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Bob McKane, USEPA Bonnie Kwiatkowski & Ed Rastetter, Marine Biological Laboratory Marc Stieglitz & Feifei Pan, Georgia Institute of Technology ~ January.

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Presentation on theme: "Bob McKane, USEPA Bonnie Kwiatkowski & Ed Rastetter, Marine Biological Laboratory Marc Stieglitz & Feifei Pan, Georgia Institute of Technology ~ January."— Presentation transcript:

1 Bob McKane, USEPA Bonnie Kwiatkowski & Ed Rastetter, Marine Biological Laboratory Marc Stieglitz & Feifei Pan, Georgia Institute of Technology ~ January 30, 2008, Presentation to NSF Riparian Zone Workshop, Indianapolis, IN ~ H 2 O NO 3, NH 4, DON Nassauer Application of an Eco-hydrology Model to Riparian Forest Buffers in Agricultural Landscapes

2 Outline  Describe GT-MEL, a spatially-distributed eco-hydrology model  Demonstrate GT-MEL for a generalized agricultural-riparian system  BMPs  Uncertainties & Challenges: Controls on C-N-H 2 O interactions Scaling up from reach to watershed

3 Georgia Tech (GT) Hydrology Model Spatially Distributed Hydrologic Processes snobear.colorado.edu/IntroHydro/hydro.gif

4 GT is relatively simple 3 “free” parameters vs. dozens for some hydrology models (e.g., HSPF) P ET 1 QsQs D1D1 ET 2 D2D2 Q1Q1 Q2Q2 Q3Q3 s1s1 s2s2 s3s3 Bedrock Q4Q4 D3D3 s4s4 S = storage P = precipitation D = drainage (infiltration) Q = runoff ET = evapotranspiration Pan, Stieglitz & McKane in prep

5 Logistic Curves For Drainage & Runoff Water Filled Pore Space (WFPS) 0 f(x) 1 fc = soil field capacity, A s = fraction of saturation area Drainage 0 D max WFPS fc D 0 Q Subsurface runoff Qmax 0 1 Surface runoff AsAs 1.0 WFPS fc 1.0 WFPS fc 1.0 ( WFPS ) 0 0 0

6 Climate Station GT Applied to HJ Andrews Experimental Forest Western Oregon Cascades Photo: Al Levno

7 Multiple soil types & layers HJ Andrews Watershed #10, Oregon 10-hectare forested catchment, clearcut in 1975 Flexible sub-catchment delineation Flexible soil layers Bedrock

8 Stream Discharge (mm/d) Soil Moisture Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec 100 cm 70 cm 30 cm

9 N Leaching Denitrification  Simulates acclimation of plants & microbes to changing resources  Resources: H 2 O, PO 4, NH 4, NO 3, DON, N fixation, CO 2, light  Effects of climate, land use, & chemicals  Daily to century-scale responses  Simulates grasslands, forests, tundra, agricultural systems, wetlands... MEL: Multiple Element Limitation Model Rastetter et al., 2005, Ecological Applications 15(1)

10 Topographic control of H 2 O, C, N, P cycling Linking Hydrology & Biogeochemistry within Landscapes Stream NH 4, NO 3, PO 4 DON, DOC Plants Soils H2OH2OH2OH2O NH 4, NO 3, PO 4 DON, DOC, H2OH2OH2OH2O Plants Soils Stream Coupling of GT-MEL Daily time step Flexible spatial scale

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12 Agricultural GT-MEL Demo 1.Identify upland & riparian best management practices (BMPs  tradeoffs in crop yield and water quality) 2.How do C-N-H 2 O interactions control nitrogen removal effectiveness of upland & riparian zones? 3.How can buffers be managed to increase their N-removal effectivenss?

13 Generalized Agricultural Hillslope for Simulating Upland & Riparian BMPs Riparian forest, 0.5% slope  3 Buffer widths: 0, 50, 100 m  2 Stand Ages: 10 or 100 yr Corn field, 1% slope  3 fertilizer rates: 50, 100, 200 kg N ha -1 y -1 for 20 years 2x3x3 factorial: identify acceptable tradeoffs in crop yield and water quality NH 4 fertilizer Denitrification H 2 O, DIN, DON Simulating ten 100 X 100 m hillslope segments

14 Simulation Matrix: 2 Forest Ages X 3 Buffer Widths X 3 Fertilizer Rates Simulation #

15 Simulation Matrix: 2 Forest Ages X 3 Buffer Widths X 3 Fertilizer Rates Simulation # BMP WQ BMP YIELD

16 Tradeoff: Corn Yield vs. Water Quality Simulations with 100-m mature forest buffer DIN Export to Stream (kg N ha -1 y -1 ) NH 4 Fertilizer (kg N ha -1 y -1 ) Corn yield DIN export Corn Yield (t DM ha -1 y -1 ) BMP

17 EPA drinking water standard Nitrate-N (mg/L) Julian Day Concentration of NO 3 Exported to Stream EPA Drinking Water Standard No forest buffer, N fert = 200 kg N ha –1 y m forest buffer, N fert = 100 kg N ha –1 y -1 NH 4 Fertilizer Does not consider in-stream attenuation of NO3 – Need to link GT-MEL to stream network model

18 Where did all the fertilizer N go?Where did all the fertilizer N go? What processes were most important for protecting water quality?What processes were most important for protecting water quality?

19 kg N / ha (35% less N leaching) 20-yr Cumulative N Inputs & Losses

20 Soil Respiration (kg C ha -1 d -1 ) Dissolved NO 3 (mg N L -1 ) Mature Forest Buffer Corn, Segment 9 Denitrification (kg N ha -1 d -1 ) WFPS %

21  Riparian Management BMPs maximized denitrification, the main factor limiting N export to streams: BMPs maximized denitrification, the main factor limiting N export to streams: Forest buffer width most importantForest buffer width most important Mature forest denitrification highest: 20% more than young forest, 500% more than corn (more detritus = more denitrification)Mature forest denitrification highest: 20% more than young forest, 500% more than corn (more detritus = more denitrification) Sequestration of N in forest vegetation & soil unimportant Sequestration of N in forest vegetation & soil unimportant  Crop Management Fertilization rates, crop yields had to be reduced to meet water quality standard, even with mature forest buffer Fertilization rates, crop yields had to be reduced to meet water quality standard, even with mature forest buffer BMP SUMMARY

22 Chesapeake Peterjohn & Correll 1984 Willamette Valley Next: real-world tests of GT-MEL

23 Chesapeake Willamette Valley Regional applications of fine-scale process models are computationally expensive

24 GT-MEL Simplified model of first-order watersheds Statistically summarize model output describing fine-scale processes Regional predictions Spatial extrapolation Alexander et al snobear.colorado.edu/IntroHydro/hydro.gif Scaling Up Process Info from Hillslope to Region

25 Thanks!


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