Validation of the GLEAMS simulation model for estimating net nitrogen mineralisation and nitrate leaching under cropping in Canterbury, New Zealand

Soil Research ◽  
2001 ◽  
Vol 39 (5) ◽  
pp. 1015 ◽  
Author(s):  
T. H. Webb ◽  
L. R. Lilburne ◽  
G. S. Francis
Keyword(s):  
Nitrate Leaching ◽  
Management Practices ◽  
Simulation Models ◽  
Model Parameters ◽  
Data Sets ◽  
Mineral N ◽  
Validation Data ◽  
Loading Effects ◽  
Annual Amount ◽  
Gleams Model

Simulation models require testing and calibration prior to their application to regions beyond those involved in their development. This paper reports on the calibration and testing of the groundwater loading effects of agricultural management systems (GLEAMS) model for the simulation of nitrate leaching under cropping in Canterbury. The GLEAMS model was first calibrated using crop and nitrogen leaching data collected from 4 consecutive years (1991–94) of spring-sown cereals following the ploughing of a temporary grass/clover pasture. Nitrate leaching losses were calculated from a combination of measured soil-solution nitrate concentration at 0.6 m depth, estimated drainage, and mineral N from soil cores. These calculated leached-N values were then used to calibrate the GLEAMS model. Parameters controlling denitrification and mineralisation rate in the model needed modification to provide sufficient mineral N for plant growth and nitrate leaching. The calibrated model was then tested against 3 independent validation data sets that were collected over 3 years from an adjacent experimental site, under the same management practices. Predictions from the calibrated GLEAMS model provided close agreement with measured values of mineralisation and leached N for the validation data sets. The amount of leached N averaged 43 kg N/ha.year and varied from 14 to 104 kg N/ha.year. The annual amount of drainage accounted for 97% of the variance in leached N, but the period in arable cropping was poorly correlated with leached N.

scholarly journals On auto-calibration algorithms for a forest growth simulation model

2011 ◽  
Vol 1 (4) ◽  
Author(s):  
Man Jia ◽  
Shiying Tian ◽  
Gaolin Zheng
Keyword(s):  
Gibbs Sampling ◽  
Line Search ◽  
Climate Changes ◽  
Management Practices ◽  
Simulation Models ◽  
Terrestrial Ecosystems ◽  
Forest Growth ◽  
Model Parameters ◽  
Growth Simulation ◽  
Optimal Set

AbstractForest growth simulation models are useful in evaluating the effects of management practices and climate changes in terrestrial ecosystems, however their successful application requires accurate calibration of model parameters. We have implemented here a stepwise line search (SLS), Gibbs sampling (GS) and preclustering based strength Pareto algorithm (K-SPEA2) to find an optimal set of parameters.

scholarly journals Potential for nitrate leaching from different land uses in the Pukekohe area

1997 ◽  
pp. 55-58
Author(s):  
J.R. Crush ◽  
S.N. Cathcart ◽  
P. Singleton ◽  
R.D. Longhurst
Keyword(s):  
Nitrate Leaching ◽  
Cover Crops ◽  
Management Practices ◽  
Nitrate Nitrogen ◽  
Potential Contribution ◽  
Mineral N ◽  
Main Crop ◽  
History Of ◽  
Winter Crops ◽  
N Management

Nitrogen balances (inputs minus outputs) were calculated for 5 dairy farms, 5 orchards and a range of crops. All the balances were positive, i.e., surplus N was present and a proportion of this N will eventually reach the groundwater as nitrate. On a per ha basis, the greatest N surplus was from early potatoes > winter cabbage, winter lettuce and squash > dairying, kiwifruit, summer cabbage and summer lettuce > pumpkins, onions and main crop potatoes > dry stock farming. The area in each activity was multiplied by the surplus N factor to obtain the potential contribution of N to groundwater in the Pukekohe area. Early potatoes (217 t N), contribute much more than onions (105 t N), dairying (59 t N) or dry stock farming (57 t N). Other activities contributed < 30 t N each. Winter crops had higher surplus N levels than the same crop grown in summer because winter crops had higher fertiliser N inputs and lower crop off-take of N. Management practices contributing to the N surpluses include high rates of N fertiliser used on some crops; a long history of cultivation, which has reduced soil organic matter contents and the ability of these soils to immobilise mineral N; and nil to intermittent use of cover crops to retain N in the topsoil. Keywords: aquifers, dairying, fertiliser, groundwater, land use, management, nitrate, nitrogen balance, nitrate leaching, vegetables.

