A spatially referenced water and nitrogen management model (WNMM) for (irrigated) intensive cropping systems in the North China Plain

Li, Yong; White, R. E.; Chen, Deli; Zhang, Jiabao; Li, Baoguo; Zhang, Yuming; Huang, Yuanfang; Edis, Robert

doi:10.1016/j.ecolmodel.2006.12.011

Cited by 129 publications

(107 citation statements)

References 56 publications

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“…Nitrate-N concentrations in the clay soil were strongly dependent on the NH þ 4 À N treatment rate, and nitrification appeared almost complete. A WNMM-based model (Xu et al, 1998;Li et al, 2007) with the addition of a moisture dependent emission coefficient (k d , equation (1)) was therefore a sound choice, and this was confirmed by the fit of equation (4) to the data.…”

Section: Modelling Observed Indirect N 2 O Emission Processesmentioning

confidence: 93%

“…Nitrous oxide emission processes were investigated in soil via modification of an existing soil process-based model (Water and Nitrogen Management Model; WNMM) (Xu et al, 1998;Li et al, 2007), selecting suitable parameters to better represent the system. These parameters are directly measurable, or determined by characterizing the statistical distribution of emission variability.…”

Section: Emission Modellingmentioning

confidence: 99%

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Soil N availability, rather than N deposition, controls indirect N2O emissions

Redding¹,

Shorten

Lewis³

et al. 2016

Soil Biology and Biochemistry

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a b s t r a c tAmmonia volatilised and re-deposited to the landscape is an indirect N 2 O emission source. This study established a relationship between N 2 O emissions, low magnitude NH 4 deposition (0e30 kg N ha À1 ), and soil moisture content in two soils using in-vessel incubations. Emissions from the clay soil peaked ( < 0:002 g N ½g soil À1 min À1 ) from 85 to 93% WFPS (water filled pore space), increasing to a plateau as remaining mineral-N increased. Peak N 2 O emissions for the sandy soil were much lower ( < 5 Â 10 À5 mg N ½g soil À1 min À1 ) and occurred at about 60% WFPS, with an indistinct relationship with increasing resident mineral N due to the low rate of nitrification in that soil. Microbial community and respiration data indicated that the clay soil was dominated by denitrifiers and was more biologically active than the sandy soil. However, the clay soil also had substantial nitrifier communities even under peak emission conditions. A process-based mathematical denitrification model was well suited to the clay soil data where all mineral-N was assumed to be nitrified (R 2 ¼ 90%), providing a substrate for denitrification. This function was not well suited to the sandy soil where nitrification was much less complete. A prototype relationship representing mineral-N pool conversions (NO 3 À and NH 4 þ ) was proposed based on time, pool concentrations, moisture relationships, and soil rate constants (preliminary testing only). A threshold for mineral-N was observed: emission of N 2 O did not occur from the clay soil for mineral-N <70 mg ðkg of soilÞ À1 , suggesting that soil N availability controls indirect N 2 O emissions.This laboratory process investigation challenges the IPCC approach which predicts indirect emissions from atmospheric N deposition alone. Crown

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Section: Modelling Observed Indirect N 2 O Emission Processesmentioning

confidence: 93%

Section: Emission Modellingmentioning

confidence: 99%

Soil N availability, rather than N deposition, controls indirect N2O emissions

Redding¹,

Shorten

Lewis³

et al. 2016

Soil Biology and Biochemistry

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“…Besides, because of the spatial and temporal variability of soils, the data of soil N mineralization kinetics derived from time-consuming laboratory incubation cannot meet the demand of regional model simulations [14], however, which is solved by pedo-transfer functions (PTFs) approach. The PTFs are generally developed by correlating readily available data or easily measured soil properties with dynamic soil processes that are costly to measure [15].…”

mentioning

confidence: 99%

Pedo-Transfer Functions to Estimate Kinetic Parameters for Anaerobic Soil Nitrogen Mineralization

Zou¹,

Zhao²,

Shi³

et al. 2018

OJSS

Self Cite

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Knowledge of potential anaerobic soil N mineralization is important for nitrogen fertilizer application. Instead of time-consuming laboratory incubation, we attempt to use pedo-transfer functions (PTFs) approach to get this information. 27 soil samples with various soil depths were collected from paddy field, woodland and tea field in subtropical central China, anaerobically incubated at 35˚C for 7 weeks to determine N mineralization, which was fitted by a modified double exponential model with two parameters (the fraction of active N pool (f) and mineralization rate constant (k) for active N pool). The PTFs for parameters were developed from significant soil properties using multiple stepwise regression method. Parameter f (range: 1.59% -10.4%, mean: 5.2%) was mainly correlated with soil total N (TN), organic C (SOC), ) was significantly related to TN, SOC, clay content, C to N ratio and pH (r = −0.6 -0.71, p < 0.05). Three variables (SOC, silt and pH) could estimate parameter f (R 2 = 0.72, p < 0.01) well and two (TN and pH) for parameter k (R 2 = 0.61, p < 0.01). The developed PTFs, integrating various land uses and soil depths, suggest that basic soil properties are helpful for estimation of anaerobic soil N mineralization.

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“…In the APSIM model, we used 0.002 as the default value of k ni , following Li et al (2007). However, this value may be soil-specific, so a larger value might have been a more appropriate value in our study.…”

Section: Characteristics Of the Dndc And Apsim Models In The Simulatimentioning

confidence: 99%

Simulation of N2o Emissions From a Sugarcane Field in Okinawa, Japan

Bellido¹

2015

Appl Ecol Env Res

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Abstract. We measured N 2 O emissions from a sugarcane field planted in spring 2011 in Okinawa, and examined their variations during the summer growing period (13 July to 4 August). Then we performed simulations with the DeNitrification and DeComposition (DNDC) and Agricultural Production Systems Simulator (APSIM) models to estimate N 2 O emissions and compared the results with the observed data from the field experiment. The results showed that (i) nitrification was the dominant process affecting N 2 O emissions and nitrifier denitrification occurred under high soil moisture conditions after rainfall; (ii) there was large spatial dispersion of N 2 O emissions even in the same field, and it was necessary to consider this dispersion to estimate total N 2 O emissions from the field; (iii) the emission factor of the N 2 O emissions might be larger than that used by the National Greenhouse Gas Inventory of Japan; (iv) the DNDC model overestimated, and the APSIM model underestimated, the observed N 2 O emissions; and (v) simulation of N 2 O emissions associated with nitrification by the DNDC model might be improved by modifying coefficients in the equation used to calculate N 2 O production during nitrification.

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A spatially referenced water and nitrogen management model (WNMM) for (irrigated) intensive cropping systems in the North China Plain

Cited by 129 publications

References 56 publications

Soil N availability, rather than N deposition, controls indirect N2O emissions

Soil N availability, rather than N deposition, controls indirect N2O emissions

Pedo-Transfer Functions to Estimate Kinetic Parameters for Anaerobic Soil Nitrogen Mineralization

Simulation of N2o Emissions From a Sugarcane Field in Okinawa, Japan

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