Coupling Nitrogen Transport and Transformation Model with Land Surface Scheme SABAE-HW: Application to the Canadian Prairies

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HW-1 Coupling Nitrogen Transport and Transformation Model with Land Surface Scheme SABAE-HW: Application to the Canadian Prairies Alireza Hejazi and Allan D. Woodbury Department of Civil Engineering DRI User Hydrology Workshop Winnipeg, Manitoba, Canada January 2010

HW-2 Acknowledgements Ph.D. Thesis work by Alireza Hejai Garth Van der Kamp (Sask Research) Wole Akinremi (U. Manitoba) Yefang Jiang (PEI Water Stewardship)

Hydrology and Nutrient Cycling HW-3 Interested in developing models for coupled hydrology and nutrient cycling, in prairie environments. Supports DRI collaboration with CWN work. This work will provide a new direction in advancing understanding of emerging water issues.

HW-4 Overall Objectives and Approach Develop coupled hydrologic models to help understand the interactions between climate, hydrology, vegetation, and nutrient cycling over diverse scales. Apply the models to understand and solve problems relevant to water quality and supply.

HW-5 Motivation and Specific Objectives Motivations: Climate and land use changes are (or will) occur in over the prairies Nutrient transport under winter conditions not well understood What are the local and regional impacts of these changes on water quality and the environment?

HW-6 Motivation Technical Objectives: Enhance modeling capabilities of SABAE, gclass, or CHRM for regional scale water, nutrient and thermal fluxes Incorporate realistic mechanisms under freeze and thaw cycles Develop ability to understand and predict the effects of climate, drought and land-use changes

HW-7 Motivation Other Objectives Build stronger ties between UM and Water Stewardship, other interested partners

Courtesy of Yefang Jiang, and Jim Young, PEI Provincial sources HW-8 Coastline on PEI 20% of land in potato production rotation Dependent on pesticide/fertilizer use Permeable till/ Redbed sandstone (0-200 m) forms a porous-fractured aquifer

Groundwater Nitrate (NO 3 ) HW-9 Many watersheds with higher ave. concentrations and in some cases, nitrate levels exceed health threshold of 10 mg/l. Areas associated with greater agricultural intensity. 90% have elevated levels beyond background. Both mean nitrate levels from tested wells and the # of wells with nitrate >10 mg/l increased over time. Contamination 0 25 50 kilometers Average Groundwater Nitrate Concentrations (mg/l) 5 to 10 (10) 3 to 5 (25) 2 to 3 (10) 0 to 2 (5) *Based on 14555 samples from 2000 to 2005 ~40% of the Island is farm land (white) Courtesy of Yefang Jiang, and Jim Young, PEI Provincial sources

Surface Water Nitrate Contamination HW-10 Nitrate (mg/l) 8 7 6 5 4 3 Bear Dunk Mill Morell Wilmot Canadian Aquatic Life Guideline SW nitrate levels increased over time and exceeded the Canadian aquatic life guideline in some cases. Excessive nitrate contributed to eutrophication in some estuaries. 2 1 0 1965 1970 1975 1980 1985 1990 1995 2000 2005 Year (Date) Courtesy of Yefang Jiang, and Jim Young, PEI Provincial sources

HW-11 Nitrogen Cycle http://www.physicalgeography.net/fundamentals/9s.html

HW-12 Background Most of the studies confirm the increase of N fluxes during the freeze and thaw. N 2 Ofluxes were also increased in this period. Depthand durationof the snow pack are the important parameters to control soil temperature and soil moisture and N cycling during the melting period. It has been reported that N netmineralizationis not negligible in winter time. Some researchers have stated that nitrogen net mineralization increasesafter thawing period while there have been other studies indicating that there is no change in the N mineralization after soil frost. The cumulative effects of multiple freeze/thaw cycles must be known to estimate soil nitrogen losses over winter.

