Simulating the Distribution of Individual Livestock Farms and Their Populations in the United States: An Example Using Domestic Swine (Sus scrofa domesticus) Farms

PubMed Central

Garza, Sarah J.; Miller, Ryan S.

2015-01-01

Livestock distribution in the United States (U.S.) can only be mapped at a county-level or worse resolution. We developed a spatial microsimulation model called the Farm Location and Agricultural Production Simulator (FLAPS) that simulated the distribution and populations of individual livestock farms throughout the conterminous U.S. Using domestic pigs (Sus scrofa domesticus) as an example species, we customized iterative proportional-fitting algorithms for the hierarchical structure of the U.S. Census of Agriculture and imputed unpublished state- or county-level livestock population totals that were redacted to ensure confidentiality. We used a weighted sampling design to collect data on the presence and absence of farms and used them to develop a national-scale distribution model that predicted the distribution of individual farms at a 100 m resolution. We implemented microsimulation algorithms that simulated the populations and locations of individual farms using output from our imputed Census of Agriculture dataset and distribution model. Approximately 19% of county-level pig population totals were unpublished in the 2012 Census of Agriculture and needed to be imputed. Using aerial photography, we confirmed the presence or absence of livestock farms at 10,238 locations and found livestock farms were correlated with open areas, cropland, and roads, and also areas with cooler temperatures and gentler topography. The distribution of swine farms was highly variable, but cross-validation of our distribution model produced an area under the receiver-operating characteristics curve value of 0.78, which indicated good predictive performance. Verification analyses showed FLAPS accurately imputed and simulated Census of Agriculture data based on absolute percent difference values of < 0.01% at the state-to-national scale, 3.26% for the county-to-state scale, and 0.03% for the individual farm-to-county scale. Our output data have many applications for risk management of agricultural systems including epidemiological studies, food safety, biosecurity issues, emergency-response planning, and conflicts between livestock and other natural resources. PMID:26571497

Simulating the Distribution of Individual Livestock Farms and Their Populations in the United States: An Example Using Domestic Swine (Sus scrofa domesticus) Farms.

PubMed

Burdett, Christopher L; Kraus, Brian R; Garza, Sarah J; Miller, Ryan S; Bjork, Kathe E

2015-01-01

Livestock distribution in the United States (U.S.) can only be mapped at a county-level or worse resolution. We developed a spatial microsimulation model called the Farm Location and Agricultural Production Simulator (FLAPS) that simulated the distribution and populations of individual livestock farms throughout the conterminous U.S. Using domestic pigs (Sus scrofa domesticus) as an example species, we customized iterative proportional-fitting algorithms for the hierarchical structure of the U.S. Census of Agriculture and imputed unpublished state- or county-level livestock population totals that were redacted to ensure confidentiality. We used a weighted sampling design to collect data on the presence and absence of farms and used them to develop a national-scale distribution model that predicted the distribution of individual farms at a 100 m resolution. We implemented microsimulation algorithms that simulated the populations and locations of individual farms using output from our imputed Census of Agriculture dataset and distribution model. Approximately 19% of county-level pig population totals were unpublished in the 2012 Census of Agriculture and needed to be imputed. Using aerial photography, we confirmed the presence or absence of livestock farms at 10,238 locations and found livestock farms were correlated with open areas, cropland, and roads, and also areas with cooler temperatures and gentler topography. The distribution of swine farms was highly variable, but cross-validation of our distribution model produced an area under the receiver-operating characteristics curve value of 0.78, which indicated good predictive performance. Verification analyses showed FLAPS accurately imputed and simulated Census of Agriculture data based on absolute percent difference values of < 0.01% at the state-to-national scale, 3.26% for the county-to-state scale, and 0.03% for the individual farm-to-county scale. Our output data have many applications for risk management of agricultural systems including epidemiological studies, food safety, biosecurity issues, emergency-response planning, and conflicts between livestock and other natural resources.

Integrated Farm System Model Version 4.1 and Dairy Gas Emissions Model Version 3.1 software release and distribution

USDA-ARS?s Scientific Manuscript database

Animal facilities are significant contributors of gaseous emissions including ammonia (NH3) and nitrous oxide (N2O). Previous versions of the Integrated Farm System Model (IFSM version 4.0) and Dairy Gas Emissions Model (DairyGEM version 3.0), two whole-farm simulation models developed by USDA-ARS, ...

Simulation of Turbulent Flow Inside and Above Wind Farms: Model Validation and Layout Effects

NASA Astrophysics Data System (ADS)

Wu, Yu-Ting; Porté-Agel, Fernando

2013-02-01

A recently-developed large-eddy simulation framework is validated and used to investigate turbulent flow within and above wind farms under neutral conditions. Two different layouts are considered, consisting of thirty wind turbines occupying the same total area and arranged in aligned and staggered configurations, respectively. The subgrid-scale (SGS) turbulent stress is parametrized using a tuning-free Lagrangian scale-dependent dynamic SGS model. The turbine-induced forces are modelled using two types of actuator-disk models: (a) the `standard' actuator-disk model (ADM-NR), which calculates only the thrust force based on one-dimensional momentum theory and distributes it uniformly over the rotor area; and (b) the actuator-disk model with rotation (ADM-R), which uses blade-element momentum theory to calculate the lift and drag forces (that produce both thrust and rotation), and distributes them over the rotor disk based on the local blade and flow characteristics. Validation is performed by comparing simulation results with turbulence measurements collected with hot-wire anemometry inside and above an aligned model wind farm placed in a boundary-layer wind tunnel. In general, the ADM-R model yields improved predictions compared with the ADM-NR in the wakes of all the wind turbines, where including turbine-induced flow rotation and accounting for the non-uniformity of the turbine-induced forces in the ADM-R appear to be important. Another advantage of the ADM-R model is that, unlike the ADM-NR, it does not require a priori specification of the thrust coefficient (which varies within a wind farm). Finally, comparison of simulations of flow through both aligned and staggered wind farms shows important effects of farm layout on the flow structure and wind-turbine performance. For the limited-size wind farms considered in this study, the lateral interaction between cumulated wakes is stronger in the staggered case, which results in a farm wake that is more homogeneous in the spanwise direction, thus resembling more an internal boundary layer. Inside the staggered farm, the relatively longer separation between consecutive downwind turbines allows the wakes to recover more, exposing the turbines to higher local wind speeds (leading to higher turbine efficiency) and lower turbulence intensity levels (leading to lower fatigue loads), compared with the aligned farm. Above the wind farms, the area-averaged velocity profile is found to be logarithmic, with an effective wind-farm aerodynamic roughness that is larger for the staggered case.

Modeling greenhouse gas emissions from dairy farms.

PubMed

Rotz, C Alan

2017-11-15

Dairy farms have been identified as an important source of greenhouse gas emissions. Within the farm, important emissions include enteric CH 4 from the animals, CH 4 and N 2 O from manure in housing facilities during long-term storage and during field application, and N 2 O from nitrification and denitrification processes in the soil used to produce feed crops and pasture. Models using a wide range in level of detail have been developed to represent or predict these emissions. They include constant emission factors, variable process-related emission factors, empirical or statistical models, mechanistic process simulations, and life cycle assessment. To fully represent farm emissions, models representing the various emission sources must be integrated to capture the combined effects and interactions of all important components. Farm models have been developed using relationships across the full scale of detail, from constant emission factors to detailed mechanistic simulations. Simpler models, based upon emission factors and empirical relationships, tend to provide better tools for decision support, whereas more complex farm simulations provide better tools for research and education. To look beyond the farm boundaries, life cycle assessment provides an environmental accounting tool for quantifying and evaluating emissions over the full cycle, from producing the resources used on the farm through processing, distribution, consumption, and waste handling of the milk and dairy products produced. Models are useful for improving our understanding of farm processes and their interacting effects on greenhouse gas emissions. Through better understanding, they assist in the development and evaluation of mitigation strategies for reducing emissions and improving overall sustainability of dairy farms. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

A survey of modelling methods for high-fidelity wind farm simulations using large eddy simulation.

PubMed

Breton, S-P; Sumner, J; Sørensen, J N; Hansen, K S; Sarmast, S; Ivanell, S

2017-04-13

Large eddy simulations (LES) of wind farms have the capability to provide valuable and detailed information about the dynamics of wind turbine wakes. For this reason, their use within the wind energy research community is on the rise, spurring the development of new models and methods. This review surveys the most common schemes available to model the rotor, atmospheric conditions and terrain effects within current state-of-the-art LES codes, of which an overview is provided. A summary of the experimental research data available for validation of LES codes within the context of single and multiple wake situations is also supplied. Some typical results for wind turbine and wind farm flows are presented to illustrate best practices for carrying out high-fidelity LES of wind farms under various atmospheric and terrain conditions.This article is part of the themed issue 'Wind energy in complex terrains'. © 2017 The Author(s).

A survey of modelling methods for high-fidelity wind farm simulations using large eddy simulation

PubMed Central

Sumner, J.; Sørensen, J. N.; Hansen, K. S.; Sarmast, S.; Ivanell, S.

2017-01-01

Large eddy simulations (LES) of wind farms have the capability to provide valuable and detailed information about the dynamics of wind turbine wakes. For this reason, their use within the wind energy research community is on the rise, spurring the development of new models and methods. This review surveys the most common schemes available to model the rotor, atmospheric conditions and terrain effects within current state-of-the-art LES codes, of which an overview is provided. A summary of the experimental research data available for validation of LES codes within the context of single and multiple wake situations is also supplied. Some typical results for wind turbine and wind farm flows are presented to illustrate best practices for carrying out high-fidelity LES of wind farms under various atmospheric and terrain conditions. This article is part of the themed issue ‘Wind energy in complex terrains’. PMID:28265021

Simulation of a 7.7 MW onshore wind farm with the Actuator Line Model

NASA Astrophysics Data System (ADS)

Guggeri, A.; Draper, M.; Usera, G.

2017-05-01

Recently, the Actuator Line Model (ALM) has been evaluated with coarser resolution and larger time steps than what is generally recommended, taking into account an atmospheric sheared and turbulent inflow condition. The aim of the present paper is to continue these studies, assessing the capability of the ALM to represent the wind turbines’ interactions in an onshore wind farm. The ‘Libertad’ wind farm, which consists of four 1.9MW Vestas V100 wind turbines, was simulated considering different wind directions, and the results were compared with the wind farm SCADA data, finding good agreement between them. A sensitivity analysis was performed to evaluate the influence of the spatial resolution, finding acceptable agreement, although some differences were found. It is believed that these differences are due to the characteristics of the different Atmospheric Boundary Layer (ABL) simulations taken as inflow condition (precursor simulations).

Turbulent kinetics of a large wind farm and their impact in the neutral boundary layer

DOE PAGES

Na, Ji Sung; Koo, Eunmo; Munoz-Esparza, Domingo; ...

2015-12-28

High-resolution large-eddy simulation of the flow over a large wind farm (64 wind turbines) is performed using the HIGRAD/FIRETEC-WindBlade model, which is a high-performance computing wind turbine–atmosphere interaction model that uses the Lagrangian actuator line method to represent rotating turbine blades. These high-resolution large-eddy simulation results are used to parameterize the thrust and power coefficients that contain information about turbine interference effects within the wind farm. Those coefficients are then incorporated into the WRF (Weather Research and Forecasting) model in order to evaluate interference effects in larger-scale models. In the high-resolution WindBlade wind farm simulation, insufficient distance between turbines createsmore » the interference between turbines, including significant vertical variations in momentum and turbulent intensity. The characteristics of the wake are further investigated by analyzing the distribution of the vorticity and turbulent intensity. Quadrant analysis in the turbine and post-turbine areas reveals that the ejection motion induced by the presence of the wind turbines is dominant compared to that in the other quadrants, indicating that the sweep motion is increased at the location where strong wake recovery occurs. Regional-scale WRF simulations reveal that although the turbulent mixing induced by the wind farm is partly diffused to the upper region, there is no significant change in the boundary layer depth. The velocity deficit does not appear to be very sensitive to the local distribution of turbine coefficients. However, differences of about 5% on parameterized turbulent kinetic energy were found depending on the turbine coefficient distribution. Furthermore, turbine coefficients that consider interference in the wind farm should be used in wind farm parameterization for larger-scale models to better describe sub-grid scale turbulent processes.« less

Recent Advancements in the Numerical Simulation of Surface Irradiance for Solar Energy Applications: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Yu; Sengupta, Manajit; Deline, Chris

This paper briefly reviews the National Renewable Energy Laboratory's recent efforts on developing all-sky solar irradiance models for solar energy applications. The Fast All-sky Radiation Model for Solar applications (FARMS) utilizes the simulation of clear-sky transmittance and reflectance and a parameterization of cloud transmittance and reflectance to rapidly compute broadband irradiances on horizontal surfaces. FARMS delivers accuracy that is comparable to the two-stream approximation, but it is approximately 1,000 times faster. A FARMS-Narrowband Irradiance over Tilted surfaces (FARMS-NIT) has been developed to compute spectral irradiances on photovoltaic (PV) panels in 2002 wavelength bands. Further, FARMS-NIT has been extended for bifacialmore » PV panels.« less

Evaluating the mitigation of greenhouse gas emissions and adaptation in dairy production.

USDA-ARS?s Scientific Manuscript database

Process-level modeling at the farm scale provides a tool for evaluating strategies for both mitigating greenhouse gas emissions and adapting to climate change. The Integrated Farm System Model (IFSM) simulates representative crop, beef or dairy farms over many years of weather to predict performance...

Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model.

PubMed

Mena, Carlos F; Walsh, Stephen J; Frizzelle, Brian G; Xiaozheng, Yao; Malanson, George P

2011-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways.

Weather Research and Forecasting model simulation of an onshore wind farm: assessment against LiDAR and SCADA data

NASA Astrophysics Data System (ADS)

Santoni, Christian; Garcia-Cartagena, Edgardo J.; Zhan, Lu; Iungo, Giacomo Valerio; Leonardi, Stefano

2017-11-01

The integration of wind farm parameterizations into numerical weather prediction models is essential to study power production under realistic conditions. Nevertheless, recent models are unable to capture turbine wake interactions and, consequently, the mean kinetic energy entrainment, which are essential for the development of power optimization models. To address the study of wind turbine wake interaction, one-way nested mesoscale to large-eddy simulation (LES) were performed using the Weather Research and Forecasting model (WRF). The simulation contains five nested domains modeling the mesoscale wind on the entire North Texas Panhandle region to the microscale wind fluctuations and turbine wakes of a wind farm located at Panhandle, Texas. The wind speed, direction and boundary layer profile obtained from WRF were compared against measurements obtained with a sonic anemometer and light detection and ranging system located within the wind farm. Additionally, the power production were assessed against measurements obtained from the supervisory control and data acquisition system located in each turbine. Furthermore, to incorporate the turbines into very coarse LES, a modification to the implementation of the wind farm parameterization by Fitch et al. (2012) is proposed. This work was supported by the NSF, Grants No. 1243482 (WINDINSPIRE) and IIP 1362033 (WindSTAR), and TACC.

The Environmental Impact of a Wave Dragon Array Operating in the Black Sea

PubMed Central

Rusu, Eugen

2013-01-01

The present work describes a study related to the influence on the shoreline dynamics of a wave farm consisting of Wave Dragon devices operating in the western side of the Black Sea. Based on historical data analysis of the wave climate, the most relevant environmental conditions that could occur were defined, and for these cases, simulations with SWAN spectral phase averaged wave model were performed. Two situations were considered for the most representative patterns: model simulations without any wave energy converter and simulations considering a wave farm consisting of six Wave Dragon devices. Comparisons of the wave model outputs have been carried out in both geographical and spectral spaces. The results show that although a significant influence appears near the wave farm, this gradually decreases to the coast line level. In order to evaluate the influence of the wave farm on the longshore currents, a nearshore circulation modeling system was used. In relative terms, the longshore current velocities appear to be more sensitive to the presence of the wave farm than the significant wave height. Finally, the possible impact on the marine flora and fauna specific to the target area was also considered and discussed. PMID:23844401

The environmental impact of a Wave Dragon array operating in the Black Sea.

PubMed

Diaconu, Sorin; Rusu, Eugen

2013-01-01

The present work describes a study related to the influence on the shoreline dynamics of a wave farm consisting of Wave Dragon devices operating in the western side of the Black Sea. Based on historical data analysis of the wave climate, the most relevant environmental conditions that could occur were defined, and for these cases, simulations with SWAN spectral phase averaged wave model were performed. Two situations were considered for the most representative patterns: model simulations without any wave energy converter and simulations considering a wave farm consisting of six Wave Dragon devices. Comparisons of the wave model outputs have been carried out in both geographical and spectral spaces. The results show that although a significant influence appears near the wave farm, this gradually decreases to the coast line level. In order to evaluate the influence of the wave farm on the longshore currents, a nearshore circulation modeling system was used. In relative terms, the longshore current velocities appear to be more sensitive to the presence of the wave farm than the significant wave height. Finally, the possible impact on the marine flora and fauna specific to the target area was also considered and discussed.

Turbulence and entrainment length scales in large wind farms.

PubMed

Andersen, Søren J; Sørensen, Jens N; Mikkelsen, Robert F

2017-04-13

A number of large wind farms are modelled using large eddy simulations to elucidate the entrainment process. A reference simulation without turbines and three farm simulations with different degrees of imposed atmospheric turbulence are presented. The entrainment process is assessed using proper orthogonal decomposition, which is employed to detect the largest and most energetic coherent turbulent structures. The dominant length scales responsible for the entrainment process are shown to grow further into the wind farm, but to be limited in extent by the streamwise turbine spacing, which could be taken into account when developing farm layouts. The self-organized motion or large coherent structures also yield high correlations between the power productions of consecutive turbines, which can be exploited through dynamic farm control.This article is part of the themed issue 'Wind energy in complex terrains'. © 2017 The Author(s).

Turbulence and entrainment length scales in large wind farms

PubMed Central

2017-01-01

A number of large wind farms are modelled using large eddy simulations to elucidate the entrainment process. A reference simulation without turbines and three farm simulations with different degrees of imposed atmospheric turbulence are presented. The entrainment process is assessed using proper orthogonal decomposition, which is employed to detect the largest and most energetic coherent turbulent structures. The dominant length scales responsible for the entrainment process are shown to grow further into the wind farm, but to be limited in extent by the streamwise turbine spacing, which could be taken into account when developing farm layouts. The self-organized motion or large coherent structures also yield high correlations between the power productions of consecutive turbines, which can be exploited through dynamic farm control. This article is part of the themed issue ‘Wind energy in complex terrains’. PMID:28265028

A Hybrid Wind-Farm Parametrization for Mesoscale and Climate Models

NASA Astrophysics Data System (ADS)

Pan, Yang; Archer, Cristina L.

2018-04-01

To better understand the potential impact of wind farms on weather and climate at the regional to global scales, a new hybrid wind-farm parametrization is proposed for mesoscale and climate models. The proposed parametrization is a hybrid model because it is not based on physical processes or conservation laws, but on the multiple linear regression of the results of large-eddy simulations (LES) with the geometric properties of the wind-farm layout (e.g., the blockage ratio and blockage distance). The innovative aspect is that each wind turbine is treated individually based on its position in the farm and on the wind direction by predicting the velocity upstream of each turbine. The turbine-induced forces and added turbulence kinetic energy (TKE) are first derived analytically and then implemented in the Weather Research and Forecasting model. Idealized simulations of the offshore Lillgrund wind farm are conducted. The wind-speed deficit and TKE predicted with the hybrid model are in excellent agreement with those from the LES results, while the wind-power production estimated with the hybrid model is within 10% of that observed. Three additional wind farms with larger inter-turbine spacing than at Lillgrund are also considered, and a similar agreement with LES results is found, proving that the hybrid parametrization works well with any wind farm regardless of the spacing between turbines. These results indicate the wind-turbine position, wind direction, and added TKE are essential in accounting for the wind-farm effects on the surroundings, for which the hybrid wind-farm parametrization is a promising tool.

Fast All-Sky Radiation Model for Solar Applications (FARMS): A Brief Overview of Mechanisms, Performance, and Applications: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Yu; Sengupta, Manajit

Solar radiation can be computed using radiative transfer models, such as the Rapid Radiation Transfer Model (RRTM) and its general circulation model applications, and used for various energy applications. Due to the complexity of computing radiation fields in aerosol and cloudy atmospheres, simulating solar radiation can be extremely time-consuming, but many approximations--e.g., the two-stream approach and the delta-M truncation scheme--can be utilized. To provide a new fast option for computing solar radiation, we developed the Fast All-sky Radiation Model for Solar applications (FARMS) by parameterizing the simulated diffuse horizontal irradiance and direct normal irradiance for cloudy conditions from the RRTMmore » runs using a 16-stream discrete ordinates radiative transfer method. The solar irradiance at the surface was simulated by combining the cloud irradiance parameterizations with a fast clear-sky model, REST2. To understand the accuracy and efficiency of the newly developed fast model, we analyzed FARMS runs using cloud optical and microphysical properties retrieved using GOES data from 2009-2012. The global horizontal irradiance for cloudy conditions was simulated using FARMS and RRTM for global circulation modeling with a two-stream approximation and compared to measurements taken from the U.S. Department of Energy's Atmospheric Radiation Measurement Climate Research Facility Southern Great Plains site. Our results indicate that the accuracy of FARMS is comparable to or better than the two-stream approach; however, FARMS is approximately 400 times more efficient because it does not explicitly solve the radiative transfer equation for each individual cloud condition. Radiative transfer model runs are computationally expensive, but this model is promising for broad applications in solar resource assessment and forecasting. It is currently being used in the National Solar Radiation Database, which is publicly available from the National Renewable Energy Laboratory at http://nsrdb.nrel.gov.« less

Flow Field Analysis of Fish Farm and Planting Area in Floodplain during Flood

NASA Astrophysics Data System (ADS)

Wu, M.; Tan, H. N.; Lo, W. C.; Tsai, C. T.

2017-12-01

Fish farms constructing and crops planting is common in floodplain in Taiwan. The physiographic soil erosion-deposition (PSED) model was applied to simulate the sediment yield, the runoff, and sediment transport rate of the river watershed corresponding to one-day rainstorms of the return periods of 25, 50, and 100 year. The variation of flow field in the river sections could be simulated by utilizing the alluvial river-movable bed two dimensional (ARMB-2D) model. The results reveal that the tendency of river discharge, sediment deposition and erosion obtained from these two models is agreeable by calibration and verification. The water flow affected by fish farms and planting areas in floodplain during flood was analyzed. Lastly, based on the simulation results obtained from the PESD and ARMB-2D models for one-day rainstorms of the return periods of 25, 50, and 100 year, the illegal fish farms and planting area with severe variations of river flow and affected he capability for flood conveyance will be referred to as the demolishing-to-be areas. We could also suggest the management strategy of application for fish farms constructing and crops planting in river areas by incorporating the ability of our model to provide information of river flow to enhance the flood conveyance.

Impact simulation of shrimp farm effluent on BOD-DO in Setiu River

NASA Astrophysics Data System (ADS)

Chong, Michael Sueng Lock; Teh, Su Yean; Koh, Hock Lye

2017-08-01

Release of effluent from intensive aquaculture farms into a river can pollute the receiving river and exert negative impacts on the aquatic ecosystem. In this paper, we simulate the effects of effluent released from a marine shrimp aquaculture farm into Sg Setiu, focusing on two critical water quality parameters i.e. DO (dissolved oxygen) and BOD (biochemical oxygen demand). DO is an important constituent in a river in sustaining water quality, with levels of DO below 5 mg/L deemed undesirable. DO levels can be depressed by the presence of BOD and other organics that consume DO. Water quality simulations in conjunction with management of effluent treatment can suggest mitigation measures for reducing the adverse environmental impact. For this purpose, an in-house two-dimensional water quality simulation model codenamed TUNA-WQ will be used for these simulations. TUNA-WQ has been undergoing regular updates and improvements to broaden the applicability and to improve the robustness. Here, the model is calibrated and verified for simulation of DO and BOD dynamics in Setiu River (Sg Setiu). TUNA-WQ simulated DO and BOD in Setiu River due to the discharge from a marine shrimp aquaculture farm will be presented.

Understanding the Impacts of Soil, Climate, and Farming Practices on Soil Organic Carbon Sequestration: A Simulation Study in Australia.

PubMed

Godde, Cécile M; Thorburn, Peter J; Biggs, Jody S; Meier, Elizabeth A

2016-01-01

Carbon sequestration in agricultural soils has the capacity to mitigate greenhouse gas emissions, as well as to improve soil biological, physical, and chemical properties. The review of literature pertaining to soil organic carbon (SOC) dynamics within Australian grain farming systems does not enable us to conclude on the best farming practices to increase or maintain SOC for a specific combination of soil and climate. This study aimed to further explore the complex interactions of soil, climate, and farming practices on SOC. We undertook a modeling study with the Agricultural Production Systems sIMulator modeling framework, by combining contrasting Australian soils, climates, and farming practices (crop rotations, and management within rotations, such as fertilization, tillage, and residue management) in a factorial design. This design resulted in the transposition of contrasting soils and climates in our simulations, giving soil-climate combinations that do not occur in the study area to help provide insights into the importance of the climate constraints on SOC. We statistically analyzed the model's outputs to determinate the relative contributions of soil parameters, climate, and farming practices on SOC. The initial SOC content had the largest impact on the value of SOC, followed by the climate and the fertilization practices. These factors explained 66, 18, and 15% of SOC variations, respectively, after 80 years of constant farming practices in the simulation. Tillage and stubble management had the lowest impacts on SOC. This study highlighted the possible negative impact on SOC of a chickpea phase in a wheat-chickpea rotation and the potential positive impact of a cover crop in a sub-tropical climate (QLD, Australia) on SOC. It also showed the complexities in managing to achieve increased SOC, while simultaneously aiming to minimize nitrous oxide (N2O) emissions and nitrate leaching in farming systems. The transposition of contrasting soils and climates in our simulations revealed the importance of the climate constraints on SOC.

Simulation and optimal control of wind-farm boundary layers

NASA Astrophysics Data System (ADS)

Meyers, Johan; Goit, Jay

2014-05-01

In large wind farms, the effect of turbine wakes, and their interaction leads to a reduction in farm efficiency, with power generated by turbines in a farm being lower than that of a lone-standing turbine by up to 50%. In very large wind farms or `deep arrays', this efficiency loss is related to interaction of the wind farms with the planetary boundary layer, leading to lower wind speeds at turbine level. Moreover, for these cases it has been demonstrated both in simulations and wind-tunnel experiments that the wind-farm energy extraction is dominated by the vertical turbulent transport of kinetic energy from higher regions in the boundary layer towards the turbine level. In the current study, we investigate the use of optimal control techniques combined with Large-Eddy Simulations (LES) of wind-farm boundary layer interaction for the increase of total energy extraction in very large `infinite' wind farms. We consider the individual wind turbines as flow actuators, whose energy extraction can be dynamically regulated in time so as to optimally influence the turbulent flow field, maximizing the wind farm power. For the simulation of wind-farm boundary layers we use large-eddy simulations in combination with actuator-disk and actuator-line representations of wind turbines. Simulations are performed in our in-house pseudo-spectral code SP-Wind that combines Fourier-spectral discretization in horizontal directions with a fourth-order finite-volume approach in the vertical direction. For the optimal control study, we consider the dynamic control of turbine-thrust coefficients in an actuator-disk model. They represent the effect of turbine blades that can actively pitch in time, changing the lift- and drag coefficients of the turbine blades. Optimal model-predictive control (or optimal receding horizon control) is used, where the model simply consists of the full LES equations, and the time horizon is approximately 280 seconds. The optimization is performed using a nonlinear conjugate gradient method, and the gradients are calculated by solving the adjoint LES equations. We find that the extracted farm power increases by approximately 20% when using optimal model-predictive control. However, the increased power output is also responsible for an increase in turbulent dissipation, and a deceleration of the boundary layer. Further investigating the energy balances in the boundary layer, it is observed that this deceleration is mainly occurring in the outer layer as a result of higher turbulent energy fluxes towards the turbines. In a second optimization case, we penalize boundary-layer deceleration, and find an increase of energy extraction of approximately 10%. In this case, increased energy extraction is balanced by a reduction in of turbulent dissipation in the boundary layer. J.M. acknowledges support from the European Research Council (FP7-Ideas, grant no. 306471). Simulations were performed on the computing infrastructure of the VSC Flemish Supercomputer Center, funded by the Hercules Foundation and the Flemish Government.

Modelling Infectious Hematopoietic Necrosis Virus Dispersion from Marine Salmon Farms in the Discovery Islands, British Columbia, Canada.

PubMed

Foreman, Michael G G; Guo, Ming; Garver, Kyle A; Stucchi, Dario; Chandler, Peter; Wan, Di; Morrison, John; Tuele, Darren

2015-01-01

Finite volume ocean circulation and particle tracking models are used to simulate water-borne transmission of infectious hematopoietic necrosis virus (IHNV) among Atlantic salmon (Salmo salar) farms in the Discovery Islands region of British Columbia, Canada. Historical simulations for April and July 2010 are carried out to demonstrate the seasonal impact of river discharge, wind, ultra-violet (UV) radiation, and heat flux conditions on near-surface currents, viral dispersion and survival. Numerical particles released from infected farm fish in accordance with IHNV shedding rates estimated through laboratory experiments are dispersed by model oceanic flows. Viral particles are inactivated by ambient UV radiation levels and by the natural microbial community at rates derived through laboratory studies. Viral concentration maps showing temporal and spatial changes are produced and combined with lab-determined minimum infectious dosages to estimate the infective connectivity among farms. Results demonstrate that neighbouring naïve farms can become exposed to IHNV via water-borne transport from an IHNV diseased farm, with a higher risk in April than July, and that many events in the sequence of farm outbreaks in 2001-2002 are consistent with higher risks in our farm connectivity matrix. Applications to other diseases, transfers between farmed and wild fish, and the effect of vaccinations are also discussed.

Modelling Infectious Hematopoietic Necrosis Virus Dispersion from Marine Salmon Farms in the Discovery Islands, British Columbia, Canada

PubMed Central

Foreman, Michael G. G.; Guo, Ming; Garver, Kyle A.; Stucchi, Dario; Chandler, Peter; Wan, Di; Morrison, John; Tuele, Darren

2015-01-01

Finite volume ocean circulation and particle tracking models are used to simulate water-borne transmission of infectious hematopoietic necrosis virus (IHNV) among Atlantic salmon (Salmo salar) farms in the Discovery Islands region of British Columbia, Canada. Historical simulations for April and July 2010 are carried out to demonstrate the seasonal impact of river discharge, wind, ultra-violet (UV) radiation, and heat flux conditions on near-surface currents, viral dispersion and survival. Numerical particles released from infected farm fish in accordance with IHNV shedding rates estimated through laboratory experiments are dispersed by model oceanic flows. Viral particles are inactivated by ambient UV radiation levels and by the natural microbial community at rates derived through laboratory studies. Viral concentration maps showing temporal and spatial changes are produced and combined with lab-determined minimum infectious dosages to estimate the infective connectivity among farms. Results demonstrate that neighbouring naïve farms can become exposed to IHNV via water-borne transport from an IHNV diseased farm, with a higher risk in April than July, and that many events in the sequence of farm outbreaks in 2001-2002 are consistent with higher risks in our farm connectivity matrix. Applications to other diseases, transfers between farmed and wild fish, and the effect of vaccinations are also discussed. PMID:26114643

DOE Office of Scientific and Technical Information (OSTI.GOV)

Na, Ji Sung; Koo, Eunmo; Munoz-Esparza, Domingo

High-resolution large-eddy simulation of the flow over a large wind farm (64 wind turbines) is performed using the HIGRAD/FIRETEC-WindBlade model, which is a high-performance computing wind turbine–atmosphere interaction model that uses the Lagrangian actuator line method to represent rotating turbine blades. These high-resolution large-eddy simulation results are used to parameterize the thrust and power coefficients that contain information about turbine interference effects within the wind farm. Those coefficients are then incorporated into the WRF (Weather Research and Forecasting) model in order to evaluate interference effects in larger-scale models. In the high-resolution WindBlade wind farm simulation, insufficient distance between turbines createsmore » the interference between turbines, including significant vertical variations in momentum and turbulent intensity. The characteristics of the wake are further investigated by analyzing the distribution of the vorticity and turbulent intensity. Quadrant analysis in the turbine and post-turbine areas reveals that the ejection motion induced by the presence of the wind turbines is dominant compared to that in the other quadrants, indicating that the sweep motion is increased at the location where strong wake recovery occurs. Regional-scale WRF simulations reveal that although the turbulent mixing induced by the wind farm is partly diffused to the upper region, there is no significant change in the boundary layer depth. The velocity deficit does not appear to be very sensitive to the local distribution of turbine coefficients. However, differences of about 5% on parameterized turbulent kinetic energy were found depending on the turbine coefficient distribution. Furthermore, turbine coefficients that consider interference in the wind farm should be used in wind farm parameterization for larger-scale models to better describe sub-grid scale turbulent processes.« less

Modeling emissions of volatile organic compounds from silage storages and feed lanes

USDA-ARS?s Scientific Manuscript database

An initial volatile organic compound (VOC) emission model for silage sources, developed using experimental data from previous studies, was incorporated into the Integrated Farm System Model (IFSM), a whole-farm simulation model used to assess the performance, environmental impacts, and economics of ...

