LAND COVER EFFECTS ON WATERSHED HYDROLOGIC MEMORY. Jason P. Julian Robert H. Gardner

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1 LAND COVER EFFECTS ON WATERSHED HYDROLOGIC MEMORY Jason P. Julian Robert H. Gardner Oct 14, 2013

2 Watershed Hydrologic Memory Runoff = Precip ET Soil Moisture Groundwater Daily Discharge (m 3 /s)

5 Runoff affected by Morphometric variables Area (A) Stream order (O HS ) Drainage density (D d ) Mean channel slope (S c ) Basin shape (R f ) Geologic variables Silt-clay percentage (SC%) Hydrologic variables Reservoir storage percentage (RS%) Precipitation effectiveness ratio (R pe ) Land-cover variables Percent water-wetland (%WW) Percent urban (%UR) Percent forest (%FO) Percent agriculture (%AG) Soil depth to bedrock (Z br )

Eastern Piedmont 87 watersheds Similar morphometry Pear- or oval-shaped Dendritic drainage Moderate relief neither topographic or subsurface controls dominate Similar

6 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

7 Urban Agriculture Forest Grassland Barren Wetland Water Urban

8 Runoff affected by Morphometric variables Area (A) Stream order (O HS ) Drainage density (D d ) Mean channel slope (S c ) Basin form ratio (R f ) Geologic variables Silt-clay percentage (SC%) Hydrologic variables Reservoir storage percentage (RS%) Precipitation effectiveness ratio (R pe ) Land-cover variables Percent water-wetland (%WW) Percent urban (%UR) Percent forest (%FO) Percent agriculture (%AG) Depth to bedrock (Z br )

9 What about stationarity with respect to climate? We use the same 40-y ( ) records for all watersheds Which period or frequency will you analyze? All of them

10 yearly monthly decadal IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII daily

11 Power Spectral Analysis (think temporal correlation using a moving window) -4 P a annual peak spectral power (or variance) β lf (long-term memory) P cp β hf (short-term memory) cross point P d -12 decadal yearly monthly frequency weekly daily

12 Rainfall - (white-noise) Runoff - (red-noise) cross-point Short-term memory Long-term memory f cp = 5.6 ± 0.6 -β hf = 0.42 ± β lf = 0.02 ± 0.02 f cp = 6.0 ± 1.3 -β hf = 1.84 ± β lf = 0.45 ± 0.16

13 Do landscape attributes dictate a catchment s hydrologic memory? Spectral Variable Best landscape predictor (r) Stepwise model r 2 (α = 0.05) Daily power, P d %Wetland (-0.49) 0.57 Annual power, P a %Wetland (0.41) 0.21* Spectral slope, -β 0 %Wetland (0.57) 0.62 Cross point power, P cp %Urban (0.50) 0.39 Cross point frequency, f cp Slope (-0.32) 0.20* Long-term memory, -β lf %Urban (-0.47) 0.43 Short-term memory, -β hf %Wetland (0.55) 0.58 * Low correlation

14 Runoff Variance Density Annual power, P a Daily power, P d Cross-point power, P cp Density Density Cross point frequency, f cp Watershed Memory Spectral slope, -β 0 Low-frequency slope, -β lf High-frequency slope, -β hf

15 r = Pd r = 0.67 cp = 11% Pcp r = 0.68 cp = 13% r = cp = 14% -βlf Daily Power Cross-point power Long-term memory Urban Thresholds r = r = 0.37 Urban coverage, %UR 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

r = -0.20 Pd r = 0.67 cp = 11% Pcp r = 0.68 cp = 13% r = -0.

16 r = Pd r = 0.67 cp = 11% Pcp r = 0.68 cp = 13% r = cp = 14% -βlf Daily Power Cross-point power Long-term memory Urban Thresholds r = r = 0.37 Urban coverage, %UR Affects hydrologic drought?

17 Longitudinal Spatial Patterns in Spectral Variables Stream Order adapted from Vannote et al., 1980

18 Runoff variance Precipitation Runoff memory

19 A matrix for characterizing Hydrologic Signatures? Low frequency P a Climateinfluenced Landscapeinfluenced -β lf High frequency f cp -β hf

20 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 3 rd -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]

22 Questions?

BAEN 673 / February 18, 2016 Hydrologic Processes

BAEN 673 / February 18, 2016 Hydrologic Processes Assignment: HW#7 Next class lecture in AEPM 104 Today s topics SWAT exercise #2 The SWAT model review paper Hydrologic processes The Hydrologic Processes