LAND COVER EFFECTS ONWATERSHED HYDROLOGIC
MEMORY
Jason P. JulianRobert H. Gardner
Oct 14, 2013
Dai
ly D
isch
arge
(m3 /s
)
Runoff = Precip – ET – Soil Moisture – Groundwater
Watershed Hydrologic Memory
Morphometric variablesArea (A)
Stream order (OHS)
Drainage density (Dd)
Mean channel slope (Sc)
Basin shape (Rf)
Geologic variablesSilt-clay percentage (SC%)
Soil depth to bedrock (Zbr)
Hydrologic variablesReservoir storage percentage (RS%)
Precipitation effectiveness ratio (Rpe)
Land-cover variablesPercent water-wetland (%WW)
Percent urban (%UR)
Percent forest (%FO)
Percent agriculture (%AG)
Runoff affected by …
Eastern Piedmont – 87 watersheds• Similar morphometry
• Pear- or oval-shaped• Dendritic drainage
• Moderate relief • neither topographic or
subsurface controls dominate
• Similar geology• Thick clay-rich soils• Deeply weathered bedrock
• Similar climate• Mid-latitude, humid subtropical• No dry season
• Many flow gages with long continuous daily records
Urban
Urban
Agriculture
Forest
Grassland
Barren
Wetland
Water
Morphometric variablesArea (A)
Stream order (OHS)
Drainage density (Dd)
Mean channel slope (Sc)
Basin form ratio (Rf)
Geologic variablesSilt-clay percentage (SC%)
Depth to bedrock (Zbr)
Hydrologic variablesReservoir storage percentage (RS%)
Precipitation effectiveness ratio (Rpe)
Land-cover variablesPercent water-wetland (%WW)
Percent urban (%UR)
Percent forest (%FO)
Percent agriculture (%AG)
Runoff affected by …
Which period or frequency will you analyze?
All of them
What about stationarity with respect to climate?
We use the same 40-y (1968-2007) records for all watersheds
1968 2008
decadal
yearly
monthly
dailyIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII
Pd
Pcp
Pa
annual peak
cross point
βlf
βhf
-4
-6
-12
-10
-8
dailyweeklymonthlyyearlydecadal
frequency
spec
tral p
ower
(or v
aria
nce)
Power Spectral Analysis(think temporal correlation using a moving window)
(long-term memory)
(short-term memory)
Rainfall - (white-noise) Runoff - (red-noise)
fcp = 5.6 ± 0.6-βhf = 0.42 ± 0.05-βlf = 0.02 ± 0.02
fcp = 6.0 ± 1.3-βhf = 1.84 ± 1.15-βlf = 0.45 ± 0.16
cross-pointShort-term memoryLong-term memory
Spectral VariableBest landscape predictor
(r)Stepwise model r2
(α = 0.05)Daily power, Pd %Wetland (-0.49) 0.57
Annual power, Pa %Wetland (0.41) 0.21*
Spectral slope, -β0 %Wetland (0.57) 0.62
Cross point power, Pcp %Urban (0.50) 0.39
Cross point frequency, fcp Slope (-0.32) 0.20*
Long-term memory, -βlf %Urban (-0.47) 0.43
Short-term memory, -βhf %Wetland (0.55) 0.58
Do landscape attributes dictate a catchment’s hydrologic memory?
* Low correlation
Annual power, Pa Daily power, Pd Cross-point power, Pcp
Den
sity
Cross point frequency, fcp
Den
sity
Den
sity
Spectral slope, -β0 Low-frequency slope, -βlf High-frequency slope, -βhf
Watershed Memory
Runoff Variance
Urban coverage, %UR
Dai
ly P
ower
P dr = -0.20
r = 0.67
r = -0.24
r = 0.68
cp = 11%
cp = 13%
Lon
g-te
rm m
emor
y
-βlf
cp = 14%
r = 0.37r = -0.65
Cro
ss-p
oint
pow
er
P cp
Urban Thresholds
Stream biota studies with 10-15% threshold• Paul and Meyer, 2001, Ann Rev Ecology,
Evolution, and Systematics• Utz et al., 2009, Ecological Indicators• Roy et al., 2003, Freshwater Biology
Urban coverage, %UR
Dai
ly P
ower
P dr = -0.20
r = 0.67
r = -0.24
r = 0.68
cp = 11%
cp = 13%
Lon
g-te
rm m
emor
y
-βlf
cp = 14%
r = 0.37r = -0.65
Cro
ss-p
oint
pow
er
P cp
Urban Thresholds
Affects hydrologic drought?
adapted fromVannote et al., 1980
Longitudinal Spatial Patterns in Spectral Variables
Stream Order12
3
4
5
6
7
Precipitation
Runoff ‐ variance
Runoff ‐memory
Climate-influenced
Landscape-influenced
Low frequency Pa -βlf
High frequency fcp -βhf
A matrix for characterizing Hydrologic Signatures?
Land Cover Effects on Runoff Land cover can have considerable and predictable
effects on runoff patterns (aka watershed memory)
10-15% urban threshold above which urban coverage becomes the dominant control on runoff patterns
Downstream threshold (after 3rd-order) where watershed processes become dominant over precipitation in determining runoff patterns in Eastern Piedmont
Matrix for hydrologic signatures:[climate vs. landscape effects] [low vs. high frequency events]
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