AGRO-2014: A time dependent model for assessing the fate and food-web bioaccumulation of organic pesticides in farm ponds: Model testing and performance analysis.

PubMed

Gobas, Frank A P C; Lai, Hao-Feng; Mackay, Donald; Padilla, Lauren E; Goetz, Andy; Jackson, Scott H

2018-10-15

A time-dependent environmental fate and food-web bioaccumulation model is developed to improve the evaluation of the behaviour of non-ionic hydrophobic organic pesticides in farm ponds. The performance of the model was tested by simulating the behaviour of 3 hydrophobic organic pesticides, i.e., metaflumizone (CAS Number: 139968-49-3), kresoxim-methyl (CAS Number: 144167-04-4) and pyraclostrobin (CAS Number: 175013-18-0), in microcosm studies and a Bluegill bioconcentration study for metaflumizone. In general, model-calculated concentrations of the pesticides were in reasonable agreement with the observed concentrations. Also, calculated bioaccumulation metrics were in good agreement with observed values. The model's application to simulate concentrations of organic pesticides in water, sediment and biota of farm ponds after episodic pesticide applications is illustrated. It is further shown that the time dependent model has substantially better accuracy in simulating the concentrations of pesticides in farm ponds resulting from episodic pesticide application than corresponding steady-state models. The time dependent model is particularly useful in describing the behaviour of highly hydrophobic pesticides that have a potential to biomagnify in aquatic food-webs. Copyright © 2018 Elsevier B.V. All rights reserved.

Development and application of incrementally complex tools for wind turbine aerodynamics

NASA Astrophysics Data System (ADS)

Gundling, Christopher H.

Advances and availability of computational resources have made wind farm design using simulation tools a reality. Wind farms are battling two issues, affecting the cost of energy, that will make or break many future investments in wind energy. The most significant issue is the power reduction of downstream turbines operating in the wake of upstream turbines. The loss of energy from wind turbine wakes is difficult to predict and the underestimation of energy losses due to wakes has been a common problem throughout the industry. The second issue is a shorter lifetime of blades and past failures of gearboxes due to increased fluctuations in the unsteady loading of waked turbines. The overall goal of this research is to address these problems by developing a platform for a multi-fidelity wind turbine aerodynamic performance and wake prediction tool. Full-scale experiments in the field have dramatically helped researchers understand the unique issues inside a large wind farm, but experimental methods can only be used to a limited extent due to the cost of such field studies and the size of wind farms. The uncertainty of the inflow is another inherent drawback of field experiments. Therefore, computational fluid dynamics (CFD) predictions, strategically validated using carefully performed wind farm field campaigns, are becoming a more standard design practice. The developed CFD models include a blade element model (BEM) code with a free-vortex wake, an actuator disk or line based method with large eddy simulations (LES) and a fully resolved rotor based method with detached eddy simulations (DES) and adaptive mesh refinement (AMR). To create more realistic simulations, performance of a one-way coupling between different mesoscale atmospheric boundary layer (ABL) models and the three microscale CFD solvers is tested. These methods are validated using data from incrementally complex test cases that include the NREL Phase VI wind tunnel test, the Sexbierum wind farm and the Lillgrund offshore wind farm. By cross-comparing the lowest complexity free-vortex method with the higher complexity methods, a fast and accurate simulation tool has been generated that can perform wind farm simulations in a few hours.

Simulation of wake effects between two wind farms

NASA Astrophysics Data System (ADS)

Hansen, K. S.; Réthoré, P.-E.; Palma, J.; Hevia, B. G.; Prospathopoulos, J.; Peña, A.; Ott, S.; Schepers, G.; Palomares, A.; van der Laan, M. P.; Volker, P.

2015-06-01

SCADA data, recorded on the downstream wind farm, has been used to identify flow cases with visible clustering effects. The inflow condition is derived from a partly undisturbed wind turbine, due to lack of mast measurements. The SCADA data analysis concludes that centre of the deficit for the downstream wind farm with disturbed inflow has a distinct visible maximum deficit zone located only 5-10D downstream from the entrance. This zone, representing 20-30% speed reduction, increases and moves downstream for increasing cluster effect and is not visible outside a flow sector of 20-30°. The eight flow models represented in this benchmark include both RANS models, mesoscale models and engineering models. The flow cases, identified according to the wind speed level and inflow sector, have been simulated and validated with the SCADA results. The model validation concludes that all models more or less are able to predict the location and size of the deficit zone inside the downwind wind farm.

Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model

PubMed Central

Mena, Carlos F.; Walsh, Stephen J.; Frizzelle, Brian G.; Xiaozheng, Yao; Malanson, George P.

2010-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways. PMID:24436501

Numerical simulations of flow fields through conventionally controlled wind turbines & wind farms

NASA Astrophysics Data System (ADS)

Emre Yilmaz, Ali; Meyers, Johan

2014-06-01

In the current study, an Actuator-Line Model (ALM) is implemented in our in-house pseudo-spectral LES solver SP-WIND, including a turbine controller. Below rated wind speed, turbines are controlled by a standard-torque-controller aiming at maximum power extraction from the wind. Above rated wind speed, the extracted power is limited by a blade pitch controller which is based on a proportional-integral type control algorithm. This model is used to perform a series of single turbine and wind farm simulations using the NREL 5MW turbine. First of all, we focus on below-rated wind speed, and investigate the effect of the farm layout on the controller calibration curves. These calibration curves are expressed in terms of nondimensional torque and rotational speed, using the mean turbine-disk velocity as reference. We show that this normalization leads to calibration curves that are independent of wind speed, but the calibration curves do depend on the farm layout, in particular for tightly spaced farms. Compared to turbines in a lone-standing set-up, turbines in a farm experience a different wind distribution over the rotor due to the farm boundary-layer interaction. We demonstrate this for fully developed wind-farm boundary layers with aligned turbine arrangements at different spacings (5D, 7D, 9D). Further we also compare calibration curves obtained from full farm simulations with calibration curves that can be obtained at a much lower cost using a minimal flow unit.

Optimal control of energy extraction in LES of large wind farms

NASA Astrophysics Data System (ADS)

Meyers, Johan; Goit, Jay; Munters, Wim

2014-11-01

We investigate the use of optimal control combined with Large-Eddy Simulations (LES) of wind-farm boundary layer interaction for the increase of total energy extraction in very large ``infinite'' wind farms and in finite farms. We consider the individual wind turbines as flow actuators, whose energy extraction can be dynamically regulated in time so as to optimally influence the turbulent flow field, maximizing the wind farm power. For the simulation of wind-farm boundary layers we use large-eddy simulations in combination with an actuator-disk representation of wind turbines. Simulations are performed in our in-house pseudo-spectral code SP-Wind. For the optimal control study, we consider the dynamic control of turbine-thrust coefficients in the actuator-disk model. They represent the effect of turbine blades that can actively pitch in time, changing the lift- and drag coefficients of the turbine blades. In a first infinite wind-farm case, we find that farm power is increases by approximately 16% over one hour of operation. This comes at the cost of a deceleration of the outer layer of the boundary layer. A detailed analysis of energy balances is presented, and a comparison is made between infinite and finite farm cases, for which boundary layer entrainment plays an import role. The authors acknowledge support from the European Research Council (FP7-Ideas, Grant No. 306471). Simulations were performed on the computing infrastructure of the VSC Flemish Supercomputer Center, funded by the Hercules Foundation and the Flemish Govern.

Research on large-scale wind farm modeling

NASA Astrophysics Data System (ADS)

Ma, Longfei; Zhang, Baoqun; Gong, Cheng; Jiao, Ran; Shi, Rui; Chi, Zhongjun; Ding, Yifeng

2017-01-01

Due to intermittent and adulatory properties of wind energy, when large-scale wind farm connected to the grid, it will have much impact on the power system, which is different from traditional power plants. Therefore it is necessary to establish an effective wind farm model to simulate and analyze the influence wind farms have on the grid as well as the transient characteristics of the wind turbines when the grid is at fault. However we must first establish an effective WTGs model. As the doubly-fed VSCF wind turbine has become the mainstream wind turbine model currently, this article first investigates the research progress of doubly-fed VSCF wind turbine, and then describes the detailed building process of the model. After that investigating the common wind farm modeling methods and pointing out the problems encountered. As WAMS is widely used in the power system, which makes online parameter identification of the wind farm model based on off-output characteristics of wind farm be possible, with a focus on interpretation of the new idea of identification-based modeling of large wind farms, which can be realized by two concrete methods.

Wake characteristics of wind turbines in utility-scale wind farms

NASA Astrophysics Data System (ADS)

Yang, Xiaolei; Foti, Daniel; Sotiropoulos, Fotis

2017-11-01

The dynamics of turbine wakes is affected by turbine operating conditions, ambient atmospheric turbulent flows, and wakes from upwind turbines. Investigations of the wake from a single turbine have been extensively carried out in the literature. Studies on the wake dynamics in utility-scale wind farms are relatively limited. In this work, we employ large-eddy simulation with an actuator surface or actuator line model for turbine blades to investigate the wake dynamics in utility-scale wind farms. Simulations of three wind farms, i.e., the Horns Rev wind farm in Denmark, Pleasant Valley wind farm in Minnesota, and the Vantage wind farm in Washington are carried out. The computed power shows a good agreement with measurements. Analysis of the wake dynamics in the three wind farms is underway and will be presented in the conference. This work was support by Xcel Energy (RD4-13). The computational resources were provided by National Renewable Energy Laboratory.

Numerical investigation of interactions between marine atmospheric boundary layer and offshore wind farm

NASA Astrophysics Data System (ADS)

Lyu, Pin; Chen, Wenli; Li, Hui; Shen, Lian

2017-11-01

In recent studies, Yang, Meneveau & Shen (Physics of Fluids, 2014; Renewable Energy, 2014) developed a hybrid numerical framework for simulation of offshore wind farm. The framework consists of simulation of nonlinear surface waves using a high-order spectral method, large-eddy simulation of wind turbulence on a wave-surface-fitted curvilinear grid, and an actuator disk model for wind turbines. In the present study, several more precise wind turbine models, including the actuator line model, actuator disk model with rotation, and nacelle model, are introduced into the computation. Besides offshore wind turbines on fixed piles, the new computational framework has the capability to investigate the interaction among wind, waves, and floating wind turbines. In this study, onshore, offshore fixed pile, and offshore floating wind farms are compared in terms of flow field statistics and wind turbine power extraction rate. The authors gratefully acknowledge financial support from China Scholarship Council (No. 201606120186) and the Institute on the Environment of University of Minnesota.

Understanding African Swine Fever infection dynamics in Sardinia using a spatially explicit transmission model in domestic pig farms.

PubMed

Mur, L; Sánchez-Vizcaíno, J M; Fernández-Carrión, E; Jurado, C; Rolesu, S; Feliziani, F; Laddomada, A; Martínez-López, B

2018-02-01

African swine fever virus (ASFV) has been endemic in Sardinia since 1978, resulting in severe losses for local pig producers and creating important problems for the island's veterinary authorities. This study used a spatially explicit stochastic transmission model followed by two regression models to investigate the dynamics of ASFV spread amongst domestic pig farms, to identify geographic areas at highest risk and determine the role of different susceptible pig populations (registered domestic pigs, non-registered domestic pigs [brado] and wild boar) in ASF occurrence. We simulated transmission within and between farms using an adapted version of the previously described model known as Be-FAST. Results from the model revealed a generally low diffusion of ASF in Sardinia, with only 24% of the simulations resulting in disease spread, and for each simulated outbreak on average only four farms and 66 pigs were affected. Overall, local spread (indirect transmission between farms within a 2 km radius through fomites) was the most common route of transmission, being responsible for 98.6% of secondary cases. The risk of ASF occurrence for each domestic pig farm was estimated from the spread model results and integrated in two regression models together with available data for brado and wild boar populations. There was a significant association between the density of all three populations (domestic pigs, brado, and wild boar) and ASF occurrence in Sardinia. The most significant risk factors were the high densities of brado (OR = 2.2) and wild boar (OR = 2.1). The results of both analyses demonstrated that ASF epidemiology and infection dynamics in Sardinia create a complex and multifactorial disease situation, where all susceptible populations play an important role. To stop ASF transmission in Sardinia, three main factors (improving biosecurity on domestic pig farms, eliminating brado practices and better management of wild boars) need to be addressed. © 2017 Blackwell Verlag GmbH.

Farm Simulation: a tool for evaluating the mitigation of greenhouse gas emissions and the adaptation of dairy production to climate change

USDA-ARS?s Scientific Manuscript database

Farms both produce greenhouse gas emissions that drive human-induced climate change and are impacted by that climate change. Whole farm and global climate models provide useful tools for studying the benefits and costs of greenhouse gas mitigation and the adaptation of farms to changing climate. The...

Regional climate model simulations indicate limited climatic impacts by operational and planned European wind farms.

PubMed

Vautard, Robert; Thais, Françoise; Tobin, Isabelle; Bréon, François-Marie; Devezeaux de Lavergne, Jean-Guy; Colette, Augustin; Yiou, Pascal; Ruti, Paolo Michele

2014-01-01

The rapid development of wind energy has raised concerns about environmental impacts. Temperature changes are found in the vicinity of wind farms and previous simulations have suggested that large-scale wind farms could alter regional climate. However, assessments of the effects of realistic wind power development scenarios at the scale of a continent are missing. Here we simulate the impacts of current and near-future wind energy production according to European Union energy and climate policies. We use a regional climate model describing the interactions between turbines and the atmosphere, and find limited impacts. A statistically significant signal is only found in winter, with changes within ±0.3 °C and within 0-5% for precipitation. It results from the combination of local wind farm effects and changes due to a weak, but robust, anticyclonic-induced circulation over Europe. However, the impacts remain much weaker than the natural climate interannual variability and changes expected from greenhouse gas emissions.

Modeling large wind farms in conventionally neutral atmospheric boundary layers under varying initial conditions

NASA Astrophysics Data System (ADS)

Allaerts, Dries; Meyers, Johan

2014-05-01

Atmospheric boundary layers (ABL) are frequently capped by an inversion layer limiting the entrainment rate and boundary layer growth. Commonly used analytical models state that the entrainment rate is inversely proportional to the inversion strength. The height of the inversion turns out to be a second important parameter. Conventionally neutral atmospheric boundary layers (CNBL) are ABLs with zero surface heat flux developing against a stratified free atmosphere. In this regime the inversion-filling process is merely driven by the downward heat flux at the inversion base. As a result, CNBLs are strongly dependent on the heating history of the boundary layer and strong inversions will fail to erode during the course of the day. In case of large wind farms, the power output of the farm inside a CNBL will depend on the height and strength of the inversion above the boundary layer. On the other hand, increased turbulence levels induced by wind farms may partially undermine the rigid lid effect of the capping inversion, enhance vertical entrainment of air into the farm, and increase boundary layer growth. A suite of large eddy simulations (LES) is performed to investigate the effect of the capping inversion on the conventionally neutral atmospheric boundary layer and on the wind farm performance under varying initial conditions. For these simulations our in-house pseudo-spectral LES code SP-Wind is used. The wind turbines are modelled using a non-rotating actuator disk method. In the absence of wind farms, we find that a decrease in inversion strength corresponds to a decrease in the geostrophic angle and an increase in entrainment rate and geostrophic drag. Placing the initial inversion base at higher altitudes further reduces the effect of the capping inversion on the boundary layer. The inversion can be fully neglected once it is situated above the equilibrium height that a truly neutral boundary layer would attain under the same external conditions such as geostrophic wind speed and surface roughness. Wind farm simulations show the expected increase in boundary layer height and growth rate with respect to the case without wind farms. Raising the initial strength of the capping inversion in these simulations dampens the turbulent growth of the boundary layer above the farm, decreasing the farms energy extraction. The authors acknowledge support from the European Research Council (FP7-Ideas, grant no. 306471). Simulations were performed on the computing infrastructure of the VSC Flemish Supercomputer Center, funded by the Hercules Foundation and the Flemish Government.

The consideration of atmospheric stability within wind farm AEP calculations

NASA Astrophysics Data System (ADS)

Schmidt, Jonas; Chang, Chi-Yao; Dörenkämper, Martin; Salimi, Milad; Teichmann, Tim; Stoevesandt, Bernhard

2016-09-01

The annual energy production of an existing wind farm including thermal stratification is calculated with two different methods and compared to the average of three years of SCADA data. The first method is based on steady state computational fluid dynamics simulations and the assumption of Reynolds-similarity at hub height. The second method is a wake modelling calculation, where a new stratification transformation model was imposed on the Jensen an Ainslie wake models. The inflow states for both approaches were obtained from one year WRF simulation data of the site. Although all models underestimate the mean wind speed and wake effects, the results from the phenomenological wake transformation are compatible with high-fidelity simulation results.

Wind farm density and harvested power in very large wind farms: A low-order model

NASA Astrophysics Data System (ADS)

Cortina, G.; Sharma, V.; Calaf, M.

2017-07-01

In this work we create new understanding of wind turbine wakes recovery process as a function of wind farm density using large-eddy simulations of an atmospheric boundary layer diurnal cycle. Simulations are forced with a constant geostrophic wind and a time varying surface temperature extracted from a selected period of the Cooperative Atmospheric Surface Exchange Study field experiment. Wind turbines are represented using the actuator disk model with rotation and yaw alignment. A control volume analysis around each turbine has been used to evaluate wind turbine wake recovery and corresponding harvested power. Results confirm the existence of two dominant recovery mechanisms, advection and flux of mean kinetic energy, which are modulated by the background thermal stratification. For the low-density arrangements advection dominates, while for the highly loaded wind farms the mean kinetic energy recovers through fluxes of mean kinetic energy. For those cases in between, a smooth balance of both mechanisms exists. From the results, a low-order model for the wind farms' harvested power as a function of thermal stratification and wind farm density has been developed, which has the potential to be used as an order-of-magnitude assessment tool.

Understanding the Impacts of Soil, Climate, and Farming Practices on Soil Organic Carbon Sequestration: A Simulation Study in Australia

PubMed Central

Godde, Cécile M.; Thorburn, Peter J.; Biggs, Jody S.; Meier, Elizabeth A.

2016-01-01

Carbon sequestration in agricultural soils has the capacity to mitigate greenhouse gas emissions, as well as to improve soil biological, physical, and chemical properties. The review of literature pertaining to soil organic carbon (SOC) dynamics within Australian grain farming systems does not enable us to conclude on the best farming practices to increase or maintain SOC for a specific combination of soil and climate. This study aimed to further explore the complex interactions of soil, climate, and farming practices on SOC. We undertook a modeling study with the Agricultural Production Systems sIMulator modeling framework, by combining contrasting Australian soils, climates, and farming practices (crop rotations, and management within rotations, such as fertilization, tillage, and residue management) in a factorial design. This design resulted in the transposition of contrasting soils and climates in our simulations, giving soil–climate combinations that do not occur in the study area to help provide insights into the importance of the climate constraints on SOC. We statistically analyzed the model’s outputs to determinate the relative contributions of soil parameters, climate, and farming practices on SOC. The initial SOC content had the largest impact on the value of SOC, followed by the climate and the fertilization practices. These factors explained 66, 18, and 15% of SOC variations, respectively, after 80 years of constant farming practices in the simulation. Tillage and stubble management had the lowest impacts on SOC. This study highlighted the possible negative impact on SOC of a chickpea phase in a wheat–chickpea rotation and the potential positive impact of a cover crop in a sub-tropical climate (QLD, Australia) on SOC. It also showed the complexities in managing to achieve increased SOC, while simultaneously aiming to minimize nitrous oxide (N2O) emissions and nitrate leaching in farming systems. The transposition of contrasting soils and climates in our simulations revealed the importance of the climate constraints on SOC. PMID:27242862

e-Dairy: a dynamic and stochastic whole-farm model that predicts biophysical and economic performance of grazing dairy systems.

PubMed

Baudracco, J; Lopez-Villalobos, N; Holmes, C W; Comeron, E A; Macdonald, K A; Barry, T N

2013-05-01

A whole-farm, stochastic and dynamic simulation model was developed to predict biophysical and economic performance of grazing dairy systems. Several whole-farm models simulate grazing dairy systems, but most of them work at a herd level. This model, named e-Dairy, differs from the few models that work at an animal level, because it allows stochastic behaviour of the genetic merit of individual cows for several traits, namely, yields of milk, fat and protein, live weight (LW) and body condition score (BCS) within a whole-farm model. This model accounts for genetic differences between cows, is sensitive to genotype × environment interactions at an animal level and allows pasture growth, milk and supplements price to behave stochastically. The model includes an energy-based animal module that predicts intake at grazing, mammary gland functioning and body lipid change. This whole-farm model simulates a 365-day period for individual cows within a herd, with cow parameters randomly generated on the basis of the mean parameter values, defined as input and variance and co-variances from experimental data sets. The main inputs of e-Dairy are farm area, use of land, type of pasture, type of crops, monthly pasture growth rate, supplements offered, nutritional quality of feeds, herd description including herd size, age structure, calving pattern, BCS and LW at calving, probabilities of pregnancy, average genetic merit and economic values for items of income and costs. The model allows to set management policies to define: dry-off cows (ceasing of lactation), target pre- and post-grazing herbage mass and feed supplementation. The main outputs are herbage dry matter intake, annual pasture utilisation, milk yield, changes in BCS and LW, economic farm profit and return on assets. The model showed satisfactory accuracy of prediction when validated against two data sets from farmlet system experiments. Relative prediction errors were <10% for all variables, and concordance correlation coefficients over 0.80 for annual pasture utilisation, yields of milk and milk solids (MS; fat plus protein), and of 0.69 and 0.48 for LW and BCS, respectively. A simulation of two contrasting dairy systems is presented to show the practical use of the model. The model can be used to explore the effects of feeding level and genetic merit and their interactions for grazing dairy systems, evaluating the trade-offs between profit and the associated risk.

Monitoring, modeling and mitigating impacts of wind farms on local meteorology

NASA Astrophysics Data System (ADS)

Baidya Roy, Somnath; Traiteur, Justin; Kelley, Neil

2010-05-01

Wind power is one of the fastest growing sources of energy. Most of the growth is in the industrial sector comprising of large utility-scale wind farms. Recent modeling studies have suggested that such wind farms can significantly affect local and regional weather and climate. In this work, we present observational evidence of the impact of wind farms on near-surface air temperatures. Data from perhaps the only meteorological field campaign in an operational wind farm shows that downwind temperatures are lower during the daytime and higher at night compared to the upwind environment. Corresponding radiosonde profiles at the nearby Edwards Air Force Base WMO meteorological station show that the diurnal environment is unstable while the nocturnal environment is stable during the field campaign. This behavior is consistent with the hypothesis proposed by Baidya Roy et al. (JGR 2004) that states that turbulence generated in the wake of rotors enhance vertical mixing leading to a warming/cooling under positive/negative potential temperature lapse rates. We conducted a set of 306 simulations with the Regional Atmospheric Modeling System (RAMS) to test if regional climate models can capture the thermal effects of wind farms. We represented wind turbines with a subgrid parameterization that assumes rotors to be sinks of momentum and sources of turbulence. The simulated wind farms consistently generated a localized warming/cooling under positive/negative lapse rates as hypothesized. We found that these impacts are inversely correlated with background atmospheric boundary layer turbulence. Thus, if the background turbulence is high due to natural processes, the effects of additional turbulence generated by wind turbine rotors are likely to be small. We propose the following strategies to minimize impacts of wind farms: • Engineering solution: design rotors that generate less turbulence in their wakes. Sensitivity simulations show that these turbines also increase the productivity of wind farms and reduce damages to downwind rotors. • Siting solution: develop wind farms in regions where ABL turbulence is naturally high. Since, turbulence data is not widely recorded, we use surface KE dissipation rate as a proxy for ABL turbulence. Indeed, in our simulations, these 2 parameters are strongly positively correlated (P<0.99). Using the JRA25 dataset, comprising of 25-year long 6-hourly global meteorological data, we identify such regions in the world. These regions that include the Midwest and Great Plains as well as large parts of northern Europe and western China are appropriate sites for low-impact wind farms.

Validation of Individual-Based Markov-Like Stochastic Process Model of Insect Behavior and a "Virtual Farm" Concept for Enhancement of Site-Specific IPM.

PubMed

Lux, Slawomir A; Wnuk, Andrzej; Vogt, Heidrun; Belien, Tim; Spornberger, Andreas; Studnicki, Marcin

2016-01-01

The paper reports application of a Markov-like stochastic process agent-based model and a "virtual farm" concept for enhancement of site-specific Integrated Pest Management. Conceptually, the model represents a "bottom-up ethological" approach and emulates behavior of the "primary IPM actors"-large cohorts of individual insects-within seasonally changing mosaics of spatiotemporally complex faming landscape, under the challenge of the local IPM actions. Algorithms of the proprietary PESTonFARM model were adjusted to reflect behavior and ecology of R. cerasi. Model parametrization was based on compiled published information about R. cerasi and the results of auxiliary on-farm experiments. The experiments were conducted on sweet cherry farms located in Austria, Germany, and Belgium. For each farm, a customized model-module was prepared, reflecting its spatiotemporal features. Historical data about pest monitoring, IPM treatments and fruit infestation were used to specify the model assumptions and calibrate it further. Finally, for each of the farms, virtual IPM experiments were simulated and the model-generated results were compared with the results of the real experiments conducted on the same farms. Implications of the findings for broader applicability of the model and the "virtual farm" approach-were discussed.

The Farm Process Version 2 (FMP2) for MODFLOW-2005 - Modifications and Upgrades to FMP1

USGS Publications Warehouse

Schmid, Wolfgang; Hanson, R.T.

2009-01-01

The ability to dynamically simulate the integrated supply-and-demand components of irrigated agricultural is needed to thoroughly understand the interrelation between surface water and groundwater flow in areas where the water-use by vegetation is an important component of the water budget. To meet this need, the computer program Farm Process (FMP1) was updated and refined for use with the U.S. Geological Survey's MODFLOW-2005 groundwater-flow model, and is referred to as MF2005-FMP2. The updated program allows the simulation, analysis, and management of nearly all components of human and natural water use. MF2005-FMP2 represents a complete hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for water consumption of irrigated agriculture, but also of urban use, and of natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply-constrained conditions. From large- to small-scale settings, the MF2005-FMP2 has the unique set of capabilities to simulate and analyze historical, present, and future conditions. MF2005-FMP2 facilitates the analysis of agricultural water use where little data is available for pumpage, land use, or agricultural information. The features presented in this new version of FMP2 along with the linkages to the Streamflow Routing (SFR), Multi-Node Well (MNW), and Unsaturated Zone Flow (UZF) Packages prevents mass loss to an open system and helps to account for 'all of the water everywhere and all of the time'. The first version, FMP1 for MODFLOW-2000, is limited to (a) transpiration uptake from unsaturated root zones, (b) on-farm efficiency defined solely by farm and not by crop type, (c) a simulation of water use and returnflows related only to irrigated agriculture and not also to non-irrigated vegetation, (d) a definition of consumptive use as potential crop evapotranspiration, (e) percolation being instantly recharged to the uppermost active aquifer, (f) automatic routing of returnflow from runoff either to reaches of tributary stream segments adjacent to a farm or to one reach nearest to the farm's lowest elevation, (g) farm-well pumping from cell locations regardless of whether an irrigation requirement from these cells exists or not, and (h) specified non-routed water transfers from an undefined source outside the model domain. All of these limitations are overcome in MF2005-FMP2. The new features include (a) simulation of transpiration uptake from variably saturated, fully saturated, or ponded root zones (for example, for crops like rice or riparian vegetation), (b) definition of on-farm efficiency not only by farm but also by crop, (c) simulation of water use and returnflow from non-irrigated vegetation (for example, rain-fed agriculture or native vegetation), (d) use of crop coefficients and reference evapotranspiration, (e) simulation of the delay between percolation from farms through the unsaturated zone and recharge into the uppermost active aquifer by linking FMP2 to the UZF Package, (f) an option to manually control the routing of returnflow from farm runoff to streams, (g) an option to limit pumping to wells located only in cells where an irrigation requirement exists, and (h) simulation of water transfers to farms from a series of well fields (for example, recovery well field of an aquifer-storage-and-recovery system, ASR). In addition to the output of an economic budget for each farm between irrigation demand and supply ('Farm Demand and Supply Budget' in FMP1), a new output option called 'Farm Budget' was created for FMP2, which allows the user to track all physical flows into and out of a water accounting unit at all times. Such a unit can represent individual farms, farming districts, natural areas, or urban areas. The example model demonstrates the application of MF2005-FMP2 with delayed recharge through an unsaturated zone, rejected infiltration in a riparian area, changes in de

Coupling dairy manure storage with injection to improve nitrogen management: whole-farm simulation using the integrated farm system Model

USDA-ARS?s Scientific Manuscript database

Application of livestock manure to farm soils represents a priority nutrient management concern in the Chesapeake Bay Watershed. Historically strong emphasis has been placed on adding manure storage to dairy operations, and, there has been recognition that manure application methods can be improved....

The System Dynamics Model for Development of Organic Agriculture

NASA Astrophysics Data System (ADS)

Rozman, Črtomir; Škraba, Andrej; Kljajić, Miroljub; Pažek, Karmen; Bavec, Martina; Bavec, Franci

2008-10-01

Organic agriculture is the highest environmentally valuable agricultural system, and has strategic importance at national level that goes beyond the interests of agricultural sector. In this paper we address development of organic farming simulation model based on a system dynamics methodology (SD). The system incorporates relevant variables, which affect the development of the organic farming. The group decision support system (GDSS) was used in order to identify most relevant variables for construction of causal loop diagram and further model development. The model seeks answers to strategic questions related to the level of organically utilized area, levels of production and crop selection in a long term dynamic context and will be used for simulation of different policy scenarios for organic farming and their impact on economic and environmental parameters of organic production at an aggregate level.

Simulation and study of power quality issues in a fixed speed wind farm substation.

PubMed

Magesh, T; Chellamuthu, C

2015-01-01

Power quality issues associated with the fixed speed wind farm substation located at Coimbatore district are investigated as the wind generators are tripping frequently. The investigations are carried out using two power quality analyzers, Fluke 435 and Dranetz PX5.8, with one of them connected at group control breaker of the 110 kV feeder and the other at the selected 0.69 kV generator busbar during the period of maximum power generation. From the analysis of the recorded data it is found that sag, swell, and transients are the major events which are responsible for the tripping of the generators. In the present study, simulation models for wind, turbine, shaft, pitch mechanism, induction generator, and grid are developed using DIgSILENT. Using the turbine characteristics, a two-dimensional lookup table is designed to generate a reference pitch angle necessary to simulate the power curve of the passive stall controlled wind turbine. Various scenarios and their effects on the performance of the wind farm are studied and validated with the recorded data and waveforms. The simulation model will be useful for the designers for planning and development of the wind farm before implementation.

Simulation and Study of Power Quality Issues in a Fixed Speed Wind Farm Substation

PubMed Central

Magesh, T.; Chellamuthu, C.

2015-01-01

Power quality issues associated with the fixed speed wind farm substation located at Coimbatore district are investigated as the wind generators are tripping frequently. The investigations are carried out using two power quality analyzers, Fluke 435 and Dranetz PX5.8, with one of them connected at group control breaker of the 110 kV feeder and the other at the selected 0.69 kV generator busbar during the period of maximum power generation. From the analysis of the recorded data it is found that sag, swell, and transients are the major events which are responsible for the tripping of the generators. In the present study, simulation models for wind, turbine, shaft, pitch mechanism, induction generator, and grid are developed using DIgSILENT. Using the turbine characteristics, a two-dimensional lookup table is designed to generate a reference pitch angle necessary to simulate the power curve of the passive stall controlled wind turbine. Various scenarios and their effects on the performance of the wind farm are studied and validated with the recorded data and waveforms. The simulation model will be useful for the designers for planning and development of the wind farm before implementation. PMID:25950016

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations

PubMed Central

Antle, John M.; Stoorvogel, Jetse J.; Valdivia, Roberto O.

