Ramesh S. Kanwar

Evaluation of the CERES-Maize water and nitrogen balances under tile-drained conditions

The CERES-Maize model was developed to investigate how variations in environmental conditions, management decisions, and genetics interact to aAect crop development and growth. A tile drainage subroutine was incorporated into CERES-Maize to improve soil-water and nitrogen leaching under subsurface tile drainage conditions. The purpose of this work was to evaluate the soil-water, soil-nitrogen, tile drainage, and tile-nitrogen loss routines of CERES-Maize for tile-drained fields in Iowa. An analysis was conducted based on information collected from a study of 36 plots consisting of five management systems during a 4-year period from 1993 to 1996, at Nashua, IA. The model was calibrated for each plot using data from 1994 and 1995, and validated using data from 1993 and 1996. Temporal soil-water contents and water flow from tile drains were calibrated to an average root mean square error (RMSE) of 0.036 cm 3 cm ˇ3 and 2.62 cm, respectively, compared to measured values. Validation trials gave an average RMSE for soil-water and tile drainage of 0.046 cm 3 cm ˇ3 and 5.3 cm, respectively. Soil-nitrate and tile-nitrogen flows were calibrated, with an RMSE of 6.27 m gN O3 g ˇ1 soil ˇ1 and 3.21 kg N ha ˇ1 soil ˇ1 , respectively. For the validation trials, the RMSE for soil-nitrate content and cumulative tile-nitrate flow was 6.82 m gN O3 g ˇ1 soil ˇ1 and 8.8 kg N ha ˇ1 , respectively. These results indicate that the new tile drainage algorithms describe water and nitrate movement reasonably well, which will improve the performance of CERES-Maize for artificially drained fields. # 2000 Elsevier Science Ltd. All rights reserved.

Herbicide and tracer movement to field drainage tiles under simulated rainfall conditions

The extent of herbicide and tracer leaching to field drainage tiles may help to predict chemical movement to deeper groundwater systems. Field experiments were conducted in 1988 and 1989 to measure herbicide and tracer movement to tile lines during and immediately after a simulated heavy rainstorm. The eight tile lines monitored were 1.2 m deep and 3.4 m long. In 1988, alachlor (2-chloro-N-(2,6-diethylphenyl)-N-(methoxymethyl)acetamide), cyanazine (2-[[4-chloro-6-(ethylamino)-1,3,5-triazin-2-yl]amino]-2-methylpropanenitrile) and Rhodamine WT dye were applied to 4.5-m2 plots directly over field drainage tiles. In 1989, alachlor, cyanazine, Rhodamine WT, and pendimethalin (N-(1-ethylpropyl)-3,4 dimethyl-2,6 dinitrobenzenamine) were used. Chloride or bromide tracers were also soil applied. The plots were irrigated 24 h after chemical application with a rainfall simulator. In 1988, 53 mm of rainfall was applied, whereas 81 mm of rain was applied in 1989. Tile effluent was intensively sampled for 8 h after irrigation. In 1988, herbicide and Rhodamine dye concentration peaks ranged from 1 to 38 μg l−1. In 1989, concentrations were higher than in 1988, with alachlor and cyanazine concentration peaks exceeding 500 μg l−1 from one tile line. In contrast, pendimethalin was found in only one sample, barely above the detection limit. Rhodamine WT was found to be useful as a tracer to study the movement of alachlor and cyanazine in the soil profile. In all tile effluent samples containing Rhodamine WT, alachlor and cyanazine were also detected. In both years, herbicide and dye concentrations peaked within 130 min after the start of rainfall. The rapid solute movement to the 1.2 m tile depth suggests that preferential flow is an important mechanism affecting chemical transport through structured soils.

