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.

scholarly journals Modular Dynamic Biomolecular Modelling: The Unification of Stoichiometry, Thermodynamics, Kinetics and Data

2021 ◽  
Author(s):  
Peter J. Gawthrop ◽  
Michael Pan ◽  
Edmund J. Crampin
Keyword(s):  
Dynamic Models ◽  
System Development ◽  
Kinetic Modelling ◽  
Simulation Models ◽  
Bond Graph ◽  
Model Parameters ◽  
Biomolecular Systems ◽  
Genome Wide ◽  
Estimation Of Model Parameters ◽  
Genome Scale

AbstractRenewed interest in dynamic simulation models of biomolecular systems has arisen from advances in genome-wide measurement and applications of such models in biotechnology and synthetic biology. In particular, genome-scale models of cellular metabolism beyond the steady state are required in order to represent transient and dynamic regulatory properties of the system. Development of such whole-cell models requires new modelling approaches. Here we propose the energy-based bond graph methodology, which integrates stoichiometric models with thermo-dynamic principles and kinetic modelling. We demonstrate how the bond graph approach intrinsically enforces thermodynamic constraints, provides a modular approach to modelling, and gives a basis for estimation of model parameters leading to dynamic models of biomolecular systems. The approach is illustrated using a well-established stoichiometric model of E. coli and published experimental data.

scholarly journals Brief history and future of animal simulation models for science and application

2014 ◽  
Vol 54 (12) ◽  
pp. 1883 ◽  
Author(s):  
J. L. Black
Keyword(s):  
Animal Models ◽  
Real Time ◽  
Dynamic Models ◽  
Management Strategies ◽  
Simulation Models ◽  
Real Time Control ◽  
Livestock Farming ◽  
Animal Metabolism ◽  
The Impact ◽  
Further Development

Mathematical equations have been used to add quantitative rigour to the description of animal systems for the last 100 years. Initially, simple equations were used to describe the growth of animals or their parts and to predict nutrient requirements for different livestock species. The advent of computers led to development of complex multi-equation, dynamic models of animal metabolism and of the interaction between animals and their environment. An understanding was developed about how animal systems could be integrated in models to obtain the most realistic prediction of observations and allow accurate predictions of as yet unobserved events. Animal models have been used to illustrate how well animal systems are understood and to identify areas requiring further research. Many animal models have been developed with the aim of evaluating alternative management strategies within animal enterprises. Several important gaps in current animal models requiring further development are identified: including a more mechanistic representation of the control of feed intake; inclusion of methyl-donor requirements and simulation of the methionine cycle; plus a more mechanistic representation of disease and the impact of microbial loads under production environments. Reasons are identified why few animal models have been used for day-to-day decision making on farm. In the future, animal simulation models are envisaged to function as real-time control of systems within animal enterprises to optimise animal productivity, carcass quality, health, welfare and to maximise profit. Further development will be required for the integration of models that run real time in enterprise management systems adopting precision livestock farming technologies.

FlyBoss: a web-based flystrike information and decision support system

2010 ◽  
Vol 50 (12) ◽  
pp. 1069 ◽  
Author(s):  
B. Horton ◽  
L. Hogan
Keyword(s):  
Best Practice ◽  
Control Strategies ◽  
Present Report ◽  
Decision Aids ◽  
Simulation Models ◽  
Weather Data ◽  
Economic Management ◽  
Control Programs ◽  
Comprehensive Information ◽  
Control And Prevention

The FlyBoss system consists of comprehensive information on flystrike management and control, programs for assisting decision making, and sortable lists of products for preventing and treating flystrike. Readily accessible, up-to-date, best-practice information on flystrike is essential for effective, humane and economic management of flystrike by Australian wool producers, particularly those who are phasing out mulesing and those looking to adopt optimal insecticidal fly-control strategies. FlyBoss provides information on breeding and management to reduce flystrike susceptibility, effective methods of treating existing flystrike and flystrike prevention programs. The FlyBoss decision aids, which are based on simulation models and incorporate local weather data and sheep susceptibility factors, can assist sheep farmers who wish to optimise sheep management, chemical treatment and non-chemical options to minimise the risk of flystrike. FlyBoss also contains comprehensive information on fly biology, sheep and environmental factors associated with flystrike and information on appropriate chemicals for various situations. FlyBoss draws on expertise from organisations throughout Australia to provide the sheep industry with easily accessible, current and locally targeted information on flystrike management. The present report briefly describes the development of FlyBoss and associated workshops and provides an overview of current recommendations for the control and prevention of flystrike.