2014-01-01

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models. PMID:24535388

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations.

PubMed

Antle, John M; Stoorvogel, Jetse J; Valdivia, Roberto O

2014-04-05

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models.

SD simulation study on degraded farmland policy on farming-pastoral area under the constrains of water resources-Taking Tongliao City of Inner Mongolia as example

NASA Astrophysics Data System (ADS)

Xu, D. P.; Zhao, B.; Li, T. S.; Zhu, J. W.; Yu, M. M.

2017-08-01

Water resources are the primary factor in restricting the sustainable development of farming-pastoral regions. To support the sustainable development of water resources, whether or not the land uses patterns of farming-pastoral areas is a reasonably important issue. This paper takes Tongliao city as example for the purpose of sustainably developing the farming-pastoral area in the north. Several scientific preductions and evaluations were conducted to study the farming-pastoral landuse pattern, which is the key problem that effects sustainable development of farming-pastoral areas. The paper then proposes that 1:7 landuse pattern is suitable for the sustainable development of farming-pastotal area. Based on the analysis of the research findings on sustainable development of farming-pastoral area, the paper established a suitability evaluation indicators system of degraded farmland policies in Tongliao city, and used an Analytical Hierarchy Process (AHP) method to determine the weight to run system dynamic (SD) model. The simulation results were then obtained on social economic ecological development in Tongliao city under different degraded farmland policies, and used the comprehensive evaluation model to optimize the results. It is concluded that stabilizing the policy of degraded farmland policy is the preferential policy in Tongliao, which provides useful theoretical research for the sustainable development of farming-pastoral area.

Environmental and economic comparisons of manure application methods in farming systems.

PubMed

Rotz, C A; Kleinman, P J A; Dell, C J; Veith, T L; Beegle, D B

2011-01-01

Alternative methods for applying livestock manure to no-till soils involve environmental and economic trade-offs. A process-level farm simulation model (Integrated Farm System Model) was used to evaluate methods for applying liquid dairy (Bos taurus L.) and swine (Sus scrofa L.) manure, including no application, broadcast spreading with and without incorporation by tillage, band application with soil aeration, and shallow disk injection. The model predicted ammonia emissions, nitrate leaching, and phosphorus (P) runoff losses similar to those measured over 4 yr of field trials. Each application method was simulated over 25 yr of weather on three Pennsylvania farms. On a swine and cow-calf beef operation under grass production, shallow disk injection increased profit by $340 yr(-1) while reducing ammonia nitrogen and soluble P losses by 48 and 70%, respectively. On a corn (Zea mays L.)-and-grass-based grazing dairy farm, shallow disk injection reduced ammonia loss by 21% and soluble P loss by 76% with little impact on farm profit. Incorporation by tillage and band application with aeration provided less environmental benefit with a net decrease in farm profit. On a large corn-and-alfalfa (Medicago sativa L.)-based dairy farm where manure nutrients were available in excess of crop needs, incorporation methods were not economically beneficial, but they provided environmental benefits with relatively low annual net costs ($13 to $18 cow). In all farming systems, shallow disk injection provided the greatest environmental benefit at the least cost or greatest profit for the producer. With these results, producers are better informed when selecting manure application equipment.

Simulating the evolution of glyphosate resistance in grains farming in northern Australia.

PubMed

Thornby, David F; Walker, Steve R

2009-09-01

The evolution of resistance to herbicides is a substantial problem in contemporary agriculture. Solutions to this problem generally consist of the use of practices to control the resistant population once it evolves, and/or to institute preventative measures before populations become resistant. Herbicide resistance evolves in populations over years or decades, so predicting the effectiveness of preventative strategies in particular relies on computational modelling approaches. While models of herbicide resistance already exist, none deals with the complex regional variability in the northern Australian sub-tropical grains farming region. For this reason, a new computer model was developed. The model consists of an age- and stage-structured population model of weeds, with an existing crop model used to simulate plant growth and competition, and extensions to the crop model added to simulate seed bank ecology and population genetics factors. Using awnless barnyard grass (Echinochloa colona) as a test case, the model was used to investigate the likely rate of evolution under conditions expected to produce high selection pressure. Simulating continuous summer fallows with glyphosate used as the only means of weed control resulted in predicted resistant weed populations after approx. 15 years. Validation of the model against the paddock history for the first real-world glyphosate-resistant awnless barnyard grass population shows that the model predicted resistance evolution to within a few years of the real situation. This validation work shows that empirical validation of herbicide resistance models is problematic. However, the model simulates the complexities of sub-tropical grains farming in Australia well, and can be used to investigate, generate and improve glyphosate resistance prevention strategies.

Dispersive stresses in wind farms

NASA Astrophysics Data System (ADS)

Segalini, Antonio; Braunbehrens, Robert; Hyvarinen, Ann

2017-11-01

One of the most famous models of wind farms is provided by the assumption that the farm can be approximated as a horizontally-homogeneous forest canopy with vertically-varying force intensity. By means of this approximation, the flow-motion equations become drastically simpler, as many of the three-dimensional effects are gone. However, the application of the horizontal average operator to the RANS equations leads to the appearance of new transport terms (called dispersive stresses) originating from the horizontal (small-scale) variation of the mean velocity field. Since these terms are related to the individual turbine signature, they are expected to vanish outside the roughness sublayer, providing a definition for the latter. In the present work, an assessment of the dispersive stresses is performed by means of a wake-model approach and through the linearised code ORFEUS developed at KTH. Both approaches are very fast and enable the characterization of a large number of wind-farm layouts. The dispersive stress tensor and its effect on the turbulence closure models are investigated, providing guidelines for those simulations where it is impossible to resolve the farm at a turbine scale due to grid requirements (as, for instance, mesoscale simulations).

Agroforestry versus farm mosaic systems - Comparing land-use efficiency, economic returns and risks under climate change effects.

PubMed

Paul, Carola; Weber, Michael; Knoke, Thomas

2017-06-01

Increasing land-use conflicts call for the development of land-use systems that reconcile agricultural production with the provisioning of multiple ecosystem services, including climate change mitigation. Agroforestry has been suggested as a global solution to increase land-use efficiency, while reducing environmental impacts and economic risks for farmers. Past research has often focused on comparing tree-crop combinations with agricultural monocultures, but agroforestry has seldom been systematically compared to other forms of land-use diversification, including a farm mosaic. This form of diversification mixes separate parcels of different land uses within the farm. The objective of this study was to develop a modelling approach to compare the performance of the agroforestry and farm mosaic diversification strategies, accounting for tree-crop interaction effects and economic and climate uncertainty. For this purpose, Modern Portfolio Theory and risk simulation were coupled with the process-based biophysical simulation model WaNuLCAS 4.0. For an example application, we used data from a field trial in Panama. The results show that the simulated agroforestry systems (Taungya, alley cropping and border planting) could outperform a farm mosaic approach in terms of cumulative production and return. Considering market and climate uncertainty, agroforestry showed an up to 21% higher economic return at the same risk level (i.e. standard deviation of economic returns). Farm compositions with large shares of land allocated to maize cultivation were also more severely affected by an increasing drought frequency in terms of both risks and returns. Our study demonstrates that agroforestry can be an economically efficient diversification strategy, but only if the design allows for economies of scope, beneficial interactions between trees and crops and higher income diversification compared to a farm mosaic. The modelling approach can make an important contribution to support land-use decisions at the farm level and reduce land-use conflicts at the landscape level. Copyright © 2017 Elsevier B.V. All rights reserved.

Analysis of economic benefit of wind power based on system dynamics

NASA Astrophysics Data System (ADS)

Zhao, Weibo; Han, Yaru; Niu, Dongxiao

2018-04-01

The scale of renewable power generation, such as wind power, has increased gradually in recent years. Considering that the economic benefits of wind farms are affected by many dynamic factors. The dynamic simulation model of wind power economic benefit system is established based on the system dynamics method. By comparing the economic benefits of wind farms under different setting scenarios through this model, the impact of different factors on the economic benefits of wind farms can be reflected.

SIMULATION MODEL FOR WATERSHED MANAGEMENT PLANNING. VOLUME 2. MODEL USER MANUAL

EPA Science Inventory

This report provides a user manual for the hydrologic, nonpoint source pollution simulation of the generalized planning model for evaluating forest and farming management alternatives. The manual contains an explanation of application of specific code and indicates changes that s...

NREL and Sandia National Laboratories to Sharpen Wind Farm Turbine Controls

Science.gov Websites

| News | NREL NREL and Sandia National Laboratories to Sharpen Wind Farm Turbine Controls NREL and Sandia National Laboratories to Sharpen Wind Farm Turbine Controls April 1, 2016 Researchers at wind turbine modeling. The NREL controls team have been evaluating their control theory in simulations

Using wind tunnels to predict bird mortality in wind farms: the case of griffon vultures.

PubMed

de Lucas, Manuela; Ferrer, Miguel; Janss, Guyonne F E

2012-01-01

Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed). We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality.

Simulating the evolution of glyphosate resistance in grains farming in northern Australia

PubMed Central

Thornby, David F.; Walker, Steve R.

2009-01-01

Background and Aims The evolution of resistance to herbicides is a substantial problem in contemporary agriculture. Solutions to this problem generally consist of the use of practices to control the resistant population once it evolves, and/or to institute preventative measures before populations become resistant. Herbicide resistance evolves in populations over years or decades, so predicting the effectiveness of preventative strategies in particular relies on computational modelling approaches. While models of herbicide resistance already exist, none deals with the complex regional variability in the northern Australian sub-tropical grains farming region. For this reason, a new computer model was developed. Methods The model consists of an age- and stage-structured population model of weeds, with an existing crop model used to simulate plant growth and competition, and extensions to the crop model added to simulate seed bank ecology and population genetics factors. Using awnless barnyard grass (Echinochloa colona) as a test case, the model was used to investigate the likely rate of evolution under conditions expected to produce high selection pressure. Key Results Simulating continuous summer fallows with glyphosate used as the only means of weed control resulted in predicted resistant weed populations after approx. 15 years. Validation of the model against the paddock history for the first real-world glyphosate-resistant awnless barnyard grass population shows that the model predicted resistance evolution to within a few years of the real situation. Conclusions This validation work shows that empirical validation of herbicide resistance models is problematic. However, the model simulates the complexities of sub-tropical grains farming in Australia well, and can be used to investigate, generate and improve glyphosate resistance prevention strategies. PMID:19567415

Impacts of Farmers' Knowledge Increase on Farm Profit and Watershed Water Quality

NASA Astrophysics Data System (ADS)

Ding, D.; Bennett, D. A.

2013-12-01

This study explores the impact that an increase in real-time data might have on farmers' nitrogen management, on-farm profit, and watershed water quality in the Midwestern US. In this study, an agent-based model (ABM) is used to simulate farmers' decisions about nitrogen application rate and timing in corn fields. SWAT (soil-water assessment tool) is used to generate a database that characterizes the response of corn yields to nitrogen fertilizer application and the dynamics of nitrogen loss under different scenarios of rainfall events. The database simulates a scenario where farmers would receive real-time feedback about the fate and impact of nitrogen applied to their fields from in-situ sensors. The ability to transform these data into optimal actions is simulated at multiple levels for farmer agents. In a baseline scenario, the farmer agent is only aware of the yield potential of the land field and single values of N rates for achieving the yield potential and is not aware of N loss from farm fields. Knowledge increase is represented by greater accuracy in predicting rainfall events, and the increase of the number of discrete points in a field-specific quadratic curve that captures crop yield response to various levels of nitrogen perceived by farmer agents. In addition, agents perceive N loss from farm fields at increased temporal resolutions. Correspondingly, agents make adjustments to the rate of N application for crops and the timing of fertilizer application given the rainfall events predictions. Farmers' decisions simulated by the ABM are input into SWAT to model nitrogen concentration in impacted streams. Farm profit statistics and watershed-level nitrogen loads are compared among different scenarios of knowledge increase. The hypothesis that the increase of farmers' knowledge benefits both farm profits and watershed water quality is tested through the comparison.

Simulation of logistics to supply Corn Stover to the Ontario Power Generation (OPG) Plant in Lambton, Ontario

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khaleghi Hamedani, Hamid; Lau, Anthony K.; DeBruyn, Jake

The overall goal of this research is to investigate the logistics of agricultural biomass in Ontario, Canada using the Integrated Biomass Supply Analysis and Logistics Model (IBSAL). The supply of corn stover to the Ontario Power Generation (OPG) power plant in Lambton is simulated. This coal-fired power plant is currently not operating and there are no active plans by OPG to fuel it with biomass. Rather, this scenario is considered only to demonstrate the application of the IBSAL Model to this type of scenario. Here, five scenarios of delivering corn stover to the Lambton Generating Station (GS) power plant inmore » Lambton Ontario are modeled: (1) truck transport from field edge to OPG (base scenario); (2) farm to central storage located on the highway, then truck transport bales to OPG; (3) direct truck transport from farm (no-stacking) to OPG; (4) farm to a loading port on Lake Huron and from there on a barge to OPG; and (5) farm to a railhead and then to OPG by rail.« less

Simulation of logistics to supply Corn Stover to the Ontario Power Generation (OPG) Plant in Lambton, Ontario

DOE PAGES

Khaleghi Hamedani, Hamid; Lau, Anthony K.; DeBruyn, Jake; ...

2016-05-10

The overall goal of this research is to investigate the logistics of agricultural biomass in Ontario, Canada using the Integrated Biomass Supply Analysis and Logistics Model (IBSAL). The supply of corn stover to the Ontario Power Generation (OPG) power plant in Lambton is simulated. This coal-fired power plant is currently not operating and there are no active plans by OPG to fuel it with biomass. Rather, this scenario is considered only to demonstrate the application of the IBSAL Model to this type of scenario. Here, five scenarios of delivering corn stover to the Lambton Generating Station (GS) power plant inmore » Lambton Ontario are modeled: (1) truck transport from field edge to OPG (base scenario); (2) farm to central storage located on the highway, then truck transport bales to OPG; (3) direct truck transport from farm (no-stacking) to OPG; (4) farm to a loading port on Lake Huron and from there on a barge to OPG; and (5) farm to a railhead and then to OPG by rail.« less

Simulating effects of a wind-turbine array using LES and RANS: Simulating turbines using LES and RANS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vanderwende, Brian J.; Kosović, Branko; Lundquist, Julie K.

2016-08-27

Growth in wind power production has motivated investigation of wind-farm impacts on in situ flow fields and downstream interactions with agriculture and other wind farms. These impacts can be simulated with both large-eddy simulations (LES) and mesoscale wind-farm parameterizations (WFP). The Weather Research and Forecasting (WRF) model offers both approaches. We used the validated generalized actuator disk (GAD) parameterization in WRF-LES to assess WFP performance. A 12-turbine array was simulated using the GAD model and the WFP in WRF. We examined the performance of each scheme in both convective and stable conditions. The GAD model and WFP produced qualitatively similarmore » wind speed deficits and turbulent kinetic energy (TKE) production across the array in both stability regimes, though the magnitudes of velocity deficits and TKE production levels were underestimated and overestimated, respectively. While wake growth slowed in the latter half of the WFP array as expected, wakes did not approach steady state by the end of the array as simulated by the GAD model. A sensitivity test involving the deactivation of explicit TKE production by the WFP resulted in turbulence levels within the array well that were below those produced by the GAD in both stable and unstable conditions. Finally, the WFP overestimated downwind power production deficits in stable conditions because of the lack of wake stabilization in the latter half of the array.« less

Roguing with replacement in perennial crops: conditions for successful disease management.

PubMed

Sisterson, Mark S; Stenger, Drake C

2013-02-01

Replacement of diseased plants with healthy plants is commonly used to manage spread of plant pathogens in perennial cropping systems. This strategy has two potential benefits. First, removing infected plants may slow pathogen spread by eliminating inoculum sources. Second, replacing infected plants with uninfected plants may offset yield losses due to disease. The extent to which these benefits are realized depends on multiple factors. In this study, sensitivity analyses of two spatially explicit simulation models were used to evaluate how assumptions concerning implementation of a plant replacement program and pathogen spread interact to affect disease suppression. In conjunction, effects of assumptions concerning yield loss associated with disease and rates of plant maturity on yields were simultaneously evaluated. The first model was used to evaluate effects of plant replacement on pathogen spread and yield on a single farm, consisting of a perennial crop monoculture. The second model evaluated effects of plant replacement on pathogen spread and yield in a 100 farm crop growing region, with all farms maintaining a monoculture of the same perennial crop. Results indicated that efficient replacement of infected plants combined with a high degree of compliance among farms effectively slowed pathogen spread, resulting in replacement of few plants and high yields. In contrast, inefficient replacement of infected plants or limited compliance among farms failed to slow pathogen spread, resulting in replacement of large numbers of plants (on farms practicing replacement) with little yield benefit. Replacement of infected plants always increased yields relative to simulations without plant replacement provided that infected plants produced no useable yield. However, if infected plants produced useable yields, inefficient removal of infected plants resulted in lower yields relative to simulations without plant replacement for perennial crops with long maturation periods in some cases.

Analysis and model on space-time characteristics of wind power output based on the measured wind speed data

NASA Astrophysics Data System (ADS)

Shi, Wenhui; Feng, Changyou; Qu, Jixian; Zha, Hao; Ke, Dan

2018-02-01

Most of the existing studies on wind power output focus on the fluctuation of wind farms and the spatial self-complementary of wind power output time series was ignored. Therefore the existing probability models can’t reflect the features of power system incorporating wind farms. This paper analyzed the spatial self-complementary of wind power and proposed a probability model which can reflect temporal characteristics of wind power on seasonal and diurnal timescales based on sufficient measured data and improved clustering method. This model could provide important reference for power system simulation incorporating wind farms.

Model for wind resource analysis and for wind farm planning

NASA Astrophysics Data System (ADS)

Rozsavolgyi, K.

2008-12-01

Due to the ever increasing anthropogenic environmental pollution and the worldwide energy demand, the research and exploitation of environment-friendly renewable energy sources like wind, solar, geothermal, biomass become more and more important. During the last decade wind energy utilization has developed dynamically with big steps. Over just the past seven years, annual worldwide growth in installed wind capacity is near 30 %. Over 94 000 MW installed currently all over the world. Besides important economic incentives, the most extensive and most accurate scientific results are required in order to provide beneficial help for regional planning of wind farms to find appropriate sites for optimal exploitation of this renewable energy source. This research is on the spatial allocation of possible wind energy usage for wind farms. In order to carry this out a new model (CMPAM = Complex Multifactoral Polygenetic Adaptive Model) is being developed, which basically is a wind climate-oriented system, but other kind of factors are also considered. With this model those areas and terrains can be located where construction of large wind farms would be reasonable under the given conditions. This model consist of different sub- modules such as wind field modeling sub module (CMPAM/W) that is in high focus in this model development procedure. The wind field modeling core of CMPAM is mainly based on sGs (sequential Gaussian simulation) hence geostatistics, but atmospheric physics and GIS are used as well. For the application developed for the test area (Hungary) WAsP visualization results were used from 10 m height as input data. This data was geocorrected (GIS geometric correction) before it was used for further calculations. Using optimized variography and sequential Gaussian simulation, results were applied for the test area (Hungary) at different heights. Simulation results were produced and summarized for different heights. Furthermore an exponential regressive function describing the vertical wind profile was also established. The following altitudes were examined: 10 m, 30 m, 60 m, 80 m, 100 m, 120 m and 140 m. By the help of the complex analyses of CMPAM, where not just mere wind climatic and meteorological factors are considered, detailed results have been produced to 100 m height. Results at this altitude were analyzed and explained in a more detailed way because this altitude proved to be the first height that can ensure adequate wind speed for larger wind farms for wind energy exploitation in the test area. Keywords: wind site assessment, wind field modeling, complex modeling for planning of wind farm, sequential Gaussian simulation, GIS, wind profile

Assessing manure management strategies through small-plot research and whole-farm modeling

USGS Publications Warehouse

Garcia, A.M.; Veith, T.L.; Kleinman, P.J.A.; Rotz, C.A.; Saporito, L.S.

2008-01-01

Plot-scale experimentation can provide valuable insight into the effects of manure management practices on phosphorus (P) runoff, but whole-farm evaluation is needed for complete assessment of potential trade offs. Artificially-applied rainfall experimentation on small field plots and event-based and long-term simulation modeling were used to compare P loss in runoff related to two dairy manure application methods (surface application with and without incorporation by tillage) on contrasting Pennsylvania soils previously under no-till management. Results of single-event rainfall experiments indicated that average dissolved reactive P losses in runoff from manured plots decreased by up to 90% with manure incorporation while total P losses did not change significantly. Longer-term whole farm simulation modeling indicated that average dissolved reactive P losses would decrease by 8% with manure incorporation while total P losses would increase by 77% due to greater erosion from fields previously under no-till. Differences in the two methods of inference point to the need for caution in extrapolating research findings. Single-event rainfall experiments conducted shortly after manure application simulate incidental transfers of dissolved P in manure to runoff, resulting in greater losses of dissolved reactive P. However, the transfer of dissolved P in applied manure diminishes with time. Over the annual time frame simulated by whole farm modeling, erosion processes become more important to runoff P losses. Results of this study highlight the need to consider the potential for increased erosion and total P losses caused by soil disturbance during incorporation. This study emphasizes the ability of modeling to estimate management practice effectiveness at the larger scales when experimental data is not available.

Wind Farm LES Simulations Using an Overset Methodology

NASA Astrophysics Data System (ADS)

Ananthan, Shreyas; Yellapantula, Shashank

2017-11-01

Accurate simulation of wind farm wakes under realistic atmospheric inflow conditions and complex terrain requires modeling a wide range of length and time scales. The computational domain can span several kilometers while requiring mesh resolutions in O(10-6) to adequately resolve the boundary layer on the blade surface. Overset mesh methodology offers an attractive option to address the disparate range of length scales; it allows embedding body-confirming meshes around turbine geomtries within nested wake capturing meshes of varying resolutions necessary to accurately model the inflow turbulence and the resulting wake structures. Dynamic overset hole-cutting algorithms permit relative mesh motion that allow this nested mesh structure to track unsteady inflow direction changes, turbine control changes (yaw and pitch), and wake propagation. An LES model with overset mesh for localized mesh refinement is used to analyze wind farm wakes and performance and compared with local mesh refinements using non-conformal (hanging node) unstructured meshes. Turbine structures will be modeled using both actuator line approaches and fully-resolved structures to test the efficacy of overset methods for wind farm applications. Exascale Computing Project (ECP), Project Number: 17-SC-20-SC, a collaborative effort of two DOE organizations - the Office of Science and the National Nuclear Security Administration.

Volume sharing of reservoir water

NASA Astrophysics Data System (ADS)

Dudley, Norman J.

1988-05-01

Previous models optimize short-, intermediate-, and long-run irrigation decision making in a simplified river valley system characterized by highly variable water supplies and demands for a single decision maker controlling both reservoir releases and farm water use. A major problem in relaxing the assumption of one decision maker is communicating the stochastic nature of supplies and demands between reservoir and farm managers. In this paper, an optimizing model is used to develop release rules for reservoir management when all users share equally in releases, and computer simulation is used to generate an historical time sequence of announced releases. These announced releases become a state variable in a farm management model which optimizes farm area-to-irrigate decisions through time. Such modeling envisages the use of growing area climatic data by the reservoir authority to gauge water demand and the transfer of water supply data from reservoir to farm managers via computer data files. Alternative model forms, including allocating water on a priority basis, are discussed briefly. Results show lower mean aggregate farm income and lower variance of aggregate farm income than in the single decision-maker case. This short-run economic efficiency loss coupled with likely long-run economic efficiency losses due to the attenuated nature of property rights indicates the need for quite different ways of integrating reservoir and farm management.

Multi-agent modeling and simulation of farmland use change in the farming-pastoral zone: A case study of Qianjingou Town in Inner Mongolia, China

NASA Astrophysics Data System (ADS)

Yan, H.

2015-12-01

Farmland is the most basic material conditions for guaranteeing rural livelihoods and national food security, and exploring management strategies that take both of the sustainable rural livelihoods and sustainable farmland use into account has vital significance of theory and practice. Farmland is a complex and self-adaptive system that couples human and natural systems together, and natural factors and social factors that are related to its changing process need to be considered when modeling farmland changing process. This paper takes Qianjingou Town in Inner Mongolia farming-pastoral zone as study area. From the perspective of the relationship between households' livelihoods and farmland use, this study builds the process mechanism of farmland use change based on questionnaires data, and constructs multi-agent simulation model of farmland use change with the help of Eclipse and Repast toolbox. Through simulating the relationship between natural factors (with geographical location) and households' behaviors, this paper systematically simulates households' renting and abandoning farmland behaviors, and truly describes dynamic interactions between households' livelihoods and factors related to farmland use change. These factors include natural factors (net primary productivity, road accessibility, slope and relief amplitude) and social factors (households' family structures, economic development and government policies). In the end, this study scientifically predicts farmland use change trend in the future 30 years. The simulation results show that, the number of abandoned and sublet farmland plots has a gradually increasing trend, the number of non-farm households and pure-outwork households has a remarkable increasing trend, and the number of part-farm households and pure-farm households shows a decreasing trend. Households' livelihoods sustainability in the study area is confronted with increasing pressure, and households' nonfarm employment has an increasing trend, while regional appropriate-scale agricultural management can be maintained. The research results establish the theory foundation and basic method for developing sustainable farmland use managements that can both meet households' willing and guarantee grain and ecology security.

Evaluating the APEX model for simulating streamflow and water quality on ten agricultural watersheds in the U.S.

USDA-ARS?s Scientific Manuscript database

Simulation models are increasingly used to assess water quality constituent losses from agricultural systems. Mis-use often gives irrelevant or erroneous answers. The Agricultural Policy Environmental Extender (APEX) model is emerging as one of the premier modeling tools for fields, farms, and agr...

Benthic processes and coastal aquaculture: merging models and field data at a local scale

NASA Astrophysics Data System (ADS)

Brigolin, Daniele; Rabouille, Christophe; Bombled, Bruno; Colla, Silvia; Pastres, Roberto; Pranovi, Fabio

2016-04-01

Shellfish farming is regarded as an organic extractive aquaculture activity. However, the production of faeces and pseudofaeces, in fact, leads to a net transfer of organic matter from the water column to the surface sediment. This process, which is expected to locally affect the sediment biogeochemistry, may also cause relevant changes in coastal areas characterized by a high density of farms. In this paper, we present the result of a study recently carried out in the Gulf of Venice (northern Adriatic sea), combining mathematical modelling and field sampling efforts. The work aimed at using a longline mussel farm as an in-situ test-case for modelling the differences in soft sediments biogeochemical processes along a gradient of organic deposition. We used an existing integrated model, allowing to describe biogeochemical fluxes towards the mussel farm and to predict the extent of the deposition area underneath it. The model framework includes an individual-based population dynamic model of the Mediterranean mussel coupled with a Lagrangian deposition model and a 1D benthic model of early diagenesis. The work was articulated in 3 steps: 1) the integrated model allowed to simulate the downward fluxes of organic matter originated by the farm, and the extent of its deposition area; 2) based on the first model application, two stations were localized, at which sediment cores were collected during a field campaign, carried out in June 2015. Measurements included O2 and pH microprofiling, porosity and micro-porosity, Total Organic Carbon, and pore waters NH4, PO4, SO4, Alkalinity, and Dissolved Inorganic Carbon; 3) two distinct early diagenesis models were set-up, reproducing observed field data in the sampled cores. Observed oxygen microprofiles showed a different behavior underneath the farm with respect to the outside reference station. In particular, a remarkable decrease in the oxygen penetration depth, and an increase in the O2 influx calculated from the concentration gradients were observed. The integrated model described above allowed to extend the simulation over the entire farmed area, and to explore the response of the prediction to changes in water temperature.

A comparison of emission calculations using different modeled indicators with 1-year online measurements.

PubMed

Lengers, Bernd; Schiefler, Inga; Büscher, Wolfgang

2013-12-01

The overall measurement of farm level greenhouse gas (GHG) emissions in dairy production is not feasible, from either an engineering or administrative point of view. Instead, computational model systems are used to generate emission inventories, demanding a validation by measurement data. This paper tests the GHG calculation of the dairy farm-level optimization model DAIRYDYN, including methane (CH₄) from enteric fermentation and managed manure. The model involves four emission calculation procedures (indicators), differing in the aggregation level of relevant input variables. The corresponding emission factors used by the indicators range from default per cow (activity level) emissions up to emission factors based on feed intake, manure amount, and milk production intensity. For validation of the CH₄ accounting of the model, 1-year CH₄ measurements of an experimental free-stall dairy farm in Germany are compared to model simulation results. An advantage of this interdisciplinary study is given by the correspondence of the model parameterization and simulation horizon with the experimental farm's characteristics and measurement period. The results clarify that modeled emission inventories (2,898, 4,637, 4,247, and 3,600 kg CO₂-eq. cow(-1) year(-1)) lead to more or less good approximations of online measurements (average 3,845 kg CO₂-eq. cow(-1) year(-1) (±275 owing to manure management)) depending on the indicator utilized. The more farm-specific characteristics are used by the GHG indicator; the lower is the bias of the modeled emissions. Results underline that an accurate emission calculation procedure should capture differences in energy intake, owing to milk production intensity as well as manure storage time. Despite the differences between indicator estimates, the deviation of modeled GHGs using detailed indicators in DAIRYDYN from on-farm measurements is relatively low (between -6.4% and 10.5%), compared with findings from the literature.

Validation of Individual-Based Markov-Like Stochastic Process Model of Insect Behavior and a “Virtual Farm” Concept for Enhancement of Site-Specific IPM

PubMed Central

Lux, Slawomir A.; Wnuk, Andrzej; Vogt, Heidrun; Belien, Tim; Spornberger, Andreas; Studnicki, Marcin

2016-01-01

The paper reports application of a Markov-like stochastic process agent-based model and a “virtual farm” concept for enhancement of site-specific Integrated Pest Management. Conceptually, the model represents a “bottom-up ethological” approach and emulates behavior of the “primary IPM actors”—large cohorts of individual insects—within seasonally changing mosaics of spatiotemporally complex faming landscape, under the challenge of the local IPM actions. Algorithms of the proprietary PESTonFARM model were adjusted to reflect behavior and ecology of R. cerasi. Model parametrization was based on compiled published information about R. cerasi and the results of auxiliary on-farm experiments. The experiments were conducted on sweet cherry farms located in Austria, Germany, and Belgium. For each farm, a customized model-module was prepared, reflecting its spatiotemporal features. Historical data about pest monitoring, IPM treatments and fruit infestation were used to specify the model assumptions and calibrate it further. Finally, for each of the farms, virtual IPM experiments were simulated and the model-generated results were compared with the results of the real experiments conducted on the same farms. Implications of the findings for broader applicability of the model and the “virtual farm” approach—were discussed. PMID:27602000

Stochastic Simulation Using @ Risk for Dairy Business Investment Decisions

USDA-ARS?s Scientific Manuscript database

A dynamic, stochastic, mechanistic simulation model of a dairy business was developed to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm system within a partial budgeting fram...

Using Wind Tunnels to Predict Bird Mortality in Wind Farms: The Case of Griffon Vultures

PubMed Central

de Lucas, Manuela; Ferrer, Miguel; Janss, Guyonne F. E.

2012-01-01

Background Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. Methodology/Principal Findings As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. Conclusions Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed). We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality. PMID:23152764

Forecasting fluid milk and cheese demands for the next decade.

