L. R. Ahuja

Integrating system modeling with field research in agriculture: applications of the root zone water quality model (RZWQM)

Publisher Summary Models provide a ready means of translating research to other locations and thus minimize duplication of field research. They also provide a ready means to transfer the integrated knowledge and technology to farmers and other users. This chapter focuses on root zone water quality model (RZWQM), an agricultural system model that integrates the state-of-the-science knowledge of agricultural systems into a tool for agricultural research and management, environmental assessment, and technology transfer. RZWQM has been tested for different aspects of water movement, several pesticides, crop growth, nitrogen dynamics, and several agricultural management practices. The model has been used nationally and internationally and the degree of success in RZWQM application depends on the agricultural system simulated, data availability and quality, processes of interest, and, to some extent, the modeling experience of users. Both the successes and failures of the model have provided information to improve the model and data collection. During these numerous calibration and validation exercises, many new ideas have been developed on model application. Moreover, RZWQM applications have furthered understanding of agricultural systems and promoted the integration of models with field research.

Microwave remote sensing of temporal variations of brightness temperature and near‐surface soil water content during a watershed‐scale field experiment, and its application to the estimation of soil physical properties

Passive microwave airborne remote sensing was employed to collect daily brightness temperature (TB) and near-surface (0–5 cm depth) soil water content (referred to as “soil water content”) data during June 10–18, 1992, in the Little Washita watershed, Oklahoma. A comparison of multitemporal data with the soils data revealed a direct correlation between changes in TB and soil water content, and soil texture. Regression relationships were developed for the ratio of percent sand to percent clay (RSC) and effective saturated hydraulic conductivity (Ksat) in terms of TB and soil water content change. Validation of results indicated that both RSC and Ksat can be estimated with adequate accuracy. The relationships are valid for the region with small variation of soil organic matter content, soils with fewer macropores, and limiting experimental conditions. However, the findings have potential to employ microwave remote sensing for obtaining quick estimates of soil properties over large areas.

RZWQM: Simulating the effects of management on water quality and crop production

Abstract The interactive use of experimentation and modeling is an efficient way to devise and test new agricultural management systems. The Root Zone Water Quality Model (RZWQM) is a comprehensive simulation model designed to predict the hydrologic response, including potential for groundwater contamination, of alternative crop-management systems. The model is one-dimensional (vertical into the soil profile) and integrates physical, biological and chemical processes. It simulates crop development and the movement of water, nutrients and pesticides over and through the root zone for a representative unit area of an agricultural field over multiple years. RZWQM allows for a variety of management practices: tillage; irrigation, fertilizer, manure and pesticide applications; tile drainage and crop rotations. Several significant validation efforts have shown the usefulness of RZWQM for evaluating and developing management scenarios.

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

Modeling nitrogen and water management effects in a wheat-maize double-cropping system

Excessive N and water use in agriculture causes environmental degradation and can potentially jeopardize the sustainability of the system. A field study was conducted from 2000 to 2002 to study the effects of four N treatments (0, 100, 200, and 300 kg N ha(-1) per crop) on a wheat (Triticum aestivum L.) and maize (Zea mays L.) double cropping system under 70 +/- 15% field capacity in the North China Plain (NCP). The root zone water quality model (RZWQM), with the crop estimation through resource and environment synthesis (CERES) plant growth modules incorporated, was evaluated for its simulation of crop production, soil water, and N leaching in the double cropping system. Soil water content, biomass, and grain yield were better simulated with normalized root mean square errors (NRMSE, RMSE divided by mean observed value) from 0.11 to 0.15 than soil NO(3)-N and plant N uptake that had NRMSE from 0.19 to 0.43 across these treatments. The long-term simulation with historical weather data showed that, at 200 kg N ha(-1) per crop application rate, auto-irrigation triggered at 50% of the field capacity and recharged to 60% field capacity in the 0- to 50-cm soil profile were adequate for obtaining acceptable yield levels in this intensified double cropping system. Results also showed potential savings of more than 30% of the current N application rates per crop from 300 to 200 kg N ha(-1), which could reduce about 60% of the N leaching without compromising crop yields.

