A model of ammonia volatilization from applied urea. III. Sensitivity analysis, mechanisms, and applications

Rachhpal-Singh,; Nye, P. H.

doi:10.1111/j.1365-2389.1986.tb00004.x

Cited by 24 publications

(7 citation statements)

References 12 publications

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“…The model requires various inputs, of which we will consider three; pH, volumetric moisture content and bulk density, which were shown to be important in a sensitivity analysis (Rachhpal‐Singh & Nye, 1986b). The model is numerically stable over a pH range 6 to 12.…”

Section: Methodsmentioning

confidence: 99%

“…In the Rachhpal‐Singh model (1986a), ammonia volatilization also depends on the urease activity in the soil, the exchange isotherm for NH 4 + and a transfer coefficient describing the transfer of ammonia gas in the soil air to the immediate atmosphere. For the purpose of the illustrating the effective linearity diagnostic, we used the standard values for the following inputs from the sensitivity analysis of Rachhpal‐Singh & Nye (1986b): transfer coefficient = 133 dm h –1 ; rate of urea application = 210 kg N ha –1 ; Soil pH buffer capacity = 0.03 mol kg –1 pH –1 ; Freundlich coefficients = 0.35 and 0.66; Urease activity by Michaelis–Menten kinetic constants V max = 0.636 and k m = 0.663. For the three inputs for which we considered in evaluating the effective linearity we used the following mean values from a data set (see below), and when variables were held constant they took these values: pH = 7.24; bulk density = 1.2 kg dm –3 and moisture content = 0.35.…”

Section: Methodsmentioning

confidence: 99%

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On effective linearity of soil process models

Corstanje

Lark

2008

European J Soil Science

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There are various circumstances in which it is important to know whether we can treat a model of a soil process as linear with respect to its parameters. In particular this is necessary when we decide how to apply that model so as to generate outputs at different spatial scales. Very few, if any, interesting soil models are strictly linear. However, the assumption of linearity might not be unreasonable if, for the region of interest, the variation of a particular input is fairly limited, or is limited to certain regions of the model's parameter space, or both. For this reason we propose the concept of effective linearity.We propose that the effective linearity of a model is quantified by the mean square deviation of the model output from a best linear approximation, given some distribution of inputs. This can be computed for a full set of inputs, or for one input with the other inputs assumed to have an independent non-linear effect.We computed these measures of non-linearity for a model of ammonia volatilization from the soil. We computed them for regions of different size, given a particular geostatistical model of the spatial covariation of the inputs of interest. This showed that, except for small regions, the model could not be regarded as effectively linear because of the model response to soil pH. As a result the mean square deviation of model predictions relative to a best linear approximation is large by comparison to the analytical variance of the model output.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

On effective linearity of soil process models

Corstanje

Lark

2008

European J Soil Science

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“…Its CEC was 164 meq kg -I (replacement of all exchangeable cations with a 0.1 M BaCl2 solution buffered at pH 8.1, Thomas, 1982; subsequent replacement of Ba-ions with MgC12 solution and determination of Ba-ions via AAS). Soil pretreatment was carried out as described in Rachhpal-Singh and Nye (1986), with addition of 50 #g g-I soil 4-amino-1,2,4-triazole (ATC), a nitrification inhibitor. Soil pretreatment was carried out as described in Rachhpal-Singh and Nye (1986), with addition of 50 #g g-I soil 4-amino-1,2,4-triazole (ATC), a nitrification inhibitor.…”

Section: Methodsmentioning

confidence: 99%

“…To predict NH3-volatilization and concentration profiles of urea-N and ammoniacal-N as well as soil pH profiles, simulations were run with the mechanistic model of Rachhpal-Singh and Nye (1986), which only considers diffusive transport processes. Urease activity of this soil was not determined independently.…”