Fate of major degradation products of Atrazine in Iowa soils

Abstract Five Iowa soils, sampled at two depths each were treated with 14C‐deethylatrazine (DEA) and 14C‐hydroxyatrazine (HYA) and incubated for nine and 17 weeks. 14CO2 evolution was monitored over this period. The degradation of DEA was influenced by both soil type and soil depth. For each soil studied, the degradation of DEA was much higher in the surface layer compared to the respective subsurface layer. The major degradation products from DEA included CO2, soil bound residues, and polar metabolites. Deethylhydroxyatrazine (DEHYA) and didealkylatrazine (DAA) were detected in minor quantities. Increased mineralization of DEA in the extended incubations confirmed the susceptibility of DEA to microbial degradation. In the complete metabolism studies with HYA, the major components identified included HYA, soil bound residues, and CO2. Deethylhydroxyatrazine deisopropylhydroxyatrazine and ammeline were found in smaller quantities. The relatively long persistence (45 to 69% remaining) of HYA was observed in...

TILLAGE AND NITROGEN MANAGEMENT EFFECTS ON CROP YIELD AND RESIDUAL SOIL NITRATE

Tillage and N management can have great impact on crop yield and off-site transport of nitrate-nitrogen (NO 3 -N). This six-year field study on tile-drained Clyde-Kenyon-Floyd soils in northeast Iowa was conducted to quantify corn (Zea mays L.) and soybean (Glycine max (L.) Merr.) yield and residual soil NO 3 -N. Eight treatments (chisel plow vs no-tillage by preplant versus late-spring N-management for both corn and soybean phases of a rotation) were evaluated using a randomized complete block design. Preplant N was applied by injecting liquid urea-ammonium nitrate solution (UAN) at a rate of 110 kg N ha –1 . Late-spring soil-test based N-rates averaged 179 and 156 kg N ha –1 for no-till and chisel treatments, respectively. No additional N was applied to soybean. Average corn yield on chisel plots was significantly (P = 0.05) higher than with no-tillage for both preplant (7.9 vs 6.9 Mg ha –1 ) and late-spring (8.6 vs 8.1 Mg ha –1 ) N-management. Average soybean yield where corn had received preplant N (3.6 Mg ha –1 ) was significantly (P = 0.05) greater than where late-spring N-management (3.4 Mg ha –1 ) was used. Residual tillage effects did not significantly (P = 0.05) affect soybean yield. The average residual soil NO 3 -N to a depth of 1.2 m following corn was significantly (P = 0.05) lower for preplant (21 kg N ha –1 ) than late spring (29 kg N ha –1 ) N-management under no-till system, presumably reflecting differences in N application rates. Residual soil NO 3 -N following soybean was significantly (P = 0.05) lower in no-till (28 kg N ha –1 ) than chisel (37 kg N ha –1 ) plots. Average over-winter changes in residual soil NO 3 -N were greatest in corn plots previously fertilized with a single preplant application (+13 to 18 kg N ha –1 ) and most variable following soybean in plots where corn was fertilized based on late-spring nitrate test (LSNT) values (-8.5 to +6.3 kg N ha –1 ). Therefore development of efficient N-management strategies may require complete understanding of N-cycling processes taking place in the soil profile over winter months. The results of the study demonstrate that chisel plow increased corn yield with late-spring N-management and with preplant N when compared to no-till system.

Separating preferential and matrix flows using subsurface tile flow data 1

Abstract Preferential flow is primary mechanism for faster movement of agricultural chemicals to groundwater. Subsurface tile flow data were used to quantify the contributions of preferential flow and matrix flow at the field scale over time. Tile flow hydrographs were constructed using hourly tile flow data related to rainfall events that were equal to or greater than 25.4 mm. A hydrograph separation technique was applied to separate preferential and matrix flow components of the subsurface tile flows. On the average, preferential flow was found to contribute about 13% of the total subsurface tile outflow for all the rain events, and an annual contribution of 10–20% is reasonable approximation. However, considerable spatial and temporal variability was observed, even among contiguous plots. Preferential flow for some rain storms was found to be as high as 60% of the total subsurface tile flow. This study also indicated that for storms greater than or equal to 25.4 mm, the subsurface tile outflow, on the ...