Available Models: Solute Transport and Transformations European nitrogen dynamics model: ANIMO DAISY SUNDIAL SOIL/SOILN (COUP) U.S. nitrogen dynamics model: NLEAP GLEAMS LEACHM RZWQM Solute transport model: SHAW HYDRUS HW-13

SABAE Model (Soil Atmosphere Boundary, Accurate Evaluations of Heat and Water) Is a soil-multilayer version of the Canadian Land Surface Scheme (CLASS) It allows a user to specify depth and number of soil layers. It extends the CLASS model to perform computations over refined discretization of any unsaturated soil column Input data ( Atmospheric, soil properties and vegetation cover) Out put ( Snow Pack, Soil temperature and soil moisture) HW-14

Benchmarking Field Comparisons A. Compare the results of SABAE-HW with Observation data HW-15 B. Compare the results of SABAE-HW with SHAW model Two Boundary Conditions: - Water table - Unit Gradient Soil Column was extended to: - 3 meters (11 layers) - 7meters (19 layers)

HW-16 Elevation 579.27 m Mean Annual Air Temp. 0.4 C Mean Total Annual Precipitation 467.2 mm Soil type is sand and sandy loam Cover Type mature jack pine, very sparse green alder

Snow Depth HW-17 Simulated and measured snow depths from June 2003 to Dec. 2005 Measured data versus SABAE Measured data versus SHAW Average err RMSE Correlation Average err RMSE Correlation -0.01 0.03 0.97-0.02 0.06 0.86 Average Error, Root Mean Square Error and Correlation values for simulated and measured snow depth within Old Jack Pine site from June 2003 to Dec. 2005

Soil Temperature HW-18

HW-19 Average Error, Root Mean Square Error and Correlation values for simulated and measured soil temperatures at various soil depths within Old Jack Pine site from Nov. 2004 to Feb. 2005 Measured data versus SABAE Measured data versus SHAW depth Average err RMSE Correlation Average err RMSE Correlation 7.5-2.11 2.60 0.90-0.7 1.84 0.66 22.5-1.34 1.82 0.90-0.33 1.31 0.79 50 0.47 0.91 0.89-0.2 0.91 0.89 100-1.23 1.66 0.94 0.7 0.94 0.97 June to Oct, 2005 Measured data versus SABAE Measured data versus SHAW depth Average err RMSE Correlation Average err RMSE Correlation 7.5-0.58 1.43 0.95-1.52 1.52 0.96 22.5-0.86 1.26 0.96-1.54 1.54 0.97 50-1.17 1.33 0.97-1.49 1.49 0.97 100-2.39 2.7 0.87-1.77 1.77 0.99

Soil Moisture HW-20

HW-21

Nitrogen Transport and Transformations Model HW-22 Assume here that manure is the only source of organic matter Single pool nitrogen transformation NH 4+ is strongly adsorbed by soil particles A majority of the leachatenitrogen is in the NO 3- form

HW-23 Processes Advection-dispersion, reaction and retardation Mass input from land-surface, atmosphere and not some average recharge Heat transport, energy fluxes Advective fluxes at flow sources/sinks, constant head and river boundaries NO 3 -N from all sources Freeze-Thaw mechanisms

Descriptive Algorithm for SABAE-HWS Model HW-24

Manure Application HW-25 Manure as a source of nutrients: Improves the physical condition of the soil Increases the organic matter content of the soil affects the changes of runoff and soil erosion The main concerns of regulators, agriculture: The rate of nitrate and nitrogen Over fertilizing ( mineralizable form )

Winter Manure Application HW-26 Manure is only applied in winter if there is a lack of storage capacity or inflexibility in spreading manure due to limited storage. Limited manure storage structures Availability of time for manure spreading Reduced soil compaction It should be studied under two conditions: 1. Hydrological process 2. Nutrient transport a. Infiltration b. runoff

Future Work HW-27 Currently running SABAE-HW over the drought period of 10 years (1997-2006) and compare the results with OJP measured data and SHAW model A detailed discretizationof ammonium and nitrate equations including nitrogen transformation processes should be completed soon Solute transport model will be compared to analytical solutions developed by Carlier, 2008 and Kumar et al., 2009 subjected to their boundary conditions, and also SHAW model Nitrogen transport and transformation model will be coupled with SABAE-HW at the time step level (SABAE-HWS). First order coefficients need to be optimized The field data will be applied for calibration and validation of SABAE- HWS. Winter manure application needs to be validated

Conclusions HW-28 Outcome: coupled CHRM or SABAE with nitrogen biogeochemistry a. Study effects of climate on N-cycling b. Scale on process model results c. Sensitivities to various properties/ parameters. Significance: Hydrologic synthesis is needed to inform policy makers to deal with challenges of water quality and supply.