Nitrate Leaching to a Shallow Mid-Atlantic Coastal Plain Aquifer as Influenced by Conventional No-Till and Low-Input Sustainable Grain Production Systems

1993 ◽  
Vol 28 (3-5) ◽  
pp. 691-700 ◽  
Author(s):  
J. P. Craig ◽  
R. R. Weil
Keyword(s):  
Management Practices ◽  
Production Systems ◽  
Cropping Systems ◽  
Cropping System ◽  
Atlantic Coastal Plain ◽  
Grain Production ◽  
Nitrogen And Phosphorus ◽  
Mineral N ◽  
Low Input ◽  
No Till

In December, 1987, the states in the Chesapeake Bay region, along with the federal government, signed an agreement which called for a 40% reduction in nitrogen and phosphorus loadings to the Bay by the year 2000. To accomplish this goal, major reductions in nutrient loadings associated with agricultural management practices were deemed necessary. The objective of this study was to determine if reducing fertilizer inputs to the NT system would result in a reduction in nitrogen contamination of groundwater. In this study, groundwater, soil, and percolate samples were collected from two cropping systems. The first system was a conventional no-till (NT) grain production system with a two-year rotation of corn/winter wheat/double crop soybean. The second system, denoted low-input sustainable agriculture (LISA), produced the same crops using a winter legume and relay-cropped soybeans into standing wheat to reduce nitrogen and herbicide inputs. Nitrate-nitrogen concentrations in groundwater were significantly lower under the LISA system. Over 80% of the NT groundwater samples had NO3-N concentrations greater than 10 mgl-1, compared to only 4% for the LISA cropping system. Significantly lower soil mineral N to a depth of 180 cm was also observed. The NT soil had nearly twice as much mineral N present in the 90-180 cm portion than the LISA cropping system.

scholarly journals Legumes increase grassland productivity with no effect on nitrous oxide emissions

2019 ◽  
Vol 446 (1-2) ◽  
pp. 163-177 ◽  
Author(s):  
Arlete S. Barneze ◽  
Jeanette Whitaker ◽  
Niall P. McNamara ◽  
Nicholas J. Ostle
Keyword(s):  
Management Practices ◽  
Production Systems ◽  
N Uptake ◽  
Relative Proportion ◽  
Management Strategies ◽  
Ghg Emissions ◽  
Chemical Properties ◽  
Nitrous Oxide Emissions ◽  
Mineral N ◽  
Grassland Productivity

Abstract Aims Grasslands are important agricultural production systems, where ecosystem functioning is affected by land management practices. Grass-legume mixtures are commonly cultivated to increase grassland productivity while reducing the need for nitrogen (N) fertiliser. However, little is known about the effect of this increase in productivity on greenhouse gas (GHG) emissions in grass-legume mixtures. The aim of this study was to investigate interactions between the proportion of legumes in grass-legume mixtures and N-fertiliser addition on productivity and GHG emissions. We tested the hypotheses that an increase in the relative proportion of legumes would increase plant productivity and decrease GHG emissions, and the magnitude of these effects would be reduced by N-fertiliser addition. Methods This was tested in a controlled environment mesocosm experiment with one grass and one legume species grown in mixtures in different proportions, with or without N-fertiliser. The effects on N cycling processes were assessed by measurement of above- and below-ground biomass, shoot N uptake, soil physico-chemical properties and GHG emissions. Results Above-ground productivity and shoot N uptake were greater in legume-grass mixtures compared to grass or legume monocultures, in fertilised and unfertilised soils. However, we found no effect of legume proportion on N2O emissions, total soil N or mineral-N in fertilised or unfertilised soils. Conclusions This study shows that the inclusion of legumes in grass-legume mixtures positively affected productivity, however N cycle were in the short-term unaffected and mainly affected by nitrogen fertilisation. Legumes can be used in grassland management strategies to mitigate climate change by reducing crop demand for N-fertilisers.

scholarly journals Theory and Applications of the Unit Gamma/Gompertz Distribution

