What’s the Diel with this Signal?
Jason Albright
Nathaniel Gustafson
Michaeline Nelson
Bianca Rodríguez-Cardona
Chris Shughrue
Funded by NSF and DOD
Award Number 1005175
Water Height (m)
Diel Fluctuations in stream height
8
9
10
Days in July, 2010
11
12
13
Which Areas Contribute?
Evapotranspiration
Solar
Radiation
Air Temp
VPD
Q
Soil
Moisture
Sap Flow
Volume from S.G.
• Q = P – ET + ∆S
Significance
• Use discharge to approximate ET
• Interesting eco-informatics question because
looks at watershed as a complete system
Eco-informatics conceptual model
Observed Diel
Empirical Model
Analytical Model
Questions
• What factors are principally responsible for
creating diel signals?
• How are ET induced signals affected by base-flow
levels and watershed characteristics?
• Are diel fluctuations synchronized across a
watershed?
• Does channel morphology influence diel
fluctuations?
• What are the mechanisms for the influence of ET
on diel fluctuations?
Watershed 1
• 95.9ha area
• Clear cut in the 60’s
– Red Alder
• Most steam reaches are
alluvial deposits
Watershed 2
• 60.3ha area
• Old Growth
– Western Hemlock and
Douglas Fir
• Channel mostly bedrock
What factors are principally
responsible for creating diel signals?
What we have to work with
• Abundant data available through HJ Andrews
• Lots of collaboration, local knowledge
• Personally ‘familiar’ with 2-3
watersheds
WS
Max signal
amplitude
1
0.055 cfs
2
0.005 cfs
10
0.005 cfs
9
0.003 cfs
8
0.001 cfs
Stream
network
length
slope
Air
temp
soil
type
Data
Effective
Riparian
area**
Process
Diel
Solar
strength*
Snowmelt
(mm/day)
WS Snow
content
Radia’n
EvapoTranspiration
(mm/day)
WS groundwater content
Temporal
Drainage
parameters
Parameters
WS property
Measured
Estimated
*Diel Strength = amplitude of diel signal in cfs
** (Riparian) area contributing to diel signal, m2
Diel signals
Overview of a year
Summertime
~.05cfs
Temperature vs. Solar Radiation
What we’re seeing
• Diel signal ≈ Solar Radiation
– Conditional: WS has enough ground-water
Another fun metric
Another fun metric
Mack Creek
WS1
http://farm4.static.flickr.com/3407/4617034064_e46e675a86.jpg
Early summer signal?
Discharge spike with that signal?
Snowmelt!
Temp helpful
What we’re seeing
• Diel signal ≈ Sol.Rad. via ET in summer
– Conditional: WS has enough ground-water
• Temperature -> Snowmelt signals in spring
– IF snow is present and melting
What we’re seeing
• Diel signal ≈ Sol.Rad. via ET in summer
– Conditional: WS has enough ground-water
• Temperature -> Snowmelt signals in spring
– IF snow is present and melting
• Watersheds may have neither, one, or both
Stream
network
length
slope
Air
temp
soil
type
Data
Effective
Riparian
area**
Process
Diel
Solar
strength*
Snowmelt
(mm/day)
WS Snow
content
Radia’n
EvapoTranspiration
(mm/day)
WS groundwater content
Temporal
Drainage
parameters
Parameters
WS property
Measured
Estimated
*Diel Strength = amplitude of diel signal in cfs
** (Riparian) area contributing to diel signal, m2
How are ET induced signals affected by
base-flow levels and watershed
characteristics?
Watershed 1: July 1 -July 7, 2000 - 2009
Watershed 1: 2009
Watershed 10: 2009
Watershed 9: 2009
How are ET induced signals affected
by base-flow levels and watershed
characteristics?
1. WS1, WS9, and WS10 show signals that
correlate with air temperature, while WS2, WS3,
WS6, WS7 and WS8 signals don’t correlate
2. WS1 phase shifts are correlated to precipitation
and height of base flow.
3. WS1 time lags behave different from WS9 and
WS10.
Are diel fluctuations synchronized
across a watershed?
• Cap. Rod graph
8
9
10
11
Days in July, 2010
Data provided by Tom Voltz
12
13
Are diel fluctuations synchronized
across a watershed?
Yes: staff gage, capacitance rod, wells and
stream in phase
Does channel morphology influence
diel fluctuations?
Staff Gages in WS2
Bedrock channel staff gage
(July 7-8, 2010)
Bedrock channel staff gage
(July 14-15, 2010)
Change in Stage Height= 0.2- 0.3 cm
Alluvial channel staff gage (July 7-8, 2010)
Alluvial channel staff gage (July 14-15, 2010)
Change in Stage Height= 0.6 - 3.5 cm
Does channel morphology influence
diel fluctuations?
Yes: signal in alluvial reaches is stronger than
bedrock reaches
What are the mechanisms for the
influence of ET on diel fluctuations?
A Mathematical Model for
Stream Bank Outflow
Equations Modeling Saturated Flow:
 h  h 


