Root Zone Water Quality Model Research Articles

Simulating Planting Date Effects on Corn Production Using RZWQM and CERES‐Maize Models

Corn (Zea mays L.) production in northeastern Colorado is constrained by a frost‐free period averaging 11 May to 27 September. For optimization of yield, planting at the appropriate time to fit the hybrid maturity length and growing season is critical. Crop models could be used to determine optimum planting windows for a locality. We calibrated the plant parameters of the Root Zone Water Quality Model (RZWQM) and genetic coefficients for the CERES‐Maize model and validated their performance against experimental data of three corn hybrids varying in days to maturity, planted on three planting dates in 2 yr at Akron, CO, under irrigation. Both models could be calibrated to predict leaf area index, soil water content, crop water use, and yield with similar levels of accuracy. Both models simulated the observed decline in yield with delayed planting date, but CERES‐Maize simulated the yield from the latest planting date much more accurately for all three hybrids than did RZWQM (13% underpredicted by CERES‐Maize; 50% overpredicted by RZWQM). Using the long‐term Akron weather record, the latest planting dates for the short‐, mid‐, and long‐season hybrids to have a 50% chance of achieving a break‐even yield under irrigation were 13 May, 20 May, and 6 May, respectively. Long‐term simulations also revealed that the longer maturity length hybrids lose yield faster than short maturity length hybrids with planting delay. The information generated by either RZWQM or CERES‐Maize can be useful for making both planting and replanting decisions for corn hybrids of varying maturity length in northeastern Colorado.

Predicting Runoff and Associated Nitrogen Losses from Turfgrass using the Root Zone Water Quality Model (RZWQM)

Nitrogen fertilizers are used to maintain optimum turfgrass quality, but off-site movement of this primary nutrient can affect water quality. We conducted a 4-yr study (1998-2001) designed to measure nitrate N runoff from turfgrass, gathering data to be used in the model. The process-based Root Zone Water Quality Model (RZWQM) was used to predict nitrate associated with runoff from turfgrass. The measurements were made on 12 sloped (5%), 25-m2 plots of 'Tifway' bermudagrass [Cynodon dactylon (L.) Pers.], managed as golf course fair-ways and exposed to natural and simulated rainfall. Surface runoff volume and nitrate N loads were monitored after applying simulated rainfall at an average intensity of 27.4 mm h(-1). The irrigation occurred (25 or 50 mm) 4 through 168 h after treatment with various rates of N fertilizers for 1998-2001. RZWQM adequately simulated water runoff volumes (<19%; nonsignificant, paired t test) in the first three (normal or wet) years, but overpredicted (70%) in the fourth, dry year. RZWQM overpredicted nitrate N loads by a factor of 1.3 for the first three years (nonsignificant), and by a factor of almost 6 for the fourth year (highly significant). These overpredictions occurred when the runoff volumes and N loads were very small. The research has shown that refinements to RZWQM are needed for turfgrass management applications.

PREDICTION OF PESTICIDE LOSSES IN SURFACE RUNOFF FROM AGRICULTURAL FIELDS USING GLEAMS AND RZWQM

Seepage zones have been shown to be of critical importance in controlling contaminant export from agricultural watersheds. To date, no multipurpose agricultural water quality model has seepage zones incorporated into its process-level representations. We chose to test two widely used models of agricultural water quality, the Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) and the Root Zone Water Quality Model (RZWQM), by seeing how well each predicted solution pesticide concentration and loss in surface runoff from two agricultural fields: one with and one without seepage zones. Daily simulated atrazine and metolachlor concentration and loss in surface runoff from both calibrated and default (or non-calibrated) GLEAMS and RZWQM were compared with three years of measured data from the two fields. The results of the study show that GLEAMS and RZWQM using default input parameters were not capable of predicting atrazine and metolachlor concentration and loss in surface runoff from the fields with and without seepage zones (modeling efficiency <0.16). Site-calibrated GLEAMS and RZWQM predicted atrazine and metolachlor concentration and loss in surface runoff from both fields (coefficient of determination >0.52, index of agreement >0.83, and modeling efficiency >0.53) and can be used for assessing the effects of seepage zones on pesticide loss in surface runoff from agricultural fields.

