Effect of tillage and crop rotation on soil nitrate and moisture

Weed, D. A. J.

doi:10.31274/rtd-180813-7611

Cited by 5 publications

(3 citation statements)

References 21 publications

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“…Plots used in this study were located in Readlyn, and Kenyon soil types (table 2). Soil physical properties, including percent sand, silt, and clay, available water, bulk density, and saturated hydraulic conductivity at different depths for each soil type, were measured at the site by Ratliff et al (1983), Weed (1992), and Mirjat (1992). These data are shown in table 1.…”

Section: Model Calibration and Validationmentioning

confidence: 99%

Incorporation of a Subsurface Tile Drainage Component Into a Soybean Growth Model

Shen¹,

Batchelor²,

Jones³

et al. 1998

Transactions of the ASAE

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A simple tile drainage model was incorporated into a recent version of the CROPGRO-soybean model. The model was calibrated and validated using four years of data from the Water Quality Research site, located at the Iowa State University Northeast-Research Center near Nashua, Iowa having two soil types (Readlyn and Kenyon). The data consisted of measurements of soil water contents at different depths and times, cumulative monthly tile flow, and final crop yield from 36 different 0.41 ha plots that were individually tile drained. The model was calibrated to give the best fit between the predicted and measured tile flow, soil water content, and crop yield from 1993 and 1994 for each soil type. It was validated by using data from 1995 and 1996 for each soil type. Predicted soil water contents, tile drainage and soybean yield matched measured values very well over all years for these two soil types. The results of this study show that the modified CROPGRO model does a very good job in simulating soybean yields and water dynamics for Readlyn and Kenyon soil in the experiment.Agricultural Science | Agriculture | Agronomy and Crop Sciences | Bioresource and Agricultural Engineering | Forest Management | Water Resource Management Comments ABSTRACT. A simple tile drainage model was incorporated into a recent version of the CROPGRO-soybean model. The model was calibrated and validated using four years of data from the Water Quality Research site, located at the Iowa State University Northeast-Research Center near Nashua, Iowa having two soil types (Readlyn and Kenyon). The data consisted of measurements of soil water contents at different depths and times, cumulative monthly tile flow, and final crop yield from 36 different 0.41 ha plots that were individually tile drained. The model was calibrated to give the best fit between the predicted and measured tile flow, soil water content, and crop yield from 1993 and 1994 for each soil type. It was validated by using data from 1995 and 1996 for each soil type. Predicted soil water contents, tile drainage and soybean yield matched measured values very well over all years for these two soil types. The results of this study show that the modified CROPGRO model does a very good job in simulating soybean yields and water dynamics for Readlyn and Kenyon soil in the experiment.

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Section: Model Calibration and Validationmentioning

confidence: 99%

Incorporation of a Subsurface Tile Drainage Component Into a Soybean Growth Model

Shen¹,

Batchelor²,

Jones³

et al. 1998

Transactions of the ASAE

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“…Many studies demonstrated the importance of the application of fertilizer at rates not exceeding the optimal crop demand (Mercado, 1976;Varvel and Peterson, 1990;Weed and Karlen, 1992;Puckett et al, 1999). Puckett et al (1999) cited many studies that estimated a fertilizer application rate that is 24 to 38 percent higher than the crop demand.…”

Section: Alternative 2: Reduction Of Fertilizer Applicationmentioning

confidence: 99%

IMPLICATIONS OF ON‐GROUND NITROGEN LOADING AND SOIL TRANSFORMATIONS ON GROUND WATER QUALITY MANAGEMENT¹

Almasri¹,

Kaluarachchi²

2004

J American Water Resour Assoc

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This paper presents a modeling approach based on a geographic information system (GIS) to estimate the variability of on‐ground nitrogen loading and the corresponding nitrate leaching to ground water. The methodology integrates all point and nonpoint sources of nitrogen, the national land cover database, soil nitrogen transformations, and the uncertainty of key soil and land use‐related parameters to predict the nitrate mass leaching to ground water. The analysis considered 21 different land use classes with information derived from nitrogen sources such as fertilizer and dairy manure applications, dairy lagoons, septic systems, and dry and wet depositions. Simulations were performed at a temporal resolution of one month to capture seasonal trends. The model was applied to a large aquifer of 376 square miles in Washington State that serves more than 100,000 residents with drinking water. The results showed that dairy manure is the main source of nitrogen in the area followed by fertilizers. It was also seen that nitrate leaching is controlled by the recharge rate, and there can be a substantial buildup of soil nitrogen over long periods of time. Uncertainty analysis showed that denitrification rate is the most influential parameter on nitrate leaching. The results showed that combining management alternatives is a successful strategy, especially with the use of nitrification inhibitors. Also, change in the land use pattern has a noticeable impact on nitrate leaching.

