Stochastic use of the LEACHN model to forecast nitrate leaching in different maize cropping systems

Acutis, Marco; Ducco, G.; Grignani, Carlo

doi:10.1016/s1161-0301(00)00074-5

Cited by 39 publications

(19 citation statements)

References 31 publications

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“…When a threshold value for N res is available, the riskyness of a system to result in excessive nitrate leaching can be assessed by the breakthrough probability, based on N res values of several years (Acutis et al, 2000). It turns out that the risk of trespassing the current Flemish threshold value of 90 kg N ha −1 within the N rate range of N opt −50 to N opt +50 was small (9%).…”

Section: Residual Soil Nitrate Nmentioning

confidence: 99%

Agronomical and environmental evaluation of a long-term experiment with cattle slurry and supplemental inorganic N applications in silage maize

Nevens¹,

Reheul²

2005

European Journal of Agronomy

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During 19 years of research on silage maize grown a fertile sandy loam soil in Flanders, we compared the use of only inorganic nitrogen (S−) with a system of an annual application of dairy cattle slurry (S+, corresponding with an average rate of 180 kg N ha −1 ) supplemented with inorganic fertilizer nitrogen. The objectives were to study the efficiency of slurry-N, to determine the economic optimum of additional fertilizer-N use and to relate this optimum with the local threshold on residual soil nitrate-N. During the last 5 years, the economically optimal fertilizer rates in the S− and the S+ system were centred around 150 and 90 kg N ha −1 , respectively. So, saving on fertilizer N amounted to about 60 kg N ha −1 . At these N rates, the risk for trespassing the local legal threshold value for residual soil nitrate-N content (90 kg ha −1 , 0-90 cm) was small (less than one out of ten seasons); economic and ecological optima of N fertilization concurred well. Meeting the standards of the EU nitrates directive and/or a doubled fertilizer N price would urge to decrease the applied amount of inorganic N by ca. 50 kg ha −1 , resulting in yield losses of about 5% on the studied sandy loam soil with an important content of total N (5300 kg ha −1 , 0-30 cm). The ratio of N-fertilizer replacement to the total amount of applied slurry-N increased during the experimental period to an average level of 59% during the last 5 years.

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Section: Residual Soil Nitrate Nmentioning

confidence: 99%

Agronomical and environmental evaluation of a long-term experiment with cattle slurry and supplemental inorganic N applications in silage maize

Nevens¹,

Reheul²

2005

European Journal of Agronomy

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“…The use of SOM models (alone or integrated into more complex ecological, cropping and farming system models) spans many fields of application: e.g., the interpretation of SOM dynamics at micro-scale in laboratory incubation experiments (Van Veen et al, 1985;, the estimation of longterm C dynamics in soils (Gijsman et al, 2002;Grace et al, 2006;Izaurralde et al, 2006), the quantification of N availability for plants (Coucheney et al, 2015) and N losses in the environment (Acutis et al, 2000), and the study of how SOM mineralization changes in response to a change of environmental variables (Davidson and Janssens, 2006;Conant et al, 2011;Liang et al, 2015;Sierra et al, 2015b).…”

Section: Introductionmentioning

confidence: 99%

Sensitivity analysis of six soil organic matter models applied to the decomposition of animal manures and crop residues