Interrelationship of Macropores and Subsurface Drainage for Conservative Tracer and Pesticide Transport

Macropore flow results in the rapid movement of pesticides to subsurface drains, which may be caused in part by a small portion of macropores directly connected to drains. However, current models fail to account for this direct connection. This research investigated the interrelationship between macropore flow and subsurface drainage on conservative solute and pesticide transport using the Root Zone Water Quality Model (RZWQM). Potassium bromide tracer and isoxaflutole, the active ingredient in BALANCE herbicide [(5-cyclopropyl-4-isoxazolyl) [2(methylsulfonyl)-4-(trifluoromethyl)phenyl] methanone], with average half-life of 1.7 d were applied to a 30.4-ha Indiana corn (Zea mays L.) field. Water flow and chemical concentrations emanating from the drains were measured from two samplers. Model predictions of drain flow after minimal calibration reasonably matched observations (slope = 1.03, intercept = 0.01, and R(2) = 0.75). Without direct hydraulic connection of macropores to drains, RZWQM under predicted bromide and isoxaflutole concentration during the first measured peak after application (e.g., observed isoxaflutole concentration was between 1.2 and 1.4 mug L(-1), RZWQM concentration was 0.1 mug L(-1)). This research modified RZWQM to include an express fraction relating the percentage of macropores in direct hydraulic connection to drains. The modified model captured the first measured peak in bromide and isoxaflutole concentrations using an express fraction of 2% (e.g., simulated isoxaflutole concentration increased to 1.7 mug L(-1)). The RZWQM modified to include a macropore express fraction more accurately simulates chemical movement through macropores to subsurface drains. An express fraction is required to match peak concentrations in subsurface drains shortly after chemical applications.

Modeling the Fate of Acetochlor and Terbuthylazine in the Field Using the Root Zone Water Quality Model

Data collected from a 3‐yr controlled field study in Hamilton, New Zealand were used to examine whether the Root Zone Water Quality Model is capable of predicting water movement and pesticide fate in the field based on key lab‐measured parameters and environmental variables. Acetochlor [2‐chloro‐N‐(ethoxymethyl)‐N‐(2‐ethyl‐6‐methylphenyl) acetamide; 2.5 and 5.0 kg a.i. ha−1] and terbuthylazine (C9H16ClN5; 1.5 and 3.0 kg a.i. ha−1) were applied onto nine field plots (3 by 9 m each). Soil core samples were taken to a depth of 1 m to determine soil water contents and pesticide concentrations. Dissipation of both pesticides in the field at both application rates followed first‐order kinetics (adjusted r2 &gt; 0.91). The mean dissipation half‐life was 16 d for acetochlor and 25 d for terbuthylazine. Relatively small amounts of the pesticides leached below 5 cm and none leached below 10 cm. Predicted soil water contents in the soil profile were not significantly different from those measured in the field (p &gt; 0.84). Predicted acetochlor and terbuthylazine masses in the soil profile based on a linear instantaneous‐equilibrium (I‐E) partitioning model matched those measured in the field (adjusted r2 &gt; 0.93). However, predicted pesticide concentrations in the soil profile were less satisfactory, with 68 and 35% of the predicted concentrations being within a factor of 2 of the measured concentrations for 0‐ to 5‐ and 5‐ to 10‐cm depths, respectively. Calibration of each pesticide sensitive parameter individually did not significantly improve the overall predictions of pesticide mass and concentrations in the soil profile when the I‐E partitioning model was used. The predictions were improved when a two‐site, equilibrium‐kinetic (E‐K) sorption model was used.