Simulating nitrogen management effects of subsurface drainage water quality

Abstract Increased level of NO 3 -N in the drinking water supplies is a major health concern these days. The long-term effects of actual nitrogen (N) fertilizer management practices are not well understood. The use of computer models allows the simulation of different N management practices on a long-term basis and their related effects on water quality. The RZWQM (Root Zone Water Quality Model, Version 3.0) was used to simulate the long-term (1978–1992) impacts of N management practices (single N applications at 50, 100, 150, and 200 kg per ha; and single and split N applications at 150 and 200 kg per ha) on NO 3 -N losses with subsurface drain flows and crop yields under two tillage systems (moldboard plow (MB) and no till (NT)). Simulations conducted in this study were based on input parameters calibrated by Singh et al. ( J. Environ. Qual., in press ) for NO 3 -N transport to subsurface drains. However, calibration of some additional parameters was required in this study for long-term simulations. The long-term climatic data and soil properties data for these simulations were obtained from a water quality research site at Nashua, Iowa. The results of this study showed that increasing rates of N applications (50, 100, 150, and 200 kg per ha) resulted in increased NO 3 -N losses with subsurface drain flows and increased crop yields. However, increasing rates of NO 3 -N losses and crop yields were not linearly proportional with increasing rates of N applications. These trends were similar for both MB and NT treatments. Also, NO 3 -N losses and crop yields were not significantly different under single and split N applications at both 150 and 200 kg per ha levels of application. The single N application of 150 kg per ha was considered the best N application practice as the simulated NO 3 -N losses under this practice were reduced considerably (40.3% less in MB and 52.4% less in NT) when compared with the single N application of 200 kg per ha. At the same time, the reduction in crop yields at 150 kg per ha single N application was very small (5.9% reduction under MB and about 6.1% under NT) when compared with the crop yields at 200 kg per ha single N application. This study also shows that RZWQM can be used successfully in evaluating similar N management schemes for other geographic regions of the world by utilizing site-specific data on soils, geological features, crops, and climatic parameters such as rainfall and evaporation.

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) since its release in 1999 for the Management System Evaluation Areas (MSEA) project. This study was designed to evaluate the herbicide 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 field within the Walnut Creek watershed in central Iowa. The model evaluation criterion was based on percent difference between the predicted and measured data (%D), root mean square error (RMSE), and model efficiency (EF). Atrazine and metolachlor were 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 agreement with the measured data showing %D = 1, RMSE = 8, and EF = 0.99, when averaged over the validation years. Herbicide half-life (t1/2) and soil organic based partitioning coefficient (Koc) were found to be the most sensitive parameters for simulating herbicide leaching losses in subsurface drainage water. Both t1/2 and Koc affected the mass and temporal distribution of the herbicide leaching losses in subsurface drainage flows. The predicted herbicide leaching losses in subsurface drainage water were the same order of magnitude as the measured data, when averaged across the validation years. 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 RZWQM to consider the dynamics of the preferential flow paths development in cultivated soils similar to that of the study area.

Escherichia coli transport from surface-applied manure to subsurface drains through artificial biopores.

Bacteria transport in soils primarily occurs through soil mesopores and macropores (e.g., biopores and cracks). Field research has demonstrated that biopores and subsurface drains can be hydraulically connected. This research was conducted to investigate the importance of surface connected and disconnected (buried) biopores on Escherichia coli (E. coli) transport when biopores are located near subsurface drains. A soil column (28 by 50 by 95 cm) was packed with loamy sand and sandy loam soils to bulk densities of 1.6 and 1.4 Mg m(-3), respectively, and containing an artificial biopore located directly above a subsurface drain. The sandy loam soil was packed using two different methods: moist soil sieved to 4.0 mm and air-dried soil manually crushed and then sieved to 2.8 mm. A 1-cm constant head was induced on the soil surface in three flushes: (i) water, (ii) diluted liquid swine (Sus scrofa) manure 48 h later, and (iii) water 48 h after the manure. Escherichia coli transport to the drain was observed with either open surface connected or buried biopores. In surface connected biopores, E. coli transport was a function of the soil type and the layer thickness between the end of the biopore and drain. Buried biopores contributed flow and E. coli in the less sorptive soil (loamy sand) and the sorptive soil (sandy loam) containing a wide (i.e., with mesopores) pore space distribution prevalent due to the moist soil packing technique. Biopores provide a mechanism for rapidly transporting E. coli into subsurface drains during flow events.