PubMed

Schmit, T M; Kaiser, H M

2006-12-01

Predictions of future market demands and farm prices for dairy products are important determinants in developing marketing strategies and farm-production planning decisions. The objective of this report was to use current aggregate forecast data, combined with existing econometric models of demand and supply, to forecast retail demands for fluid milk and cheese and the supply and price of farm milk over the next decade. In doing so, we can investigate whether projections of population and consumer food-spending patterns will extend or alter current consumption trends and examine the implications of future generic advertising strategies for dairy products. To conduct the forecast simulations and appropriately allocate the farm milk supply to various uses, we used a partial equilibrium model of the US domestic dairy sector that segmented the industry into retail, wholesale, and farm markets. Model simulation results indicated that declines in retail per capita demand would persist but at a reduced rate from years past and that retail per capita demand for cheese would continue to grow and strengthen over the next decade. These predictions rely on expected changes in the size of populations of various ages, races, and ethnicities and on existing patterns of spending on food at home and away from home. The combined effect of these forecasted changes in demand levels was reflected in annualized growth in the total farm-milk supply that was similar to growth realized during the past few years. Although we expect nominal farm milk prices to increase over the next decade, we expect real prices (relative to assumed growth in feed costs) to remain relatively stable and show no increase until the end of the forecast period. Supplemental industry model simulations also suggested that net losses in producer revenues would result if only nominal levels of generic advertising spending were maintained in forthcoming years. In fact, if real generic advertising expenditures are increased relative to 2005 levels, returns to the investment in generic advertising can be improved. Specifically, each additional real dollar invested in generic advertising for fluid milk and cheese products over the forecast period would result in an additional 5.61 dollars in producer revenues.

A simulation study demonstrating the importance of large-scale trailing vortices in wake steering

DOE PAGES

Fleming, Paul; Annoni, Jennifer; Churchfield, Matthew; ...

2018-05-14

In this article, we investigate the role of flow structures generated in wind farm control through yaw misalignment. A pair of counter-rotating vortices are shown to be important in deforming the shape of the wake and in explaining the asymmetry of wake steering in oppositely signed yaw angles. We motivate the development of new physics for control-oriented engineering models of wind farm control, which include the effects of these large-scale flow structures. Such a new model would improve the predictability of control-oriented models. Results presented in this paper indicate that wind farm control strategies, based on new control-oriented models withmore » new physics, that target total flow control over wake redirection may be different, and perhaps more effective, than current approaches. We propose that wind farm control and wake steering should be thought of as the generation of large-scale flow structures, which will aid in the improved performance of wind farms.« less

A simulation study demonstrating the importance of large-scale trailing vortices in wake steering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fleming, Paul; Annoni, Jennifer; Churchfield, Matthew

In this article, we investigate the role of flow structures generated in wind farm control through yaw misalignment. A pair of counter-rotating vortices are shown to be important in deforming the shape of the wake and in explaining the asymmetry of wake steering in oppositely signed yaw angles. We motivate the development of new physics for control-oriented engineering models of wind farm control, which include the effects of these large-scale flow structures. Such a new model would improve the predictability of control-oriented models. Results presented in this paper indicate that wind farm control strategies, based on new control-oriented models withmore » new physics, that target total flow control over wake redirection may be different, and perhaps more effective, than current approaches. We propose that wind farm control and wake steering should be thought of as the generation of large-scale flow structures, which will aid in the improved performance of wind farms.« less

Forage-based dairying in a water-limited future: use of models to investigate farming system adaptation in southern Australia.

PubMed

Chapman, D F; Dassanayake, K; Hill, J O; Cullen, B R; Lane, N

2012-07-01

The irrigated dairy industry in southern Australia has experienced significant restrictions in irrigation water allocations since 2005, consistent with climate change impact predictions for the region. Simulation models of pasture growth (DairyMod), crop yield (Agricultural Production Systems Simulator, APSIM), and dairy system management and production (UDDER) were used in combination to investigate a range of forage options that may be capable of sustaining dairy business profitability under restricted water-allocation scenarios in northern Victoria, Australia. A total of 23 scenarios were simulated and compared with a base farm system (100% of historical water allocations, grazed perennial ryegrass pasture with supplements; estimated operating surplus $A2,615/ha at a milk price of $A4.14/kg of milk solids). Nine simulations explored the response of the base farm to changes in stocking rate or the implementation of a double cropping rotation on 30% of farm area, or both. Five simulations explored the extreme scenario of dairying without any irrigation water. Two general responses to water restrictions were investigated in a further 9 simulations. Annual ryegrass grazed pasture, complemented by a double cropping rotation (maize grown in summer for silage, followed by either brassica forage crop and annual ryegrass for silage in winter and spring) on 30% of farm area, led to an estimated operating surplus of $A1746/ha at the same stocking rate as the base farm when calving was moved to autumn (instead of late winter, as in the base system). Estimated total irrigation water use was 2.7ML/ha compared with 5.4ML/ha for the base system. Summer-dormant perennial grass plus double cropping (30% of farm area) lifted operating surplus by a further $A100/ha if associated with autumn calving (estimated total irrigation water use 3.1ML/ha). Large shifts in the forage base of dairy farms could sustain profitability in the face of lower, and fluctuating, water allocations. However, changes in other strategic management policies, notably calving date and stocking rate, would be required, and these systems would be more complex to manage. The adaptation scenarios that resulted in the highest estimated operating surplus were those where at least 10 t of pasture or crop DM was grazed directly by cows per hectare per year, resulting in grazed pasture intake of at least 2 t of DM/cow, and at least 60% of all homegrown feed that was consumed was grazed directly. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

User guide for the farm process (FMP1) for the U.S. Geological Survey's modular three-dimensional finite-difference ground-water flow model, MODFLOW-2000

USGS Publications Warehouse

Schmid, Wolfgang; Hanson, R.T.; Maddock, Thomas; Leake, S.A.

2006-01-01

There is a need to estimate dynamically integrated supply-and-demand components of irrigated agriculture as part of the simulation of surface-water and ground-water flow. To meet this need, a computer program called the Farm Process (FMP1) was developed for the U.S. Geological Survey three-dimensional finite-difference modular ground-water flow model, MODFLOW- 2000 (MF2K). The FMP1 allows MF2K users to simulate conjunctive use of surface- and ground water for irrigated agriculture for historical and future simulations, water-rights issues and operational decisions, nondrought and drought scenarios. By dynamically integrating farm delivery requirement, surface- and ground-water delivery, as well as irrigation-return flow, the FMP1 allows for the estimation of supplemental well pumpage. While farm delivery requirement and irrigation return flow are simulated by the FMP1, the surface-water delivery to the farm can be simulated optionally by coupling the FMP1 with the Streamflow Routing Package (SFR1) and the farm well pumping can be simulated optionally by coupling the FMP1 to the Multi-Node Well (MNW) Package. In addition, semi-routed deliveries can be specified that are associated with points of diversion in the SFR1 stream network. Nonrouted surface-water deliveries can be specified independently of any stream network. The FMP1 maintains a dual mass balance of a farm budget and as part of the ground-water budget. Irrigation demand, supply, and return flow are in part subject to head-dependent sources and sinks such as evapotranspiration from ground water and leakage between the conveyance system and the aquifer. Farm well discharge and farm net recharge are source/sink terms in the FMP1, which depend on transpiration uptake from ground water and other head dependent consumptive use components. For heads rising above the bottom of the root zone, the actual transpiration is taken to vary proportionally with the depth of the active root zone, which can be restricted by anoxia or wilting. Depths corresponding to anoxia- or wilting-related pressure heads within the root zone are found using analytical solutions of a vertical pseudo steady-state pressure- head distribution over the depth of the total root zone (Consumptive Use Concept 1). Alternatively, a simpler, conceptual model is available, which defines how consumptive use (CU) components vary with changing head (CU Concept 2). Subtracting the ground water and precipitation transpiration components from the total transpiration yields a transpiratory irrigation requirement for each cell. The total farm delivery requirement (TFDR) then is determined as cumulative transpiratory and evaporative irrigation requirements of all farm cells and increased sufficiently to compensate for inefficient use from irrigation with respect to plant consumption. The TFDR subsequently is satisfied with surface- and ground-water delivery, respectively constrained by allotments, water rights, or maximum capacities. Five economic and noneconomic drought response policies can be applied optionally, if the potential supply of surface water and ground water is insufficient to meet the crop demand: acreage-optimization with or without a water conservation pool, deficit irrigation with or without water-stacking, and zero policy.

High-resolution computational algorithms for simulating offshore wind turbines and farms: Model development and validation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Calderer, Antoni; Yang, Xiaolei; Angelidis, Dionysios

2015-10-30

The present project involves the development of modeling and analysis design tools for assessing offshore wind turbine technologies. The computational tools developed herein are able to resolve the effects of the coupled interaction of atmospheric turbulence and ocean waves on aerodynamic performance and structural stability and reliability of offshore wind turbines and farms. Laboratory scale experiments have been carried out to derive data sets for validating the computational models.

Wake Dynamics in the Atmospheric Boundary Layer Over Complex Terrain

NASA Astrophysics Data System (ADS)

Markfort, Corey D.

The goal of this research is to advance our understanding of atmospheric boundary layer processes over heterogeneous landscapes and complex terrain. The atmospheric boundary layer (ABL) is a relatively thin (˜ 1 km) turbulent layer of air near the earth's surface, in which most human activities and engineered systems are concentrated. Its dynamics are crucially important for biosphere-atmosphere couplings and for global atmospheric dynamics, with significant implications on our ability to predict and mitigate adverse impacts of land use and climate change. In models of the ABL, land surface heterogeneity is typically represented, in the context of Monin-Obukhov similarity theory, as changes in aerodynamic roughness length and surface heat and moisture fluxes. However, many real landscapes are more complex, often leading to massive boundary layer separation and wake turbulence, for which standard models fail. Trees, building clusters, and steep topography produce extensive wake regions currently not accounted for in models of the ABL. Wind turbines and wind farms also generate wakes that combine in complex ways to modify the ABL. Wind farms are covering an increasingly significant area of the globe and the effects of large wind farms must be included in regional and global scale models. Research presented in this thesis demonstrates that wakes caused by landscape heterogeneity must be included in flux parameterizations for momentum, heat, and mass (water vapor and trace gases, e.g. CO2 and CH4) in ABL simulation and prediction models in order to accurately represent land-atmosphere interactions. Accurate representation of these processes is crucial for the predictions of weather, air quality, lake processes, and ecosystems response to climate change. Objectives of the research reported in this thesis are: 1) to investigate turbulent boundary layer adjustment, turbulent transport and scalar flux in wind farms of varying configurations and develop an improved modeling framework for wind farm - atmosphere interaction, 2) to determine how heterogeneous patches of forest affect the structure of the ABL and its interactions with clearings and water bodies, 3) to investigate how landscape heterogeneity, including wakes, may be parameterized in regional-scale weather and climate models to improve the representation of surface fluxes, e.g. from lakes/wetlands and forest clearings. To achieve these objectives, this research employs an interdisciplinary strategy, utilizing concepts and methods from fluid mechanics, micrometeorology, ecosystem ecology and environmental sciences, and combines laboratory and field experiments. In particular, a) wind tunnel experiments of flow through and over model wind farms and model forest canopies were used to improve our fundamental understanding of how wakes affect land-atmosphere coupling, including surface fluxes, after wind farm installation and for heterogeneous landscapes of canopies and clearings or lakes, and b) extensive field studies over lakes and wetlands were undertaken to study the effects of wakes downwind of forest canopies and the effect of wind sheltering on lake stratification dynamics and gas fluxes. These experiments were also used to improve and validate numerical simulation techniques for the atmospheric boundary layer, specifically the large eddy simulation technique, which is used to simulate flow in wind farms and flow over heterogeneous terrain.

Simulation of an offshore wind farm using fluid power for centralized electricity generation

NASA Astrophysics Data System (ADS)

Jarquin-Laguna, A.

2016-09-01

A centralized approach for electricity generation within a wind farm is explored through the use of fluid power technology. This concept considers a new way of generation, collection and transmission of wind energy inside a wind farm, in which electrical conversion does not occur during any intermediate conversion step before the energy has reached the offshore central platform. A numerical model was developed to capture the relevant physics from the dynamic interaction between different turbines coupled to a common hydraulic network and controller. This paper presents two examples of the time-domain simulation results for an hypothetical hydraulic wind farm subject to turbulent wind conditions. The performance and operational parameters of individual turbines are compared with those of a reference wind farm with conventional technology turbines, using the same wind farm layout and environmental conditions. For the presented case study, results indicate that the individual wind turbines are able to operate within operational limits with the current pressure control concept. Despite the stochastic turbulent wind input and wake effects, the hydraulic wind farm is able to produce electricity with reasonable performance in both below and above rated conditions.

Contribution of large scale coherence to wind turbine power: A large eddy simulation study in periodic wind farms

NASA Astrophysics Data System (ADS)

Chatterjee, Tanmoy; Peet, Yulia T.

2018-03-01

Length scales of eddies involved in the power generation of infinite wind farms are studied by analyzing the spectra of the turbulent flux of mean kinetic energy (MKE) from large eddy simulations (LES). Large-scale structures with an order of magnitude bigger than the turbine rotor diameter (D ) are shown to have substantial contribution to wind power. Varying dynamics in the intermediate scales (D -10 D ) are also observed from a parametric study involving interturbine distances and hub height of the turbines. Further insight about the eddies responsible for the power generation have been provided from the scaling analysis of two-dimensional premultiplied spectra of MKE flux. The LES code is developed in a high Reynolds number near-wall modeling framework, using an open-source spectral element code Nek5000, and the wind turbines have been modelled using a state-of-the-art actuator line model. The LES of infinite wind farms have been validated against the statistical results from the previous literature. The study is expected to improve our understanding of the complex multiscale dynamics in the domain of large wind farms and identify the length scales that contribute to the power. This information can be useful for design of wind farm layout and turbine placement that take advantage of the large-scale structures contributing to wind turbine power.

Maximum capacity model of grid-connected multi-wind farms considering static security constraints in electrical grids

NASA Astrophysics Data System (ADS)

Zhou, W.; Qiu, G. Y.; Oodo, S. O.; He, H.

2013-03-01

An increasing interest in wind energy and the advance of related technologies have increased the connection of wind power generation into electrical grids. This paper proposes an optimization model for determining the maximum capacity of wind farms in a power system. In this model, generator power output limits, voltage limits and thermal limits of branches in the grid system were considered in order to limit the steady-state security influence of wind generators on the power system. The optimization model was solved by a nonlinear primal-dual interior-point method. An IEEE-30 bus system with two wind farms was tested through simulation studies, plus an analysis conducted to verify the effectiveness of the proposed model. The results indicated that the model is efficient and reasonable.

Agricultural Policy Environmental eXtender simulation of three adjacent row-crop watersheds in the claypan region

USDA-ARS?s Scientific Manuscript database

The Agricultural Policy Environmental Extender (APEX) model can simulate crop yields, and pollutant loadings in whole farms or small watersheds with variety of management practices. The study objectives were to identify sensitive parameters and parameterize, calibrate and validate the APEX model fo...

Evaluating GPFARM Crop Growth, Soil Water, and Soil Nitrogen Components for Colorado Dryland Locations

USDA-ARS?s Scientific Manuscript database

GPFARM is a farm/ranch decision support system (DSS) designed to assist in strategic management planning for land units from the field to the whole-farm level. This study evaluated the regional applicability and efficacy of GPFARM based on simulation model performance for dry mass grain yield, tota...

Data Farming and Defense Applications

NASA Technical Reports Server (NTRS)

Horne, Gary; Meyer, Ted

2011-01-01

.Data farm,ing uses simulation modeling, high performance computing, experimental design and analysis to examine questions of interest with large possibility spaces. This methodology allows for the examination of whole landscapes of potential outcomes and provides the capability of executing enough experiments so that outliers might be captured and examined for insights. It can be used to conduct sensitivity studies, to support validation and verification of models, to iteratively optimize outputs using heuristic search and discovery, and as an aid to decision-makers in understanding complex relationships of factors. In this paper we describe efforts at the Naval Postgraduate School in developing these new and emerging tools. We also discuss data farming in the context of application to questions inherent in military decision-making. The particular application we illustrate here is social network modeling to support the countering of improvised explosive devices.

A large-eddy simulation based power estimation capability for wind farms over complex terrain

NASA Astrophysics Data System (ADS)

Senocak, I.; Sandusky, M.; Deleon, R.

2017-12-01

There has been an increasing interest in predicting wind fields over complex terrain at the micro-scale for resource assessment, turbine siting, and power forecasting. These capabilities are made possible by advancements in computational speed from a new generation of computing hardware, numerical methods and physics modelling. The micro-scale wind prediction model presented in this work is based on the large-eddy simulation paradigm with surface-stress parameterization. The complex terrain is represented using an immersed-boundary method that takes into account the parameterization of the surface stresses. Governing equations of incompressible fluid flow are solved using a projection method with second-order accurate schemes in space and time. We use actuator disk models with rotation to simulate the influence of turbines on the wind field. Data regarding power production from individual turbines are mostly restricted because of proprietary nature of the wind energy business. Most studies report percentage drop of power relative to power from the first row. There have been different approaches to predict power production. Some studies simply report available wind power in the upstream, some studies estimate power production using power curves available from turbine manufacturers, and some studies estimate power as torque multiplied by rotational speed. In the present work, we propose a black-box approach that considers a control volume around a turbine and estimate the power extracted from the turbine based on the conservation of energy principle. We applied our wind power prediction capability to wind farms over flat terrain such as the wind farm over Mower County, Minnesota and the Horns Rev offshore wind farm in Denmark. The results from these simulations are in good agreement with published data. We also estimate power production from a hypothetical wind farm in complex terrain region and identify potential zones suitable for wind power production.

Integrated water flow model and modflow-farm process: A comparison of theory, approaches, and features of two integrated hydrologic models

USGS Publications Warehouse

Dogrul, Emin C.; Schmid, Wolfgang; Hanson, Randall T.; Kadir, Tariq; Chung, Francis

2016-01-01

Effective modeling of conjunctive use of surface and subsurface water resources requires simulation of land use-based root zone and surface flow processes as well as groundwater flows, streamflows, and their interactions. Recently, two computer models developed for this purpose, the Integrated Water Flow Model (IWFM) from the California Department of Water Resources and the MODFLOW with Farm Process (MF-FMP) from the US Geological Survey, have been applied to complex basins such as the Central Valley of California. As both IWFM and MFFMP are publicly available for download and can be applied to other basins, there is a need to objectively compare the main approaches and features used in both models. This paper compares the concepts, as well as the method and simulation features of each hydrologic model pertaining to groundwater, surface water, and landscape processes. The comparison is focused on the integrated simulation of water demand and supply, water use, and the flow between coupled hydrologic processes. The differences in the capabilities and features of these two models could affect the outcome and types of water resource problems that can be simulated.

Modelling potential production of macroalgae farms in UK and Dutch coastal waters

NASA Astrophysics Data System (ADS)

van der Molen, Johan; Ruardij, Piet; Mooney, Karen; Kerrison, Philip; O'Connor, Nessa E.; Gorman, Emma; Timmermans, Klaas; Wright, Serena; Kelly, Maeve; Hughes, Adam D.; Capuzzo, Elisa

2018-02-01

There is increasing interest in macroalgae farming in European waters for a range of applications, including food, chemical extraction for biofuel production. This study uses a 3-D numerical model of hydrodynamics and biogeochemistry to investigate potential production and environmental effects of macroalgae farming in UK and Dutch coastal waters. The model included four experimental farms in different coastal settings in Strangford Lough (Northern Ireland), in Sound of Kerrera and Lynn of Lorne (north-west Scotland) and in the Rhine plume (the Netherlands), as well as a hypothetical large-scale farm off the UK north Norfolk coast. The model could not detect significant changes in biogeochemistry and plankton dynamics at any of the farm sites averaged over the farming season. The results showed a range of macroalgae growth behaviours in response to simulated environmental conditions. These were then compared with in situ observations where available, showing good correspondence for some farms and less good correspondence for others. At the most basic level, macroalgae production depended on prevailing nutrient concentrations and light conditions, with higher levels of both resulting in higher macroalgae production. It is shown that under non-elevated and interannually varying winter nutrient conditions, farming success was modulated by the timings of the onset of increasing nutrient concentrations in autumn and nutrient drawdown in spring. Macroalgae carbohydrate content also depended on nutrient concentrations, with higher nutrient concentrations leading to lower carbohydrate content at harvest. This will reduce the energy density of the crop and thus affect its suitability for conversion into biofuel. For the hypothetical large-scale macroalgae farm off the UK north Norfolk coast, the model suggested high, stable farm yields of macroalgae from year to year with substantial carbohydrate content and limited environmental effects.

Linearized simulation of flow over wind farms and complex terrains.

PubMed

Segalini, Antonio

2017-04-13

The flow over complex terrains and wind farms is estimated here by numerically solving the linearized Navier-Stokes equations. The equations are linearized around the unperturbed incoming wind profile, here assumed logarithmic. The Boussinesq approximation is used to model the Reynolds stress with a prescribed turbulent eddy viscosity profile. Without requiring the boundary-layer approximation, two new linear equations are obtained for the vertical velocity and the wall-normal vorticity, with a reduction in the computational cost by a factor of 8 when compared with a primitive-variables formulation. The presence of terrain elevation is introduced as a vertical coordinate shift, while forestry or wind turbines are included as body forces, without any assumption about the wake structure for the turbines. The model is first validated against some available experiments and simulations, and then a simulation of a wind farm over a Gaussian hill is performed. The speed-up effect of the hill is clearly beneficial in terms of the available momentum upstream of the crest, while downstream of it the opposite can be said as the turbines face a decreased wind speed. Also, the presence of the hill introduces an additional spanwise velocity component that may also affect the turbines' operations. The linear superposition of the flow over the hill and the flow over the farm alone provided a first estimation of the wind speed along the farm, with discrepancies of the same order of magnitude for the spanwise velocity. Finally, the possibility of using a parabolic set of equations to obtain the turbulent kinetic energy after the linearized model is investigated with promising results.This article is part of the themed issue 'Wind energy in complex terrains'. © 2017 The Author(s).

Linearized simulation of flow over wind farms and complex terrains

NASA Astrophysics Data System (ADS)

Segalini, Antonio

2017-03-01

The flow over complex terrains and wind farms is estimated here by numerically solving the linearized Navier-Stokes equations. The equations are linearized around the unperturbed incoming wind profile, here assumed logarithmic. The Boussinesq approximation is used to model the Reynolds stress with a prescribed turbulent eddy viscosity profile. Without requiring the boundary-layer approximation, two new linear equations are obtained for the vertical velocity and the wall-normal vorticity, with a reduction in the computational cost by a factor of 8 when compared with a primitive-variables formulation. The presence of terrain elevation is introduced as a vertical coordinate shift, while forestry or wind turbines are included as body forces, without any assumption about the wake structure for the turbines. The model is first validated against some available experiments and simulations, and then a simulation of a wind farm over a Gaussian hill is performed. The speed-up effect of the hill is clearly beneficial in terms of the available momentum upstream of the crest, while downstream of it the opposite can be said as the turbines face a decreased wind speed. Also, the presence of the hill introduces an additional spanwise velocity component that may also affect the turbines' operations. The linear superposition of the flow over the hill and the flow over the farm alone provided a first estimation of the wind speed along the farm, with discrepancies of the same order of magnitude for the spanwise velocity. Finally, the possibility of using a parabolic set of equations to obtain the turbulent kinetic energy after the linearized model is investigated with promising results. This article is part of the themed issue 'Wind energy in complex terrains'.

Using biological-physical modelling for informing sea lice dispersal in Loch Linnhe, Scotland.

PubMed

Salama, N K G; Dale, A C; Ivanov, V V; Cook, P F; Pert, C C; Collins, C M; Rabe, B

2018-06-01

Sea lice are a constraint on the sustainable growth of Scottish marine salmonid aquaculture. As part of an integrated pest management approach, farms coordinate procedures within spatial units. We present observations of copepodids being at relatively greater density than nauplii in upper waters, which informs the development of surface layer sea lice transmission modelling of Loch Linnhe, Scotland, for informing farm parasite management. A hydrodynamic model is coupled with a biological particle-tracking model, with characteristics of plankton sea lice. Simulations are undertaken for May and October 2011-2013, forced by local wind data collected for those periods. Particles are continually released from positions representing farm locations, weighted by relative farm counts, over a 2-week period and tracked for a further 5 days. A comparison is made between modelled relative concentrations against physical and biological surveys to provide confidence in model outputs. Connectivity between farm locations is determined in order to propose potential coordination areas. Generally, connectivity depends on flow patterns in the loch and decreases with increased farm separation. The connectivity indices are used to estimate the origins of the sea lice population composition at each site, which may influence medicinal regimens to avoid loss of efficacy. © 2017 John Wiley & Sons Ltd.

Large-Eddy Simulation of Waked Turbines in a Scaled Wind Farm Facility

NASA Astrophysics Data System (ADS)

Wang, J.; McLean, D.; Campagnolo, F.; Yu, T.; Bottasso, C. L.

2017-05-01

The aim of this paper is to present the numerical simulation of waked scaled wind turbines operating in a boundary layer wind tunnel. The simulation uses a LES-lifting-line numerical model. An immersed boundary method in conjunction with an adequate wall model is used to represent the effects of both the wind turbine nacelle and tower, which are shown to have a considerable effect on the wake behavior. Multi-airfoil data calibrated at different Reynolds numbers are used to account for the lift and drag characteristics at the low and varying Reynolds conditions encountered in the experiments. The present study focuses on low turbulence inflow conditions and inflow non-uniformity due to wind tunnel characteristics, while higher turbulence conditions are considered in a separate study. The numerical model is validated by using experimental data obtained during test campaigns conducted with the scaled wind farm facility. The simulation and experimental results are compared in terms of power capture, rotor thrust, downstream velocity profiles and turbulence intensity.

Spatiotemporal structure of wind farm-atmospheric boundary layer interactions

NASA Astrophysics Data System (ADS)

Cervarich, Matthew; Baidya Roy, Somnath; Zhou, Liming

2013-04-01

Wind power is currently one of the fastest growing energy sources in the world. Most of the growth is in the utility sector consisting of large wind farms with numerous industrial-scale wind turbines. Wind turbines act as a sink of mean kinetic energy and a source of turbulent kinetic energy in the atmospheric boundary layer (ABL). In doing so, they modify the ABL profiles and land-atmosphere exchanges of energy, momentum, mass and moisture. This project explores theses interactions using remote sensing data and numerical model simulations. The domain is central Texas where 4 of the world's largest wind farms are located. A companion study of seasonally-averaged Land Surface Temperature data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on TERRA and AQUA satellites shows a warming signal at night and a mixed cooling/warming signal during the daytime within the wind farms. In the present study, wind farm-ABL interactions are simulated with the Weather Research and Forecasting (WRF) model. The simulations show that the model is capable of replicating the observed signal in land surface temperature. Moreover, similar warming/cooling effect, up to 1C, was observed in seasonal mean 2m air temperature as well. Further analysis show that enhanced turbulent mixing in the rotor wakes is responsible for the impacts on 2m and surface air temperatures. The mixing is due to 2 reasons: (i) turbulent momentum transport to compensate the momentum deficit in the wakes of the turbines and (ii) turbulence generated due to motion of turbine rotors. Turbulent mixing also alters vertical profiles of moisture. Changes in land-atmosphere temperature and moisture gradient and increase in turbulent mixing leads to more than 10% change in seasonal mean surface sensible and latent heat flux. Given the current installed capacity and the projected installation across the world, wind farms are likely becoming a major driver of anthropogenic land use change on Earth. Hence, understanding WF-ABL interactions and its effects is of significant scientific and societal importance.

Organic dairy production systems in Pennsylvania: a case study evaluation.

PubMed

Rotz, C A; Kamphuis, G H; Karsten, H D; Weaver, R D

2007-08-01

The current market demand and price for organic milk is encouraging dairy producers, particularly those on smaller farms, to consider organic production as a means for improving the economic viability of their operations. Organic production systems vary widely in scale, in practices, and across agroclimatic settings. Within this context, case studies of 4 actual organic dairy farms were used to characterize existing systems in Pennsylvania. Based on data from these farms, a whole-farm simulation model (Integrated Farm System Model) was used to compare 4 production systems representing organic grass, organic crop, conventional crop with grazing, and conventional confinement production. The performance of each of these systems was simulated over each year of 25 yr of central Pennsylvania weather data. Simulation results indicated that farm level accumulation of soil P and K may be a concern on organic farms that use poultry manure as a primary crop nutrient source, and that erosion and runoff loss of P may be of concern on organic farms producing annual crops because more tillage is required for weed control. Whole-farm budgets with prices that reflect recent conditions showed an economic advantage for organic over conventional production. A sensitivity analysis showed that this economic advantage depended on a higher milk price for producers of organic milk and was influenced by the difference in milk production maintained by herds using organic and conventional systems. Factors found to have little effect on the relative profitability of organic over conventional production included the differences between organic and conventional prices for seed, chemicals, forage, and animals and the overall costs or prices assumed for organic certification, machinery, pasture fencing, fuel, and labor. Thus, at the current organic milk price, relative to other prices, the case study organic production systems seem to provide an option for improving the economic viability of dairy operations of the scale considered in Pennsylvania. To motivate transition to organic systems, the economic advantage found requires the persistence of a substantial difference between conventional and organic raw milk prices.

Farm-specific economic value of automatic lameness detection systems in dairy cattle: From concepts to operational simulations.

PubMed

Van De Gucht, Tim; Saeys, Wouter; Van Meensel, Jef; Van Nuffel, Annelies; Vangeyte, Jurgen; Lauwers, Ludwig

2018-01-01

Although prototypes of automatic lameness detection systems for dairy cattle exist, information about their economic value is lacking. In this paper, a conceptual and operational framework for simulating the farm-specific economic value of automatic lameness detection systems was developed and tested on 4 system types: walkover pressure plates, walkover pressure mats, camera systems, and accelerometers. The conceptual framework maps essential factors that determine economic value (e.g., lameness prevalence, incidence and duration, lameness costs, detection performance, and their relationships). The operational simulation model links treatment costs and avoided losses with detection results and farm-specific information, such as herd size and lameness status. Results show that detection performance, herd size, discount rate, and system lifespan have a large influence on economic value. In addition, lameness prevalence influences the economic value, stressing the importance of an adequate prior estimation of the on-farm prevalence. The simulations provide first estimates for the upper limits for purchase prices of automatic detection systems. The framework allowed for identification of knowledge gaps obstructing more accurate economic value estimation. These include insights in cost reductions due to early detection and treatment, and links between specific lameness causes and their related losses. Because this model provides insight in the trade-offs between automatic detection systems' performance and investment price, it is a valuable tool to guide future research and developments. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

IBSEM: An Individual-Based Atlantic Salmon Population Model.

PubMed

Castellani, Marco; Heino, Mikko; Gilbey, John; Araki, Hitoshi; Svåsand, Terje; Glover, Kevin A

2015-01-01

Ecology and genetics can influence the fate of individuals and populations in multiple ways. However, to date, few studies consider them when modelling the evolutionary trajectory of populations faced with admixture with non-local populations. For the Atlantic salmon, a model incorporating these elements is urgently needed because many populations are challenged with gene-flow from non-local and domesticated conspecifics. We developed an Individual-Based Salmon Eco-genetic Model (IBSEM) to simulate the demographic and population genetic change of an Atlantic salmon population through its entire life-cycle. Processes such as growth, mortality, and maturation are simulated through stochastic procedures, which take into account environmental variables as well as the genotype of the individuals. IBSEM is based upon detailed empirical data from salmon biology, and parameterized to reproduce the environmental conditions and the characteristics of a wild population inhabiting a Norwegian river. Simulations demonstrated that the model consistently and reliably reproduces the characteristics of the population. Moreover, in absence of farmed escapees, the modelled populations reach an evolutionary equilibrium that is similar to our definition of a 'wild' genotype. We assessed the sensitivity of the model in the face of assumptions made on the fitness differences between farm and wild salmon, and evaluated the role of straying as a buffering mechanism against the intrusion of farm genes into wild populations. These results demonstrate that IBSEM is able to capture the evolutionary forces shaping the life history of wild salmon and is therefore able to model the response of populations under environmental and genetic stressors.

Knowledge Integration to Make Decisions About Complex Systems: Sustainability of Energy Production from Agriculture

ScienceCinema

Danuso, Francesco

2017-12-22

A major bottleneck for improving the governance of complex systems, rely on our ability to integrate different forms of knowledge into a decision support system (DSS). Preliminary aspects are the classification of different types of knowledge (a priori or general, a posteriori or specific, with uncertainty, numerical, textual, algorithmic, complete/incomplete, etc.), the definition of ontologies for knowledge management and the availability of proper tools like continuous simulation models, event driven models, statistical approaches, computational methods (neural networks, evolutionary optimization, rule based systems etc.) and procedure for textual documentation. Following these views at University of Udine, a computer language (SEMoLa, Simple, Easy Modelling Language) for knowledge integration has been developed.  SEMoLa can handle models, data, metadata and textual knowledge; it implements and extends the system dynamics ontology (Forrester, 1968; Jørgensen, 1994) in which systems are modelled by the concepts of material, group, state, rate, parameter, internal and external events and driving variables. As an example, a SEMoLa model to improve management and sustainability (economical, energetic, environmental) of the agricultural farms is presented. The model (X-Farm) simulates a farm in which cereal and forage yield, oil seeds, milk, calves and wastes can be sold or reused. X-Farm is composed by integrated modules describing fields (crop and soil), feeds and materials storage, machinery management, manpower  management, animal husbandry, economic and energetic balances, seed oil extraction, manure and wastes management, biogas production from animal wastes and biomasses.