Modeling Nitrogen Management Effects on Winter Wheat Production Using RZWQM and CERES‐Wheat

Agricultural system models can provide an alternative, less time‐consuming and inexpensive means of determining the optimum crop N requirement under varied soil and climatic conditions. In this context, we parameterized the Root Zone Water Quality Model (RZWQM) for winter wheat (Triticum aestivum L.) production and then evaluated it along with the CERES‐Wheat model to assess their potential as N management tools at Akron, Co. Both models were evaluated with data from five N treatments (0, 28, 56, 84, and 112 kg N ha−1) and three crop seasons (1987–1988, 1988–1989, and 1989–1990). Data from 1987–1988 zero‐N treatment were used for model calibration, and the rest of the data were used for model validation. Genetic coefficients for winter wheat (cv. TAM 107) were developed for the CERES‐Wheat model. The crop parameters required for the generic crop model of RZWQM were parameterized using information from the literature or by calibration. Both models were calibrated first for soil moisture and then for biomass and grain yield. Grain yield predictions had a root mean square error (RMSE) of 500 and 363 kg ha−1, respectively, for CERES‐Wheat and RZWQM. Aboveground biomass was predicted with RMSEs of 1247 and 1441 kg ha−1, respectively. Long‐term simulations of both RZWQM and CERES for winter wheat growth using historical weather data (1912–2001) showed that 56 kg ha−1 N applied as broadcast incorporated is a viable N management option in eastern Colorado, taking into account the grain yield, crop N uptake, N leaching into groundwater, and residual soil N at harvest. Model simulations also showed that the wheat–fallow cropping system is less water use efficient than a continuous wheat system under rainfed agriculture in eastern Colorado.

Application of the Root Zone Water Quality Model (RZWQM) to pesticide fate and transport: an overview.

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.

Modeling hydrology, metribuzin degradation and metribuzin transport in macroporous tilled and no-till silt loam soil using RZWQM.

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.

Herbicide leaching as affected by macropore flow and within-storm rainfall intensity variation: a RZWQM simulation.

Within-event variability in rainfall intensity may affect pesticide leaching rates in soil, but most laboratory studies of pesticide leaching use a rainfall simulator operating at constant rainfall intensity, or cover the soil with ponded water. This is especially true in experiments where macropores are present--macroporous soils present experimental complexities enough without the added complexity of variable rainfall intensity. One way to get around this difficulty is to use a suitable pesticide transport model, calibrate it to describe accurately a fixed-intensity experiment, and then explore the affects of within-event rainfall intensity variation on pesticide leaching through macropores. We used the Root Zone Water Quality Model (RZWQM) to investigate the effect of variable rainfall intensity on alachlor and atrazine transport through macropores. Data were used from an experiment in which atrazine and alachlor were surface-applied to 30 x 30 x 30 cm undisturbed blocks of two macroporous silt loam soils from glacial till regions. One hour later the blocks were subjected to 30-mm simulated rain with constant intensity for 0.5 h. Percolate was collected and analyzed from 64 square cells at the base of the blocks. RZWQM was calibrated to describe accurately the atrazine and alachlor leaching data, and then a median Mid-west variable-intensity storm, in which the initial intensity was high, was simulated. The variable-intensity storm more than quadrupled alachlor losses and almost doubled atrazine losses in one soil over the constant-intensity storm of the same total depth. Also rainfall intensity may affect percolate-producing macroporosity and consequently pesticide transport through macropores. For example, under variable rainfall intensity RZWQM predicted the alachlor concentration to be 2.7 microg ml(-1) with an effective macroporosity of 2.2 E(-4) cm(3) cm(-3) and 1.4 microg ml(-1) with an effective macroporosity of 4.6 E(-4) cm(3) cm(-3). Percolate-producing macroporosity and herbicide leaching under different rainfall intensity patterns, however, are not well understood. Clearly, further investigation of rainfall intensity variation on pesticide leaching through macropores is needed.

The pesticide module of the Root Zone Water Quality Model (RZWQM): testing and sensitivity analysis of selected algorithms for pesticide fate and surface runoff.