Section: Simulationsmentioning

confidence: 99%

“…The relationships between NH3-volatilization, soil pH and the buffering action of CaCO3 have been described both theoretically and experimentally (Avnimelech and Laher, 1977;Ferguson et al, 1984; Vlek and Stumpe, 1978). For a neutral, carbonate-free soil, the diffusion of HCO~-ions to the soil surface, resisting the decrease in surface pH caused by the reaction NH + ~-~ NH3 1" +H +, was shown to be the main rate limiting process of NH3-volatilization in Rachhpal-Singh and Nye's (1986) measurements and simulations. So far, existing simulation models of NH3-volatilization do not properly account for the effect of high soil CaCO3contents on changes in soil pH resulting from urea hydrolysis and ammonia volatilization.…”

Section: Introductionmentioning

confidence: 96%

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Laboratory measurements and simulations of ammonia volatilization from urea applied to calcareous Chinese loess soils

Roelcke¹,

Han

Li³

et al. 1996

Plant Soil

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Ammonia volatilization is the major pathway for mineral nitrogen loss in the calcareous soils of the Chinese loess plateau, with maximum losses reaching 50% of the fertilizer-N applied. A volatilization-diffusion experiment was carried out in the laboratory using a forced-draft system and soil columns of 15.5 cm depth. Urea was surface applied at rates of 210 kg N ha-I to a soil with 10% CaCO3 and a pH of 7.7. The amount of ammonia volatilized as well as the concentration profiles of ammoniacal-nitrogen and soil pH in the upper 50 mm of the soil columns after 4, 7 and 10 days were measured and subsequently modelled. The mechanistic model of Rachhpal-Singh and Nye, originally developed for neutral, non-calcareous soils, was modified to include the pH-buffering action of the soil carbonates. Model parameters were independently determined or taken from the literature. Measured and predicted cumulative NH3 losses agreed very well in the first 10 days following fertilizer application. However, in contrast to the simulations, NH3-volatilization was still proceeding in the experiment even after 13 days, with cumulative losses reaching 60% of the applied N. In addition to the high initial soil pH, the low bulk density and high volumetric air content of the soil columns used for the experiment proved decisive for the high rates of ammonia volatilization, provoking a strong increase in the amount of ammoniacal-N diffusing towards the soil surface as gaseous NH3. The simulations showed that due to the high soil pH, the buffering action of the soil carbonates played a comparatively smaller role.

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Simulatingin situammonia volatilization losses in the North China Plain using a dynamic soil‐crop model

Michalczyk

Kersebaum

Heimann

et al. 2016

J. Plant Nutr. Soil Sci.

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Ammonia (NH 3 ) volatilization is an important N loss pathway in intensive agriculture of the North China Plain (NCP). Simulation models can help to assess complex N and water processes of agricultural soil-crop systems. Four variations (Var) of a sub-module for the deterministic, process-based HERMES model were implemented ranging from simple empirical functions (Var 3 and 4) to process-oriented approaches (Var 1 and 2) including the main processes of NH 3 volatilization, urea hydrolysis, nitrification from ammonium-based N fertilizer, and changes in soil solution pH. Ammonia volatilization, plant growth, and changes in ammonium and nitrate pools in the soil over several winter wheat-summer maize double-crop rotations at three locations in the NCP were simulated. Results were calibrated with two data sets (Dongbeiwang 1, Shunyi) and validated using two data sets (Dongbeiwang 2, Quzhou). They showed that the ammonia volatilization sub-module of the HERMES model worked well under the climatic and soil conditions of N China. Although the simpler equations, Var 3 and 4, showed lower deviations to observed volatilization across all sites and treatments with a mean absolute error (MAE) of 1.8 and 1.4 in % of applied N, respectively, compared to process-oriented approaches, Var 1 and 2, with a MAE of 2.2 and 1.9 in % of applied N, respectively. Environmental conditions were reflected better by the process-oriented approaches. Generally, simulation results were satisfying but simulated changes in topsoil pH need further verification with measurements.

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A model of ammonia volatilization from applied urea. III. Sensitivity analysis, mechanisms, and applications

Cited by 24 publications

References 12 publications

On effective linearity of soil process models

On effective linearity of soil process models

Laboratory measurements and simulations of ammonia volatilization from urea applied to calcareous Chinese loess soils

Simulatingin situammonia volatilization losses in the North China Plain using a dynamic soil‐crop model

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