Integrated Water Resources Simulation Model for Rural Community

NASA Astrophysics Data System (ADS)

Li, Y.-H.; Liao, W.-T.; Tung, C.-P.

2012-04-01

The purpose of this study is to develop several water resources simulation models for residence houses, constructed wetlands and farms and then integrate these models for a rural community. Domestic and irrigation water uses are the major water demand in rural community. To build up a model estimating domestic water demand for residence houses, the average water use per person per day should be accounted first, including water uses of kitchen, bathroom, toilet and laundry. On the other hand, rice is the major crop in the study region, and its productive efficiency sometimes depends on the quantity of irrigation water. The water demand can be estimated by crop water use, field leakage and water distribution loss. Irrigation water comes from rainfall, water supply system and reclaimed water which treated by constructed wetland. In recent years, constructed wetlands play an important role in water resources recycle. They can purify domestic wastewater for water recycling and reuse. After treating from constructed wetlands, the reclaimed water can be reused in washing toilets, watering gardens and irrigating farms. Constructed wetland is one of highly economic benefits for treating wastewater through imitating the processing mechanism of natural wetlands. In general, the treatment efficiency of constructed wetlands is determined by evapotranspiration, inflow, and water temperature. This study uses system dynamics modeling to develop models for different water resource components in a rural community. Furthermore, these models are integrated into a whole system. The model not only is utilized to simulate how water moves through different components, including residence houses, constructed wetlands and farms, but also evaluates the efficiency of water use. By analyzing the flow of water, the water resource simulation model can optimizes water resource distribution under different scenarios, and the result can provide suggestions for designing water resource system of a rural community. Keywords: Water Resources, Simulation Model, Domestic Water, Irrigation, Constructed Wetland, Rural Community

Non-hazardous pesticide concentrations in surface waters: An integrated approach simulating application thresholds and resulting farm income effects.

PubMed

Bannwarth, M A; Grovermann, C; Schreinemachers, P; Ingwersen, J; Lamers, M; Berger, T; Streck, T

2016-01-01

Pesticide application rates are high and increasing in upland agricultural systems in Thailand producing vegetables, fruits and ornamental crops, leading to the pollution of stream water with pesticide residues. The objective of this study was to determine the maximum per hectare application rates of two widely used pesticides that would achieve non-hazardous pesticide concentrations in the stream water and to evaluate how farm household incomes would be affected if farmers complied with these restricted application rates. For this purpose we perform an integrated modeling approach of a hydrological solute transport model (the Soil and Water Assessment Tool, SWAT) and an agent-based farm decision model (Mathematical Programming-based Multi-Agent Systems, MPMAS). SWAT was used to simulate the pesticide fate and behavior. The model was calibrated to a 77 km(2) watershed in northern Thailand. The results show that to stay under a pre-defined eco-toxicological threshold, the current average application of chlorothalonil (0.80 kg/ha) and cypermethrin (0.53 kg/ha) would have to be reduced by 80% and 99%, respectively. The income effect of such reductions was simulated using MPMAS. The results suggest that if farm households complied with the application thresholds then their income would reduce by 17.3% in the case of chlorothalonil and by 38.3% in the case of cypermethrin. Less drastic income effects can be expected if methods of integrated pest management were more widely available. The novelty of this study is to combine two models from distinctive disciplines to evaluate pesticide reduction scenarios based on real-world data from a single study site. Copyright © 2014 Elsevier Ltd. All rights reserved.

Building a stakeholder's vision of an offshore wind-farm project: A group modeling approach.

PubMed

Château, Pierre-Alexandre; Chang, Yang-Chi; Chen, Hsin; Ko, Tsung-Ting

2012-03-15

This paper describes a Group Model Building (GMB) initiative that was designed to discuss the various potential effects that an offshore wind-farm may have on its local ecology and socioeconomic development. The representatives of various organizations in the study area, Lu-Kang, Taiwan, have held several meetings, and structured debates have been organized to promote the emergence of a consensual view on the main issues and their implications. A System Dynamics (SD) model has been built and corrected iteratively with the participants through the GMB process. The diverse interests within the group led the process toward the design of multifunctional wind-farms with different modalities. The scenario analyses, using the SD model under various policies, including no wind-farm policy, objectively articulates the vision of the local stakeholders. The results of the SD simulations show that the multifunctional wind-farms may have superior economic effects and the larger wind-farms with bird corridors could reduce ecological impact. However, the participants of the modeling process did not appreciate any type of offshore wind-farm development when considering all of the identified key factors of social acceptance. The insight gained from the study can provide valuable information to actualize feasible strategies for the green energy technique to meet local expectations. Copyright © 2012 Elsevier B.V. All rights reserved.

A Dynamic Spatio-Temporal Model to Investigate the Effect of Cattle Movements on the Spread of Bluetongue BTV-8 in Belgium

PubMed Central

Ensoy, Chellafe; Aerts, Marc; Welby, Sarah; Van der Stede, Yves; Faes, Christel

2013-01-01

When Bluetongue Virus Serotype 8 (BTV-8) was first detected in Northern Europe in 2006, several guidelines were immediately put into place with the goal to protect farms and stop the spreading of the disease. This however did not prevent further rapid spread of BTV-8 across Northern Europe. Using information on the 2006 Bluetongue outbreak in cattle farms in Belgium, a spatio-temporal transmission model was formulated. The model quantifies the local transmission of the disease between farms within a municipality, the short-distance transmission between farms across neighbouring municipalities and the transmission as a result of cattle movement. Different municipality-level covariates such as farm density, land composition variables, temperature and precipitation, were assessed as possibly influencing each component of the transmission process. Results showed a significant influence of the different covariates in each model component, particularly the significant effect of temperature and precipitation values in the number of infected farms. The model which allowed us to predict the dynamic spreading of BTV for different movement restriction scenarios, also affirmed the significant impact of cattle movement in the 2006 BTV outbreak pattern. Simulation results further showed the importance of considering the size of restriction zones in the formulation of guidelines for animal infectious diseases. PMID:24244324

A dynamic spatio-temporal model to investigate the effect of cattle movements on the spread of bluetongue BTV-8 in Belgium.

PubMed

Ensoy, Chellafe; Aerts, Marc; Welby, Sarah; Van der Stede, Yves; Faes, Christel

2013-01-01

When Bluetongue Virus Serotype 8 (BTV-8) was first detected in Northern Europe in 2006, several guidelines were immediately put into place with the goal to protect farms and stop the spreading of the disease. This however did not prevent further rapid spread of BTV-8 across Northern Europe. Using information on the 2006 Bluetongue outbreak in cattle farms in Belgium, a spatio-temporal transmission model was formulated. The model quantifies the local transmission of the disease between farms within a municipality, the short-distance transmission between farms across neighbouring municipalities and the transmission as a result of cattle movement. Different municipality-level covariates such as farm density, land composition variables, temperature and precipitation, were assessed as possibly influencing each component of the transmission process. Results showed a significant influence of the different covariates in each model component, particularly the significant effect of temperature and precipitation values in the number of infected farms. The model which allowed us to predict the dynamic spreading of BTV for different movement restriction scenarios, also affirmed the significant impact of cattle movement in the 2006 BTV outbreak pattern. Simulation results further showed the importance of considering the size of restriction zones in the formulation of guidelines for animal infectious diseases.

Temporal and spatial water use on irrigated and nonirrigated pasture-based dairy farms.

PubMed

Higham, C D; Horne, D; Singh, R; Kuhn-Sherlock, B; Scarsbrook, M R

2017-08-01

Robust information for water use on pasture-based dairy farms is critical to farmers' attempts to use water more efficiently and the improved allocation of freshwater resources to dairy farmers. To quantify the water requirements of dairy farms across regions in a practicable manner, it will be necessary to develop predictive models. The objectives of this study were to compare water use on a group of irrigated and nonirrigated farms, validate existing water use models using the data measured on the group of nonirrigated farms, and modify the model so that it can be used to predict water use on irrigated dairy farms. Water use data were collected on a group of irrigated dairy farms located in the Canterbury, New Zealand, region with the largest area under irrigation. The nonirrigated farms were located in the Manawatu region. The amount of water used for irrigation was almost 52-fold greater than the amount of all other forms of water use combined. There were large differences in measured milking parlor water use, stock drinking water, and leakage rates between the irrigated and nonirrigated farms. As expected, stock drinking water was lower on irrigated dairy farms. Irrigation lowers the dry matter percentage of pasture, ensuring that the amount of water ingested from pasture remains high throughout the year, thereby reducing the demand for drinking water. Leakage rates were different between the 2 groups of farms; 47% of stock drinking water was lost as leakage on nonirrigated farms, whereas leakage on the irrigated farms equated to only 13% of stock drinking water. These differences in leakage were thought to be related to regional differences rather than differences in irrigated versus nonirrigated farms. Existing models developed to predict milking parlor, corrected stock drinking water, and total water use on nonirrigated pasture-based dairy farms in a previous related study were tested on the data measured in the present research. As expected, these models performed well for nonirrigated dairy farms but provided poor predictive power for irrigated farms. Partial least squares regression models were developed specifically to simulate corrected stock drinking water, milking parlor water, and total water use on irrigated dairy farms. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Object view in spatial system dynamics: a grassland farming example

PubMed Central

Neuwirth, Christian; Hofer, Barbara; Schaumberger, Andreas

2016-01-01

Abstract Spatial system dynamics (SSD) models are typically implemented by linking stock variables to raster grids while the use of object representations of human artefacts such as buildings or ownership has been limited. This limitation is addressed by this article, which demonstrates the use of object representations in SSD. The objects are parcels of land that are attributed to grassland farms. The model simulates structural change in agriculture, i.e., change in the size of farms. The aim of the model is to reveal relations between structural change, farmland fragmentation and variable farmland quality. Results show that fragmented farms tend to become consolidated by structural change, whereas consolidated initial conditions result in a significant increase of fragmentation. Consolidation is reinforced by a dynamic land market and high transportation costs. The example demonstrates the capabilities of the object-based approach for integrating object geometries (parcel shapes) and relations between objects (distances between parcels) dynamically in SSD. PMID:28190972

Sensitivity of North American agriculture to ENSO-based climate scenarios and their socio-economic consequences: Modeling in an integrated assessment framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosenberg, N.J.; Izaurralde, R.C.; Brown, R.A.

1997-09-01

A group of Canadian, US and Mexican natural resource specialists, organized by the Pacific Northwest National Laboratory (PNNL) under its North American Energy, Environment and Economy (NA3E) Program, has applied a simulation modeling approach to estimating the impact of ENSO-driven climatic variations on the productivity of major crops grown in the three countries. Methodological development is described and results of the simulations presented in this report. EPIC (the Erosion Productivity Impact Calculator) was the agro-ecosystem model selected-for this study. EPIC uses a daily time step to simulate crop growth and yield, water use, runoff and soil erosion among other variables.more » The model was applied to a set of so-called representative farms parameterized through a specially-assembled Geographic Information System (GIS) to reflect the soils, topography, crop management and weather typical of the regions represented. Fifty one representative farms were developed for Canada, 66 for the US and 23 for Mexico. El Nino-Southern Oscillation (ENSO) scenarios for the EPIC simulations were created using the historic record of sea-surface temperature (SST) prevailing in the eastern tropical Pacific for the period October 1--September 30. Each year between 1960 and 1989 was thus assigned to an ENSO category or state. The ENSO states were defined as El Nino (EN, SST warmer than the long-term mean), Strong El Nino (SEN, much warmer), El Viejo (EV, cooler) and Neutral (within {+-}0.5 C of the long-term mean). Monthly means of temperature and precipitation were then calculated at each farm for the period 1960--1989 and the differences (or anomalies) between the means in Neutral years and EN, SEN and EV years determined. The average monthly anomalies for each ENSO state were then used to create new monthly statistics for each farm and ENSO-state combination. The adjusted monthly statistics characteristic of each ENSO state were then used to drive a stochastic-weather simulator that provided 30 years of daily-weather data needed to run EPIC. Maps and tables of the climate anomalies by farm show climatic conditions that differ considerably by region, season and ENSO state.« less

Simulation of Long-Term Carbon and Nitrogen Dynamics in Grassland-Based Dairy Farming Systems to Evaluate Mitigation Strategies for Nutrient Losses

PubMed Central

Shah, Ghulam Abbas; Groot, Jeroen C.J.; Shah, Ghulam Mustafa; Lantinga, Egbert A.

2013-01-01

Many measures have been proposed to mitigate gaseous emissions and other nutrient losses from agroecosystems, which can have large detrimental effects for the quality of soils, water and air, and contribute to eutrophication and global warming. Due to complexities in farm management, biological interactions and emission measurements, most experiments focus on analysis of short-term effects of isolated mitigation practices. Here we present a model that allows simulating long-term effects at the whole-farm level of combined measures related to grassland management, animal housing and manure handling after excretion, during storage and after field application. The model describes the dynamics of pools of organic carbon and nitrogen (N), and of inorganic N, as affected by farm management in grassland-based dairy systems. We assessed the long-term effects of delayed grass mowing, housing type (cubicle and sloping floor barns, resulting in production of slurry and solid cattle manure, respectively), manure additives, contrasting manure storage methods and irrigation after application of covered manure. Simulations demonstrated that individually applied practices often result in compensatory loss pathways. For instance, methods to reduce ammonia emissions during storage like roofing or covering of manure led to larger losses through ammonia volatilization, nitrate leaching or denitrification after application, unless extra measures like irrigation were used. A strategy of combined management practices of delayed mowing and fertilization with solid cattle manure that is treated with zeolite, stored under an impermeable sheet and irrigated after application was effective to increase soil carbon stocks, increase feed self-sufficiency and reduce losses by ammonia volatilization and soil N losses. Although long-term datasets (>25 years) of farm nutrient dynamics and loss flows are not available to validate the model, the model is firmly based on knowledge of processes and measured effects of individual practices, and allows the integrated exploration of effective emission mitigation strategies. PMID:23826255

Epidemiological modelling for the assessment of bovine tuberculosis surveillance in the dairy farm network in Emilia-Romagna (Italy).

PubMed

Rossi, Gianluigi; De Leo, Giulio A; Pongolini, Stefano; Natalini, Silvano; Vincenzi, Simone; Bolzoni, Luca

2015-06-01

Assessing the performance of a surveillance system for infectious diseases of domestic animals is a challenging task for health authorities. Therefore, it is important to assess what strategy is the most effective in identifying the onset of an epidemic and in minimizing the number of infected farms. The aim of the present work was to evaluate the performance of the bovine tuberculosis (bTB) surveillance system in the network of dairy farms in the Emilia-Romagna (ER) Region, Italy. A bTB-free Region since 2007, ER implements an integrated surveillance strategy based on three components, namely routine on-farm tuberculin skin-testing performed every 3 years, tuberculin skin-testing of cattle exchanged between farms, and post-mortem inspection at slaughterhouses. We assessed the effectiveness of surveillance by means of a stochastic network model of both within-farm and between-farm bTB dynamics calibrated on data available for ER dairy farms. Epidemic dynamics were simulated for five scenarios: the current ER surveillance system, a no surveillance scenario that we used as the benchmark to characterize epidemic dynamics, three additional scenarios in which one of the surveillance components was removed at a time so as to outline its significance in detecting the infection. For each scenario we ran Monte Carlo simulations of bTB epidemics following the random introduction of an infected individual in the network. System performances were assessed through the comparative analysis of a number of statistics, including the time required for epidemic detection and the total number of infected farms during the epidemic. Our analysis showed that slaughterhouse inspection is the most effective surveillance component in reducing the time for disease detection, while routine surveillance in reducing the number of multi-farms epidemics. On the other hand, testing exchanged cattle improved the performance of the surveillance system only marginally. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Species distribution models: A comparison of statistical approaches for livestock and disease epidemics.

PubMed

Hollings, Tracey; Robinson, Andrew; van Andel, Mary; Jewell, Chris; Burgman, Mark

2017-01-01

In livestock industries, reliable up-to-date spatial distribution and abundance records for animals and farms are critical for governments to manage and respond to risks. Yet few, if any, countries can afford to maintain comprehensive, up-to-date agricultural census data. Statistical modelling can be used as a proxy for such data but comparative modelling studies have rarely been undertaken for livestock populations. Widespread species, including livestock, can be difficult to model effectively due to complex spatial distributions that do not respond predictably to environmental gradients. We assessed three machine learning species distribution models (SDM) for their capacity to estimate national-level farm animal population numbers within property boundaries: boosted regression trees (BRT), random forests (RF) and K-nearest neighbour (K-NN). The models were built from a commercial livestock database and environmental and socio-economic predictor data for New Zealand. We used two spatial data stratifications to test (i) support for decision making in an emergency response situation, and (ii) the ability for the models to predict to new geographic regions. The performance of the three model types varied substantially, but the best performing models showed very high accuracy. BRTs had the best performance overall, but RF performed equally well or better in many simulations; RFs were superior at predicting livestock numbers for all but very large commercial farms. K-NN performed poorly relative to both RF and BRT in all simulations. The predictions of both multi species and single species models for farms and within hypothetical quarantine zones were very close to observed data. These models are generally applicable for livestock estimation with broad applications in disease risk modelling, biosecurity, policy and planning.

Species distribution models: A comparison of statistical approaches for livestock and disease epidemics

PubMed Central

Robinson, Andrew; van Andel, Mary; Jewell, Chris; Burgman, Mark

2017-01-01

In livestock industries, reliable up-to-date spatial distribution and abundance records for animals and farms are critical for governments to manage and respond to risks. Yet few, if any, countries can afford to maintain comprehensive, up-to-date agricultural census data. Statistical modelling can be used as a proxy for such data but comparative modelling studies have rarely been undertaken for livestock populations. Widespread species, including livestock, can be difficult to model effectively due to complex spatial distributions that do not respond predictably to environmental gradients. We assessed three machine learning species distribution models (SDM) for their capacity to estimate national-level farm animal population numbers within property boundaries: boosted regression trees (BRT), random forests (RF) and K-nearest neighbour (K-NN). The models were built from a commercial livestock database and environmental and socio-economic predictor data for New Zealand. We used two spatial data stratifications to test (i) support for decision making in an emergency response situation, and (ii) the ability for the models to predict to new geographic regions. The performance of the three model types varied substantially, but the best performing models showed very high accuracy. BRTs had the best performance overall, but RF performed equally well or better in many simulations; RFs were superior at predicting livestock numbers for all but very large commercial farms. K-NN performed poorly relative to both RF and BRT in all simulations. The predictions of both multi species and single species models for farms and within hypothetical quarantine zones were very close to observed data. These models are generally applicable for livestock estimation with broad applications in disease risk modelling, biosecurity, policy and planning. PMID:28837685

Large Eddy Simulation of Vertical Axis Wind Turbines

NASA Astrophysics Data System (ADS)

Hezaveh, Seyed Hossein

Due to several design advantages and operational characteristics, particularly in offshore farms, vertical axis wind turbines (VAWTs) are being reconsidered as a complementary technology to horizontal axial turbines (HAWTs). However, considerable gaps remain in our understanding of VAWT performance since they have been significantly less studied than HAWTs. This thesis examines the performance of isolated VAWTs based on different design parameters and evaluates their characteristics in large wind farms. An actuator line model (ALM) is implemented in an atmospheric boundary layer large eddy simulation (LES) code, with offline coupling to a high-resolution blade-scale unsteady Reynolds-averaged Navier-Stokes (URANS) model. The LES captures the turbine-to-farm scale dynamics, while the URANS captures the blade-to-turbine scale flow. The simulation results are found to be in good agreement with existing experimental datasets. Subsequently, a parametric study of the flow over an isolated VAWT is carried out by varying solidities, height-to-diameter aspect ratios, and tip speed ratios. The analyses of the wake area and power deficits yield an improved understanding of the evolution of VAWT wakes, which in turn enables a more informed selection of turbine designs for wind farms. One of the most important advantages of VAWTs compared to HAWTs is their potential synergistic interactions that increase their performance when placed in close proximity. Field experiments have confirmed that unlike HAWTs, VAWTs can enhance and increase the total power production when placed near each other. Based on these experiments and using ALM-LES, we also present and test new approaches for VAWT farm configuration. We first design clusters with three turbines then configure farms consisting of clusters of VAWTs rather than individual turbines. The results confirm that by using a cluster design, the average power density of wind farms can be increased by as much as 60% relative to regular arrays. Finally, the thesis conducts an investigation of the influence of farm length (parallel to the wind) to assess the fetch needed for equilibrium to be reached, as well as the origin of the kinetic energy extracted by the turbines.

Modelling Farm Animal Welfare

PubMed Central

Collins, Lisa M.; Part, Chérie E.

2013-01-01

Simple Summary In this review paper we discuss the different modeling techniques that have been used in animal welfare research to date. We look at what questions they have been used to answer, the advantages and pitfalls of the methods, and how future research can best use these approaches to answer some of the most important upcoming questions in farm animal welfare. Abstract The use of models in the life sciences has greatly expanded in scope and advanced in technique in recent decades. However, the range, type and complexity of models used in farm animal welfare is comparatively poor, despite the great scope for use of modeling in this field of research. In this paper, we review the different modeling approaches used in farm animal welfare science to date, discussing the types of questions they have been used to answer, the merits and problems associated with the method, and possible future applications of each technique. We find that the most frequently published types of model used in farm animal welfare are conceptual and assessment models; two types of model that are frequently (though not exclusively) based on expert opinion. Simulation, optimization, scenario, and systems modeling approaches are rarer in animal welfare, despite being commonly used in other related fields. Finally, common issues such as a lack of quantitative data to parameterize models, and model selection and validation are discussed throughout the review, with possible solutions and alternative approaches suggested. PMID:26487411

Validation of the Dynamic Wake Meander model with focus on tower loads

NASA Astrophysics Data System (ADS)

Larsen, T. J.; Larsen, G. C.; Pedersen, M. M.; Enevoldsen, K.; Madsen, H. A.

2017-05-01

This paper presents a comparison between measured and simulated tower loads for the Danish offshore wind farm Nysted 2. Previously, only limited full scale experimental data containing tower load measurements have been published, and in many cases the measurements include only a limited range of wind speeds. In general, tower loads in wake conditions are very challenging to predict correctly in simulations. The Nysted project offers an improved insight to this field as six wind turbines located in the Nysted II wind farm have been instrumented to measure tower top and tower bottom moments. All recorded structural data have been organized in a database, which in addition contains relevant wind turbine SCADA data as well as relevant meteorological data - e.g. wind speed and wind direction - from an offshore mast located in the immediate vicinity of the wind farm. The database contains data from a period extending over a time span of more than 3 years. Based on the recorded data basic mechanisms driving the increased loading experienced by wind turbines operating in offshore wind farm conditions have been identified, characterized and modeled. The modeling is based on the Dynamic Wake Meandering (DWM) approach in combination with the state-of-the-art aeroelastic model HAWC2, and has previously as well as in this study shown good agreement with the measurements. The conclusions from the study have several parts. In general the tower bending and yaw loads show a good agreement between measurements and simulations. However, there are situations that are still difficult to match. One is tower loads of single-wake operation near rated ambient wind speed for single wake situations for spacing’s around 7-8D. A specific target of the study was to investigate whether the largest tower fatigue loads are associated with a certain downstream distance. This has been identified in both simulations and measurements, though a rather flat optimum is seen in the measurements.

Evaluation of aqua crop simulation of early season evaporation and water flux in a semiarid environment

USDA-ARS?s Scientific Manuscript database

The AquaCrop model of crop growth, water use, yield and water use efficiency (WUE) is intended for use by extension personnel, farm and irrigation managers, planners and other less advanced users of simulation models in irrigation planning and scheduling. It could be useful in estimating changes in ...

Sensitivity analysis of the DRAINWAT model applied to an agricultural watershed in the lower coastal plain, North Carolina, USA

Treesearch

Hyunwoo Kim; Devendra M. Amatya; Stephen W. Broome; Dean L. Hesterberg; Minha Choi

2011-01-01

The DRAINWAT, DRAINmod for WATershed model, was selected for hydrological modelling to obtain water table depths and drainage outflows at Open Grounds Farm in Carteret County, North Carolina, USA. Six simulated storm events from the study period were compared with the measured data and analysed. Simulation results from the whole study period and selected rainfall...

IBSEM: An Individual-Based Atlantic Salmon Population Model

PubMed Central

Castellani, Marco; Heino, Mikko; Gilbey, John; Araki, Hitoshi; Svåsand, Terje; Glover, Kevin A.

2015-01-01

Ecology and genetics can influence the fate of individuals and populations in multiple ways. However, to date, few studies consider them when modelling the evolutionary trajectory of populations faced with admixture with non-local populations. For the Atlantic salmon, a model incorporating these elements is urgently needed because many populations are challenged with gene-flow from non-local and domesticated conspecifics. We developed an Individual-Based Salmon Eco-genetic Model (IBSEM) to simulate the demographic and population genetic change of an Atlantic salmon population through its entire life-cycle. Processes such as growth, mortality, and maturation are simulated through stochastic procedures, which take into account environmental variables as well as the genotype of the individuals. IBSEM is based upon detailed empirical data from salmon biology, and parameterized to reproduce the environmental conditions and the characteristics of a wild population inhabiting a Norwegian river. Simulations demonstrated that the model consistently and reliably reproduces the characteristics of the population. Moreover, in absence of farmed escapees, the modelled populations reach an evolutionary equilibrium that is similar to our definition of a ‘wild’ genotype. We assessed the sensitivity of the model in the face of assumptions made on the fitness differences between farm and wild salmon, and evaluated the role of straying as a buffering mechanism against the intrusion of farm genes into wild populations. These results demonstrate that IBSEM is able to capture the evolutionary forces shaping the life history of wild salmon and is therefore able to model the response of populations under environmental and genetic stressors. PMID:26383256

Using heterogeneity in the population structure of U.S. swine farms to compare transmission models for porcine epidemic diarrhoea

PubMed Central

O’Dea, Eamon B.; Snelson, Harry; Bansal, Shweta

2016-01-01

In 2013, U.S. swine producers were confronted with the disruptive emergence of porcine epidemic diarrhoea (PED). Movement of animals among farms is hypothesised to have played a role in the spread of PED among farms. Via this or other mechanisms, the rate of spread may also depend on the geographic density of farms and climate. To evaluate such effects on a large scale, we analyse state-level counts of outbreaks with variables describing the distribution of farm sizes and types, aggregate flows of animals among farms, and an index of climate. Our first main finding is that it is possible for a correlation analysis to be sensitive to transmission model parameters. This finding is based on a global sensitivity analysis of correlations on simulated data that included a biased and noisy observation model based on the available PED data. Our second main finding is that flows are significantly associated with the reports of PED outbreaks. This finding is based on correlations of pairwise relationships and regression modeling of total and weekly outbreak counts. These findings illustrate how variation in population structure may be employed along with observational data to improve understanding of disease spread. PMID:26947420

Spatiotemporal Variation in Distance Dependent Animal Movement Contacts: One Size Doesn’t Fit All

PubMed Central

Brommesson, Peter; Wennergren, Uno; Lindström, Tom

2016-01-01

The structure of contacts that mediate transmission has a pronounced effect on the outbreak dynamics of infectious disease and simulation models are powerful tools to inform policy decisions. Most simulation models of livestock disease spread rely to some degree on predictions of animal movement between holdings. Typically, movements are more common between nearby farms than between those located far away from each other. Here, we assessed spatiotemporal variation in such distance dependence of animal movement contacts from an epidemiological perspective. We evaluated and compared nine statistical models, applied to Swedish movement data from 2008. The models differed in at what level (if at all), they accounted for regional and/or seasonal heterogeneities in the distance dependence of the contacts. Using a kernel approach to describe how probability of contacts between farms changes with distance, we developed a hierarchical Bayesian framework and estimated parameters by using Markov Chain Monte Carlo techniques. We evaluated models by three different approaches of model selection. First, we used Deviance Information Criterion to evaluate their performance relative to each other. Secondly, we estimated the log predictive posterior distribution, this was also used to evaluate their relative performance. Thirdly, we performed posterior predictive checks by simulating movements with each of the parameterized models and evaluated their ability to recapture relevant summary statistics. Independent of selection criteria, we found that accounting for regional heterogeneity improved model accuracy. We also found that accounting for seasonal heterogeneity was beneficial, in terms of model accuracy, according to two of three methods used for model selection. Our results have important implications for livestock disease spread models where movement is an important risk factor for between farm transmission. We argue that modelers should refrain from using methods to simulate animal movements that assume the same pattern across all regions and seasons without explicitly testing for spatiotemporal variation. PMID:27760155

Short-term Wind Forecasting at Wind Farms using WRF-LES and Actuator Disk Model

NASA Astrophysics Data System (ADS)

Kirkil, Gokhan

2017-04-01

Short-term wind forecasts are obtained for a wind farm on a mountainous terrain using WRF-LES. Multi-scale simulations are also performed using different PBL parameterizations. Turbines are parameterized using Actuator Disc Model. LES models improved the forecasts. Statistical error analysis is performed and ramp events are analyzed. Complex topography of the study area affects model performance, especially the accuracy of wind forecasts were poor for cross valley-mountain flows. By means of LES, we gain new knowledge about the sources of spatial and temporal variability of wind fluctuations such as the configuration of wind turbines.

A predictive control framework for optimal energy extraction of wind farms

NASA Astrophysics Data System (ADS)

Vali, M.; van Wingerden, J. W.; Boersma, S.; Petrović, V.; Kühn, M.

2016-09-01

This paper proposes an adjoint-based model predictive control for optimal energy extraction of wind farms. It employs the axial induction factor of wind turbines to influence their aerodynamic interactions through the wake. The performance index is defined here as the total power production of the wind farm over a finite prediction horizon. A medium-fidelity wind farm model is utilized to predict the inflow propagation in advance. The adjoint method is employed to solve the formulated optimization problem in a cost effective way and the first part of the optimal solution is implemented over the control horizon. This procedure is repeated at the next controller sample time providing the feedback into the optimization. The effectiveness and some key features of the proposed approach are studied for a two turbine test case through simulations.

Spatiotemporal distribution of nitrogen dioxide within and around a large-scale wind farm - a numerical case study

NASA Astrophysics Data System (ADS)

Mo, Jingyue; Huang, Tao; Zhang, Xiaodong; Zhao, Yuan; Liu, Xiao; Li, Jixiang; Gao, Hong; Ma, Jianmin

2017-12-01

As a renewable and clean energy source, wind power has become the most rapidly growing energy resource worldwide in the past decades. Wind power has been thought not to exert any negative impacts on the environment. However, since a wind farm can alter the local meteorological conditions and increase the surface roughness lengths, it may affect air pollutants passing through and over the wind farm after released from their sources and delivered to the wind farm. In the present study, we simulated the nitrogen dioxide (NO2) air concentration within and around the world's largest wind farm (Jiuquan wind farm in Gansu Province, China) using a coupled meteorology and atmospheric chemistry model WRF-Chem. The results revealed an edge effect, which featured higher NO2 levels at the immediate upwind and border region of the wind farm and lower NO2 concentration within the wind farm and the immediate downwind transition area of the wind farm. A surface roughness length scheme and a wind turbine drag force scheme were employed to parameterize the wind farm in this model investigation. Modeling results show that both parameterization schemes yield higher concentration in the immediate upstream of the wind farm and lower concentration within the wind farm compared to the case without the wind farm. We infer this edge effect and the spatial distribution of air pollutants to be the result of the internal boundary layer induced by the changes in wind speed and turbulence intensity driven by the rotation of the wind turbine rotor blades and the enhancement of surface roughness length over the wind farm. The step change in the roughness length from the smooth to rough surfaces (overshooting) in the upstream of the wind farm decelerates the atmospheric transport of air pollutants, leading to their accumulation. The rough to the smooth surface (undershooting) in the downstream of the wind farm accelerates the atmospheric transport of air pollutants, resulting in lower concentration level.

Evaluation of weather-based rice yield models in India.