The Root Zone Water Quality Model (RZWQM) is a one-dimensional, numerical model for simulating water movement and chemical transport under a variety of management and weather scenarios at the field scale. The pesticide module of RZWQM includes detailed algorithms that describe the complex interactions between pesticides and the environment. We have simulated a range of situations with RZWQM, including foliar interception and washoff of a multiply applied insecticide (chlorpyrifos) to growing corn, and herbicides (alachlor, atrazine, flumetsulam) with pH-dependent soil sorption, to examine whether the model appears to generate reasonable results. The model was also tested using chlorpyrifos and flumetsulam for the sensitivity of its predictions of chemical fate and water and pesticide runoff to various input parameters. The model appears to generate reasonable representations of the fate and partitioning of surface- and foliar-applied chemicals, and the sorption of weakly acidic or basic pesticides, processes that are becoming increasingly important for describing adequately the environmental behavior of newer pesticides. However, the kinetic sorption algorithms for charged pesticides appear to be faulty. Of the 29 parameters and variables analyzed, chlorpyrifos half-life, the Freundlich adsorption exponent, the fraction of kinetic sorption sites, air temperature, soil bulk density, soil-water content at 33 kPa suction head and rainfall were most sensitive for predictions of chlorpyrifos residues in soil. The latter three inputs and the saturated hydraulic conductivity of the soil and surface crusts were most sensitive for predictions of surface water runoff and water-phase loss of chlorpyrifos. In addition, predictions of flumetsulam (a weak acid) runoff and dynamics in soil were sensitive to the Freundlich equilibrium adsorption constant, soil pH and its dissociation coefficient.

Documenting the pesticide processes module of the ARS RZWQM agroecosystem model.

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.

THE IMPORTANCE OF SEEPAGE ZONES IN PREDICTING SOIL MOISTURE CONTENT AND SURFACE RUNOFF USING GLEAMS AND RZWQM

Seepage zones have been shown to be of critical importance in controlling contaminant export from agriculturalcatchments. To date, no multi-purpose agricultural water quality model has incorporated seepage zones into its process-levelrepresentations. We chose to test two commonly used models of agricultural water quality, Groundwater Loading Effects of AgriculturalManagement Systems (GLEAMS) and the Root Zone Water Quality Model (RZWQM), by seeing how well each predictedsurface runoff and soil moisture content in two agricultural fields: one with and one without seepage zones. Dailysimulated surface runoff and soil moisture content from both calibrated and default (or non-calibrated) GLEAMS and RZWQMwere compared with three years of measured surface runoff and soil moisture content in the two fields. The results of the studyshow that GLEAMS and RZWQM, using default model parameters, were not capable of predicting surface runoff and soil moisturecontent in either field. Site-calibrated GLEAMS and RZWQM performed well in simulating surface runoff trends from thefield with and without seepage zones, but they predicted soil moisture content poorly. Several statistical tests were used thatshowed that although both site-calibrated GLEAMS and RZWQM performed well, RZWQM performed better than GLEAMSand is better suited in assessing the effects of seepage zones on soil moisture content and surface runoff from agricultural fields.

Simulating Nitrate Drainage Losses from a Walnut Creek Watershed Field

This study was designed to evaluate the improved version of the Root Zone Water Quality Model (RZWQM) using 6 yr (1992-1997) of field-measured data from a field within Walnut Creek watershed located in central Iowa. Measured data included subsurface drainage flows, NO3-N concentrations and loads in subsurface drainage water, and corn (Zea mays L.) and soybean [Glycine mar (L.) Merr.] yields. The dominant soil within this field was Webster (fine-loamy, mixed, superactive, mesic Typic Endoaquolls) and cropping system was corn-soybean rotation. The model was calibrated with 1992 data and was validated with 1993 to 1997 data. Simulations of subsurface drainage flow closely matched observed data showing model efficiency of 99% (EF = 0.99), and difference (D) of 1% between measured and predicted data. The model simulated NO3-N losses with subsurface drainage water reasonably well with EF = 0.8 and D = 13%. The simulated corn grain yields were in close agreement with measured data with D < 10%. Nitrogen-scenario simulations demonstrated that corn yield response function reached a plateau when N-application rate exceeded 90 kg ha(-1). Fraction of applied N lost with subsurface drainage water varied from 7 to 16% when N-application rate varied from 30 to 180 kg ha(-1) after accounting for the nitrate loss with no-fertilizer application. These results indicate that the RZWQM has the potential to simulate the impact of N application rates on corn yields and NO3-N losses with subsurface drainage flows for agricultural fields in central Iowa.