2
2
x
z
k
2
2
Piezometric Head:
pw (x,z)
h(x,z)  z 
g
Conservation of Mass:
q  
Darcy’s Law:
q  k  h
Combining Darcy’s Law and Conservation of mass:
 k  h    h    k
2
Equations Modeling Saturated Flow:
 h  h




k
max
2
2
x
z
2
2
 h  h




k
min
2
2
x
z
2
2
Boundary Conditions:
h(0,z  H)  H
h(x,z)  z
h(x,Z)  Z
h
(X,z)  0
x
h
(x,0)  0
z

Solution to the Boundary Value Problem:
Z 
h(x,z)  Z   G( , ) (0,z  Z)  h(0,z  Z)dz
0 x
Z X


    G( , ) (x,z  Z)dxdz)

0 0 k
Piezometric Distribution:
Applications:
Model Outputs:
Q  2q l
Q  Qmax  Qmin
Physical Data:
Q  Qmax  Qmin
Water Table Geometry and Discharge:
q( )  k  h
Assuming the diel signal is local
and additive over channel length, does
sap flow in the vegetated alluvial
channel account for observed diel
fluctuations at the stream gage?
Diel Signal and Channel Lithology
Objective:
• Compare diel signal at stream gage to water
lost to trees growing in the channel:
– 1) approximating water loss from different
combinations of channel reaches using LiDAR tree
data
– 2) comparing these estimates to observed water
loss to transpiration
Methods: Channel Classification
Allometric Conversions
• Chapman-Richards function (Richards, 1959)
 H 1.37 1 b2 
ln 1  b0



DBH 
b1
where:
DBH = diameter at breast height (cm)
H = tree height (m)
b0, b1, b2 = species-specific coefficient
(Garman, 1995)


Allometric Conversions
• Douglas Fir Sapwood Area (Turner, 2000)

SW  c 1  ed DBH

2 
DBH 2 DBH

ib
ib
SBA   
 SW  
  
 
 2   2
Where:
SW = sapwood width
DBHib = DBH(1- 0.11)
SBA = sapwood area (m2)
c, d = species-specific coefficients
Allometric Conversions
• Red Alder
– Used liner relationship derived from data in
Moore, 2004
SBA  0.302443  DBH  - 0.03433
• For both species:
– Volume of water per tree per day = SBA x Sap flux
density
– Sum volumes for trees in combinations of reaches
Methods: Observed Water Loss
Results
Results
Interpretation
• Overestimation implies too many trees are
being included
– Low flow zones upstream?
• Best approximations exclude bedrock
channels and include all alluvial channels
• Solely vegetation in channel is capable of
producing the entire diel signal
Novel Findings
• Solar radiation is correlated to the amplitude of
the diel signal.
• Air temperature and discharge time lags depend
on watershed and antecedent precipitation.
• Diel signals exist and are in phase up the stream
network.
• Alluvial stage height fluctuations are greater than
bedrock stage height fluctuations.
• Vegetated alluvial channel area can produce the
measured diel fluctuations observed at stream
gage.
References
•
•
•
•
•
•
•
Barnard, H.R., Graham, C.B., Van Verseveld, W.J., Brooks, J.R., Bond, B.J., and McDonnell, J.J.
2010. Mechanistic assessment of hillslope transpiration controls of diel subsurface flow: a
steady-state irrigation approach. Ecohydrology. 3: 133–142
Bond, B.J., Jones, J.A., Phillips, N., Post, D., and McDonnell, J.J. 2002. The zone of vegetation
influence on baseflow revealed by diel patterns of streamflow and vegetation water use in a
headwater basin. Hydrol. Process. 16: 1671–1677
Clark, J. 2007. Models for Ecological Data: An Introduction. Oxford University Press.
Garman, Steven L., Acker, Steven A., Ohmann, Juliet L., Spies, Thomas A. 1995. Asympytotic
Height-Diameter Equations for Twenty-Four Tree Species in Western Oregon. Forest Research
Laboratory, Oregon State University. Research Contribution 10
Moore, G.W., Bond, B.J., Jones, J.A., Phillips, N., and Meinzer, F.C. 2004. Structural and
compositional controls on transpiration in 40- and 450-year-old riparian forests in western
Oregon, USA. Tree Physiology 24:481–491
Richards, F.J. 1959. A flexible growth function for empirical use. Journal of Experimental
Biology 10:290-300.
Turner, David P., Acker, Steven A., Means, Joseph E., Garman, Steven L. 1999. Assessing
alternative allometric algorithms for estimating leaf area of Douglas-fir trees and stands.
Forest Ecology and Management. 126:61-76