Techniques to reliably calibrate computer models are needed before the models can be applied to help solve natural resource problems. The USDA‐ARS Root Zone Water Quality Model (RZWQM) is a comprehensive simulation model designed to predict hydrologic and chemical response, including potential for ground‐water contamination, of agricultural management systems. RZWQM Version 3.2 was calibrated and evaluated at sites in Iowa, Minnesota, Missouri, Nebraska, and Ohio as part of the Management Systems Evaluation Areas (MSEA) project and at a site near Sterling in northeastern Colorado. Soil horizon description and a description of the physical and hydraulic properties of the soil were required to initialize the model. Calibration for nutrient cycling involved adjusting the model coefficients for mineralization, infiltration, and denitrification. Initial N pool sizes were estimated using medium to long‐term computer simulations. Maximum N uptake rate, plant respiration, specific leaf area, and the effect of age at the time of propagule development and senescence were used to calibrate the plant production and yield component. To match the observed results for soil water, N, and plant growth, an iterative approach for calibrating the model was followed. When done methodically, total biomass estimates were within 5%, yield estimates were within l0%, and N uptake was within 20% of field measurements. Calibration of the C and N dynamics module produced results that were generally within 20 to 50 kg ha−1 of measured values for soil profile NO−3‐N. Independent evaluations of the calibrated model focused on four indicator output variables related to plant growth—total biomass, yield, N uptake, and N in the soil profile. Predictions matched the observed data in most cases. The crop model is very sensitive to plant N content. Even small errors in simulating N uptake levels can result in substantial errors in estimates of yield and total aboveground biomass. The model predicted biomass and yield well on irrigated and most dryland management systems and adequately simulated crop variables at various positions along the landscape.
On agricultural lands, animal waste disposal as fertilizer has been practiced since the beginning of agriculture. However, the practice has been an environmental concern in recent years due to over disposal of animal waste in some instances. This study evaluated soil NO3 response to beef‐manure application on a corn (Zea mays L.) field and tested the Root Zone Water Quality Model (RZWQM) for manure management. The experiment site was located in Northeastern Colorado on a silage‐corn field with a history of fertilization with beef manure every fall after corn harvest. To study the residual effect of long‐term manure application, 582 kg ha‐1 of manure‐N was applied to the east side of the field in the Fall of 1993, 1994, and 1995, while the west side received manure in 1993 only. Average silage‐corn yields from the west site were 25.4, 31.9, and 22.5 Mg ha‐1 for 1994, 1995, and 1996, respectively, which were not significantly different from that harvested from the east site (25.1, 30.9, and 24.3 Mg ha‐1, respectively). Average soil NO3 concentrations decreased significantly from 14.9 to 8.5 mg N kg‐1 in the top 30 cm of soil, and from 5.4 to 3.7 mg N kg‐1 in the 30‐ to 60‐cm soil profile after stopping manure application. No significant difference in soil NO3 concentrations between the manured and not‐manured sites was found below 60 cm. Average plant N uptake ranged from 140 to 362 kg N ha‐1 and was not significantly different between the two sites. The RZWQM was calibrated on the basis of the measured silage‐corn yield and plant N uptake, and was then used to predict soil NO3 concentration and total water storage in the soil profile. Generally, the calibrated model provided adequate predictions for both NO3 and soil water content with r2 > 0.83. The model was further used to evaluate alternative scenarios of manure and water management.
We describe the theory and current development state of the pesticide process module of the USDA‐Agricultural Research Service Root Zone Water Quality Model, or RZWQM. Several processes which are significant in determining the fate of a pesticide application are included together in this module for the first time, including application technique, root uptake, ionic dissociation, soil depth dependence of persistence, volatilization, wicking upward in soil and aging of residues. The pesticide module requires a large number of parameters to run (as does the RZWQM model as a whole) and it is becoming clear that RZWQM will find most interest and use as part of a ‘scenario’ in which all data requirements are supplied and the predictions of the system compared with a real (usually partial) data set. Such a scenario may then be modified to examine the response of the system to changes in inputs. It also has significant potential as a technology transfer or teaching tool, providing detailed understanding of a specific agronomic system and its potential impacts on the environment. Published in 2004 for SCI by John Wiley & Sons, Ltd.
Due to the complex nature of pesticide transport, process-based models can be difficult to use. For example, pesticide transport can be effected by macropore flow, and can be further complicated by sorption, desorption and degradation occurring at different rates in different soil compartments. We have used the Root Zone Water Quality Model (RZWQM) to investigate these phenomena with field data that included two management conditions (till and no-till) and metribuzin concentrations in percolate, runoff and soil. Metribuzin degradation and transport were simulated using three pesticide sorption models available in RZWQM: (a) instantaneous equilibrium-only (EO); (b) equilibrium-kinetic (EK, includes sites with slow desorption and no degradation); (c) equilibrium-bound (EB, includes irreversibly bound sites with relatively slow degradation). Site-specific RZWQM input included water retention curves from four soil depths, saturated hydraulic conductivity from four soil depths and the metribuzin partition coefficient. The calibrated parameters were macropore radius, surface crust saturated hydraulic conductivity, kinetic parameters, irreversible binding parameters and metribuzin half-life. The results indicate that (1) simulated metribuzin persistence was more accurate using the EK (root mean square error, RMSE = 0.03 kg ha(-1)) and EB (RMSE = 0.03 kg ha(-1)) sorption models compared to the EO (RMSE = 0.08 kg ha(-1)) model because of slowing metribuzin degradation rate with time and (2) simulating macropore flow resulted in prediction of metribuzin transport in percolate over the simulation period within a factor of two of that observed using all three pesticide sorption models. Moreover, little difference in simulated daily transport was observed between the three pesticide sorption models, except that the EB model substantially under-predicted metribuzin transport in runoff and percolate >30 days after application when transported concentrations were relatively low. This suggests that when macropore flow and hydrology are accurately simulated, metribuzin transport in the field may be adequately simulated using a relatively simple, equilibrium-only pesticide model.
Pesticide transport models are tools used to develop improved pesticide management strategies, study pesticide processes under different conditions (management, soils, climates, etc) and illuminate aspects of a system in need of more field or laboratory study. This paper briefly overviews RZWQM history and distinguishing features, overviews key RZWQM components and reviews RZWQM validation studies. RZWQM is a physically based agricultural systems model that includes sub-models to simulate: infiltration, runoff, water distribution and chemical movement in the soil; macropore flow and chemical movement through macropores; evapotranspiration (ET); heat transport; plant growth; organic matter/nitrogen cycling; pesticide processes; chemical transfer to runoff; and the effect of agricultural management practices on these processes. Research to date shows that if key input parameters are calibrated, RZWQM can adequately simulate the processes involved with pesticide transport (ET, soil-water content, percolation and runoff, plant growth and pesticide fate). A review of the validation studies revealed that (1) accurate parameterization of restricting soil layers (low permeability horizons) may improve simulated soil-water content; (2) simulating pesticide sorption kinetics may improve simulated soil pesticide concentration with time (persistence) and depth and (3) calibrating the pesticide half-life is generally necessary for accurate pesticide persistence simulations. This overview/review provides insight into the processes involved with the RZWQM pesticide component and helps identify model weaknesses, model strengths and successful modeling strategies.
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