2016

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Two features distinguishing soil organic matter simulation models are the type of kinetics used to calculate pool decomposition rates, and the algorithm used to handle the effects of nitrogen (N) shortage on carbon (C) decomposition. Compared to widely used first-order kinetics, Monod kinetics more realistically represent organic matter decomposition, because they relate decomposition to both substrate and decomposer size. Most models impose a fixed C to N ratio for microbial biomass. When N required by microbial biomass to decompose a given amount of substrate-C is larger than soil available N, carbon decomposition rates are limited proportionally to N deficit (N inhibition hypothesis). Alternatively, C-overflow was proposed as a way of getting rid of excess C, by allocating it to a storage pool of polysaccharides. We built six models to compare the combinations of three decomposition kinetics (first-order, Monod, and reverse Monod), and two ways to simulate the effect of N shortage on C decomposition (N inhibition and C-overflow). We conducted sensitivity analysis to identify model parameters that mostly affected CO2 emissions and soil mineral N during a simulated 189-day laboratory incubation assuming constant water content and temperature. We evaluated model outputs sensitivity at different stages of organic matter decomposition in a soil amended with three inputs of increasing C to N ratio: liquid manure, solid manure, and low-N crop residue.Only few model parameters and their interactions were responsible for consistent variations of CO2 and soil mineral N. These parameters were mostly related to microbial biomass and to the partitioning of applied C among input pools, as well as their decomposition constants. In addition, in models with Monod kinetics, CO2 was also sensitive to a variation of the half-saturation constants.C-overflow enhanced pool decomposition compared to N inhibition hypothesis when N shortage occurred. Accumulated C in the polysaccharides pool decomposed slowly; therefore model outputs were not sensitive to a variation of its decay constant.Six-month organic matter decomposition was generally higher for models implementing classical Monod kinetics, followed by models with first-order and reverse Monod kinetics, due to the effect of soil microbial biomass growth on decomposition rates. Moreover, models implementing Monod kinetics predicted positive priming effects of native organic matter after soil amendment, according to co-metabolism theory. Thus, priming was proportional to the increase of the microbial biomass and in turn to the decomposability of applied organic matter. We conclude that model calibration should focus only on the few important parameters.

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“…In some studies, it was used to estimate the change of both water content and nitrate concentration at different soil depth, soil texture, and weather conditions (Ramos and Carbonell 1991;Johnson et al 1999;Schmied et al 2000;Roy et al 2000;Mahmood 2005). In other studies, nitrate leaching was simulated with the model at different fertilizer levels and crops, and then the simulation results were compared to the measured field data (Jemison et al 1994;Acutis et al 2000;Ng et al 2000;Singh and Sondhi 2001;Mahmood et al 2002). LEACHN has been applied to many different cases in many previous researches as shown above, which exemplifies the robust and wide field applicability of the model.…”

Section: Introductionmentioning

confidence: 99%

“…LEACHN has been applied to many different cases in many previous researches as shown above, which exemplifies the robust and wide field applicability of the model. Sensitivity analyses of LEACHN model were previously performed by Acutis et al (2000), Schmied et al (2000), Mahmood et al (2002), and Vachaud and Chen (2002a, b). These studies, however, analyzed the sensitivities of only a limited number of parameters at specific conditions.…”

Section: Introductionmentioning

confidence: 99%

Calibration of LEACHN model using LH-OAT sensitivity analysis

Jung

Oh²,

Kim

et al. 2009

Nutr Cycl Agroecosyst

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LEACHN model is useful to describe the nitrogen transport and transformation in soil but requires many input parameters. A sensitivity analysis can help to sort out the sensitive ones among many input parameters. A global sensitivity analysis technique, Latin Hypercube One factor At a Time (LH-OAT) method, was applied to LEACHN model in this study. Only a few parameters were found to be sensitive compared to many input parameters of the model from the sensitivity analysis. Using the results from the sensitivity analysis, calibration and validation of LEACHN model for nitrate leaching was performed for the experimental results from pot experiments that consisted of six types with different soil depth in mini-lysimeters and different fertilizer additions. The results indicated that the use of LH-OAT method could help the facile field application of LEACHN model. Model fitting could be improved by adopting current values in yearly crop parameters in validation.

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Stochastic use of the LEACHN model to forecast nitrate leaching in different maize cropping systems

Cited by 39 publications

References 31 publications

Agronomical and environmental evaluation of a long-term experiment with cattle slurry and supplemental inorganic N applications in silage maize

Agronomical and environmental evaluation of a long-term experiment with cattle slurry and supplemental inorganic N applications in silage maize

Sensitivity analysis of six soil organic matter models applied to the decomposition of animal manures and crop residues

Calibration of LEACHN model using LH-OAT sensitivity analysis

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