PubMed

Sudharsan, D; Adinarayana, J; Reddy, D Raji; Sreenivas, G; Ninomiya, S; Hirafuji, M; Kiura, T; Tanaka, K; Desai, U B; Merchant, S N

2013-01-01

The objective of this study was to compare two different rice simulation models--standalone (Decision Support System for Agrotechnology Transfer [DSSAT]) and web based (SImulation Model for RIce-Weather relations [SIMRIW])--with agrometeorological data and agronomic parameters for estimation of rice crop production in southern semi-arid tropics of India. Studies were carried out on the BPT5204 rice variety to evaluate two crop simulation models. Long-term experiments were conducted in a research farm of Acharya N G Ranga Agricultural University (ANGRAU), Hyderabad, India. Initially, the results were obtained using 4 years (1994-1997) of data with weather parameters from a local weather station to evaluate DSSAT simulated results with observed values. Linear regression models used for the purpose showed a close relationship between DSSAT and observed yield. Subsequently, yield comparisons were also carried out with SIMRIW and DSSAT, and validated with actual observed values. Realizing the correlation coefficient values of SIMRIW simulation values in acceptable limits, further rice experiments in monsoon (Kharif) and post-monsoon (Rabi) agricultural seasons (2009, 2010 and 2011) were carried out with a location-specific distributed sensor network system. These proximal systems help to simulate dry weight, leaf area index and potential yield by the Java based SIMRIW on a daily/weekly/monthly/seasonal basis. These dynamic parameters are useful to the farming community for necessary decision making in a ubiquitous manner. However, SIMRIW requires fine tuning for better results/decision making.

Carbon farming economics: What have we learned?

PubMed

Tang, Kai; Kragt, Marit E; Hailu, Atakelty; Ma, Chunbo

2016-05-01

This study reviewed 62 economic analyses published between 1995 and 2014 on the economic impacts of policies that incentivise agricultural greenhouse (GHG) mitigation. Typically, biophysical models are used to evaluate the changes in GHG mitigation that result from landholders changing their farm and land management practices. The estimated results of biophysical models are then integrated with economic models to simulate the costs of different policy scenarios to production systems. The cost estimates vary between $3 and $130/t CO2 equivalent in 2012 US dollars, depending on the mitigation strategies, spatial locations, and policy scenarios considered. Most studies assessed the consequences of a single, rather than multiple, mitigation strategies, and few considered the co-benefits of carbon farming. These omissions could challenge the reality and robustness of the studies' results. One of the biggest challenges facing agricultural economists is to assess the full extent of the trade-offs involved in carbon farming. We need to improve our biophysical knowledge about carbon farming co-benefits, predict the economic impacts of employing multiple strategies and policy incentives, and develop the associated integrated models, to estimate the full costs and benefits of agricultural GHG mitigation to farmers and the rest of society. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simulations for Making On-farm Decisions in Relation to ENSO in Semi-arid Areas, South Africa

NASA Astrophysics Data System (ADS)

Tesfuhuney, W. A.; Crespo, O. O.; Walker, S. S.; Steyn, S. A.

2017-12-01

The study was employed to investigate and improve on-farm decision making on planting dates and fertilization by relating simulated yield and seasonal outlook information. The Agricultural Production Systems SIMulator model (APSIM) was used to explore ENSO/SOI effects for small-scale farmers to represent weather conditions and soil forms of semi-arid areas of Bothaville, Bethlehem and Bloemfontein regions in South Africa. The relationships of rainfall and SOI anomalies indicate a positive correlation, signifies ENSO/SOI as seasonal outlooks for study areas. Model evaluation results showed higher degree of bias (RMSEs/RMSE value of 0.88-0.98). The D-index of agreement in the range 0.61-0.71 indicate the ability of the APSIM-Maize model is an adequate tool in evaluating relative changes in maize yield in relation to various management practices and seasonal variations. During rainy, La Niño years (SOI > +5), highest simulated yields were found for Bethlehem in November with addition of 100 - 150 kg ha-1 N fertilization and up to 50 kg ha-1 for both Bothaville and Bloemfontein. With respect to various levels of fertilization, the dry El Niño years (SOI < -5) had a range of 0.90-1.31, 3.03-3.54 and 1.11-1.26 t ha-1 yields and showed to increase during La Niña years with a range of 2.50-2.66, 3.36-4.79 and 2.24-2.38 t ha-1 at Bothaville, Bethlehem and Bloemfontein for November planting. During El Niño episodes planting earlier and using 50 kg ha-1 fertilizer with improved short maturing cultivar are effective adaptation measures to counteract poor soils and erratic rainfall of semi-arid environment, Under optimal soil conditions and/or when probability of La Niño episodes, optimal yields are obtained by maximizing fertilization. Effective rainfall and tactical on-farm management decisions in associate with seasonal rainfall out looks information is a useful mechanism in reducing risk for dryland farming in semi-arid regions. Key word: Semi-arid; APSIM; SOI; El Niño / La Niña; On-farm Decisions

Disease spread models to estimate highly uncertain emerging diseases losses for animal agriculture insurance policies: an application to the U.S. farm-raised catfish industry.

PubMed

Zagmutt, Francisco J; Sempier, Stephen H; Hanson, Terril R

2013-10-01

Emerging diseases (ED) can have devastating effects on agriculture. Consequently, agricultural insurance for ED can develop if basic insurability criteria are met, including the capability to estimate the severity of ED outbreaks with associated uncertainty. The U.S. farm-raised channel catfish (Ictalurus punctatus) industry was used to evaluate the feasibility of using a disease spread simulation modeling framework to estimate the potential losses from new ED for agricultural insurance purposes. Two stochastic models were used to simulate the spread of ED between and within channel catfish ponds in Mississippi (MS) under high, medium, and low disease impact scenarios. The mean (95% prediction interval (PI)) proportion of ponds infected within disease-impacted farms was 7.6% (3.8%, 22.8%), 24.5% (3.8%, 72.0%), and 45.6% (4.0%, 92.3%), and the mean (95% PI) proportion of fish mortalities in ponds affected by the disease was 9.8% (1.4%, 26.7%), 49.2% (4.7%, 60.7%), and 88.3% (85.9%, 90.5%) for the low, medium, and high impact scenarios, respectively. The farm-level mortality losses from an ED were up to 40.3% of the total farm inventory and can be used for insurance premium rate development. Disease spread modeling provides a systematic way to organize the current knowledge on the ED perils and, ultimately, use this information to help develop actuarially sound agricultural insurance policies and premiums. However, the estimates obtained will include a large amount of uncertainty driven by the stochastic nature of disease outbreaks, by the uncertainty in the frequency of future ED occurrences, and by the often sparse data available from past outbreaks. © 2013 Society for Risk Analysis.

How to measure the agroecological performance of farming in order to assist with the transition process.

PubMed

Trabelsi, Meriam; Mandart, Elisabeth; Le Grusse, Philippe; Bord, Jean-Paul

2016-01-01

The use of plant protection products enables farmers to maximize economic performance and yields, but in return, the environment and human health can be greatly affected because of their toxicity. There are currently strong calls for farmers to reduce the use of these toxic products for the preservation of the environment and the human health, and it has become urgent to invest in more sustainable models that help reduce these risks. One possible solution is the transition toward agroecological production systems. These new systems must be beneficial economically, socially, and environmentally in terms of human health. There are many tools available, based on a range of indicators, for assessing the sustainability of agricultural systems on conventional farm holdings. These methods are little suitable to agroecological farms and do not measure the performance of agroecological transition farms. In this article, we therefore develop a model for the strategic definition, guidance, and assistance for a transition to agroecological practices, capable of assessing performance of this transition and simulating the consequences of possible changes. This model was built by coupling (i) a decision-support tool and a technico-economic simulator with (ii) a conceptual model built from the dynamics of agroecological practices. This tool is currently being tested in the framework of a Compte d'Affectation Spéciale pour le Développement Agricole et Rural (CASDAR) project (CASDAR: project launched in 2013 by the French Ministry of Agriculture, Food and Forestry, on the theme "collective mobilisation for agroecology," http://agriculture.gouv.fr/Appel-a-projets-CASDAR ) using data from farms, most of which are engaged in agroenvironmental process and reducing plant protection treatments since 2008.

A process-based model for cattle manure compost windrows: Model performance and application

USDA-ARS?s Scientific Manuscript database

A model was developed and incorporated in the Integrated Farm System Model (IFSM, v.4.3) that simulates important processes occurring during windrow composting of manure. The model, documented in an accompanying paper, predicts changes in windrow properties and conditions and the resulting emissions...

A Dynamic Simulation Model of Land-Use, Population, and Rural Livelihoods in the Central Rift Valley of Ethiopia

NASA Astrophysics Data System (ADS)

Garedew, Efrem; Sandewall, Mats; Soderberg, Ulf

2012-01-01

The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years and to improve our understanding of the interactions among them. The modeling output is characterized by rapid population growth, declining farm size and household incomes, deteriorating woody vegetation cover and worsening land degradation if current conditions remain. However, through integrated intervention strategies (including forest increase, micro-finance, family planning, health and education) the woody vegetation cover is likely to increase in the landscape, population growth is likely to slow down and households' income is likely to improve. A validation assessment of the simulation model based on historical data on land-use and population from 1973 to 2006 showed that the model is relatively robust. We conclude that as a supporting tool, the simulation model can contribute to the decision making process.

Modelling the fate of pesticides in paddy rice-fish pond farming system in Northern Vietnam

NASA Astrophysics Data System (ADS)

Lamers, M.; Nguyen, N.; Streck, T.

2012-04-01

During the last decade rice production in Vietnam has tremendously increased due to the introduction of new high yield, short duration rice varieties and an increased application of pesticides. Since pesticides are toxic by design, there is a natural concern on the possible impacts of their presence in the environment on human health and environment quality. In North Vietnam, lowland and upland rice fields were identified to be a major non-point source of agrochemical pollution to surface and ground water, which are often directly used for domestic purposes. Field measurements, however, are time consuming, costly and logistical demanding. Hence, quantification, forecast and risk assessment studies are hampered by a limited amount of field data. One potential way to cope with this shortcoming is the use of process-based models. In the present study we developed a model for simulating short-term pesticide dynamics in combined paddy rice field - fish pond farming systems under the specific environmental conditions of south-east Asia. Basic approaches and algorithms to describe the key underlying biogeochemical processes were mainly adopted from the literature to assure that the model reflects the current standard of scientific knowledge and commonly accepted theoretical background. The model was calibrated by means of the Gauss-Marquardt-Levenberg algorithm and validated against measured pesticide concentrations (dimethoate and fenitrothion) during spring and summer rice crop season 2008, respectively, of a paddy field - fish pond system typical for northern Vietnam. First simulation results indicate that our model is capable to simulate the fate of pesticides in such paddy - fish pond farming systems. The model efficiency for the period of calibration, for example, was 0.97 and 0.95 for dimethoate and fenitrothion, respectively. For the period of validation, however, the modeling efficiency slightly decreased to 0.96 and 0.81 for dimethoate and fenitrothion, respectively. In our presentation we will picture key model features and algorithms and demonstrate that our model provides a useful and appropriate tool for analyzing and quantifying the transport and behavior of pesticides in paddy rice farming systems.

Economic efficiency analysis of different strategies to control post-weaning multi-systemic wasting syndrome and porcine circovirus type 2 subclinical infection in 3-weekly batch system farms

PubMed Central

Alarcon, Pablo; Rushton, Jonathan; Nathues, Heiko; Wieland, Barbara

2013-01-01

The study assessed the economic efficiency of different strategies for the control of post-weaning multi-systemic wasting syndrome (PMWS) and porcine circovirus type 2 subclinical infection (PCV2SI), which have a major economic impact on the pig farming industry worldwide. The control strategies investigated consisted on the combination of up to 5 different control measures. The control measures considered were: (1) PCV2 vaccination of piglets (vac); (2) ensuring age adjusted diet for growers (diets); (3) reduction of stocking density (stock); (4) improvement of biosecurity measures (bios); and (5) total depopulation and repopulation of the farm for the elimination of other major pathogens (DPRP). A model was developed to simulate 5 years production of a pig farm with a 3-weekly batch system and with 100 sows. A PMWS/PCV2SI disease and economic model, based on PMWS severity scores, was linked to the production model in order to assess disease losses. This PMWS severity scores depends on the combination post-weaning mortality, PMWS morbidity in younger pigs and proportion of PCV2 infected pigs observed on farms. The economic analysis investigated eleven different farm scenarios, depending on the number of risk factors present before the intervention. For each strategy, an investment appraisal assessed the extra costs and benefits of reducing a given PMWS severity score to the average score of a slightly affected farm. The net present value obtained for each strategy was then multiplied by the corresponding probability of success to obtain an expected value. A stochastic simulation was performed to account for uncertainty and variability. For moderately affected farms PCV2 vaccination alone was the most cost-efficient strategy, but for highly affected farms it was either PCV2 vaccination alone or in combination with biosecurity measures, with the marginal profitability between ‘vac’ and ‘vac + bios’ being small. Other strategies such as ‘diets’, ‘vac + diets’ and ‘bios + diets’ were frequently identified as the second or third best strategy. The mean expected values of the best strategy for a moderately and a highly affected farm were £14,739 and £57,648 after 5 years, respectively. This is the first study to compare economic efficiency of control strategies for PMWS and PCV2SI. The results demonstrate the economic value of PCV2 vaccination, and highlight that on highly affected farms biosecurity measures are required to achieve optimal profitability. The model developed has potential as a farm-level decision support tool for the control of this economically important syndrome. PMID:23375866

Economic modelling of grazing management against gastrointestinal nematodes in dairy cattle.

PubMed

van der Voort, M; Van Meensel, J; Lauwers, L; de Haan, M H A; Evers, A G; Van Huylenbroeck, G; Charlier, J

2017-03-15

Grazing management (GM) interventions, such as reducing the grazing time or mowing pasture before grazing, have been proposed to limit the exposure to gastrointestinal (GI) nematode infections in grazed livestock. However, the farm-level economic effects of these interventions have not yet been assessed. In this paper, the economic effects of three GM interventions in adult dairy cattle were modelled for a set of Flemish farms: later turnout on pasture (GM1), earlier housing near the end of the grazing season (GM2), and reducing the daily grazing time (GM3). Farm accountancy data were linked to Ostertagia ostertagi bulk tank milk ELISA results and GM data for 137 farms. The economic effects of the GM interventions were investigated through a combination of efficiency analysis and a whole-farm simulation model. Modelling of GM1, GM2 and GM3 resulted in a marginal economic effect of € 8.36, € -9.05 and € -53.37 per cow per year, respectively. The results suggest that the dairy farms can improve their economic performance by postponing the turnout date, but that advancing the housing date or reducing daily grazing time mostly leads to a lower net economic farm performance. Overall, the GM interventions resulted in a higher technical efficiency and milk production but these benefits were offset by increased feed costs as a result of higher maintenance and cultivation costs. Because the results differed highly between farms, GM interventions need to be evaluated at the individual level for appropriate decision support. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-time scale energy management of wind farms based on comprehensive evaluation technology

NASA Astrophysics Data System (ADS)

Xu, Y. P.; Huang, Y. H.; Liu, Z. J.; Wang, Y. F.; Li, Z. Y.; Guo, L.

2017-11-01

A novel energy management of wind farms is proposed in this paper. Firstly, a novel comprehensive evaluation system is proposed to quantify economic properties of each wind farm to make the energy management more economical and reasonable. Then, a combination of multi time-scale schedule method is proposed to develop a novel energy management. The day-ahead schedule optimizes unit commitment of thermal power generators. The intraday schedule is established to optimize power generation plan for all thermal power generating units, hydroelectric generating sets and wind power plants. At last, the power generation plan can be timely revised in the process of on-line schedule. The paper concludes with simulations conducted on a real provincial integrated energy system in northeast China. Simulation results have validated the proposed model and corresponding solving algorithms.

Impacts of drought on grape yields in Western Cape, South Africa

NASA Astrophysics Data System (ADS)

Araujo, Julio A.; Abiodun, Babatunde J.; Crespo, Olivier

2016-01-01

Droughts remain a threat to grape yields in South Africa. Previous studies on the impacts of climate on grape yield in the country have focussed on the impact of rainfall and temperature separately; meanwhile, grape yields are affected by drought, which is a combination of rainfall and temperature influences. The present study investigates the impacts of drought on grape yields in the Western Cape (South Africa) at district and farm scales. The study used a new drought index that is based on simple water balance (Standardized Precipitation Evapotranspiration Index; hereafter, SPEI) to identify drought events and used a correlation analysis to identify the relationship between drought and grape yields. A crop simulation model (Agricultural Production Systems sIMulator, APSIM) was applied at the farm scale to investigate the role of irrigation in mitigating the impacts of drought on grape yield. The model gives a realistic simulation of grape yields. The Western Cape has experienced a series of severe droughts in the past few decades. The severe droughts occurred when a decrease in rainfall occurred simultaneously with an increase in temperature. El Niño Southern Oscillation (ENSO) appears to be an important driver of drought severity in the Western Cape, because most of the severe droughts occurred in El Niño years. At the district scale, the correlation between drought index and grape yield is weak ( r≈-0.5), but at the farm scale, it is strong ( r≈-0.9). This suggests that many farmers are able to mitigate the impacts of drought on grape yields through irrigation management. At the farm scale, where the impact of drought on grape yields is high, poor yield years coincide with moderate or severe drought periods. The APSIM simulation, which gives a realistic simulation of grape yields at the farm scale, suggests that grape yields become more sensitive to spring and summer droughts in the absence of irrigation. Results of this study may guide decision-making on how to reduce the impacts of drought on food security in South Africa.

Role of animal movement and indirect contact among farms in transmission of porcine epidemic diarrhea virus.

PubMed

VanderWaal, Kimberly; Perez, Andres; Torremorrell, Montse; Morrison, Robert M; Craft, Meggan

2018-04-12

Epidemiological models of the spread of pathogens in livestock populations primarily focus on direct contact between farms based on animal movement data, and in some cases, local spatial spread based on proximity between premises. The roles of other types of indirect contact among farms is rarely accounted for. In addition, data on animal movements is seldom available in the United States. However, the spread of porcine epidemic diarrhea virus (PEDv) in U.S. swine represents one of the best documented emergences of a highly infectious pathogen in the U.S. livestock industry, providing an opportunity to parameterize models of pathogen spread via direct and indirect transmission mechanisms in swine. Using observed data on pig movements during the initial phase of the PEDv epidemic, we developed a network-based and spatially explicit epidemiological model that simulates the spread of PEDv via both indirect and direct movement-related contact in order to answer unresolved questions concerning factors facilitating between-farm transmission. By modifying the likelihood of each transmission mechanism and fitting this model to observed epidemiological dynamics, our results suggest that between-farm transmission was primarily driven by direct mechanisms related to animal movement and indirect mechanisms related to local spatial spread based on geographic proximity. However, other forms of indirect transmission among farms, including contact via contaminated vehicles and feed, were responsible for high consequence transmission events resulting in the introduction of the virus into new geographic areas. This research is among the first reports of farm-level animal movements in the U.S. swine industry and, to our knowledge, represents the first epidemiological model of commercial U.S. swine using actual data on farm-level animal movement. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Predicting the effectiveness of depth-based technologies to prevent salmon lice infection using a dispersal model.

PubMed

Samsing, Francisca; Johnsen, Ingrid; Stien, Lars Helge; Oppedal, Frode; Albretsen, Jon; Asplin, Lars; Dempster, Tim

2016-07-01

Salmon lice is one of the major parasitic problems affecting wild and farmed salmonid species. The planktonic larval stages of these marine parasites can survive for extended periods without a host and are transported long distances by water masses. Salmon lice larvae have limited swimming capacity, but can influence their horizontal transport by vertical positioning. Here, we adapted a coupled biological-physical model to calculate the distribution of farm-produced salmon lice (Lepeophtheirus salmonis) during winter in the southwest coast of Norway. We tested 4 model simulations to see which best represented empirical data from two sources: (1) observed lice infection levels reported by farms; and (2) experimental data from a vertical exposure experiment where fish were forced to swim at different depths with a lice-barrier technology. Model simulations tested were different development time to the infective stage (35 or 50°-days), with or without the presence of temperature-controlled vertical behaviour of lice early planktonic stages (naupliar stages). The best model fit occurred with a 35°-day development time to the infective stage, and temperature-controlled vertical behaviour. We applied this model to predict the effectiveness of depth-based preventive lice-barrier technologies. Both simulated and experimental data revealed that hindering fish from swimming close to the surface efficiently reduced lice infection. Moreover, while our model simulation predicted that this preventive technology is widely applicable, its effectiveness will depend on environmental conditions. Low salinity surface waters reduce the effectiveness of this technology because salmon lice avoid these conditions, and can encounter the fish as they sink deeper in the water column. Correctly parameterized and validated salmon lice dispersal models can predict the impact of preventive approaches to control this parasite and become an essential tool in lice management strategies. Copyright © 2016 Elsevier B.V. All rights reserved.

Using models to establish the financially optimum strategy for Irish dairy farms.

PubMed

Ruelle, E; Delaby, L; Wallace, M; Shalloo, L

2018-01-01

Determining the effect of a change in management on farm with differing characteristics is a significant challenge in the evaluation of dairy systems due to the interacting components of complex biological systems. In Ireland, milk production is increasing substantially following the abolition of the European Union milk quota regime in 2015. There are 2 main ways to increase the milk production on farm (within a fixed land base): either increase the number of animals (thus increasing the stocking rate) or increase the milk production per animal through increased feeding or increased lactation length. In this study, the effect of increased concentrate feeding or an increase in grazing intensity was simulated to determine the effect on the farm system and its economic performance. Four stocking rates (2.3, 2.6, 2.9, and 3.2 cow/ha) and 5 different concentrate supplementation strategies (0, 180, 360, 600, and 900 kg of dry matter/lactation) resulting in 20 different scenarios were evaluated across different milk, concentrate, and silage purchase prices. Each simulation was run across 10 yr of meteorological data, which had been recorded over the period 2004 to 2013. Three models-the Moorepark and St Gilles grass growth model, the pasture-based herd dynamic milk model, and the Moorepark dairy systems model-were integrated and applied to simulate the different scenarios. Overall, this study has demonstrated that the most profitable scenario was a stocking rate of 2.6 cow/ha with a concentrate supplementation of 600 kg of dry matter/cow. The factor that had the greatest influence on profitability was variability of milk price. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Modeling the fate and transport of bacteria in agricultural and pasture lands using APEX

USDA-ARS?s Scientific Manuscript database

The Agricultural Policy/Environmental eXtender (APEX) model is a whole farm to small watershed scale continuous simulation model developed for evaluating various land management strategies. The current version, APEX0806, does not have the modeling capacity for fecal indicator bacteria fate and trans...

APEX simulation of runoff and total phosphorous for three adjacent row-crop watersheds with claypan soils

USDA-ARS?s Scientific Manuscript database

The Agricultural Policy Environmental Extender (APEX) model can simulate crop yields, runoff, and the transport of sediment and nutrients in small watersheds that have combinations of farm level landscapes, cropping systems and/or management practices. The objectives of the study were to parameteri...

Modeling velocity space-time correlations in wind farms

NASA Astrophysics Data System (ADS)

Lukassen, Laura J.; Stevens, Richard J. A. M.; Meneveau, Charles; Wilczek, Michael

2016-11-01

Turbulent fluctuations of wind velocities cause power-output fluctuations in wind farms. The statistics of velocity fluctuations can be described by velocity space-time correlations in the atmospheric boundary layer. In this context, it is important to derive simple physics-based models. The so-called Tennekes-Kraichnan random sweeping hypothesis states that small-scale velocity fluctuations are passively advected by large-scale velocity perturbations in a random fashion. In the present work, this hypothesis is used with an additional mean wind velocity to derive a model for the spatial and temporal decorrelation of velocities in wind farms. It turns out that in the framework of this model, space-time correlations are a convolution of the spatial correlation function with a temporal decorrelation kernel. In this presentation, first results on the comparison to large eddy simulations will be presented and the potential of the approach to characterize power output fluctuations of wind farms will be discussed. Acknowledgements: 'Fellowships for Young Energy Scientists' (YES!) of FOM, the US National Science Foundation Grant IIA 1243482, and support by the Max Planck Society.

Likelihood of a marine vessel accident from wind energy development in the Atlantic: Likelihood of shipping accident from wind energy in the Atlantic

DOE Office of Scientific and Technical Information (OSTI.GOV)

Copping, Andrea; Breithaupt, Stephen; Whiting, Jonathan

2015-11-02

Offshore wind energy development is planned for areas off the Atlantic coast. Many of the planned wind development areas fall within traditional commercial vessel routes. In order to mitigate possible hazards to ships and to wind turbines, it is important to understand the potential for increased risk to commercial shipping from the presence of wind farms. Using Automatic Identification System (AIS) data, historical shipping routes between ports in the Atlantic were identified, from Maine to the Florida Straits. The AIS data were also used as inputs to a numerical model that can simulate cargo, tanker and tug/towing vessel movement alongmore » typical routes. The model was used to recreate present day vessel movement, as well as to simulate future routing that may be required to avoid wind farms. By comparing the present and future routing of vessels, a risk analysis was carried out to determine the increased marginal risk of vessel collisions, groundings, and allisions with stationary objects, due to the presence of wind farms. The outcome of the analysis showed little increase in vessel collisions or allisions, and a decrease in groundings as more vessels were forced seaward by the wind farms.« less

Wind-farm simulation over moderately complex terrain

NASA Astrophysics Data System (ADS)

Segalini, Antonio; Castellani, Francesco

2017-05-01

A comparison between three independent software to estimate the power production and the flow field in a wind farm is conducted, validating them against SCADA (Supervisory, Control And Data Acquisition) data. The three software were ORFEUS, WindSim and WAsP: ORFEUS and WAsP are linearised solvers, while WindSim is fully nonlinear. A wake model (namely a prescribed velocity deficit associated to the turbines) is used by WAsP, while ORFEUS and WindSim use the actuator-disc method to account for the turbines presence. The comparison indicates that ORFEUS and WAsP perform slightly better than WindSim in the assessment of the polar efficiency. The wakes simulated with ORFEUS appear more persistent than the ones of WindSim, which uses a two-equation closure model for the turbulence effects.

Huntington II Simulation Program - TAG. Student Workbook, Teacher's Guide, and Resource Handbook.

ERIC Educational Resources Information Center

Friedland, James

Presented are instructions for the use of "TAG," a model for estimating animal population in a given area. The computer program asks the student to estimate the number of bass in a simulated farm pond using the technique of tagging and recovery. The objective of the simulation is to teach principles for estimating animal populations when they…

Soil erosion measurements under organic and conventional land use treatments and different tillage systems using micro-scale runoff plots and a portable rainfall simulator

NASA Astrophysics Data System (ADS)

Seitz, Steffen; Goebes, Philipp; Song, Zhengshan; Wittwer, Raphaël; van der Heijden, Marcel; Scholten, Thomas

2015-04-01

Soil erosion is a major environmental problem of our time and negatively affects soil organic matter (SOM), aggregate stability or nutrient availability for instance. It is well known that agricultural practices have a severe influence on soil erosion by water. Several long-term field trials show that the use of low input strategies (e.g. organic farming) instead of conventional high-input farming systems leads to considerable changes of soil characteristics. Organic farming relies on crop rotation, absence of agrochemicals, green manure and weed control without herbicides. As a consequence, SOM content in the top soil layer is usually higher than on arable land under conventional use. Furthermore, the soil surface is better protected against particle detachment and overland flow due to a continuous vegetation cover and a well-developed root system increases soil stability. Likewise, tillage itself can cause soil erosion on arable land. In this respect, conservation and reduced tillage systems like No-Till or Ridge-Till provide a protecting cover from the previous year's residue and reduce soil disturbance. Many studies have been carried out on the effect of farming practices on soil erosion, but with contrasting results. To our knowledge, most of those studies rely on soil erosion models to calculate soil erosion rates and replicated experimental field measurement designs are rarely used. In this study, we performed direct field assessment on a farming system trial in Rümlang, Switzerland (FAST: Farming System and Tillage experiment Agroscope) to investigate the effect of organic farming practises and tillage systems on soil erosion. A portable single nozzle rainfall simulator and a light weight tent have been used with micro-scale runoff plots (0.4 m x 0.4 m). Four treatments (Conventional/Tillage, Conventional/No-Tillage, Organic/Tillage, Organic/Reduced-tillage) have been sampled with 8 replications each for a total of 32 runoff plots. All plots have been distributed randomly within the treatments. Linear mixed effect modelling was used to examine the effects of the treatments on sediment discharge and surface runoff. Results were compared with recent findings from erosion models and laboratory studies. Results show that sediment discharge is significantly higher (59 %, p=0.018) on conventional treatments (31.8 g/m2/h) than on organic treatments (20.0 g/m2/h). This finding supports results from several studies, which found soil erosion rates from 18 % to 184 % higher on conventional than on organic treatments. Under both farming systems, ploughed treatments show higher sediment discharge (conventional farming: 104 %, organic farming: 133 %, p=0.004) than treatments with reduced or no tillage. Runoff volume did not show significant effects in our treatments. An interaction between the farming practice and the tillage system could not be found, which strengthens the importance of both. With the help of a well-replicated micro-scale runoff plot design and a portable rainfall simulator we were able to gather reliable soil erosion data in situ in short term and without external parameterization. Our field assessment shows that organic farming and reduced tillage practices protect agricultural land best against soil erosion.

A mechanistic model for electricity consumption on dairy farms: definition, validation, and demonstration.

PubMed

Upton, J; Murphy, M; Shalloo, L; Groot Koerkamp, P W G; De Boer, I J M

2014-01-01

Our objective was to define and demonstrate a mechanistic model that enables dairy farmers to explore the impact of a technical or managerial innovation on electricity consumption, associated CO2 emissions, and electricity costs. We, therefore, (1) defined a model for electricity consumption on dairy farms (MECD) capable of simulating total electricity consumption along with related CO2 emissions and electricity costs on dairy farms on a monthly basis; (2) validated the MECD using empirical data of 1yr on commercial spring calving, grass-based dairy farms with 45, 88, and 195 milking cows; and (3) demonstrated the functionality of the model by applying 2 electricity tariffs to the electricity consumption data and examining the effect on total dairy farm electricity costs. The MECD was developed using a mechanistic modeling approach and required the key inputs of milk production, cow number, and details relating to the milk-cooling system, milking machine system, water-heating system, lighting systems, water pump systems, and the winter housing facilities as well as details relating to the management of the farm (e.g., season of calving). Model validation showed an overall relative prediction error (RPE) of less than 10% for total electricity consumption. More than 87% of the mean square prediction error of total electricity consumption was accounted for by random variation. The RPE values of the milk-cooling systems, water-heating systems, and milking machine systems were less than 20%. The RPE values for automatic scraper systems, lighting systems, and water pump systems varied from 18 to 113%, indicating a poor prediction for these metrics. However, automatic scrapers, lighting, and water pumps made up only 14% of total electricity consumption across all farms, reducing the overall impact of these poor predictions. Demonstration of the model showed that total farm electricity costs increased by between 29 and 38% by moving from a day and night tariff to a flat tariff. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Modelling Management Practices in Viticulture while Considering Resource Limitations: The Dhivine Model

PubMed Central

Martin-Clouaire, Roger; Rellier, Jean-Pierre; Paré, Nakié; Voltz, Marc; Biarnès, Anne

2016-01-01

Many farming-system studies have investigated the design and evaluation of crop-management practices with respect to economic performance and reduction in environmental impacts. In contrast, little research has been devoted to analysing these practices in terms of matching the recurrent context-dependent demand for resources (labour in particular) with those available on the farm. This paper presents Dhivine, a simulation model of operational management of grape production at the vineyard scale. Particular attention focuses on representing a flexible plan, which organises activities temporally, the resources available to the vineyard manager and the process of scheduling and executing the activities. The model relies on a generic production-system ontology used in several agricultural production domains. The types of investigations that the model supports are briefly illustrated. The enhanced realism of the production-management situations simulated makes it possible to examine and understand properties of resource-constrained work-organisation strategies and possibilities for improving them. PMID:26990089

Optimizing wind farm layout via LES-calibrated geometric models inclusive of wind direction and atmospheric stability effects

NASA Astrophysics Data System (ADS)

Archer, Cristina; Ghaisas, Niranjan

2015-04-01

The energy generation at a wind farm is controlled primarily by the average wind speed at hub height. However, two other factors impact wind farm performance: 1) the layout of the wind turbines, in terms of spacing between turbines along and across the prevailing wind direction; staggering or aligning consecutive rows; angles between rows, columns, and prevailing wind direction); and 2) atmospheric stability, which is a measure of whether vertical motion is enhanced (unstable), suppressed (stable), or neither (neutral). Studying both factors and their complex interplay with Large-Eddy Simulation (LES) is a valid approach because it produces high-resolution, 3D, turbulent fields, such as wind velocity, temperature, and momentum and heat fluxes, and it properly accounts for the interactions between wind turbine blades and the surrounding atmospheric and near-surface properties. However, LES are computationally expensive and simulating all the possible combinations of wind directions, atmospheric stabilities, and turbine layouts to identify the optimal wind farm configuration is practically unfeasible today. A new, geometry-based method is proposed that is computationally inexpensive and that combines simple geometric quantities with a minimal number of LES simulations to identify the optimal wind turbine layout, taking into account not only the actual frequency distribution of wind directions (i.e., wind rose) at the site of interest, but also atmospheric stability. The geometry-based method is calibrated with LES of the Lillgrund wind farm conducted with the Software for Offshore/onshore Wind Farm Applications (SOWFA), based on the open-access OpenFOAM libraries. The geometric quantities that offer the best correlations (>0.93) with the LES results are the blockage ratio, defined as the fraction of the swept area of a wind turbine that is blocked by an upstream turbine, and the blockage distance, the weighted distance from a given turbine to all upstream turbines that can potentially block it. Based on blockage ratio and distance, an optimization procedure is proposed that explores many different layout variables and identifies, given actual wind direction and stability distributions, the optimal wind farm layout, i.e., the one with the highest wind energy production. The optimization procedure is applied to both the calibration wind farm (Lillgrund) and a test wind farm (Horns Rev) and a number of layouts more efficient than the existing ones are identified. The optimization procedure based on geometric models proposed here can be applied very quickly (within a few hours) to any proposed wind farm, once enough information on wind direction frequency and, if available, atmospheric stability frequency has been gathered and once the number of turbines and/or the areal extent of the wind farm have been identified.