USING RZWQM TO PREDICT HERBICIDE LEACHING LOSSES IN SUBSURFACE DRAINAGE WATER

Improvements have been made in the pesticide component of the Root Zone Water Quality Model (RZWQM) sinceits release in 1999 for the Management System Evaluation Areas (MSEA) project. This study was designed to evaluate theherbicide leaching component of the model using data on subsurface drainage flow and herbicide leaching losses for a 6-year(1992 to 1997) period. A sensitivity analysis was conducted for the key parameters important in the pesticide calibration process.The model was calibrated using 1992 data and validated using 1993 to 1997 data collected from a tile-drained fieldwithin the Walnut Creek watershed in central Iowa. The model evaluation criterion was based on percent difference betweenthe predicted and measured data (%D), root mean square error (RMSE), and model efficiency (EF). Atrazine and metolachlorwere applied to corn in 1993, 1995, and 1997, and metribuzin was used during the soybean growing seasons in 1992, 1994,and 1996 at the standard application rates used in Iowa. The predicted subsurface drainage volumes were in close agreementwith the measured data showing %D = 1, RMSE = 8, and EF = 0.99, when averaged over the validation years. Herbicidehalf-life (t1/2) and soil organic based partitioning coefficient (Koc) were found to be the most sensitive parameters forsimulating herbicide leaching losses in subsurface drainage water. Both t1/2 and Koc affected the mass and temporaldistribution of the herbicide leaching losses in subsurface drainage flows. The predicted herbicide leaching losses insubsurface drainage water were the same order of magnitude as the measured data, when averaged across the validationyears. The study also revealed that herbicide leaching losses were significantly (P < 0.05) controlled by the drainage volume(R2 = 0.97). The model, however, underpredicted herbicide leaching losses after crop harvest and during early spring,possibly because of preferential flow paths developed during these periods. More improvements may be needed in the RZWQMto consider the dynamics of the preferential flow paths development in cultivated soils similar to that of the study area.

RELATIONSHIP BETWEEN HERBICIDE CONCENTRATION IN PERCOLATE, PERCOLATE BREAKTHROUGH TIME, AND NUMBER OF ACTIVE MACROPORES

Identification of the major factors affecting herbicide transport through macropores improves our understandingof preferential flow and aids in the development and use of macropore-flow models, such as the Root Zone Water QualityModel (RZWQM). Recent research suggests that macropore-flow breakthrough time (bt) and the number of percolate-producingmacropores (nmacro) affect herbicide concentration in percolate (hc). Therefore, we investigated the effect of bt and nmacroon hc during the first storm after herbicide application using multiple regression and partial correlation. Observed datawere from five different leaching experiments that included five soil series and two tillage types (no-till and moldboard plow).Multiple regression was used to develop a model to predict herbicide concentration (hc) in preferential flow at 30 cm duringthe first rainfall after application using data from the five studies. The ln(hc) in macropore flow at 30 cm was related to bt(min) at 30 cm, ln(nmacro) at 30 cm, herbicide type (alachlor or atrazine), and herbicide application rate (R2 = 0.96). Partialcorrelation confirmed the relationship between ln(hc) and bt (P < 0.0001; r = -0.77) and ln(nmacro) (P < 0.0001; r = -0.46).A single-variable sensitivity analysis on the regression equation suggested that the observed range of bt (1.4 to 25 min) resultsin an eight-fold change in atrazine concentration (4.0 to 0.48 mg L-1). Clearly, breakthrough time during the first storm afterapplication affects herbicide transport.