USING DISCRIMINANT ANALYSIS AND GIS TO DELINEATE SUBSURFACE DRAINAGE PATTERNS

The contamination of soil and water resources from nutrients, transported in subsurface drainage water having different drainage patterns, has important repercussions on the ecological environment and human health. This study was designed to delineate subsurface drainage patterns using cluster analysis based on six years (1993 to 1998) of field measured data on subsurface drainage flows from thirty-six 0.4 ha field experimental plots. These drainage patterns then were related spatially to the soil and topographic attributes using discriminant analysis and the map overlay capability of Geographic Information Systems (GIS) to develop cause-effect relationships. The experimental field plots, under various tillage and nitrogen management treatments, were located on glacial till derived soils at Iowa State University’s Northeastern Research Center near Nashua, Iowa. The field-measured subsurface drainage volumes were normalized to make comparisons over all plots and years, and the normalized data were used in the subsequent statistical and GIS analyses. After performing cluster analysis, the output was generated as GIS data layers showing low, medium, and high drainage areas. Stepwise discriminant analysis identified elevation, slope, and average normalized yield as the factors contributing significantly (P < 0.10) to the formation of subsurface drainage zones. GIS data layers of the factors, identified during discriminant analysis, were overlaid on the drainage patterns to study the spatial relationships. Map overlay analysis showed that high drainage areas were consistently found at low elevation levels in the vicinity of Floyd soils over the 6-year study period. The combined use of discriminant analysis and GIS was found to be effective in delineating subsurface drainage zones so that appropriate management practices can be applied to mitigate the environmental effects resulting from medium and higher subsurface drainage effluents.

N-management and crop rotation effects on yield and residual soil nitrate levels

Swine production facilities are becoming more concentrated in Iowa, and public is concerned about the impact of using swine manure for crop production on soil and water quality. This field study was conducted from 1996 to 1998 to compare the effects of liquid swine manure and urea ammonium nitrate (UAN) application on crop yield and residual soil nitrate for continuous corn (Zea mays L.) and corn-soybean (Glycine max (L.) Merr.) rotation systems. Six N management treatments were replicated three times in a randomized complete block design at Iowa State Universitys northeastern research center in Nashua, Iowa. Injected UAN provided 135 kg N ha−1 to continuous corn and 110 kg N ha−1 to corn grown in rotation with soybean. The 3-year average amount of N from swine manure was 123 kg ha−1 for continuous corn and 97 kg ha−1 for rotated corn. The average grain yield for continuous corn for UAN and manure treatments (7.8 vs. 7.5 Mg ha−1, respectively) was not significantly (P = 0.05) different. Corn yields from plots rotated with soybean were significantly different, averaging 9.4 and 8.9 Mg ha−1 for UAN and manure plots, respectively. Similarly, rotation effects reduced the residual soil nitrate by 25% (18 vs. 24 kg-N ha−1) and 33% (20 vs. 30 kg-N ha−1) under UAN and manure N-management systems, respectively, compared with continuous corn plots. The plots fertilized with swine manure also showed greater average levels of residual soil nitrate over winter months (12 vs. 5 kg-N ha−1) compared with UAN-fertilized plots. The results of this study suggest that using swine manure as a nitrogen supplement results in greater residual soil nitrate without increasing corn grain yield, compared with UAN-application, and can, therefore, build up excessive nitrate amounts in the root zone causing increased potential for NO3-N leaching to groundwater.