Toby Ahrens 26 Oct 2004 Linking Spatial Variability of Soil N Retention Mechanisms to Landscape-level Fates in Yaqui Valley, Mexico

Goals  Quantify degrees of N contamination under different management regimes  Investigate the value of spatial data sets varying in resolution  Integrate 10+ yrs of biogeochemistry research in the Valley

What do I need to do to get there?  Link process and transport models  Improve process models Include abiotic retention mechanisms  Develop spatial data sets Eg. soil type, texture, mineralogy, management, leaching potential

Coastal eutrophication Declassified Keyhole satellite image March 8, 1978 (Thanks Mike!)

Nitrate-contaminated groundwater <10 ppm ppm 116 ppm Hungate, unpublished data,

Two Q’s guiding my efforts: 1.What soil characteristics control N availability, retention and loss in OM- deficient ag soils? 2.Can the spatial variability of these characteristics be linked to aqueous N fates throughout the Valley?

Model schematic… soil properties NLOSS soil mineralogy crop yield (+N use) Solute transport un/saturated boundary conditions management unit crop type Output maps: Leaching vulnerability Aquifer contamination Coastal N sources groundwater depth

Lee Addams’s model

Major modeling efforts:  Soil submodel including sorption isotherms and mineral fixation  Solute transport component to saturated hydrology model  Saturated/unsaturated boundary layer conditions  Spatial data referencing

Applied N: 250 kg/ha Plant uptake: 31% Leached: 2-5% (14-26%) Gaseous losses: NO+N 2 O: 2-5% NH 3 : __% N 2 : __% ? ? ? ? Drainage canals: NO NH 4 + : 2-5% NO+N 2 O: <0.1% References: Riley et al Harrison 2003 Matson et al Ortiz-Monasterio, pers. comm.

Applied N: 250 kg/ha Plant uptake: 31% Leached: 2-5% (14-26%) Gaseous losses: NO+N 2 O: 2-5% NH 3 : __% N 2 : __% ? ? ? ? Drainage canals: NO NH 4 + : 2-5% NO+N 2 O: <0.1% Field experiments: abiotic fixation link leaching potential to actual fates

Future directions and broader implications…  Does better spatial resolution increase our ability to predict SW/GW vulnerability? And the degree of how mechanistic submodels are?  Identify thresholds for N retention Or pesticides…  Investigate management scenarios Different irrigation or fertilization regimes

Resolution of input data: Field based…

Policy implications  The Danish and Dutch experiences: N control policies aimed at reducing N leaching (SW + GW) and NH3 and N2O emissions Importance of model validation