Soil architecture versus management as controls on nitrate leaching

Transcription

1 Soil architecture versus management as controls on nitrate leaching W. Adam Sigler Co-Authors: Stephanie A. Ewing, Clain A. Jones, Robert A. Payn, Simon Fordyce, EN Jack Brookshire MT AWRA; October 20 th, 2017

2 Funding Acknowledgments USDA/NIFA National Integrated Water Quality Program MSU College of Agriculture MSU Office of the Vice President of Research Montana EPSCoR MSU Extension Water Quality Montana Fertilizer Advisory Committee Research Team (who are not coauthors) Douglas Jackson-Smith, Utah State University Perry Miller, Montana State University Jane Klassen, LRES Envr. Analysis Lab, MSU Field Help (who are not coauthors) Robby Robertson, MSU/BSWC

3 Judith Basin Nitrogen Project Today s Talk Broader Project Goals M1 Nitrate-N 1. To better understand the sources of nitrates in ground and surface water 2. To evaluate which management practices are likely to be effective to reduce nitrate leaching and to be adopted 3. To engage the local community in participatory research to meet the first two goals How do agricultural management practices interact with soil architecture to control nitrate leaching?

4 Acknowledgments Producer Research Advisory Group (PRAG) Nita Bronec Greg Grove Jim Kulish Dave Linker Brandon Morris Bing VonBergen Advisory Committee Tom Butcher: Producer, Fergus County Rick Caquelin : Montana NRCS, Central Montana Region Range Specialist Chrissy Cook: MSU Extension, Judith Basin County Darren Crawford: MSU Extension, Fergus County Patricia Creamer: Montana NRCS, Judith Basin District Conservationist Pat Hensleigh: Montana NRCS, State Agronomist, Bozeman Curtis Hershberger: Producer and owner of NGS Sales, Denton Jane Holzer: Montana Salinity Control Association Mark McLendon: NRCS Soil Conservationist, Lewistown Terry Metcalfe: Producer, Benchland Deen L. Pomeroy, RS: Central Montana Health District Ken Ronish: Fergus County Commissioner, Denton David Wichman: CARC, Superintendent and Agronomist

5 Study Area Judith River Watershed and Landforms

6 Evidence of Soil Architecture Influence (Thickness of Fines) 11.1 kg N ha -1 yr kg N ha -1 yr -1 John et al. (2017) found 17.4 kg N ha -1 increase with a 60 cm decrease in thickness of fines W. Adam Sigler, Stephanie A. Ewing, Clain A. Jones, Robert A. Payn, E.N. Jack Brookshire, Jane K. Klassen, Douglas Jackson-Smith, Gary S. Weissmann, In Press. Connections among soil, ground, and surface water chemistries characterize nitrogen loss from an agricultural landscape in the upper Missouri River basin. J. Hydrol.

7 Evidence of Management Influence (Fallow in Rotation) Sigler et al., In Press, J. Hydrol.

8 Soil architecture versus management controls on nitrate leaching Questions 1.How does soil architecture dictate vulnerability to leaching? 2.How does management affect vulnerability to leaching? 3.How do management and soil architecture interact with precipitation to determine nitrate leaching rates?

9 Study Area Judith River Watershed, Landforms and Fields Field B Field C

10 Instrumented Soil Pits in Study Fields Field C Soil moisture and temperature Lysimeters

11 Lysimeter NO3 and Moisture for Five Instrumented Subfields

12 Soil Water and Solute Model Hydrus 1D Input 1. Precipitation 2. Potential Evaporation 3. Potential Transpiration 4. Soil horizon hydro param (van Genuchten) Output 1. Soil moisture content 2. Water flux Richards Equation van Genuchten Equation Parameters Θr - residual soil water content (L 3 /L 3 ) Θs - saturated soil water content (L 3 /L 3 ) α - corresponding approximately to the inverse of air-entry matric potential or bubbling pressure (1/L) n pore size distribution index (dimensionless) Ks saturated hydraulic conductivity (L/T) l pore connectivity/tortuosity parameter (dimensionless), assumed to be 2 in original Brooks and Corey 1964

13 Model Calibration using data from NRCS SCAN and BOR Agrimet Sites Volumetric soil moisture (Θ) starting A 0-15cm 2 3 Bk cm 4 Bk cm 5 Bk cm C cm

14 Model Calibration using data from NRCS SCAN and BOR Agrimet Sites 1 A 0-15cm 2 3 Bk cm 4 Bk cm van Genuchten Equation Parameters Θr - residual soil water content (L 3 /L 3 ) Θs - saturated soil water content (L 3 /L 3 ) α - corresponding approximately to the inverse of air-entry matric potential or bubbling pressure (1/L) n pore size distribution index (dimensionless) Ks saturated hydraulic conductivity (L/T) l pore connectivity/tortuosity parameter (dimensionless), assumed to be 2 in original Brooks and Corey Bk cm C cm

15 Modeling to Address Soil Architecture versus Management Question Hypothetical Thick Soil 80 cm Fines Gravel van Genuchten soil parameters Fines (clay loam) Θr = 0.08 (L3/L3) Θs = 0.44 (L3/L3) α = 0.02 (1/L) n = 1.41 (dimensionless) Ks = 8.18 (L/T) Hypothetical Thin Soil 40 cm Fines Gravel Gravel (sand) Θr = 0.05 (L3/L3) Θs = 0.37 (L3/L3) α = 0.04 (1/L) n = 3.2 (dimensionless) Ks = 640 (L/T)

16 Agrimet Precip Fallow Crop Crop Fallow Crop Agrimet PET

17 Crop Crop Fallow Crop Crop

18 Crop Fallow Crop Crop Fallow

19 Crop Fallow Crop Crop Fallow Soil Architecture (Thickness of Fines) 1. Deep perc in shallow profile is 1.5x that in the deep profile Management (Fallow in Rotation) 2. Deep perc with fallow is 4 times greater than with crop

20 Deep Percolation (Water) Nitrate Concentration (Nitrogen) Soil Architecture (Thickness of Fines) 1. Deep perc in shallow profile is 1.5x that in the deep profile 1b. Nitrate may be higher in thicker soils 2. Deep perc with fallow is 4 times greater than with crop Management (Fallow in Rotation) 2b. Nitrate is higher after fallow than after crop.

21 Next Steps Field C 2011 NAIP NDVI 1. Model calibration to measured soil moisture 2. Use of field specific precipitation 3. Comparison of modeled ET to ET measured with eddy covariance tower 4. Assessment of field scale spatial distribution of moisture and leaching dynamics C2W (Green) 0 (Not Green)

22 Management and Broader Implications Fallow Recrop Thin soils and fallow periods = highest leaching risk Need to manage soil water and soil nitrate More variable precipitation = more difficult management

23 Questions