Overview of Nitrogen Mass Balances in Agricultural Ecosystems: Mississippi River Basin Budget

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Kenneth Golden
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1 Overview of Nitrogen Mass Balances in Agricultural Ecosystems: Mississippi River Basin Budget Mark B. David University of Illinois at Urbana-Champaign Workshop on N Assessment Science in the USA May 19, 2010

2 What I will cover focus on N sources and riverine exports in the Mississippi River Basin (MRB) a little quick history of balances first state and county level data sets recent N balances predictions of riverine loads what about N inputs not exported by rivers?

3 What to include in N balances? fertilizer inputs volatilization biological N 2 fixation (legumes) atmospheric deposition manure (and volatilization) human consumption (sewage effluent) crop harvest crop senescence denitrification soil N mineralization and immobilization

4 N Inputs for Mississippi River Basin (MRB) From Goolsby et al. (1999)

5 N Outputs for MRB From Goolsby et al. (1999)

6 N Balance for MRB From Goolsby et al. (1999)

7 Illinois N Mass Balance 2001 Fertilizer Soybean N 2 Fixation Other N 2 Fixation Soil Organic N 0 Deposition Net mineralization Grain Human Manure 52 Animal Sewage Animal Product 35 Net grain export 1186? (1000 tons N yr -1 ) Riverine Export Field +? In-stream denitrification From David et al. (2001)

8 From Gentry et al. (2009)

9 Components of Nitrogen Mass Balances net nitrogen inputs (NNI) = inputs outputs inputs (deposition, fertilizer, fixation) outputs (grain harvest - human + animal consumption) NNI is N available for leaching, denitrification, adding to soil N pools data from agricultural statistics (crops and animals), fertilizer industry, assumptions about N in various components

10 Recent Changes in Assumptions decreasing corn protein N concentration was about 10% now 7 to 8% and decreasing soybean N 2 fixation was assumed to be 50% of above-ground biomass N now perhaps 65%

11 40 30 Fertilizer Mississippi River Basin nitrogen balance Nitrogen Balance Component (kg ha -1 yr -1 ) Fixation Deposition Harvest Manure Human consumption Net Nitrogen Inputs

12 Drainage by tiles and ditches

14 NH 3 Nitrification NO 3 - NO 3

15 Embarras River - Camargo

16 20 Embarras River NITRATE (mg N L -1 )

17 Linking N balances to N Export hydrology overwhelming factor tile drainage can look at watershed N export as a fraction of net N inputs most studies have found this to be about 25% however in MRB we know it is larger in critical areas fate of remainder? denitrification?

18 Major Mississippi Subbasins

19 Mississippi River Basin Riverine nitrate-n NNI Ohio Missouri Upper Miss. Lower Miss Water yield (cm yr -1 )

20 Mississippi River Basin Riverine nitrate-n NNI Ohio Missouri Upper Miss. Lower Miss Water yield (cm yr -1 )

21 Mississippi River Basin Riverine nitrate-n NNI r 2 =0.84 Ohio Missouri Upper Miss. Lower Miss. Des Moines Embarras r 2 =0.61 r 2 =0.75 r 2 = Water yield (cm yr -1 ) r 2 =0.70 r 2 =0.04

22 County Level Analysis all counties in MRB (1768) 1997 to 2006 annual data on fertilizer, crops, animals, people, deposition 153 watersheds with winter & spring nitrate concentrations and loads predictive model from watersheds applied to all MRB counties

23 Annual N Fertilizer Applications Fertilizer (kg N ha -1 )

24 Fraction of County in Row Crops Fraction of County in Crops

25 Tile drainage is concentrated in the corn belt Fraction Drain of county

26 Harvested N in Crops Harvested N

27 Net N Inputs (NNI) kg nnin ha

28 From IPNI

29 Negative N balances? this is a recent development not enough inputs compared to agronomic outputs our work and others suggest modern corn varieties now accessing and depleting soil organic N and slow rate difficult to measure and document probably only in last 10 years but, with negative balances riverine N has not decreased

30 Watershed Data 153 from across basin January to June nitrate-n concentrations and flow typically about 40 concentrations for a given location median watershed size was 2400 km 2 79 to km 2

31 Model to Predict Nitrate Load Load nitrate from January to June in kg N ha -1 = flow in cm * (0.0111*kg fertilizer N per ha) *human consumption of N in kg per ha *fraction of county tile drained R 2 = 0.83, n =153 fertilizer explains most of the variation of the overall model (76%), then tile drainage (17%), and human consumption (7%)

32 Modeled January to June Nitrate Export Predicted N Yield (kg N/ha)

33 January to June Nitrate-N Yield Predicted N Yield (kg N/ha)

34 Uncertainty in N Balances/Data Needs for Assessments N fertilizer (amounts, timing) crop coefficients biological N 2 fixation manure soil N pool changes (mineralization rates) what is net change each year? denitrification (N 2 versus N 2 O) importance in tile drained watersheds versus other? other gas fluxes ammonia volatilization

35 Acknowledgements Laurie Drinkwater, Cornell University much of this work is part of our NSF Dynamics of Coupled Natural and Human Systems Project Greg McIsaac Corey Mitchell Linda Jacobson

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