0
.8
0.9
1
1 2 3 4
34
56
78
Empirical CV(HI) model
HUI
CT
I
0
0.0
2
0.0
4
0.0
6
0.08
0.1
0.12
0.14
0.16
0.18
1 2 3 4
34
56
78
Regression models suggest that climate and topography are primary controlsPattern
Humidity IndexHumidity Index
Topographic Index
Mean: Climate (except in steep, arid regions)CV: topography (humid regions)
Mean HI CV HI
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Functional model suggests catchment capacity to vaporize and store water are
basic controls
Ep λs = λu = 0
λs = λu = 0.05
Function
Mean: - vaporization potential (~ energy) - catchment “wetability” (to a point)
P = 1000mm
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Process model also suggests keys are that climate and capacity to store water from storm eventsProcess
Mean HI: Humidity Index, storage capacityVariance: only sensitive in arid regions
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Prediction of interannual variability opens up questions about other factors
Timing of rainfall, vegetation response, landscape change, …?
ProcessFunctionPattern
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Key unresolved questions:
How does variability scale in time?
What timescales are important?
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Key unresolved questions:
What is the role of vegetation in hydrologic partitioning?
Are we only able to make predictions because of the co-evolution of vegetation, soils and geomorphology constrained by climate, geology and time?
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Variability and Vegetation
Learning from Data-Rich Sites
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Working ParadigmClassic ecohydrological approach:
ETmax ~ f(Rn, VPD, LAI,T)
ET ~ ETmax * f(θ)
“Water-limited” paradigm? Plant control of ET?
![Page 22: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/22.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
A Parsimonious Model Penman Monteith
Model
Rn VPD LAI U P T
Emax
E
T
Interception Model
PPT
Runoff
Drainage
Infiltration
Multiple Wetting Front ModelRoot Water Uptake Model
![Page 23: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/23.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Interannual variability
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Sub-daily variability
ET
(m
m/h
r)
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Seasonal variabilityE
T (
mm
/hr)
Month
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Soil Moisture Drydown v ET
0 50 100 150 200 250 300 350 4000
0.5
1
1.5
2
2.5
3
E TS o il Mo is ture
800 900 1000 1100 1200 1300 1400-0.2
0
0.2
0.4
0.6
0.8
1
1.2
Kendall
Sky OaksET increases as soil moisture declines! ET
Soil Moisture
ET correlates to soil moisture
Days
Days
ET
(m
m/h
r) o
r θ
%E
T (
mm
/hr)
or
θ %
![Page 27: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/27.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Adding Groundwater Improves PredictionE
T (
mm
/hr)
Month
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2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Phenology Changes Seasonality of ET
10 20 30 40 500
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
17
DOY
Nor
mal
ized
ET
, LA
I, R
n
L A I
E T
R n
0 50 100 1500
0.02
0.04
0.06
0.08
0.1
0.127
Radiation
ET
0 50 100 1500
0.02
0.04
0.06
0.08
0.1
0.129
Radiation
ET
0 1000
0.04
0.08
0.1213
Radiation
ET
A
B
C
A
B
C
Week
No
rmal
ized
ET
, LA
I an
d R
n
Howland Forest, Maine
![Page 29: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/29.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Phenological Effects are Predictable
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.80
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
13
Norm alized Cum ulative GDD
Nor
mal
ized
ET
0 0.2 0.4 0.6 0.8 10.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
110
Norm alized Cum ulative GDD
Nor
mal
ized
ET
0 0.1 0.2 0.3 0.4 0.5 0.6 0.70.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
111
Norm alized Cum ulative GDD
Nor
mal
ized
ET
Kendall Grasslands Donaldson Coniferous Forest Morgan Monroe Mixed Forest
Poorly correlated Well correlated
ET v Cumulative Growing Degree Days for first 150 Days of the Year
Onset of plant growth?Or leaf maturity?
![Page 30: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/30.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
0 0.5 1 1.5 2 2.5 30
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
S ky O aks
Mo rg an Mo nro e
Harvard
G o o d win C re e k
Can Patches Predict Catchments?
Humidity Index
Ho
rto
n I
nd
ex
S.O. Catchment
M.M. Catchment
H.F. Catchment
G.C. Catchment
Sky Oaks
Morg. Monroe
Harvard Forest
Goodwin Crk.
![Page 31: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/31.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Conceptual Upscaling Approach Multiple Buckets – different topography,
veg, soil etc.
PPT, Energy, C
ET, Energy, C
Deep Drainage, Water Table, Lateral Redistribution
Surface redistribution
![Page 32: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/32.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Ecohydrological catchment classification?
Sky Oaks
Fort Peck Goodwin Creek
Howland Forest
Donaldson
Kennedy
Kendall
Austin Cary
Metolius
Harvard Forest
0.5 1 1.50
Morgan Monroe
Humidity Index
HuIRadiationPhenologyGW AccessSeasonality
![Page 33: 2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA Water balance partitioning at the catchment scale: Hydrosphere-biosphere interactions Peter.](https://reader036.fdocuments.in/reader036/viewer/2022062422/56649e715503460f94b6f9d0/html5/thumbnails/33.jpg)
2009 Hydrologic Synthesis Reverse Site Visit – Arlington VA
Discussion Points
• What does all this mean for predicting water cycle dynamics in a changing environment?– Mean behavior of hydrologic partitioning is
surprisingly predictable, and– Knowing hydrologic partitioning improves
prediction of vegetation response, yet– The inter-annual variability is poorly understood
and calls for higher understanding of ecosystem control on water cycle dynamics (do we need to replace the old paradigm?)