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 importance to the agricultural community since water is the most important limiting factor for agricultural productivity, especially in semi–arid regions. This study evaluated an agricultural system model, the USDA–ARS 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 levels were 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 RZWQM was calibrated for the lowest (driest) irrigation treatment in 1985 and then used to predict soil water and agronomic attributes for other irrigation treatments in all three years. Overall, the model responded well to irrigation treatments and weather conditions. Prediction of plant height was adequate in 1985 and 1986. Although biomass was reasonably predicted in early and late growing seasons, it was over–predicted during the middle growing season in both 1984 and 1985. Maximum LAI and plant height were over–predicted in 1984, however. Total soil water storage was well predicted in 1985, and so was evapotranspiration (ET) during the crop growing season. Yield predictions were within 1% to 35% of measured values for all the three years. Even with a low prediction of yield in 1986, the model correctly simulated the relative increase of yield with irrigation amount. Therefore, once RZWQM is calibrated for a location, it can be used as a tool to simulate relative differences in crop production under different irrigation levels and as a guide to optimize water management.

A Field Test of Root Zone Water Quality Model—Pesticide and Bromide Behavior

The Root Zone Water Quality Model is a process-based model that integrates physical, chemical and biological processes to simulate the fate and movement of water and agrochemicals over and through the root zone at a representative point in a field with various management practices. The model was evaluated with field data for the movement of water and bromide, and the transformation and transport of cyanazine and metribuzin in the soil profile. The model reasonably simulated soil water and bromide movement. Pesticide persistence was predicted reasonably well with a two-site sorption model that assumes a rate-limited adsorption-desorption process with the additional assumption of negligible degradation of interaggregate-adsorbed pesticides.

MACROPORE COMPONENT ASSESSMENT OF THE ROOT ZONE WATER QUALITY MODEL (RZWQM) USING NO–TILL SOIL BLOCKS

In structured soils, macropores can contribute to rapid movement of water and solutes through the profile. To provide insight into these processes, model assessments should be performed under a variety of conditions. We evaluated the macropore component of the RZWQM using undisturbed soil blocks with natural macropores. To accomplish this, atrazine, alachlor, and bromide were surface–applied to nine 30 U 30 U 30 cm blocks of undisturbed, no–till silt loam soil at three water contents (dry, intermediate, and wet). One hour later, we subjected the blocks to a 0.5–h, 30–mm simulated rain. Percolate was collected and analyzed from 64 uniform size cells at the base of the blocks. After percolation ceased, the soil was sectioned and analyzed to determine chemical distribution. We tested the chemical sub–component of macropore flow using these blocks following hydrologic calibration, while a separate set of blocks was used to calibrate selected chemical parameters. Parameterization of the macropore component included measuring the effective macroporosity (50% of percolate producing macropores) and calibrating the effective soil radius (0.6 cm). The effective soil radius represents the soil surrounding the macropores that interacts with macropore flow. This parameterization strategy resulted in accurate simulations of the composite chemical concentrations in percolate (i.e., all simulated chemical concentrations were within a factor of 2.0 of the average observed value). However, observed herbicide concentration in percolate decreased with cumulative percolate volume, while simulated concentrations increased. Model modifications, such as incorporating a dynamic effective macroporosity (effective macroporosity increase with increasing rainfall) and chemical kinetics in macropores, may improve simulations.

Systems Modeling for Soil and Water Research and Management: Current Status and Needs for the 21st Century

Quantitative system approaches, provided by process-based models of agricultural systems, are essential for optimizing the use of increasingly limited water and soil resources, guiding tactical management, and addressing the environmental concerns and global issues of the 21st century. Agricultural engineers have made significant contributions in the past to model development and applications in soil and water research, irrigation design, and water management, and they are uniquely capable of making the much-needed and exciting further model enhancements. In this brief review, we present: (1) the current status of system model development and applications in soil and water research and management, with examples from the USDA-ARS Root Zone Water Quality Model (RZWQM); (2) lessons learned from RZWQM development and applications; and (3) future needs and directions in system model enhancements and applications to make them more effective. We make a strong case for international collaborations among modelers and experimentalists and for a common development/applications protocol and platform for the future.

Measured and RZWQM Predicted Atrazine Dissipation and Movement in a Field Soil

The ARS Root Zone Water Quality Model (RZWQM) was developed recently to study the fate and behavior of agrochemicals in the environment and the effects of agricultural management on surface and groundwater quality. In this article, model performance was tested by comparing three years of field data for water and atrazine movement (runoff and concentration profiles) and atrazine transformation obtained under different management conditions with those simulated by RZWQM. Accuracy of model simulation was quantified by standard linear regression techniques. The regression correlation coefficients (R2) between average measured and simulated data for water runoff, atrazine runoff, atrazine persistence, and atrazine distribution in the soil profile were 0.87, 0.92, 0.97, and 0.73, respectively. Evaluation of the model, using best estimates for properties of atrazine and hydrologic characteristics of the field soil and limited calibration for water runoff, suggests that the model effectively simulates the important processes operating on water and chemicals.