A model of ammonia volatilization from applied urea. I. Development of the model

Rachhpal-Singh,; Nye, P. H.

doi:10.1111/j.1365-2389.1986.tb00002.x

Cited by 83 publications

(25 citation statements)

References 7 publications

(3 reference statements)

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“…These differences are probably the result of differences in the depth of soil profiles taken for pH measurement as largest pH changes occur at the soil surface (Rachhpal-Singh and Nye, 1986). Unlike Ball et al (1979) we did not measure any decreases in soil pH at times when nitrification was evident.…”

Section: Discussioncontrasting

confidence: 80%

Transformations and fate of sheep urine-N applied to an upland U.K. pasture at different times during the growing season

Thomas¹,

Logan²,

Ironside³

et al. 1988

Plant Soil

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The fate of sheep urine-N applied to an upland grass sward at four dates representing widely differing environmental conditions, was followed in soil (0 -20 cm) and in herbage. Urine was poured onto l-m 2 plots to simulate a single urination in August 1984 (warm and dry), May (cool), July and August 1985 (cool and wet) at rates equivalent to 40-52 g N m -2.The transformation of urine-N (61-69 % urea-N) in soil over a 6-7 week period followed the same general pattern when applied at different times during the season; rapid hydrolysis of urea, the appearance of large amounts of urine-N as ammonium in soil extracts, and the appearance of nitrate about 14 days after application. The magnitude of "apparent" nitrification however differed markedly with environmental conditions, being greatest in May 1985 when a maximum of 76% of the inorganic soil N was in the form of nitrate. At all other application dates nitrate levels were relatively low. With the August 1984 application soil inorganic N returned to control levels (given water only) after 31 days but considerable amounts remained in soil for 60 -90 days with the other applications.Weekly cuts to 3-cm indicated that increases in herbage dry matter and N yields in response to urine application were greatest in absolute terms after the May 1985 application and continued for at least 70 days with all applications. Relative to control plots the May application resulted in a 3-fold increase in herbage DM compared with corresponding values of 6-, 5-, and 7-fold increases with the August 1984, July and August 1985 applications. Recovery of urine-N in herbage was poor averaging only 17% of that applied at different dates, while recovery in soil extracts was incomplete. The exact routes of loss (volatilisation, leaching, denitrification or immobilisation) were not quantified but it is evident that substantial amounts of urine-N can be lost from the soil-plant system under upland conditions.

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Section: Discussioncontrasting

confidence: 80%

Transformations and fate of sheep urine-N applied to an upland U.K. pasture at different times during the growing season

Thomas¹,

Logan²,

Ironside³

et al. 1988

Plant Soil

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“…Regarding the model structure and functionality, Móring et al (2016) provided a comparison for GAG_patch with the earlier modelling studies for urea-affected soils (Sherlock and Goh, 1985;Rachhpal and Nye, 1986) and urine patches (Laubach et al, 2012). Its field-scale application, GAG_field, is novel among the field-scale NH 3 exchange models, considering its dynamic approach for the modelling of soil pH under the urine patches.…”

Section: Model Development and Evaluationmentioning

confidence: 99%

Process-based modelling of NH<sub>3</sub> exchange with grazed grasslands

et al. 2017

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Abstract. In this study the GAG model, a process-based ammonia (NH 3 ) emission model for urine patches, was extended and applied for the field scale. The new model (GAG_field) was tested over two modelling periods, for which micrometeorological NH 3 flux data were available. Acknowledging uncertainties in the measurements, the model was able to simulate the main features of the observed fluxes. The temporal evolution of the simulated NH 3 exchange flux was found to be dominated by NH 3 emission from the urine patches, offset by simultaneous NH 3 deposition to areas of the field not affected by urine. The simulations show how NH 3 fluxes over a grazed field in a given day can be affected by urine patches deposited several days earlier, linked to the interaction of volatilization processes with soil pH dynamics. Sensitivity analysis showed that GAG_field was more sensitive to soil buffering capacity (β), field capacity (θ fc ) and permanent wilting point (θ pwp ) than the patch-scale model. The reason for these different sensitivities is dual. Firstly, the difference originates from the different scales. Secondly, the difference can be explained by the different initial soil pH and physical properties, which determine the maximum volume of urine that can be stored in the NH 3 source layer. It was found that in the case of urine patches with a higher initial soil pH and higher initial soil water content, the sensitivity of NH 3 exchange to β was stronger. Also, in the case of a higher initial soil water content, NH 3 exchange was more sensitive to the changes in θ fc and θ pwp . The sensitivity analysis showed that the nitrogen content of urine (c N ) is associated with high uncertainty in the simulated fluxes. However, model experiments based on c N values randomized from an estimated statistical distribution indicated that this uncertainty is considerably smaller in practice.Finally, GAG_field was tested with a constant soil pH of 7.5. The variation of NH 3 fluxes simulated in this way showed a good agreement with those from the simulations with the original approach, accounting for a dynamically changing soil pH. These results suggest a way for model simplification when GAG_field is applied later at regional scale.