Integrated watershed- and farm-scale modeling framework for targeting critical source areas while maintaining farm economic viability.

PubMed

Ghebremichael, Lula T; Veith, Tamie L; Hamlett, James M

2013-01-15

Quantitative risk assessments of pollution and data related to the effectiveness of mitigating best management practices (BMPs) are important aspects of nonpoint source pollution control efforts, particularly those driven by specific water quality objectives and by measurable improvement goals, such as the total maximum daily load (TMDL) requirements. Targeting critical source areas (CSAs) that generate disproportionately high pollutant loads within a watershed is a crucial step in successfully controlling nonpoint source pollution. The importance of watershed simulation models in assisting with the quantitative assessments of CSAs of pollution (relative to their magnitudes and extents) and of the effectiveness of associated BMPs has been well recognized. However, due to the distinct disconnect between the hydrological scale in which these models conduct their evaluation and the farm scale at which feasible BMPs are actually selected and implemented, and due to the difficulty and uncertainty involved in transferring watershed model data to farm fields, there are limited practical applications of these tools in the current nonpoint source pollution control efforts by conservation specialists for delineating CSAs and planning targeting measures. There are also limited approaches developed that can assess impacts of CSA-targeted BMPs on farm productivity and profitability together with the assessment of water quality improvements expected from applying these measures. This study developed a modeling framework that integrates farm economics and environmental aspects (such as identification and mitigation of CSAs) through joint use of watershed- and farm-scale models in a closed feedback loop. The integration of models in a closed feedback loop provides a way for environmental changes to be evaluated with regard to the impact on the practical aspects of farm management and economics, adjusted or reformulated as necessary, and revaluated with respect to effectiveness of environmental mitigation at the farm- and watershed-levels. This paper also outlines steps needed to extract important CSA-related information from a watershed model to help inform targeting decisions at the farm scale. The modeling framework is demonstrated with two unique case studies in the northeastern United States (New York and Vermont), with supporting data from numerous published, location-specific studies at both the watershed and farm scales. Using the integrated modeling framework, it can be possible to compare the costs (in terms of changes required in farm system components or financial compensations for retiring crop lands) and benefits (in terms of measurable water quality improvement goals) of implementing targeted BMPs. This multi-scale modeling approach can be used in the multi-objective task of mitigating CSAs of pollution to meet water quality goals while maintaining farm-level economic viability. Copyright © 2012 Elsevier Ltd. All rights reserved.

Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data.

PubMed

Groenendijk, Piet; Heinen, Marius; Klammler, Gernot; Fank, Johann; Kupfersberger, Hans; Pisinaras, Vassilios; Gemitzi, Alexandra; Peña-Haro, Salvador; García-Prats, Alberto; Pulido-Velazquez, Manuel; Perego, Alessia; Acutis, Marco; Trevisan, Marco

2014-11-15

The agricultural sector faces the challenge of ensuring food security without an excessive burden on the environment. Simulation models provide excellent instruments for researchers to gain more insight into relevant processes and best agricultural practices and provide tools for planners for decision making support. The extent to which models are capable of reliable extrapolation and prediction is important for exploring new farming systems or assessing the impacts of future land and climate changes. A performance assessment was conducted by testing six detailed state-of-the-art models for simulation of nitrate leaching (ARMOSA, COUPMODEL, DAISY, EPIC, SIMWASER/STOTRASIM, SWAP/ANIMO) for lysimeter data of the Wagna experimental field station in Eastern Austria, where the soil is highly vulnerable to nitrate leaching. Three consecutive phases were distinguished to gain insight in the predictive power of the models: 1) a blind test for 2005-2008 in which only soil hydraulic characteristics, meteorological data and information about the agricultural management were accessible; 2) a calibration for the same period in which essential information on field observations was additionally available to the modellers; and 3) a validation for 2009-2011 with the corresponding type of data available as for the blind test. A set of statistical metrics (mean absolute error, root mean squared error, index of agreement, model efficiency, root relative squared error, Pearson's linear correlation coefficient) was applied for testing the results and comparing the models. None of the models performed good for all of the statistical metrics. Models designed for nitrate leaching in high-input farming systems had difficulties in accurately predicting leaching in low-input farming systems that are strongly influenced by the retention of nitrogen in catch crops and nitrogen fixation by legumes. An accurate calibration does not guarantee a good predictive power of the model. Nevertheless all models were able to identify years and crops with high- and low-leaching rates. Copyright © 2014 Elsevier B.V. All rights reserved.

An economic decision-making support system for selection of reproductive management programs on dairy farms.

PubMed

Giordano, J O; Fricke, P M; Wiltbank, M C; Cabrera, V E

2011-12-01

Because the reproductive performance of lactating dairy cows influences the profitability of dairy operations, predicting the future reproductive and economic performance of dairy herds through decision support systems would be valuable to dairy producers and consultants. In this study, we present a highly adaptable tool created based on a mathematical model combining Markov chain simulation with partial budgeting to obtain the net present value (NPV; $/cow per year) of different reproductive management programs. The growing complexity of reproductive programs used by dairy farms demands that new decision support systems precisely reflect the events that occur on the farm. Therefore, the model requires productive, reproductive, and economic input data used for simulation of farm conditions to account for all factors related to reproductive management that increase costs and generate revenue. The economic performance of 3 different reproductive programs can be simultaneously compared with the current model. A program utilizing 100% visual estrous detection (ED) for artificial insemination (AI) is used as a baseline for comparison with 2 other programs that may include 100% timed AI (TAI) as well as any combination of TAI and ED. A case study is presented in which the model was used to compare 3 different reproductive management strategies (100% ED baseline compared with two 100% TAI options) using data from a commercial farm in Wisconsin. Sensitivity analysis was then used to assess the effect of varying specific reproductive parameters on the NPV. Under the simulated conditions of the case study, the model indicated that the two 100% TAI programs were superior to the 100% ED program and, of the 100% TAI programs, the one with the higher conception rate (CR) for resynchronized AI services was economically superior despite having higher costs and a longer interbreeding interval. A 4% increase in CR for resynchronized AI was sufficient for the inferior 100% TAI to outperform the superior program. Adding ED to the 100% TAI programs was only beneficial for the program with the lower CR. The improvement in service rate required for the 100% ED program to have the same NPV as the superior 100% TAI program was 12%. The decision support system developed in this study is a valuable tool that may be used to assist dairy producers and industry consultants in selecting the best farm-specific reproductive management strategy. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Security and Stability Analysis of Wind Farms Integration into Distribution Network

NASA Astrophysics Data System (ADS)

Guan-yang, Li; Hongzhao, Wang; Guanglei, Li; Yamei, Cheng; Hong-zheng, Liu; Yi, Sun

2017-05-01

With the increasing share of the wind power in the power system, wind power fluctuations will cause obvious negative impacts on weak local grid. This paper firstly establish electromechanical transient simulation model for doubly fed induction wind turbine, then use Matlab/Simulink to achieve power flow calculation and transient simulation of power system including wind farms, the local synchronous generator, load, etc, finally analyze wind power on the impact of the local power grid under typical circumstances. The actual calculated results indicate that wind mutation causes little effect on the power grid, but when the three-phase short circuit fault happens, active power of wind power decreases sharply and the voltage of location of wind power into the grid also drop sharply, finally wind farm split from power system. This situation is not conducive to security and stability of the local power grid. It is necessary to develop security and stability measures in the future.

Data-Mining-Based Intelligent Differential Relaying for Transmission Lines Including UPFC and Wind Farms.

PubMed

Jena, Manas Kumar; Samantaray, Subhransu Ranjan

2016-01-01

This paper presents a data-mining-based intelligent differential relaying scheme for transmission lines, including flexible ac transmission system device, such as unified power flow controller (UPFC) and wind farms. Initially, the current and voltage signals are processed through extended Kalman filter phasor measurement unit for phasor estimation, and 21 potential features are computed at both ends of the line. Once the features are extracted at both ends, the corresponding differential features are derived. These differential features are fed to a data-mining model known as decision tree (DT) to provide the final relaying decision. The proposed technique has been extensively tested for single-circuit transmission line, including UPFC and wind farms with in-feed, double-circuit line with UPFC on one line and wind farm as one of the substations with wide variations in operating parameters. The test results obtained from simulation as well as in real-time digital simulator testing indicate that the DT-based intelligent differential relaying scheme is highly reliable and accurate with a response time of 2.25 cycles from the fault inception.

Assimilating Leaf Area Index Estimates from Remote Sensing into the Simulations of a Cropping Systems Model

USDA-ARS?s Scientific Manuscript database

Spatial extrapolation of cropping systems models for regional crop growth and water use assessment and farm-level precision management has been limited by the vast model input requirements and the model sensitivity to parameter uncertainty. Remote sensing has been proposed as a viable source of spat...

Simulation and analysis of conjunctive use with MODFLOW's farm process

USGS Publications Warehouse

Hanson, R.T.; Schmid, W.; Faunt, C.C.; Lockwood, B.

2010-01-01

The extension of MODFLOW onto the landscape with the Farm Process (MF-FMP) facilitates fully coupled simulation of the use and movement of water from precipitation, streamflow and runoff, groundwater flow, and consumption by natural and agricultural vegetation throughout the hydrologic system at all times. This allows for more complete analysis of conjunctive use water-resource systems than previously possible with MODFLOW by combining relevant aspects of the landscape with the groundwater and surface water components. This analysis is accomplished using distributed cell-by-cell supply-constrained and demand-driven components across the landscape within " water-balance subregions" comprised of one or more model cells that can represent a single farm, a group of farms, or other hydrologic or geopolitical entities. Simulation of micro-agriculture in the Pajaro Valley and macro-agriculture in the Central Valley are used to demonstrate the utility of MF-FMP. For Pajaro Valley, the simulation of an aquifer storage and recovery system and related coastal water distribution system to supplant coastal pumpage was analyzed subject to climate variations and additional supplemental sources such as local runoff. For the Central Valley, analysis of conjunctive use from different hydrologic settings of northern and southern subregions shows how and when precipitation, surface water, and groundwater are important to conjunctive use. The examples show that through MF-FMP's ability to simulate natural and anthropogenic components of the hydrologic cycle, the distribution and dynamics of supply and demand can be analyzed, understood, and managed. This analysis of conjunctive use would be difficult without embedding them in the simulation and are difficult to estimate a priori. Journal compilation ?? 2010 National Ground Water Association. No claim to original US government works.

Operation and Equivalent Loads of Wind Turbines in Large Wind Farms

NASA Astrophysics Data System (ADS)

Andersen, Soren Juhl; Sorensen, Jens Norkaer; Mikkelsen, Robert Flemming

2017-11-01

Wind farms continue to grow in size and as the technology matures, the design of wind farms move towards including dynamic effects besides merely annual power production estimates. The unsteady operation of wind turbines in large wind farms has been modelled with EllipSys3D(Michelsen, 1992, and Sørensen, 1995) for a number of different scenarios using a fully coupled large eddy simulations(LES) and aero-elastic framework. The turbines are represented in the flow fields using the actuator line method(Sørensen and Shen, 2002), where the aerodynamic forces and deflections are derived from an aero-elastic code, Flex5(Øye, 1996). The simulations constitute a database of full turbine operation in terms of both production and loads for various wind speeds, turbulence intensities, and turbine spacings. The operating conditions are examined in terms of averaged power production and thrust force, as well as 10min equivalent flapwise bending, yaw, and tilt moment loads. The analyses focus on how the performance and loads change throughout a given farm as well as comparing how various input parameters affect the operation and loads of the wind turbines during different scenarios. COMWIND(Grant 2104-09- 067216/DSF), Nordic Consortium on Optimization and Control of Wind Farms, Eurotech Greentech Wind project, Winds2Loads, and CCA LES. Ressources Granted on SNIC and JESS. The Vestas NM80 turbine has been used.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanz Rodrigo, Javier; Chávez Arroyo, Roberto Aurelio; Moriarty, Patrick

The increasing size of wind turbines, with rotors already spanning more than 150 m diameter and hub heights above 100 m, requires proper modeling of the atmospheric boundary layer (ABL) from the surface to the free atmosphere. Furthermore, large wind farm arrays create their own boundary layer structure with unique physics. This poses significant challenges to traditional wind engineering models that rely on surface-layer theories and engineering wind farm models to simulate the flow in and around wind farms. However, adopting an ABL approach offers the opportunity to better integrate wind farm design tools and meteorological models. The challenge ismore » how to build the bridge between atmospheric and wind engineering model communities and how to establish a comprehensive evaluation process that identifies relevant physical phenomena for wind energy applications with modeling and experimental requirements. A framework for model verification, validation, and uncertainty quantification is established to guide this process by a systematic evaluation of the modeling system at increasing levels of complexity. In terms of atmospheric physics, 'building the bridge' means developing models for the so-called 'terra incognita,' a term used to designate the turbulent scales that transition from mesoscale to microscale. This range of scales within atmospheric research deals with the transition from parameterized to resolved turbulence and the improvement of surface boundary-layer parameterizations. The coupling of meteorological and wind engineering flow models and the definition of a formal model evaluation methodology, is a strong area of research for the next generation of wind conditions assessment and wind farm and wind turbine design tools. Some fundamental challenges are identified in order to guide future research in this area.« less

A dynamic simulation model of land-use, population, and rural livelihoods in the Central Rift Valley of Ethiopia.

PubMed

Garedew, Efrem; Sandewall, Mats; Soderberg, Ulf

2012-01-01

The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years and to improve our understanding of the interactions among them. The modeling output is characterized by rapid population growth, declining farm size and household incomes, deteriorating woody vegetation cover and worsening land degradation if current conditions remain. However, through integrated intervention strategies (including forest increase, micro-finance, family planning, health and education) the woody vegetation cover is likely to increase in the landscape, population growth is likely to slow down and households' income is likely to improve. A validation assessment of the simulation model based on historical data on land-use and population from 1973 to 2006 showed that the model is relatively robust. We conclude that as a supporting tool, the simulation model can contribute to the decision making process.

Hindcast of water availability in regional aquifer systems using MODFLOW Farm Process

USGS Publications Warehouse

Schmid, Wolfgang; Hanson, Randall T.; Faunt, Claudia C.; Phillips, Steven P.

2015-01-01

Coupled groundwater and surface-water components of the hydrologic cycle can be simulated by the Farm Process for MODFLOW (MF-FMP) in both irrigated and non-irrigated areas and aquifer-storage and recovery systems. MF-FMP is being applied to three productive agricultural regions of different scale in the State of California, USA, to assess the availability of water and the impacts of alternative management decisions. Hindcast simulations are conducted for similar periods from the 1960s to near recent times. Historical groundwater pumpage is mostly unknown in one region (Central Valley) and is estimated by MF-FMP. In another region (Pajaro Valley), recorded pumpage is used to calibrate model-estimated pumpage. Multiple types of observations are used to estimate uncertain parameters, such as hydraulic, land-use, and farm properties. MF-FMP simulates how climate variability and water-import availability affect water demand and supply. MF-FMP can be used to predict water availability based on anticipated changes in anthropogenic or natural water demands. Keywords groundwater; surface-water; irrigation; water availability; response to climate variability/change

Wind tunnel measurements of the power output variability and unsteady loading in a micro wind farm model

NASA Astrophysics Data System (ADS)

Bossuyt, Juliaan; Howland, Michael; Meneveau, Charles; Meyers, Johan

2015-11-01

To optimize wind farm layouts for a maximum power output and wind turbine lifetime, mean power output measurements in wind tunnel studies are not sufficient. Instead, detailed temporal information about the power output and unsteady loading from every single wind turbine in the wind farm is needed. A very small porous disc model with a realistic thrust coefficient of 0.75 - 0.85, was designed. The model is instrumented with a strain gage, allowing measurements of the thrust force, incoming velocity and power output with a frequency response up to the natural frequency of the model. This is shown by reproducing the -5/3 spectrum from the incoming flow. Thanks to its small size and compact instrumentation, the model allows wind tunnel studies of large wind turbine arrays with detailed temporal information from every wind turbine. Translating to field conditions with a length-scale ratio of 1:3,000 the frequencies studied from the data reach from 10-4 Hz up to about 6 .10-2 Hz. The model's capabilities are demonstrated with a large wind farm measurement consisting of close to 100 instrumented models. A high correlation is found between the power outputs of stream wise aligned wind turbines, which is in good agreement with results from prior LES simulations. Work supported by ERC (ActiveWindFarms, grant no. 306471) and by NSF (grants CBET-113380 and IIA-1243482, the WINDINSPIRE project).

Feeding strategies and manure management for cost-effective mitigation of greenhouse gas emissions from dairy farms in Wisconsin.

PubMed

Dutreuil, M; Wattiaux, M; Hardie, C A; Cabrera, V E

2014-09-01

Greenhouse gas (GHG) emissions from dairy farms are a major concern. Our objectives were to assess the effect of mitigation strategies on GHG emissions and net return to management on 3 distinct farm production systems of Wisconsin. A survey was conducted on 27 conventional farms, 30 grazing farms, and 69 organic farms. The data collected were used to characterize 3 feeding systems scaled to the average farm (85 cows and 127ha). The Integrated Farm System Model was used to simulate the economic and environmental impacts of altering feeding and manure management in those 3 farms. Results showed that incorporation of grazing practices for lactating cows in the conventional farm led to a 27.6% decrease in total GHG emissions [-0.16kg of CO2 equivalents (CO2eq)/kg of energy corrected milk (ECM)] and a 29.3% increase in net return to management (+$7,005/yr) when milk production was assumed constant. For the grazing and organic farms, decreasing the forage-to-concentrate ratio in the diet decreased GHG emissions when milk production was increased by 5 or 10%. The 5% increase in milk production was not sufficient to maintain the net return; however, the 10% increase in milk production increased net return in the organic farm but not on the grazing farm. A 13.7% decrease in GHG emissions (-0.08kg of CO2eq/kg of ECM) was observed on the conventional farm when incorporating manure the day of application and adding a 12-mo covered storage unit. However, those same changes led to a 6.1% (+0.04kg of CO2eq/kg of ECM) and a 6.9% (+0.06kg of CO2eq/kg of ECM) increase in GHG emissions in the grazing and the organic farms, respectively. For the 3 farms, manure management changes led to a decrease in net return to management. Simulation results suggested that the same feeding and manure management mitigation strategies led to different outcomes depending on the farm system, and furthermore, effective mitigation strategies were used to reduce GHG emissions while maintaining profitability within each farm. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

CFD Study of the Performance of an Operational Wind Farm and its Impact on the Local Climate: CFD sensitivity to forestry modelling

NASA Astrophysics Data System (ADS)

Wylie, Scott; Watson, Simon

2013-04-01

Any past, current or projected future wind farm developments are highly dependent on localised climatic conditions. For example the mean wind speed, one of the main factors in assessing the economic feasibility of a wind farm, can vary significantly over length scales no greater than the size of a typical wind farm. Any additional heterogeneity at a potential site, such as forestry, can affect the wind resource further not accounting for the additional difficulty of installation. If a wind farm is sited in an environmentally sensitive area then the ability to predict the wind farm performance and possible impacts on the important localised climatic conditions are of increased importance. Siting of wind farms in environmentally sensitive areas is not uncommon, such as areas of peat-land as in this example. Areas of peat-land are important sinks for carbon in the atmosphere but their ability to sequester carbon is highly dependent on the local climatic conditions. An operational wind farm's impact on such an area was investigated using CFD. Validation of the model outputs were carried out using field measurements from three automatic weather stations (AWS) located throughout the site. The study focuses on validation of both wind speed and turbulence measurement, whilst also assessing the models ability to predict wind farm performance. The use of CFD to model the variation in wind speed over heterogeneous terrain, including wind turbines effects, is increasing in popularity. Encouraging results have increased confidence in the ability of CFD performance in complex terrain with features such as steep slopes and forests, which are not well modelled by the widely used linear models such as WAsP and MS-Micro. Using concurrent measurements from three stationary AWS across the wind farm will allow detailed validation of the model predicted flow characteristics, whilst aggregated power output information will allow an assessment of how accurate the model setup can predict wind farm performance. Given the dependence of the local climatic conditions influence on the peat-land's ability to sequester carbon, accurate predictions of the local wind and turbulence features will allow us to quantify any possible wind farm influences. This work was carried out using the commercially available Reynolds Averaged Navier-Stokes (RANS) CFD package ANSYS CFX. Utilising the Windmodeller add-on in CFX, a series of simulations were carried out to assess wind flow interactions through and around the wind farm, incorporating features such as terrain, forestry and rotor wake interactions. Particular attention was paid to forestry effects, as the AWS are located close to the vicinity of forestry. Different Leaf Area Densities (LAD) were tested to assess how sensitive the models output was to this change.

Evaluation of weather-based rice yield models in India

NASA Astrophysics Data System (ADS)

Sudharsan, D.; Adinarayana, J.; Reddy, D. Raji; Sreenivas, G.; Ninomiya, S.; Hirafuji, M.; Kiura, T.; Tanaka, K.; Desai, U. B.; Merchant, S. N.

2013-01-01

The objective of this study was to compare two different rice simulation models—standalone (Decision Support System for Agrotechnology Transfer [DSSAT]) and web based (SImulation Model for RIce-Weather relations [SIMRIW])—with agrometeorological data and agronomic parameters for estimation of rice crop production in southern semi-arid tropics of India. Studies were carried out on the BPT5204 rice variety to evaluate two crop simulation models. Long-term experiments were conducted in a research farm of Acharya N G Ranga Agricultural University (ANGRAU), Hyderabad, India. Initially, the results were obtained using 4 years (1994-1997) of data with weather parameters from a local weather station to evaluate DSSAT simulated results with observed values. Linear regression models used for the purpose showed a close relationship between DSSAT and observed yield. Subsequently, yield comparisons were also carried out with SIMRIW and DSSAT, and validated with actual observed values. Realizing the correlation coefficient values of SIMRIW simulation values in acceptable limits, further rice experiments in monsoon (Kharif) and post-monsoon (Rabi) agricultural seasons (2009, 2010 and 2011) were carried out with a location-specific distributed sensor network system. These proximal systems help to simulate dry weight, leaf area index and potential yield by the Java based SIMRIW on a daily/weekly/monthly/seasonal basis. These dynamic parameters are useful to the farming community for necessary decision making in a ubiquitous manner. However, SIMRIW requires fine tuning for better results/decision making.

Reference Manual for the System Advisor Model's Wind Power Performance Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Freeman, J.; Jorgenson, J.; Gilman, P.

2014-08-01

This manual describes the National Renewable Energy Laboratory's System Advisor Model (SAM) wind power performance model. The model calculates the hourly electrical output of a single wind turbine or of a wind farm. The wind power performance model requires information about the wind resource, wind turbine specifications, wind farm layout (if applicable), and costs. In SAM, the performance model can be coupled to one of the financial models to calculate economic metrics for residential, commercial, or utility-scale wind projects. This manual describes the algorithms used by the wind power performance model, which is available in the SAM user interface andmore » as part of the SAM Simulation Core (SSC) library, and is intended to supplement the user documentation that comes with the software.« less

A Farm Management Problem. Teacher Guide. AGDEX 810.

ERIC Educational Resources Information Center

Cackler, William

This guide is intended to assist teachers in conducting a farm management simulation that has been designed to help vocational agriculture students acquire competency in both crop and livestock farming. The introductory section includes an overview of the simulation, planning considerations and suggested grading criteria, and a suggested sequence…

Economic effect of reducing nitrogen and phosphorus mass balance on Wisconsin and Québec dairy farms.

PubMed

Pellerin, D; Charbonneau, E; Fadul-Pacheco, L; Soucy, O; Wattiaux, M A

2017-10-01

Our objective was to explore the trade-offs between economic performance (farm net income, FNI) and environmental outcomes (whole-farm P and N balances) of dairy farms in Wisconsin (WI; United States) and Québec (QC; Canada). An Excel-based linear program model (N-CyCLES; nutrient cycling: crops, livestock, environment, and soil) was developed to optimize feeding, cropping, and manure management as a single unit of management. In addition to FNI, P and N balances model outputs included (1) the mix of up to 9 home-grown and 17 purchased feeds for up to 5 animal groups, (2) the mix of up to 5 crop rotations in up to 5 land units and c) the mix of up to 7 fertilizers (solid and liquid manure and 5 commercial fertilizers) to allocate in each land unit. The model was parameterized with NRC nutritional guidelines and regional nutrient management planning rules. Simulations were conducted on a typical WI farm of 107 cows and 151 ha of cropland and, a Southern QC farm of 87 cows and 142 ha of cropland and all results were expressed per kg of fat- and protein-corrected milk (FPCM). In absence of constraints on P and N balances, maximum FNI was 0.12 and 0.11 $/kg of FPCM for WI and QC, respectively, with P and N balances of 1.05 and 14.29 g/kg of FPCM in WI but 0.60 and 15.70 g/kg of FPCM in QC. The achievable reduction (balance at maximum FNI minus balance when the simulation objective was to minimize P or N balance) was 0.31 and 0.54 g of P/kg of FPCM (29 and 89% reduction), but 2.37 and 3.31 g of N/kg of FPCM (17 and 24% reduction) in WI and QC, respectively. Among other factors, differences in animal unit per hectare and reliance on biological N fixation may have contributed to lower achievable reductions of whole-farm balances in WI compared with QC. Subsequent simulations to maximize FNI under increasing constraints on nutrient balances revealed that it was possible to reduce P balance, N balance, and both together by up to 33% without a substantial effect on FNI. Partial reduction in P balance reduced N balance (synergetic effect) in WI, but increased N balance (antagonistic effect) in QC. In contrast, reducing N balance increased P balance in both regions, albeit in different magnitudes. The regional comparison highlighted the importance of site-specific conditions on modeling outcomes. This study demonstrated that even when recommended guidelines are followed for herd nutrition and crop fertilization, the optimization of herd feeding, cropping, and manure spreading as a single unit of management may help identify management options that preserve FNI, while substantially reducing whole-farm nutrient balance. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Modelling the interactions between C and N farm balances and GHG emissions from confinement dairy farms in northern Spain.

PubMed

Del Prado, A; Mas, K; Pardo, G; Gallejones, P

2013-11-01

There is world-wide concern for the contribution of dairy farming to global warming. However, there is still a need to improve the quantification of the C-footprint of dairy farming systems under different production systems and locations since most of the studies (e.g. at farm-scale or using LCA) have been carried out using too simplistic and generalised approaches. A modelling approach integrating existing and new sub-models has been developed and used to simulate the C and N flows and to predict the GHG burden of milk production (from the cradle to the farm gate) from 17 commercial confinement dairy farms in the Basque Country (northern Spain). We studied the relationship between their GHG emissions, and their management and economic performance. Additionally, we explored some of the effects on the GHG results of the modelling methodology choice. The GHG burden values resulting from this study (0.84-2.07 kg CO2-eq kg(-l) milk ECM), although variable, were within the range of values of existing studies. It was evidenced, however, that the methodology choice used for prediction had a large effect on the results. Methane from the rumen and manures, and N2O emissions from soils comprised most of the GHG emissions for milk production. Diet was the strongest factor explaining differences in GHG emissions from milk production. Moreover, the proportion of feed from the total cattle diet that could have directly been used to feed humans (e.g. cereals) was a good indicator to predict the C-footprint of milk. Not only were some other indicators, such as those in relation with farm N use efficiency, good proxies to estimate GHG emissions per ha or per kg milk ECM (C-footprint of milk) but they were also positively linked with farm economic performance. Copyright © 2013 Elsevier B.V. All rights reserved.

The creation and evaluation of a model to simulate the probability of conception in seasonal-calving pasture-based dairy heifers.

PubMed

Fenlon, Caroline; O'Grady, Luke; Butler, Stephen; Doherty, Michael L; Dunnion, John

2017-01-01

Herd fertility in pasture-based dairy farms is a key driver of farm economics. Models for predicting nulliparous reproductive outcomes are rare, but age, genetics, weight, and BCS have been identified as factors influencing heifer conception. The aim of this study was to create a simulation model of heifer conception to service with thorough evaluation. Artificial Insemination service records from two research herds and ten commercial herds were provided to build and evaluate the models. All were managed as spring-calving pasture-based systems. The factors studied were related to age, genetics, and time of service. The data were split into training and testing sets and bootstrapping was used to train the models. Logistic regression (with and without random effects) and generalised additive modelling were selected as the model-building techniques. Two types of evaluation were used to test the predictive ability of the models: discrimination and calibration. Discrimination, which includes sensitivity, specificity, accuracy and ROC analysis, measures a model's ability to distinguish between positive and negative outcomes. Calibration measures the accuracy of the predicted probabilities with the Hosmer-Lemeshow goodness-of-fit, calibration plot and calibration error. After data cleaning and the removal of services with missing values, 1396 services remained to train the models and 597 were left for testing. Age, breed, genetic predicted transmitting ability for calving interval, month and year were significant in the multivariate models. The regression models also included an interaction between age and month. Year within herd was a random effect in the mixed regression model. Overall prediction accuracy was between 77.1% and 78.9%. All three models had very high sensitivity, but low specificity. The two regression models were very well-calibrated. The mean absolute calibration errors were all below 4%. Because the models were not adept at identifying unsuccessful services, they are not suggested for use in predicting the outcome of individual heifer services. Instead, they are useful for the comparison of services with different covariate values or as sub-models in whole-farm simulations. The mixed regression model was identified as the best model for prediction, as the random effects can be ignored and the other variables can be easily obtained or simulated.