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“…These cores were composited after sectioning them into a set of nine samples representing the following depths: 0 to 0.10, 0.10 to 0.20, 0.20 to 0.30, 0.30 to 0.45, 0.45 to 0.60, 0.60 to 0.90, 0.90 to 1.20, 1.20 to 1.50, and 1.50 to 1.80 m. Composited samples were analyzed for soil water content, NO3-N, and pesticide concentrations. A detailed methodology of collecting soil samples and analyzing them is described by Weed (1992). Simulated NO3-N concentration in the soil profile were compared with the measured NO3-N concentration for 1990 and 1992.…”

Section: No3-n Concentrations In the Soil Prohlementioning

confidence: 99%

Simulating NO3-N Transport to Subsurface Drain Flows as Affected by Tillage Under Continuous Corn Using Modified RZWQM

Singh¹,

Kanwar²

1995

Transactions of the ASAE

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The Root Zone Water Quality Model (RZWQM) was previously modified to simulate subsurface drain flows and evaluate the impact of different tillage systems on subsurface drain flows (Singh and Kanwar, 1994). This article discusses further modifications made in the RZWQM to simulate nitrate-nitrogen (NO3-N) concentrations and NO3-N losses with subsurface drain flows. Daily NO3-N concentrations were simulated in subsurface drain flows under four different tillage systems: chisel plow (CP), moldboard plow (MB), notillage (NT), and ridge-tillage (RT) by using the modified RZWQM. Simulations were conducted for the growing seasons of three years (1990 to 1992). Simulated NO3-N concentrations and losses with subsurface drain flows were compared with the measured data obtained from a water quality research site at Nashua, Iowa. Predicted NO3-N concentrations generally followed the same pattern as the observed concentrations. Simulated annual average NO3-N concentrations in subsurface drain flows were within 11% (averaged over all three years) of observed annual average NO3-N concentrations in subsurface drain flows. The model correctly predicted maximum concentrations under MB treatment and minimum under NT for all three years. Simulated annual NO3-N losses were within 14% (averaged over all three years) of observed annual NO3-N losses. Various NO3-N transformation processes need to be calibrated as a function of tillage system to improve model performance.

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Effect of tillage and crop rotation on soil nitrate and moisture

Abstract: Alachlor c 2.2 Atrazine c 2.8 Alachlor 2.2 Atrazine 2.8 Alachlor 2.2 Cyanazine c 2.8 Alachlor 2.2 Cyanazine 2.8 Alachlor 2.2 Metribuzin c 0.45 a Active ingredient .

Cited by 5 publications

References 21 publications

Incorporation of a Subsurface Tile Drainage Component Into a Soybean Growth Model

Incorporation of a Subsurface Tile Drainage Component Into a Soybean Growth Model

IMPLICATIONS OF ON‐GROUND NITROGEN LOADING AND SOIL TRANSFORMATIONS ON GROUND WATER QUALITY MANAGEMENT¹

Simulating NO3-N Transport to Subsurface Drain Flows as Affected by Tillage Under Continuous Corn Using Modified RZWQM

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Effect of tillage and crop rotation on soil nitrate and moisture

Abstract: Alachlor c 2.2 Atrazine c 2.8 Alachlor 2.2 Atrazine 2.8 Alachlor 2.2 Cyanazine c 2.8 Alachlor 2.2 Cyanazine 2.8 Alachlor 2.2 Metribuzin c 0.45 a Active ingredient .

Cited by 5 publications

References 21 publications

Incorporation of a Subsurface Tile Drainage Component Into a Soybean Growth Model

Incorporation of a Subsurface Tile Drainage Component Into a Soybean Growth Model

IMPLICATIONS OF ON‐GROUND NITROGEN LOADING AND SOIL TRANSFORMATIONS ON GROUND WATER QUALITY MANAGEMENT1

Simulating NO3-N Transport to Subsurface Drain Flows as Affected by Tillage Under Continuous Corn Using Modified RZWQM

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IMPLICATIONS OF ON‐GROUND NITROGEN LOADING AND SOIL TRANSFORMATIONS ON GROUND WATER QUALITY MANAGEMENT¹