Assimilation of surface soil moisture to estimate profile soil water content

The use of surface soil water content data as additional input for the Root Zone Water Quality Model in modeling profile soil water content was investigated at four field sites in the Little Washita River Experimental Watershed in south central Oklahoma, coincident with the Southern Great Plains 1997 (SGP97) Hydrology Experiment. Modeled soil water profile estimates were compared to field measurements made periodically during the same time period using a field calibrated time-domain reflectometry (TDR) system. The model was first run in the normal mode with inputs of initial conditions and upper boundary conditions of measured rainfall intensities and daily mean meteorological variables that determined evapotranspiration (ET). Soil hydraulic properties used in the model were estimated from limited soils data information, since in practical terms this is usually the case. Moreover, in our earlier study even the complete description of hydraulic properties based on laboratory and field measurements did not improve the results over average profile estimates using only limited input data. The model runs were then repeated with the daily simulated soil water content in the surface 0–5 cm layer being replaced by 0–5 cm measured soil water content. This process of forcing measured surface water content as additional model input is called direct insertion data assimilation. The simulated profile soil water contents, with and without data assimilation, were compared with TDR-measured profiles to a depth of 60 cm. Gravimetric surface soil water content was measured during SGP97 from June 18 to July 16, 1997 and used as a surrogate for remotely sensed surface moisture data. Data assimilation of surface soil moisture improved model estimates to a depth of 30 cm at all sites. Of particular significance, with data assimilation, model estimates more closely matched the measured dynamic fluctuations of soil moisture in the top 30 cm in response to rainfall events. There was no significant improvement in soil water estimates below the 30 cm depth. This may indicate that data assimilation of surface soil moisture tends to compensate for any errors in model simulations emanating from: (1) errors in the measurement of rainfall intensities or in using 5-min averaged rainfall intensities as done here; (2) errors in using daily average values of meteorological variables that determine ET in a daily ET model; (3) errors in determining hydraulic properties of the surface soil by either laboratory methods or more simple techniques; (4) errors due to the spatial variability of soil hydraulic properties not properly represented in the model.

Tillage effect on macroporosity and herbicide transport in percolate

Research suggests that pesticide transport to tile drains and shallow groundwater may be greater for no-till than tilled soil. Also, most pesticide transport through soil can be from macropore flow, but the effect of tillage on macropore transport is uncertain. Our objective was to investigate the effect of tillage on herbicide leaching through hydraulically active macropores. The number of percolate-producing macropores at 30 cm (nmacro) and the timing of initial percolate were measured from an experiment where atrazine, alachlor and rainfall were applied to moldboard plowed (MP) and no-till (NT) undisturbed soil blocks from two different silt loam soils. Alachlor and atrazine transport through the undisturbed soil blocks was simulated using the Root Zone Water Quality Model (RZWQM). The time of initial percolate breakthrough at 30 cm was significantly less for NT than for MP ( p<0.001), but nmacro was not significantly different between MP and NT treatments. Additionally, nmacro was significantly different between the two silt loam soils ( p<0.001). Multiple linear regression revealed that flow-weighted herbicide concentration in percolate decreased with increasing nmacro (cm −2) and increasing time for initial percolate breakthrough (min) ( R 2=0.87 for alachlor and 0.85 for atrazine). Because a small fraction of nmacro produces the majority of percolate, we used half of measured nmacro for RZWQM input. Also, soil parameters were calibrated to accurately simulate the water flow component timing of percolate arrival and percolate amount through macropores. This parameterization strategy resulted in accurate predicted herbicide concentrations in percolate at 30 cm using RZWQM (within the range of observations). The modeling results suggest that differences in soil properties other than macroporosity such as a lower soil matrix saturated hydraulic conductivity and porosity in subsurface soil (8–30 cm) can cause percolate to occur sooner through macropores on NT than on MP and cause higher herbicide concentrations in percolate on NT, even when nmacro does not differ between till and no-till.

