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Robust estimation of soil hydraulic parameters is essential for predicting soil water dynamics and related biogeochemical processes; however, uncertainties in estimated parameter values limit a model's ability for prediction and application. In this study, methods of global analysis (Latin hypercube sampling, LHS) and gradient-based optimization (PEST, parameter estimation software) were explored to calibrate soil hydraulic parameters in the Root Zone Water Quality Model (RZWQM2). Six methods of estimating Brooks--Corey parameters of the soil water retention curve and saturated hydraulic conductivity were evaluated to simulate daily soil water dynamics under fallow conditions in eastern Colorado. The calibrated soil hydraulic parameters showed similar trends with soil depth for the different estimation methods in RZWQM2 but resulted in large differences between simulated and observed soil water contents. The PEST optimization based on soil type values as initial estimates gave reasonable soil water responses but with some unrealistic soil hydraulic parameters and soil evaporation. Overall, errors in simulated soil water contents were reduced by using LHS to initialize and constrain the PEST parameter space, which also stabilized the cross-validation results. Calibration results using water content measurements at four depths (30, 60, 90, and 150 cm) were similar to results using 10 depths (30, 40, 50, 60, 70, 80, 90,120,150, and 170 cm). Calibrating soil hydraulic parameters remains challenging, but the combined calibration procedures (LHS + PEST) with cross-validation can reduce parameter uncertainties and improve model performance. doi: 10.2136/sssaj2009.0380

Searching for environmentally friendly N management practices in the midwestern United States is an ongoing task in the agricultural community. Many practices have shown promise in reducing N in tile drainage that may contribute to hypoxia in the Gulf of Mexico. In this study, an agricultural system in central Iowa, managed using a corn (Zea mays L.)--soybean [Glycine max (L.) Merr.] rotation from 1996 to 2005 was evaluated with the Root Zone Water Quality Model (RZWQM) for crop yield, grain N, annual N loss in tile drainage flow, and residual soil N[O.sub.3]-N under high (H, 199 kg N [ha.sup.-1]), medium (M, 138 kg N [ha.sup.-1]), and low (L, 69 kg N [ha.sup.-1]) N application rates shortly after planting, and a split (S, 69 kg N [ha.sup.-1] shortly after planting and again at midseason) N treatment. The model adequately simulated the responses of yield and N loss to N application rates. Simulated N losses to drainage flow from 1996 to 2005 were 348, 277, and 228 kg N [ha.sup.-1] for the H, M, and L treatments, respectively, compared with corresponding measured values of 369, 265, and 201 kg N [ha.sup.-1]. The S treatment had simulated and measured total N losses in drainage flow of 194 and 172 kg N [ha.sup.-1] respectively, from 1999 to 2005. The study also demonstrated that RZWQM without soil microbial growth produced very similar simulation results for crop production and soil N and water balances as RZWQM with dynamic soil microbial growth. Abbreviations: FWANC, flow-weighted animal nitrogen concentrations; ME, Nash-Sutcliffe model efficiency; RMSE, root mean square error, RZWQM, Root Zone Water Quality Model.

Synthesis and quantification of disciplinary knowledge at the whole system level, via the process models of agricultural systems, are critical to achieving improved and dynamic management and production systems that address the environmental concerns and global issues of the 21st century. Soil physicists have made significant contributions in this area in the past, and are uniquely capable of making the much-needed and exciting new contributions. Most of the exciting new research opportunities are trans-disciplinary, that is, lie on the interracial boundaries of soil physics and other disciplines, especially in quantifying interactions among soil physical processes, plant and atmospheric processes, and agricultural management practices. Some important knowledge-gap and catting-edge areas of such research are: (1) quantification and modeling the effects of various management practices (e.g., tillage, no-tillage, crop residues, and rooting patterns) on soil properties and soil--plant--atmosphere processes; (2) the dynamics of soil structure, especially soil cracks and biochannels, and their effects on surface runoff of water and mass, and preferential water and chemical transport to subsurface waters; (3) biophysics of changes in properties and processes at the soil--plant and plant--atmosphere interfaces; (4) modeling contributions of agricultural soils to climate change and effects of climate change on soil environment and agriculture; and (5) physical (cause-effect) quantification of spatial variability of soil properties and their outcomes, new methods of parameterizing a variable field for field-scale modeling, and new innovative methods of aggregating output results from plots to fields to larger scales. The current status of the various aspects of these research areas is reviewed briefly. The future challenges are identified that will require both experimental research and development of new concepts, theories, and models.

With adoption of combine harvest technology, massive sugarcane (Saccharum Spp. Hyb.) residue is left on the soil surface following each harvest, which could affect the environmental fate and efficacy of applied pesticides in subsequent cropping seasons. The objective of this study was to quantify the retention characteristics and mobility of a commonly used herbicide, atrazine (2-chloro-4-ethylamine-6-isopropylamino-S-triazine), in soils when sugarcane mulch residue was present. Specifically, adsorption and desorption kinetic batch experiments were performed to quantify atrazine retention by the mulch residue over time. Atrazine sorption exhibited time-dependent behavior and was followed by slow release regardless of input concentration. A kinetic--equilibrium model based on a second-order two-site (SOTS) formulation was successful in describing atrazine adsorption versus time by the mulch residue. One set of model parameters was capable of describing atrazine release based on six successive desorption steps. As a test for the applicability of the model, data sets from two other experiments where sorption and release was measured for extended time periods (1348 and 2476 h) were successfully predicted by the SOTS model. Miscible displacement methods were used to measure the mobility of atrazine in packed columns where the mulch residue was mixed with a reference sand material or a Sharkey clay soil (very fine, smectitic, thermic Chromic Epiaquerts). Use of batch-measured model parameters did not adequately describe atrazine mobility in the sand-mulch column. In contrast, for a Sharkey-mulch soil column, a two-compartment SOTS model was successful in predicting atrazine breakthrough results where independently estimated parameters for the mulch residue and the soil matrix were used as the input parameters. Results also showed that mixing of mulch with soil created physical non-equilibrium condition in the columns, which was responsible for errors in model predictions.

Failure of numerous efforts to describe the movement of reactive solutes in soils is often due to inaccurate identification of solute-soil interactions or to the lack of independently derived model parameters. The main objective of this work was to test the applicability of chemical vs. physical nonequilibrium approaches in describing the transport of solutes in soils. The models evaluated are based on second-order two-site approaches (SOTS) with and without consideration of physical nonequilibrium in soils. The capability of these approaches for predicting the transport of metolachlor [2-Chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)acetamide] in Sharkey clay (very-fine, smectitic, thermic Chromic Epiaquerts) soil columns of different aggregate sizes (

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 N[O.sub.3] 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.sup.-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.sup.-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.sup.-1], respectively). Average soil N[O.sub.3] concentrations decreased significantly from 14.9 to 8.5 mg N [kg.sup.-1] in the top 30 cm of soil, and from 5.4 to 3.7 mg N [kg.sup.-1] in the 30- to 60-cm soil profile after stopping manure application. No significant difference in soil N[O.sub.3] 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.sup.-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 N[O.sub.3] concentration and total water storage in the soil profile. Generally, the calibrated model provided adequate predictions for both N[O.sub.3] and soil water content with [r.sup.2] > 0.83. The model was further used to evaluate alternative scenarios of manure and water management.