Liwang Ma

Predicting Unsaturated Zone Nitrogen Mass Balances in Agricultural Settings of the United States

Unsaturated zone N fate and transport were evaluated at four sites to identify the predominant pathways of N cycling: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard and cornfield (Zea mays L.) in the lower Merced River study basin, California; and corn-soybean [Glycine max (L.) Merr.] rotations in study basins at Maple Creek, Nebraska, and at Morgan Creek, Maryland. We used inverse modeling with a new version of the Root Zone Water Quality Model (RZWQM2) to estimate soil hydraulic and nitrogen transformation parameters throughout the unsaturated zone; previous versions were limited to 3-m depth and relied on manual calibration. The overall goal of the modeling was to derive unsaturated zone N mass balances for the four sites. RZWQM2 showed promise for deeper simulation profiles. Relative root mean square error (RRMSE) values for predicted and observed nitrate concentrations in lysimeters were 0.40 and 0.52 for California (6.5 m depth) and Nebraska (10 m), respectively, and index of agreement (d) values were 0.60 and 0.71 (d varies between 0 and 1, with higher values indicating better agreement). For the shallow simulation profile (1 m) in Maryland, RRMSE and d for nitrate were 0.22 and 0.86, respectively. Except for Nebraska, predictions of average nitrate concentration at the bottom of the simulation profile agreed reasonably well with measured concentrations in monitoring wells. The largest additions of N were predicted to come from inorganic fertilizer (153-195 kg N ha(-1) yr(-1) in California) and N fixation (99 and 131 kg N ha(-1) yr(-1) in Maryland and Nebraska, respectively). Predicted N losses occurred primarily through plant uptake (144-237 kg N ha(-1) yr(-1)) and deep seepage out of the profile (56-102 kg N ha(-1) yr(-1)). Large reservoirs of organic N (up to 17,500 kg N ha(-1) m(-1) at Nebraska) were predicted to reside in the unsaturated zone, which has implications for potential future transfer of nitrate to groundwater.

Quantifying and understanding plant nitrogen uptake for systems modeling

Current Status and Future Needs in Modeling Plant Nitrogen Uptake: A Preface, L. Ma, L.R. Ahuja, and T.W. Bruulsema Modeling Nitrogen Fixation and Its Relationship to Nitrogen Uptake in the CROPGRO Model, K.J. Boote, G. Hoogenboom, J. W. Jones, and K. T. Ingram Modeling Nitrate Uptake and Nitrogen Dynamics in Winter Oilseed Rape (Brassuca napus L.), P. Malagoli, F. Meuriot, P. Laine, E. Le Deunff, and A. Ourry Control of Plant Nitrogen Uptake in Native Ecosystems by Rhizospheric Processes, H. BassiriRad, V. Gutschick, and H.L. Sehtiya Dissolved Organic Nitrogen and Mechanisms of Its Uptake by Plants in Agricultural Systems, D.L. Jones, J.F. Farrar, A.J. Macdonald, S.J. Kemmitt, and D.V. Murphy Water and Nitrogen Uptake and Responses in Models of Wheat, Potatoes, and Maize, P.D. Jamieson, R.F. Zyskowski, F.Y. Li, and M.A. Semenov Modeling Grain Protein Formation in Relation to Nitrogen Uptake and Remobilization in Rice, Y. Zhu, W. Li, H. Ye, G.S. McMaster, and W. Cao Modeling Water and Nitrogen Uptake Using a Single-Root Concept: Exemplified by the Use in the Daisy Model, S. Hansen, and P. Abrahamsen Modeling Plant Nitrogen Uptake Using Three-Dimensional and One-Dimensional Root Architecture, L. Wu, I.J. Bingham, J.A. Baddeley, and C.A. Watson Simulation of Nitrogen Demand and Uptake in Potato Using a Carbon-Assimilation Approach, D. Timlin, M. Kouznetsov, D. Fleisher, S.-H. Kim, and V.R. Reddy Roots Below One-Meter Depth Are Important for Uptake of Nitrate by Annual Crops, H.L. Kristensen and K. Thorup-Kristensen Nitrogen-Uptake Effects on Nitrogen Loss in Tile Drainage as Estimated by RZWQM, R.W. Malone and L. Ma Simulated Soil Water Content Effect on Plant Nitrogen Uptake and Export for Watershed Management, P. Wang, A. Sadeghi, L. Linker, J. Arnold, G. Shenk, and J. Wu

Data worth and prediction uncertainty for pesticide transport and fate models in Nebraska and Maryland, United States