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“…The model shows that, where rates of CaCO 3 precipitation are sufficient, the pH rise in the zone of urea hydrolysis will in many cases be impeded by CaCO 3 precipitation, and this will lessen NH 3 losses. For a discussion and model of this system in the absence of CaCO 3 precipitation, see the series of papers by Rachhpal-Singh and Nye (1986) and Kirk and Nye (1991).…”

Section: Precipitation Rate Constantmentioning

confidence: 99%

“…From the reaction stoichiometry (CO(NH 2 ) 2 + CO 2 + 3H 2 O = 2NH 4 + + 2HCO 3 -), F B = 2F U . A realistic range of k values is 10 -7 to 10 -5 s -1 (Rachhpal-Sigh and Nye, 1986) and D U = D LU θf (Rachhpal-Singh and Nye, 1986) = 2 × 10 -9 dm 2 s -1 for θf = 0.02. So for…”

Section: Sensitivity Analysis B: For Practical Applications In Cylindmentioning

confidence: 99%

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A simple reactive-transport model of calcite precipitation in soils and other porous media

Kirk

Versteegen

Ritz

et al. 2015

Geochimica et Cosmochimica Acta

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Calcite formation in soils and other porous media generally occurs around a localised source of reactants, such as a plant root or soil macro-pore, and the rate depends on the transport of reactants to and from the precipitation zone, as well as the kinetics of the precipitation reaction itself. However most studies are conducted using well-mixed systems, in which such transport limitations are largely removed. We developed a mathematical model of calcite precipitation near a source of base in soil, allowing for transport limitations and precipitation kinetics. We tested the model against experimentally-determined rates of calcite precipitation and reactant concentration:distance profiles in columns of soil in contact with a layer of HCO 3 --saturated exchange resin. The model parameter values were determined independently. The agreement between observed and predicted results was satisfactory given experimental limitations, indicating that the model correctly describes the important processes. A sensitivity analysis showed that all model parameters are important, indicating a simpler treatment would be inadequate. The sensitivity analysis showed that the amount of calcite precipitated and the spread of the precipitation zone were sensitive to parameters controlling rates of reactant transport (soil moisture content, salt content, pH, pH buffer power and CO 2 pressure), as well as to the precipitation rate constant. We illustrate practical applications of the model with two examples, viz. the effect of pH changes and CaCO 3 precipitation in the soil around a plant root, and around a soil macro-pore containing a source of base such as urea.

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A model of ammonia volatilization from applied urea. I. Development of the model

Cited by 83 publications

References 7 publications

Transformations and fate of sheep urine-N applied to an upland U.K. pasture at different times during the growing season

Transformations and fate of sheep urine-N applied to an upland U.K. pasture at different times during the growing season

Process-based modelling of NH<sub>3</sub> exchange with grazed grasslands

A simple reactive-transport model of calcite precipitation in soils and other porous media

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A model of ammonia volatilization from applied urea. I. Development of the model

Cited by 83 publications

References 7 publications

Transformations and fate of sheep urine-N applied to an upland U.K. pasture at different times during the growing season

Transformations and fate of sheep urine-N applied to an upland U.K. pasture at different times during the growing season

Process-based modelling of NH&lt;sub&gt;3&lt;/sub&gt; exchange with grazed grasslands

A simple reactive-transport model of calcite precipitation in soils and other porous media

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Process-based modelling of NH<sub>3</sub> exchange with grazed grasslands