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Plant Production Model Evaluation for the Root Zone Water Quality Model (RZWQM 3.2) in Ohio
- Landa, Feliks M., Fausey, Norman R., Nokes, Sue E., Hanson, Jonathan D.
- Agronomy journal 1999 v.91 no.2 pp. 220-227
- Zea mays, Glycine max, mathematical models, soil water, water quality, simulation models, field experimentation, calibration, leaves, stems, seeds, dry matter partitioning, soil water content, nitrate nitrogen, validity, prediction, seasonal variation, leaf area, evapotranspiration, nutrient availability, biomass production, Ohio
- The Ohio Management Systems Evaluation Areas (MSEA) project focused on developing and evaluating improved agricultural management systems and predictive models. The Root Zone Water Quality Model (RZWQM) is an environmental model for simulating water, chemical, and biological response of agricultural management systems. This paper presents calibration and evaluation of the generic plant production model of RZWQM, as well as some evaluation results for the nitrate and soil water content predictions. Corn (L.) and soybean [ (L.) Merr.] biomass data collected at the Ohio MSEA from 1991 to 1993 were used for evaluation. Data from 1992 were used in calibrating RZWQM, and data from two other years (1991 and 1993) at the same site were used for validation. Crop growth predictions were compared with observed values of leaf, stem, and seed biomass collected throughout the growing season. Leaf and stem biomass predictions generally fell within 1 SD of the observed values, but for all years there were dates when predictions were outside of the observed range. RZWQM predicted seed biomass or yield adequately for all 3 years, with predictions falling within 1 SD of the observed values. Soil water content estimates for corn were higher than observed values late in the season, perhaps because of underestimates of evapotranspiration due to errors in leaf area predictions. The model overpredicted nitrate concentrations for the corn plot late in the season. Nitrate concentrations for the soybean plot were generally underpredicted. These differences may be due to underestimates of the fast humus pool of the nutrient model and of the N fixation rate for soybean. More evaluation is needed to refine the nitrate and soil water content predictions.