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.

Dynamic Modeling on the Hybrid MCFC-Gas Turbine Bottoming Cycle

2003 ◽  
Author(s):  
Huisheng Zhang ◽  
Shilie Weng ◽  
Ming Su
Keyword(s):  
Fuel Cell ◽  
Power Plant ◽  
Gas Turbine ◽  
Simulation Modeling ◽  
Dynamic Models ◽  
Simulation Models ◽  
Fuel Cell Stack ◽  
Hybrid Power ◽  
Hybrid Power Plant ◽  
Micro Turbine

The intention of this paper is to present the dynamic models for the MCFC-gas turbine hybrid cycle. This paper analyzes the performance of various components in the hybrid power plant, such as compressor, turbine, recuperator, generator, fuel cell stack etc. The modular simulation models of these components are presented. Based on the dynamic simulation modeling principle, one bottoming hybrid MCFC-Micro turbine cycle was studied to carry out the simulation, the simulation result is reasonable.

Lysimetric Evaluation of the APEX Model to Simulate Daily ET for Irrigated Crops in the Texas High Plains

2018 ◽  
Vol 61 (1) ◽  
pp. 65-74 ◽  
Author(s):  
Ali Saleh ◽  
Rewati Niraula ◽  
Gary W. Marek ◽  
Prasanna H. Gowda ◽  
David K. Brauer ◽  
...  
Keyword(s):  
Management Practices ◽  
Potential Evapotranspiration ◽  
Simulation Models ◽  
Weather Data ◽  
High Plains ◽  
Climate Data ◽  
Area Index ◽  
Growing Seasons ◽  
Texas High Plains ◽  
Apex Model

Abstract. The NTT (Nutrient Tracking Tool) was designed to provide an opportunity for all users, including producers, to run complex simulation models, such as APEX (Agricultural Policy Environmental eXtender), with the associated required databases. The APEX model currently nested within NTT provides estimates of the changes in nitrogen (N), phosphorus (P), and sediment losses that are associated with management practices specified by the user. Five methods (Penman-Monteith, Penman, Priestley-Taylor, Hargreaves-Samani, and Baier-Robertson) for determining potential evapotranspiration (PET) are available as inputs for estimating actual ET. This study was conducted to evaluate the accuracy of the ET values obtained from the five PET equations currently available in APEX using both onsite measured climate data and data from the NTT standard databases. The mean daily, monthly, and annual ET values predicted by each of the equations in APEX for a lysimeter field at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas, was compared to values measured for the 2001-2010 period. APEX generally underestimated ET with all PET methods (mostly during growing seasons) at both the daily and monthly levels but overpredicted for years when cotton was grown as the major cash crop due to overprediction of leaf area index during the senescing stage for cotton. The underprediction of ET in growing seasons was possibly from underprediction of rainfall due to estimation of rainfall for missing data. Overall, APEX was able to adequately (R2 = 0.82 and NSE = 0.80) predict mean monthly ET for major crops grown in the semi-arid Texas High Plains region. These results should reinforce confidence in APEX’s ability to simulate ET accurately for fully irrigated farms. ET predictions with the Hargreaves-Samani and Priestley-Taylor methods, which require limited data compared to the Penman and Penman-Monteith methods, were similar (p > 0.05, one-way ANOVA), with mean errors within 8.7% for measured weather data and 12.6% for NTT-generated weather data for both methods. This is encouraging because of the limited availability of measured climate data for the majority of locations in the world, including the U.S. Keywords: APEX, Evapotranspiration (ET), Irrigation, Lysimeters, NTT, Semiarid regions.

scholarly journals SIMULATION MODELING OF NEURAL CONTROL SYSTEM FOR SECTION OF MINE VENTILATION NETWORK

2014 ◽  
pp. 106-116
Author(s):  
Iryna Turchenko ◽  
Volodymyr Kochan ◽  
Anatoly Sachenko
Keyword(s):  
Neural Network ◽  
Simulation Modeling ◽  
Neural Control ◽  
Dynamic Models ◽  
Simulation Models ◽  
Mine Ventilation ◽  
Ventilation Network ◽  
Control Approach ◽  
Network Training ◽  
Good Potential

Static and dynamic simulation models of a section of a mine ventilation network in order to research a sequential neural control scheme of mine airflow are developed in this paper. The techniques of neural network training set creation for both simulation models, a structure of neural network and its training algorithm are described. The simulation modeling results using static and dynamic models have showed good potential capabilities of neural control approach.

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