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1850
Author(s):  
Rashad A. R. Bantan ◽  
Farrukh Jamal ◽  
Christophe Chesneau ◽  
Mohammed Elgarhy
Keyword(s):  
Stochastic Ordering ◽  
Real Data ◽  
Rate Function ◽  
The Other ◽  
Likelihood Method ◽  
Model Parameters ◽  
Data Sets ◽  
Gompertz Distribution ◽  
Probability And Statistics ◽  
Analytical Behavior

Unit distributions are commonly used in probability and statistics to describe useful quantities with values between 0 and 1, such as proportions, probabilities, and percentages. Some unit distributions are defined in a natural analytical manner, and the others are derived through the transformation of an existing distribution defined in a greater domain. In this article, we introduce the unit gamma/Gompertz distribution, founded on the inverse-exponential scheme and the gamma/Gompertz distribution. The gamma/Gompertz distribution is known to be a very flexible three-parameter lifetime distribution, and we aim to transpose this flexibility to the unit interval. First, we check this aspect with the analytical behavior of the primary functions. It is shown that the probability density function can be increasing, decreasing, “increasing-decreasing” and “decreasing-increasing”, with pliant asymmetric properties. On the other hand, the hazard rate function has monotonically increasing, decreasing, or constant shapes. We complete the theoretical part with some propositions on stochastic ordering, moments, quantiles, and the reliability coefficient. Practically, to estimate the model parameters from unit data, the maximum likelihood method is used. We present some simulation results to evaluate this method. Two applications using real data sets, one on trade shares and the other on flood levels, demonstrate the importance of the new model when compared to other unit models.

scholarly journals Bayesian Inference of Species Trees using Diffusion Models

2020 ◽  
Vol 70 (1) ◽  
pp. 145-161 ◽  
Author(s):  
Marnus Stoltz ◽  
Boris Baeumer ◽  
Remco Bouckaert ◽  
Colin Fox ◽  
Gordon Hiscott ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Numerical Algorithms ◽  
Diffusion Models ◽  
Model Parameters ◽  
Data Sets ◽  
Species Trees ◽  
Computationally Efficient ◽  
Data Set ◽  
Snp Data ◽  
Binary Markers

Abstract We describe a new and computationally efficient Bayesian methodology for inferring species trees and demographics from unlinked binary markers. Likelihood calculations are carried out using diffusion models of allele frequency dynamics combined with novel numerical algorithms. The diffusion approach allows for analysis of data sets containing hundreds or thousands of individuals. The method, which we call Snapper, has been implemented as part of the BEAST2 package. We conducted simulation experiments to assess numerical error, computational requirements, and accuracy recovering known model parameters. A reanalysis of soybean SNP data demonstrates that the models implemented in Snapp and Snapper can be difficult to distinguish in practice, a characteristic which we tested with further simulations. We demonstrate the scale of analysis possible using a SNP data set sampled from 399 fresh water turtles in 41 populations. [Bayesian inference; diffusion models; multi-species coalescent; SNP data; species trees; spectral methods.]

Review and performance of four models to assess the fate of radionuclides and heavy metals in surface soil

1997 ◽  
Vol 77 (3) ◽  
pp. 333-344 ◽  
Author(s):  
M. I. Sheppard ◽  
D. E. Elrick ◽  
S. R. Peterson
Keyword(s):  
Environmental Impact ◽  
Waste Management ◽  
Chemical Exchange ◽  
Nuclear Industry ◽  
Hydrodynamic Dispersion ◽  
Model Parameters ◽  
Validation Data ◽  
Soil Transport ◽  
And Performance ◽  
The Impact