Application of RZWQM in Predicting Subsurface Drainage under Nova Scotia Conditions

The Root Zone Water Quality Model (RZWQM) was calibrated and validated to estimate subsurface drain discharge rates for selected Nova Scotia conditions. The model was calibrated for a shallow, imperfectly drained soil at 80 cm drain depth with 100 mm drain diameter using data collected in 1997. The calibrated model was then validated for three shallow, imperfectly-to-poorly drained soil types at 50 and 80 cm drain depths using field data from both 1996 and 1997. The average mean of differences, the average absolute deviations, the standard error and the standard deviation ranged from 0.01–0.47, 0.12–1.19, 0.30–1.70 and 0.29–1.67 mm d−1, respectively. The R2 values for calibrated and validated (for all soil types) plots were 0.60 and 0.57, respectively. It can be concluded that RZWQM may be used in predicting drain discharge rates for designing and operating subsurface drainage systems in Nova Scotia.

EVALUATION OF RZWQM UNDER VARYING IRRIGATION LEVELS IN EASTERN COLORADO

The ability to predict and manage crop growth under varying available water conditions is of vital importanceto the agricultural community since water is the most important limiting factor for agricultural productivity, especially insemiarid regions. This study evaluated an agricultural system model, the USDAARS Root Zone Water Quality Model(RZWQM), for its ability to simulate the responses of corn (Zea mays L.) growth and yield to various levels of water stress.Data sets collected in 1984, 1985, and 1986 in northeastern Colorado were used for model evaluation. Three irrigation levelswere imposed in 1984 and four levels in 1985 and 1986. Measurements included soil water content in 1985, leaf area index(LAI) and aboveground biomass in 1984 and 1985, and corn yield and plant height in 1984, 1985, and 1986. The RZWQMwas calibrated for the lowest (driest) irrigation treatment in 1985 and then used to predict soil water and agronomic attributesfor other irrigation treatments in all three years. Overall, the model responded well to irrigation treatments and weatherconditions. Prediction of plant height was adequate in 1985 and 1986. Although biomass was reasonably predicted in earlyand late growing seasons, it was overpredicted during the middle growing season in both 1984 and 1985. Maximum LAI andplant height were overpredicted in 1984, however. Total soil water storage was well predicted in 1985, and so wasevapotranspiration (ET) during the crop growing season. Yield predictions were within 1% to 35% of measured values forall the three years. Even with a low prediction of yield in 1986, the model correctly simulated the relative increase of yieldwith irrigation amount. Therefore, once RZWQM is calibrated for a location, it can be used as a tool to simulate relativedifferences in crop production under different irrigation levels and as a guide to optimize water management.

Simulating Soybean Water Stress Effects with RZWQM and CROPGRO Models

The Root Zone Water Quality Model (RZWQM) and CROPGRO‐Soybean simulate soybean [Glycine max (L.) Merr.] growth, development, and yield. The models require calibration for soybean grown in the specific environmental conditions of the central Great Plains before any long‐term assessments can be made of dryland soybean yield potential under the highly variable precipitation patterns of this area. The objective of this study was to calibrate and test RZWQM and CROPGRO‐Soybean for soybean growth, yield, and water use under a range of water stress conditions normally encountered by dryland production systems in the central Great Plains. Data from five experiments, each with four levels of water availability (20 data sets), were used to evaluate leaf area, plant height, aboveground biomass, evapotranspiration (ET), soil water extraction, and yield of soybean. Data from one water level of one experiment was used to calibrate the models, and the other 19 data sets were used as evaluation data sets. Both models correctly predicted the time course of volumetric water content, leaf area development, and plant and height biomass increase although RZWQM more accurately simulated water extraction in the lower soil profile. The decline in ET that is a result of decreased water availability was generally predicted well by both models. The models generally estimated the yield to within 10 to 15% of measured values. The models should be useful tools in evaluating the potential for soybean as an alternative crop in dryland rotations in the central Great Plains.