BACKGROUND Complex environmental models are frequently extrapolated to overcome data limitations in space and time, but quantifying data worth to such models is rarely attempted. The authors determined which field observations most informed the parameters of agricultural system models applied to field sites in Nebraska (NE) and Maryland (MD), and identified parameters and observations that most influenced prediction uncertainty. RESULTS The standard error of regression of the calibrated models was about the same at both NE (0.59) and MD (0.58), and overall reductions in prediction uncertainties of metolachlor and metolachlor ethane sulfonic acid concentrations were 98.0 and 98.6% respectively. Observation data groups reduced the prediction uncertainty by 55-90% at NE and by 28-96% at MD. Soil hydraulic parameters were well informed by the observed data at both sites, but pesticide and macropore properties had comparatively larger contributions after model calibration. CONCLUSIONS Although the observed data were sparse, they substantially reduced prediction uncertainty in unsampled regions of pesticide breakthrough curves. Nitrate evidently functioned as a surrogate for soil hydraulic data in well-drained loam soils conducive to conservative transport of nitrogen. Pesticide properties and macropore parameters could most benefit from improved characterization further to reduce model misfit and prediction uncertainty.

Simulating Dryland Water Availability and Spring Wheat Production under Various Management Practices in the Northern Great Plains

Agricultural system models are useful tools to synthesize field experimental data and to extrapolate the results to longer periods of weather and other cropping systems. The objectives of this study were: 1) to quantify the effects of crop management practices and tillage on soil water and spring wheat production in a continuous spring wheat system using RZWQM2 model under a dryland condition, and 2) to extend the results to longer term weather conditions and alternate cropping systems and management practices. Measured soil water content, crop yield, and total above ground biomass under different tillage and plant management practices were used to calibrate and validate the RZWQM2 model. The model showed inevident impacts of tillage and significant reduction in grain yield and biomass under late planting, in agreement with observed differences among treatments. The hydrologic analysis under long-term climate variability showed a large water deficit (32.3 cm) for the spring wheat crop; Fallowing the dryland every other year conserved 4.2 cm water for the following wheat year, of which only 1.7 cm water was taken up by wheat, resulting in a yield increase of 249 kg ha-1 (13.7%). However, the annualized average total yield decreased 782 kg ha-1 (43.1%) due to one year fallow; thus the spring wheat-fallow rotation was not economical. Other long-term simulations showed that optimal planting dates ranged from March 1 to April 10, and the seeding rate with optimum economic return was 3.71 and 3.95 × 106 seeds ha-1 for conventional and ecological management treatments, respectively.

An Improved Express Fraction for Modeling Macropore/Subsurface Drain Interconnectivity

The rapid transport of contaminants through macropores and into subsurface drains is a concern. Recent research has proposed methods for incorporating this direct connectivity into contaminant transport models. For example, the one-dimensional pesticide fate and transport model, Root Zone Water Quality Model (RZWQM), was modified to include an express fraction parameter based on the percentage of macropores in direct hydraulic connection to subsurface drains. When macropore flow first reached the top of the water table (point midway between the drains), a macropore express fraction of water and chemical was routed directly into the subsurface drain, which improved predictions of concentration peaks. The remaining water and chemical was allowed to fill and mix with the water table, resulting in a concentration bulge at the water table. This research proposes an updated express fraction for RZWQM, which distributes water across all saturated layers between the drain and water table. Implicitly assumed is a uniform spatial distribution of macropores. This updated express fraction is evaluated using data from two isoxaflutole/metabolite field experiments in Allen County and Owen County IN (2000), where concentrations of parent and metabolite were measured in the drain flow. The results showed a slight improvement in the prediction of chemical concentrations on the recession limbs of drainage hydrographs.

Spatial Water Quality Modeling Framework Development Using ArcGIS 9Spatial Water Quality Modeling Framework Development Using ArcGIS 9

Most agricultural water quality models are based on lumped parameterizations of spatial processes. The MARIA-GIS (Management of Agricultural Resources through Integrated Assessment and Geographic Information Systems) water quality tool has been developed to predict space-time planning scenarios across spatially variable agricultural landscapes. The tool runs under the ArcGIS 9 environment, and consists of a multi-functional system for agricultural production and water quality simulation modeling; and spatial data storage, analysis, and display. MARIA-GIS offers a spatial framework for integrating a complex, agricultural system water quality model (modified USDA-ARS RZWQM) with interaction between simulated land areas via overland runoff and runon. MARIA-GIS also provides the increased interface sophistication necessary for distributed hydrologic modeling. This paper describes the MARIA-GIS development history, with special emphasis on the spatial water quality modeling GIS framework and the incorporated simulation modeling components.