The nuclear industry uses computer models to calculate and assess the impact of its present and future releases to the environment, both from operating reactors and from existing licensed and planned waste management facilities. We review four soil models varying in complexity that could be useful for environmental impact assessment. The goal of this comparison is to direct the combined use of these models in order to preserve simplicity, yet increase the rigor of Canadian environmental assessment calculations involving soil transport pathways. The four models chosen are: the Soil Chemical Exchange and Migration of Radionuclides (SCEMR1) model; the Baes and Sharp/Preclosure PREAC soil model, both used in Canada's nuclear fuel waste management program; the Convection-Dispersion Equation (CDE) model, commonly used in contaminant transport applications; and the Canadian Standards Association (CSA) derived release limit model used for normal operations at nuclear facilities. We discuss how each model operates, its timestep and depth increment options and the limitations of each of the models. Major model assumptions are discussed and the performance of these models is compared quantitatively for a scenario involving surface deposition or irrigation. A sensitivity analysis of the CDE model illustrates the influence of the important model parameters: the amount of infiltrating water, V; the hydrodynamic dispersion coefficient, D; and the soil retention or partition coefficient, Kd. The important parameters in the other models are also identified. This work shows we need tested, robust, mechanistic unsaturated soil models with easily understood and measurable inputs, including data for the sensitive or important model parameters for Canada's priority contaminants. Soil scientists need to assist industry and its regulators by recommending a selection of models and supporting them with the provision of validation data to ensure high-quality environmental risk assessments are carried out in Canada. Key words: Soil transport models, environmental impact assessments, model structure, complexity and performance, radionuclides 137Cs, 90Sr, 129I

Unknown Parameter Excitation and Estimation for Complex Systems With Dynamic Performances

2021 ◽  
Vol 143 (9) ◽  
Author(s):  
Yi-Ping Chen ◽  
Kuei-Yuan Chan
Keyword(s):  
Complex Systems ◽  
Simulation Models ◽  
Credible Interval ◽  
Specific Model ◽  
Model Parameters ◽  
Real Model ◽  
Dynamic Case ◽  
Dynamic Performances ◽  
Validation Stage ◽  
Setting Parameters

Abstract Simulation models play crucial roles in efficient product development cycles, therefore many studies aim to improve the confidence of a model during the validation stage. In this research, we proposed a dynamic model validation to provide accurate parameter settings for minimal output errors between simulation models and real model experiments. The optimal operations for setting parameters are developed to maximize the effects by specific model parameters while minimizing interactions. To manage the excessive costs associated with simulations of complex systems, we propose a procedure with three main features: the optimal excitation based on global sensitivity analysis (GSA) is done via metamodel techniques, for estimating parameters with the polynomial chaos-based Kalman filter, and validating the updated model based on hypothesis testing. An illustrative mathematical model was used to demonstrate the detail processes in our proposed method. We also apply our method on a vehicle dynamic case with a composite maneuver for exciting unknown model parameters such as inertial and coefficients of the tire model; the unknown model parameters were successfully estimated within a 95% credible interval. The contributions of this research are also underscored through multiple cases.

scholarly journals Using Simulation and Budget Models to Scale-Up Nitrogen Leaching from Field to Region in Canada

2001 ◽  
Vol 1 ◽  
pp. 699-706 ◽  
Author(s):  
E.C. Huffman ◽  
J.Y. Yang ◽  
S. Gameda ◽  
R. de Jong
Keyword(s):  
Dynamic Models ◽  
Scale Up ◽  
Simulation Models ◽  
Measured Data ◽  
Weather Data ◽  
Biophysical Modeling ◽  
Mineral N ◽  
Policy Model ◽  
Field Level ◽  
Time Of Year

Efforts are underway at Agriculture and Agri-Food Canada (AAFC) to develop an integrated, nationally applicable, socioeconomic/biophysical modeling capability in order to predict the environmental impacts of policy and program scenarios. This paper outlines our Decision Support System (DSS), which integrates the IROWCN (Indicator of the Risk of Water Contamination by Nitrogen) index with the agricultural policy model CRAM (Canadian Regional Agricultural Model) and presents an outline of our methodology to provide independent assessments of the IROWCN results through the use of nitrogen (N) simulation models in select, data-rich areas. Three field-level models — DSSAT, N_ABLE, and EPIC — were evaluated using local measured data. The results show that all three dynamic models can be used to simulate biomass, grain yield, and soil N dynamics at the field level; but the accuracy of the models differ, suggesting that models need to be calibrated using local measured data before they are used in Canada. Further simulation of IROWCN in a maize field using N_ABLE showed that soil-mineral N levels are highly affected by the amount of fertilizer N applied and the time of year, meaning that fertilizer and manure N applications and weather data are crucial for improving IROWCN. Methods of scaling-up simulated IROWCN from field-level to soil-landscape polygons and CRAM regions are discussed.

Sign in / Sign up

Export Citation Format

Share Document