A high resolution WRF model for wind energy forecasting

NASA Astrophysics Data System (ADS)

Vincent, Claire Louise; Liu, Yubao

2010-05-01

The increasing penetration of wind energy into national electricity markets has increased the demand for accurate surface layer wind forecasts. There has recently been a focus on forecasting the wind at wind farm sites using both statistical models and numerical weather prediction (NWP) models. Recent advances in computing capacity and non-hydrostatic NWP models means that it is possible to nest mesoscale models down to Large Eddy Simulation (LES) scales over the spatial area of a typical wind farm. For example, the WRF model (Skamarock 2008) has been run at a resolution of 123 m over a wind farm site in complex terrain in Colorado (Liu et al. 2009). Although these modelling attempts indicate a great hope for applying such models for detailed wind forecasts over wind farms, one of the obvious challenges of running the model at this resolution is that while some boundary layer structures are expected to be modelled explicitly, boundary layer eddies into the inertial sub-range can only be partly captured. Therefore, the amount and nature of sub-grid-scale mixing that is required is uncertain. Analysis of Liu et al. (2009) modelling results in comparison to wind farm observations indicates that unrealistic wind speed fluctuations with a period of around 1 hour occasionally occurred during the two day modelling period. The problem was addressed by re-running the same modelling system with a) a modified diffusion constant and b) two-way nesting between the high resolution model and its parent domain. The model, which was run with horizontal grid spacing of 370 m, had dimensions of 505 grid points in the east-west direction and 490 points in the north-south direction. It received boundary conditions from a mesoscale model of resolution 1111 m. Both models had 37 levels in the vertical. The mesoscale model was run with a non-local-mixing planetary boundary layer scheme, while the 370 m model was run with no planetary boundary layer scheme. It was found that increasing the diffusion constant caused damping of the unrealistic fluctuations, but did not completely solve the problem. Using two-way nesting also mitigated the unrealistic fluctuations significantly. It can be concluded that for real case LES modelling of wind farm circulations, care should be taken to ensure the consistency between the mesoscale weather forcing and LES models to avoid exciting spurious noise along the forcing boundary. The development of algorithms that adequately model the sub-grid-scale mixing that cannot be resolved by LES models is an important area for further research. References Liu, Y. Y._W. Liu, W. Y.Y. Cheng, W. Wu, T. T. Warner and K. Parks, 2009: Simulating intra-farm wind variations with the WRF-RTFDDA-LES modeling system. 10th WRF Users' Workshop, Boulder, C, USA. June 23 - 26, 2009. Skamarock, W., J. Dudhia, D.O. Gill, D.M. Barker, M.G.Duda, X-Y. Huang, W. Wang and J.G. Powers, A Description of the Advanced Research WRF version 3, NCAR Technical Note TN-475+STR, NCAR, Boulder, Colorado, 2008.

Three-dimensional modelling for assessment of far-field impact of tidal stream turbine: A case study at the Anglesey Coast, Wales, UK

NASA Astrophysics Data System (ADS)

Li, Xiaorong; Li, Ming; Wolf, Judith

2017-04-01

As a response to worldwide climate change, clean non-carbon renewable energy resources have been gaining significant attention. Among a range of renewable alternatives, tidal stream energy is considered very promising; due to its consistent predictability and availability. To investigate impacts of tidal stream devices on their surroundings, prototype experiments involving small scale laboratory studies have been implemented. Computational Flow Dynamics (CFD) modelling is also commonly applied to study turbine behaviours. However, these studies focus on impacts of the turbine in the near-field scale. As a result, in order to study and predict the far-field impacts caused by the operation of turbines, large scale 2D and 3D numerical oceanography models have been used, with routines added to reflect the impacts of turbines. In comparison to 2D models, 3D models are advantageous in providing complete prediction of vertical flow structures and hence mixing in the wake of a turbine. This research aims to deliver a thorough 3D tidal stream turbine simulation system, by considering major coastal processes, i.e. current, waves and sediment transport, based on a 3D wave-current-sediment fully coupled numerical oceanography model — the Unstructured Grid Finite Volume Community Ocean Model (FVCOM). The energy extraction of turbines is simulated by adding a body force to the momentum equations. Across the water depth, the coefficient related to the additional body force is given different values according to the turbine configuration and operation to reflect the vertical variation of the turbine's impacts on the passing flow. Three turbulence perturbation terms are added to the turbulence closure to simulate the turbine-induced turbulence generation, dissipation and interference for the turbulence length-scale. Impacts of turbine operation on surface waves are also considered by modification of wave energy flux across the device. A thorough validation study is carried out in which the developed model is tested; based on a combination of laboratory measured data and CFD simulated results. The developed turbine simulation system is then applied to the Anglesey coast, North Wales, UK for a case study. The validation study suggests that the developed turbine simulation system is able to accurately simulate both hydrodynamics and wave dynamics in the turbine wake. The case study with 18 turbines (diameter is 15 m) modelled individually in the waterway between the north-west Anglesey and the Skerries reveals impacts of the turbine farm on free surface elevation, flow field, turbulence kinetic energy (TKE), surface waves, bottom shear stress and suspended sediment transport. The wake is observable up to 4.5 km downstream of the device farm. Flow near the bed in the wake is accelerated, leading to enhanced bottom shear stress. The device farm has a strong influence on TKE and hence the vertical mixing of suspended sediment in the wake. Further, the eastwards directed residual sediment transport along the north coast of Anglesey is found to be weakened by the turbine farm.

Atmospheric stability effects on wind farm performance using large-eddy simulation

NASA Astrophysics Data System (ADS)

Archer, C. L.; Ghaisas, N.; Xie, S.

2014-12-01

Atmospheric stability has been recently found to have significant impacts on wind farm performance, especially since offshore and onshore wind farms are known to operate often under non-neutral conditions. Recent field observations have revealed that changes in stability are accompanied by changes in wind speed, direction, and turbulent kinetic energy (TKE). In order to isolate the effects of stability, large-eddy simulations (LES) are performed under neutral, stable, and unstable conditions, keeping the wind speed and direction unchanged at a fixed height. The Lillgrund wind farm, comprising of 48 turbines, is studied in this research with the Simulator for Offshore/Onshore Wind Farm Applications (SOWFA) developed by the National Renewable Energy Laboratory. Unlike most previous numerical simulations, this study does not impose periodic boundary conditions and therefore is ideal for evaluating the effects of stability in large, but finite, wind farms. Changes in power generation, velocity deficit, rate of wake recovery, TKE, and surface temperature are quantified as a function of atmospheric stability. The sensitivity of these results to wind direction is also discussed.

Minimization of bovine tuberculosis control costs in US dairy herds

PubMed Central

Smith, Rebecca L.; Tauer, Loren W.; Schukken, Ynte H.; Lu, Zhao; Grohn, Yrjo T.

2013-01-01

The objective of this study was to minimize the cost of controlling an isolated bovine tuberculosis (bTB) outbreak in a US dairy herd, using a stochastic simulation model of bTB with economic and biological layers. A model optimizer produced a control program that required 2-month testing intervals (TI) with 2 negative whole-herd tests to leave quarantine. This control program minimized both farm and government costs. In all cases, test-and-removal costs were lower than depopulation costs, although the variability in costs increased for farms with high holding costs or small herd sizes. Increasing herd size significantly increased costs for both the farm and the government, while increasing indemnity payments significantly decreased farm costs and increasing testing costs significantly increased government costs. Based on the results of this model, we recommend 2-month testing intervals for herds after an outbreak of bovine tuberculosis, with 2 negative whole herd tests being sufficient to lift quarantine. A prolonged test and cull program may cause a state to lose its bTB-free status during the testing period. When the cost of losing the bTB-free status is greater than $1.4 million then depopulation of farms could be preferred over a test and cull program. PMID:23953679

Network analysis of swine shipments in Ontario, Canada, to support disease spread modelling and risk-based disease management.

PubMed

Dorjee, S; Revie, C W; Poljak, Z; McNab, W B; Sanchez, J

2013-10-01

Understanding contact networks are important for modelling and managing the spread and control of communicable diseases in populations. This study characterizes the swine shipment network of a multi-site production system in southwestern Ontario, Canada. Data were extracted from a company's database listing swine shipments among 251 swine farms, including 20 sow, 69 nursery and 162 finishing farms, for the 2-year period of 2006 to 2007. Several network metrics were generated. The number of shipments per week between pairs of farms ranged from 1 to 6. The medians (and ranges) of out-degree were: sow 6 (1-21), nursery 8 (0-25), and finishing 0 (0-4), over the entire 2-year study period. Corresponding estimates for in-degree of nursery and finishing farms were 3 (0-9) and 3 (0-12) respectively. Outgoing and incoming infection chains (OIC and IIC), were also measured. The medians (ranges) of the monthly OIC and IIC were 0 (0-8) and 0 (0-6), respectively, with very similar measures observed for 2-week intervals. Nursery farms exhibited high measures of centrality. This indicates that they pose greater risks of disease spread in the network. Therefore, they should be given a high priority for disease prevention and control measures affecting all age groups alike. The network demonstrated scale-free and small-world topologies as observed in other livestock shipment studies. This heterogeneity in contacts among farm types and network topologies should be incorporated in simulation models to improve their validity. In conclusion, this study provided useful epidemiological information and parameters for the control and modelling of disease spread among swine farms, for the first time from Ontario, Canada. Copyright © 2013 Elsevier B.V. All rights reserved.

Farming the mitochondrial ancestor as a model of endosymbiotic establishment by natural selection

PubMed Central

Szilágyi, András; Szathmáry, Eörs

2018-01-01

The origin of mitochondria was a major evolutionary transition leading to eukaryotes, and is a hotly debated issue. It is unknown whether mitochondria were acquired early or late, and whether it was captured via phagocytosis or syntrophic integration. We present dynamical models to directly simulate the emergence of mitochondria in an ecoevolutionary context. Our results show that regulated farming of prey bacteria and delayed digestion can facilitate the establishment of stable endosymbiosis if prey-rich and prey-poor periods alternate. Stable endosymbiosis emerges without assuming any initial metabolic benefit provided by the engulfed partner, in a wide range of parameters, despite that during good periods farming is costly. Our approach lends support to the appearance of mitochondria before any metabolic coupling has emerged, but after the evolution of primitive phagocytosis by the urkaryote. PMID:29382768

Evaluation of the risk of classical swine fever (CSF) spread from backyard pigs to other domestic pigs by using the spatial stochastic disease spread model Be-FAST: the example of Bulgaria.

PubMed

Martínez-López, Beatriz; Ivorra, Benjamin; Ramos, Angel Manuel; Fernández-Carrión, Eduardo; Alexandrov, Tsviatko; Sánchez-Vizcaíno, José Manuel

2013-07-26

The study presented here is one of the very first aimed at exploring the potential spread of classical swine fever (CSF) from backyard pigs to other domestic pigs. Specifically, we used a spatial stochastic spread model, called Be-FAST, to evaluate the potential spread of CSF virus (CSFV) in Bulgaria, which holds a large number of backyards (96% of the total number of pig farms) and is one of the very few countries for which backyard pigs and farm counts are available. The model revealed that, despite backyard pigs being very likely to become infected, infections from backyard pigs to other domestic pigs were rare. In general, the magnitude and duration of the CSF simulated epidemics were small, with a median [95% PI] number of infected farms per epidemic of 1 [1,4] and a median [95% PI] duration of the epidemic of 44 [17,101] days. CSFV transmission occurs primarily (81.16%) due to indirect contacts (i.e. vehicles, people and local spread) whereas detection of infected premises was mainly (69%) associated with the observation of clinical signs on farm rather than with implementation of tracing or zoning. Methods and results of this study may support the implementation of risk-based strategies more cost-effectively to prevent, control and, ultimately, eradicate CSF from Bulgaria. The model may also be easily adapted to other countries in which the backyard system is predominant. It can also be used to simulate other similar diseases such as African swine fever. Copyright © 2013 Elsevier B.V. All rights reserved.

Measurements of Heat Flux Differences Within a Large Wind Farm During the 2013 Crop/Wind-Energy Experiment (CWEX-13)

NASA Astrophysics Data System (ADS)

Rajewski, D. A.

2015-12-01

Wind farms are an important resource for electrical generation in the Central U.S., however with each installation there are many poorly documented interactions with the local and surrounding environment. The impact of wind farms on surface microclimate is largely understood conceptually using numerical or wind tunnel models or ex situ satellite-detected changes. Measurements suitable for calibration of numerical simulations are few and of limited applicability but are urgently needed to improve parameterization of wind farm aerodynamics influenced by the diurnal evolution of the boundary layer. Among large eddy simulations of wind farm wakes in thermally stable stratification, there are discrepancies on the influence of turbine-induced mixing on the surface heat flux. We provide measurements from seven surface flux stations, vertical profiling LiDARs located upwind and downwind of turbines, and SCADA measurements from turbines during the 2013 Crop Wind Energy Experiment (CWEX-13) as the best evidence for the variability of turbine induced heat flux within a large wind farm. Examination of ambient conditions (wind direction, wind veer, and thermal stratification) and on turbine operation factors (hub-height wind speed, normalized power) reveal conditions that lead to the largest modification of heat flux. Our results demonstrate the highest flux change from the reference station to be where the leading few lines of turbines influence the surface. Under stably stratified conditions turbine-scale turbulence is highly efficient at bringing warmer air aloft to the surface, leading to an increase in downward heat flux. Conversely we see that the combination of wakes from several lines of turbines reduces the flux contrast from the reference station. In this regime of deep wind-farm flow, wake turbulence is similar in scale and intensity to the reference conditions. These analysis tools can be extended to other turbine SCADA and microclimate variables (e.g. temperature) to improve basic understanding of turbine-turbine and total wind farm wake interactions. Forthcoming tall-tower measurements will provide additional opportunities for comparison of simulated wind and thermal profiles in non-wake, and waked flow conditions.

Simulated environmental transport distances of Lepeophtheirus salmonis in Loch Linnhe, Scotland, for informing aquaculture area management structures.

PubMed

Salama, N K G; Murray, A G; Rabe, B

2016-04-01

In the majority of salmon farming countries, production occurs in zones where practices are coordinated to manage disease agents such as Lepeophtheirus salmonis. To inform the structure of zones in specific systems, models have been developed accounting for parasite biology and system hydrodynamics. These models provide individual system farm relationships, and as such, it may be beneficial to produce more generalized principles for informing structures. Here, we use six different forcing scenarios to provide simulations from a previously described model of the Loch Linnhe system, Scotland, to assess the maximum dispersal distance of lice particles released from 12 sites transported over 19 day. Results indicate that the median distance travelled is 6.1 km from release site with <2.5% transported beyond 15 km, which occurs from particles originating from half of the release sites, with an absolute simulated distance of 36 km observed. This provides information suggesting that the disease management areas developed for infectious salmon anaemia control may also have properties appropriate for salmon lice management in Scottish coastal waters. Additionally, general numerical descriptors of the simulated relative lice abundance reduction with increased distance from release location are proposed. © 2015 Crown copyright. © 2015 John Wiley & Sons Ltd.

A generic bio-economic farm model for environmental and economic assessment of agricultural systems.

PubMed

Janssen, Sander; Louhichi, Kamel; Kanellopoulos, Argyris; Zander, Peter; Flichman, Guillermo; Hengsdijk, Huib; Meuter, Eelco; Andersen, Erling; Belhouchette, Hatem; Blanco, Maria; Borkowski, Nina; Heckelei, Thomas; Hecker, Martin; Li, Hongtao; Oude Lansink, Alfons; Stokstad, Grete; Thorne, Peter; van Keulen, Herman; van Ittersum, Martin K

2010-12-01

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.

A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

PubMed Central

Louhichi, Kamel; Kanellopoulos, Argyris; Zander, Peter; Flichman, Guillermo; Hengsdijk, Huib; Meuter, Eelco; Andersen, Erling; Belhouchette, Hatem; Blanco, Maria; Borkowski, Nina; Heckelei, Thomas; Hecker, Martin; Li, Hongtao; Oude Lansink, Alfons; Stokstad, Grete; Thorne, Peter; van Keulen, Herman; van Ittersum, Martin K.

2010-01-01

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models. PMID:21113782

How do farm models compare when estimating greenhouse gas emissions from dairy cattle production?

PubMed

Hutchings, N J; Özkan Gülzari, Ş; de Haan, M; Sandars, D

2018-01-09

The European Union Effort Sharing Regulation (ESR) will require a 30% reduction in greenhouse gas (GHG) emissions by 2030 compared with 2005 from the sectors not included in the European Emissions Trading Scheme, including agriculture. This will require the estimation of current and future emissions from agriculture, including dairy cattle production systems. Using a farm-scale model as part of a Tier 3 method for farm to national scales provides a more holistic and informative approach than IPCC (2006) Tier 2 but requires independent quality control. Comparing the results of using models to simulate a range of scenarios that explore an appropriate range of biophysical and management situations can support this process by providing a framework for placing model results in context. To assess the variation between models and the process of understanding differences, estimates of GHG emissions from four farm-scale models (DairyWise, FarmAC, HolosNor and SFARMMOD) were calculated for eight dairy farming scenarios within a factorial design consisting of two climates (cool/dry and warm/wet)×two soil types (sandy and clayey)×two feeding systems (grass only and grass/maize). The milk yield per cow, follower:cow ratio, manure management system, nitrogen (N) fertilisation and land area were standardised for all scenarios in order to associate the differences in the results with the model structure and function. Potential yield and application of available N in fertiliser and manure were specified separately for grass and maize. Significant differences between models were found in GHG emissions at the farm-scale and for most contributory sources, although there was no difference in the ranking of source magnitudes. The farm-scale GHG emissions, averaged over the four models, was 10.6 t carbon dioxide equivalents (CO2e)/ha per year, with a range of 1.9 t CO2e/ha per year. Even though key production characteristics were specified in the scenarios, there were still significant differences between models in the annual milk production per ha and the amounts of N fertiliser and concentrate feed imported. This was because the models differed in their description of biophysical responses and feedback mechanisms, and in the extent to which management functions were internalised. We conclude that comparing the results of different farm-scale models when applied to a range of scenarios would build confidence in their use in achieving ESR targets, justifying further investment in the development of a wider range of scenarios and software tools.

Wind Farm Layout Optimization through a Crossover-Elitist Evolutionary Algorithm performed over a High Performing Analytical Wake Model

NASA Astrophysics Data System (ADS)

Kirchner-Bossi, Nicolas; Porté-Agel, Fernando

2017-04-01

Wind turbine wakes can significantly disrupt the performance of further downstream turbines in a wind farm, thus seriously limiting the overall wind farm power output. Such effect makes the layout design of a wind farm to play a crucial role on the whole performance of the project. An accurate definition of the wake interactions added to a computationally compromised layout optimization strategy can result in an efficient resource when addressing the problem. This work presents a novel soft-computing approach to optimize the wind farm layout by minimizing the overall wake effects that the installed turbines exert on one another. An evolutionary algorithm with an elitist sub-optimization crossover routine and an unconstrained (continuous) turbine positioning set up is developed and tested over an 80-turbine offshore wind farm over the North Sea off Denmark (Horns Rev I). Within every generation of the evolution, the wind power output (cost function) is computed through a recently developed and validated analytical wake model with a Gaussian profile velocity deficit [1], which has shown to outperform the traditionally employed wake models through different LES simulations and wind tunnel experiments. Two schemes with slightly different perimeter constraint conditions (full or partial) are tested. Results show, compared to the baseline, gridded layout, a wind power output increase between 5.5% and 7.7%. In addition, it is observed that the electric cable length at the facilities is reduced by up to 21%. [1] Bastankhah, Majid, and Fernando Porté-Agel. "A new analytical model for wind-turbine wakes." Renewable Energy 70 (2014): 116-123.

Environmental potentials of policy instruments to mitigate nutrient emissions in Chinese livestock production.

PubMed

Zheng, Chaohui; Liu, Yi; Bluemling, Bettina; Mol, Arthur P J; Chen, Jining

2015-01-01

To minimize negative environmental impact of livestock production, policy-makers face a challenge to design and implement more effective policy instruments for livestock farmers at different scales. This research builds an assessment framework on the basis of an agent-based model, named ANEM, to explore nutrient mitigation potentials of five policy instruments, using pig production in Zhongjiang county, southwest China, as the empirical filling. The effects of different policy scenarios are simulated and compared using four indicators and differentiating between small, medium and large scale pig farms. Technology standards, biogas subsidies and information provisioning prove to be the most effective policies, while pollution fees and manure markets fail to environmentally improve manure management in pig livestock farming. Medium-scale farms are the more relevant scale category for a more environmentally sound development of Chinese livestock production. A number of policy recommendations are formulated as conclusion, as well as some limitations and prospects of the simulations are discussed. Copyright © 2014 Elsevier B.V. All rights reserved.

Narrowing the agronomic yield gap with improved nitrogen use efficiency: a modeling approach.

PubMed

Ahrens, T D; Lobell, D B; Ortiz-Monasterio, J I; Li, Y; Matson, P A

2010-01-01

Improving nitrogen use efficiency (NUE) in the major cereals is critical for more sustainable nitrogen use in high-input agriculture, but our understanding of the potential for NUE improvement is limited by a paucity of reliable on-farm measurements. Limited on-farm data suggest that agronomic NUE (AE(N)) is lower and more variable than data from trials conducted at research stations, on which much of our understanding of AE(N) has been built. The purpose of this study was to determine the magnitude and causes of variability in AE(N) across an agricultural region, which we refer to as the achievement distribution of AE(N). The distribution of simulated AE(N) in 80 farmers' fields in an irrigated wheat system in the Yaqui Valley, Mexico, was compared with trials at a local research center (International Wheat and Maize Improvement Center; CIMMYT). An agroecosystem simulation model WNMM was used to understand factors controlling yield, AE(N), gaseous N emissions, and nitrate leaching in the region. Simulated AE(N) in the Yaqui Valley was highly variable, and mean on-farm AE(N) was 44% lower than trials with similar fertilization rates at CIMMYT. Variability in residual N supply was the most important factor determining simulated AE(N). Better split applications of N fertilizer led to almost a doubling of AE(N), increased profit, and reduced N pollution, and even larger improvements were possible with technologies that allow for direct measurement of soil N supply and plant N demand, such as site-specific nitrogen management.

Analysis of near-surface relative humidity in a wind turbine array boundary layer using an instrumented unmanned aerial system and large-eddy simulation

NASA Astrophysics Data System (ADS)

Adkins, Kevin; Elfajri, Oumnia; Sescu, Adrian

2016-11-01

Simulation and modeling have shown that wind farms have an impact on the near-surface atmospheric boundary layer (ABL) as turbulent wakes generated by the turbines enhance vertical mixing. These changes alter downstream atmospheric properties. With a large portion of wind farms hosted within an agricultural context, changes to the environment can potentially have secondary impacts such as to the productivity of crops. With the exception of a few observational data sets that focus on the impact to near-surface temperature, little to no observational evidence exists. These few studies also lack high spatial resolution due to their use of a limited number of meteorological towers or remote sensing techniques. This study utilizes an instrumented small unmanned aerial system (sUAS) to gather in-situ field measurements from two Midwest wind farms, focusing on the impact that large utility-scale wind turbines have on relative humidity. Results are also compared to numerical experiments conducted using large eddy simulation (LES). Wind turbines are found to differentially alter the relative humidity in the downstream, spanwise and vertical directions under a variety of atmospheric stability conditions.

Economic and environmental impacts of the corn grain ethanol industry on the United States agricultural sector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larson, J.A.; English, B.C.; De La Torre Ugarte, D. G.

2010-09-10

This study evaluated the impacts of increased ethanol production from corn starch on agricultural land use and the environment in the United States. The Policy Analysis System simulation model was used to simulate alternative ethanol production scenarios for 2007 through 2016. Results indicate that increased corn ethanol production had a positive effect on net farm income and economic wellbeing of the US agricultural sector. In addition, government payments to farmers were reduced because of higher commodity prices and enhanced net farm income. Results also indicate that if Conservation Reserve Program land was converted to crop production in response to highermore » demand for ethanol in the simulation, individual farmers planted more land in crops, including corn. With a larger total US land area in crops due to individual farmer cropping choices, total US crop output rose, which decreased crop prices and aggregate net farm income relative to the scenario where increased ethanol production happened without Conservation Reserve Program land. Substantial shifts in land use occurred with corn area expanding throughout the United States, especially in the traditional corn-growing area of the midcontinent region.« less

Simulating the impact of no-till systems on field water fluxes and maize productivity under semi-arid conditions

NASA Astrophysics Data System (ADS)

Mupangwa, W.; Jewitt, G. P. W.

Crop output from the smallholder farming sector in sub-Saharan Africa is trailing population growth leading to widespread household food insecurity. It is therefore imperative that crop production in semi-arid areas be improved in order to meet the food demand of the ever increasing human population. No-till farming practices have the potential to increase crop productivity in smallholder production systems of sub-Saharan Africa, but rarely do because of the constraints experienced by these farmers. One of the most significant of these is the consumption of mulch by livestock. In the absence of long term on-farm assessment of the no-till system under smallholder conditions, simulation modelling is a tool that provides an insight into the potential benefits and can highlight shortcomings of the system under existing soil, climatic and socio-economic conditions. Thus, this study was designed to better understand the long term impact of no-till system without mulch cover on field water fluxes and maize productivity under a highly variable rainfall pattern typical of semi-arid South Africa. The simulated on-farm experiment consisted of two tillage treatments namely oxen-drawn conventional ploughing (CT) and ripping (NT). The APSIM model was applied for a 95 year period after first being calibrated and validated using measured runoff and maize yield data. The predicted results showed significantly higher surface runoff from the conventional system compared to the no-till system. Predicted deep drainage losses were higher from the NT system compared to the CT system regardless of the rainfall pattern. However, the APSIM model predicted 62% of the annual rainfall being lost through soil evaporation from both tillage systems. The predicted yields from the two systems were within 50 kg ha -1 difference in 74% of the years used in the simulation. In only 9% of the years, the model predicted higher grain yield in the NT system compared to the CT system. It is suggested that NT systems may have great potential for reducing surface runoff from smallholder fields and that the NT systems may have potential to recharge groundwater resources through increased deep drainage. However, it was also noted that the APSIM model has major shortcomings in simulating the water balance at this level of detail and that the findings need to be confirmed by further field based and modelling studies. Nevertheless, it is clear that without mulch or a cover crop, the continued high soil evaporation and correspondingly low crop yields suggest that there is little benefit to farmers adopting NT systems in semiarid environments, despite potential water resources benefits downstream. In such cases, the potential for payment for ecosystem services should be explored.

Dynamic wake model with coordinated pitch and torque control of wind farms for power tracking

NASA Astrophysics Data System (ADS)

Shapiro, Carl; Meyers, Johan; Meneveau, Charles; Gayme, Dennice

2017-11-01

Control of wind farm power production, where wind turbines within a wind farm coordinate to follow a time-varying power set point, is vital for increasing renewable energy participation in the power grid. Previous work developed a one-dimensional convection-diffusion equation describing the advection of the velocity deficit behind each turbine (wake) as well the turbulent mixing of the wake with the surrounding fluid. Proof-of-concept simulations demonstrated that a receding horizon controller built around this time-dependent model can effectively provide power tracking services by modulating the thrust coefficients of individual wind turbines. In this work, we extend this model-based controller to include pitch angle and generator torque control and the first-order dynamics of the drive train. Including these dynamics allows us to investigate control strategies for providing kinetic energy reserves to the grid, i.e. storing kinetic energy from the wind in the rotating mass of the wind turbine rotor for later use. CS, CM, and DG are supported by NSF (ECCS-1230788, CMMI 1635430, and OISE-1243482, the WINDINSPIRE project). JM is supported by ERC (ActiveWindFarms, 306471). This research was conducted using computational resources at MARCC.

Prediction of penicillin resistance in Staphylococcus aureus isolates from dairy cows with mastitis, based on prior test results.

PubMed

Grinberg, A; Lopez-Villalobos, N; Lawrence, K; Nulsen, M

2005-10-01

To gauge how well prior laboratory test results predict in vitro penicillin resistance of Staphylococcus aureus isolates from dairy cows with mastitis. Population-based data on the farm of origin (n=79), genotype based on pulsed-field gel electrophoresis (PFGE) results, and the penicillin-resistance status of Staph. aureus isolates (n=115) from milk samples collected from dairy cows with mastitis submitted to two diagnostic laboratories over a 6-month period were used. Data were mined stochastically using the all-possible-pairs method, binomial modelling and bootstrap simulation, to test whether prior test results enhance the accuracy of prediction of penicillin resistance on farms. Of all Staph. aureus isolates tested, 38% were penicillin resistant. A significant aggregation of penicillin-resistance status was evident within farms. The probability of random pairs of isolates from the same farm having the same penicillin-resistance status was 76%, compared with 53% for random pairings of samples across all farms. Thus, the resistance status of randomly selected isolates was 1.43 times more likely to correctly predict the status of other isolates from the same farm than the random population pairwise concordance probability (p=0.011). This effect was likely due to the clonal relationship of isolates within farms, as the predictive fraction attributable to prior test results was close to nil when the effect of within-farm clonal infections was withdrawn from the model. Knowledge of the penicillin-resistance status of a prior Staph. aureus isolate significantly enhanced the predictive capability of other isolates from the same farm. In the time and space frame of this study, clinicians using previous information from a farm would have more accurately predicted the penicillin-resistance status of an isolate than they would by chance alone on farms infected with clonal Staph. aureus isolates, but not on farms infected with highly genetically heterogeneous bacterial strains.

The epidemiological and economic effects from systematic depopulation of Norwegian marine salmon farms infected with pancreas disease virus.

PubMed

Pettersen, J M; Brynildsrud, O B; Huseby, R B; Rich, K M; Aunsmo, A; Bang, B Jensen; Aldrin, M

2016-09-15

Pancreas disease (PD) is a viral disease associated with significant economic losses in Scottish, Irish, and Norwegian marine salmon aquaculture. In this paper, we investigate how disease-triggered harvest strategies (systematic depopulation of infected marine salmon farms) towards PD can affect disease dynamics and salmon producer profits in an endemic area in the southwestern part of Norway. Four different types of disease-triggered harvest strategies were evaluated over a four-year period (2011-2014), each scenario with different disease-screening procedures, timing for initiating the harvest interventions on infected cohorts, and levels of farmer compliance to the strategy. Our approach applies a spatio-temporal stochastic model for simulating the spread of PD in the separate scenarios. Results from these simulations were then used in cost-benefit analyses to estimate the net benefits of different harvest strategies over time. We find that the most aggressive strategy, in which infected farms are harvested without delay, was most efficient in terms of reducing infection pressure in the area and providing economic benefits for the studied group of salmon producers. On the other hand, lower farm compliance leads to higher infection pressure and less economic benefits. Model results further highlight trade-offs in strategies between those that primarily benefit individual producers and those that have collective benefits, suggesting a need for institutional mechanisms that address these potential tensions. Copyright © 2016 Elsevier B.V. All rights reserved.

Experimental Study on the Wake Meandering Within a Scale Model Wind Farm Subject to a Wind-Tunnel Flow Simulating an Atmospheric Boundary Layer

NASA Astrophysics Data System (ADS)

Coudou, Nicolas; Buckingham, Sophia; Bricteux, Laurent; van Beeck, Jeroen

2017-12-01

The phenomenon of meandering of the wind-turbine wake comprises the motion of the wake as a whole in both horizontal and vertical directions as it is advected downstream. The oscillatory motion of the wake is a crucial factor in wind farms, because it increases the fatigue loads, and, in particular, the yaw loads on downstream turbines. To address this phenomenon, experimental investigations are carried out in a wind-tunnel flow simulating an atmospheric boundary layer with the Coriolis effect neglected. A 3 × 3 scaled wind farm composed of three-bladed rotating wind-turbine models is subject to a neutral boundary layer over a slightly-rough surface, i.e. corresponding to offshore conditions. Particle-image-velocimetry measurements are performed in a horizontal plane at hub height in the wakes of the three wind turbines occupying the wind-farm centreline. These measurements allow determination of the wake centrelines, with spectral analysis indicating the characteristic wavelength of the wake-meandering phenomenon. In addition, measurements with hot-wire anemometry are performed along a vertical line in the wakes of the same wind turbines, with both techniques revealing the presence of wake meandering behind all three turbines. The spectral analysis performed with the spatial and temporal signals obtained from these two measurement techniques indicates a Strouhal number of ≈ 0.20 - 0.22 based on the characteristic wake-meandering frequency, the rotor diameter and the flow speed at hub height.

Experimental Study on the Wake Meandering Within a Scale Model Wind Farm Subject to a Wind-Tunnel Flow Simulating an Atmospheric Boundary Layer

NASA Astrophysics Data System (ADS)

Coudou, Nicolas; Buckingham, Sophia; Bricteux, Laurent; van Beeck, Jeroen

2018-04-01

The phenomenon of meandering of the wind-turbine wake comprises the motion of the wake as a whole in both horizontal and vertical directions as it is advected downstream. The oscillatory motion of the wake is a crucial factor in wind farms, because it increases the fatigue loads, and, in particular, the yaw loads on downstream turbines. To address this phenomenon, experimental investigations are carried out in a wind-tunnel flow simulating an atmospheric boundary layer with the Coriolis effect neglected. A 3 × 3 scaled wind farm composed of three-bladed rotating wind-turbine models is subject to a neutral boundary layer over a slightly-rough surface, i.e. corresponding to offshore conditions. Particle-image-velocimetry measurements are performed in a horizontal plane at hub height in the wakes of the three wind turbines occupying the wind-farm centreline. These measurements allow determination of the wake centrelines, with spectral analysis indicating the characteristic wavelength of the wake-meandering phenomenon. In addition, measurements with hot-wire anemometry are performed along a vertical line in the wakes of the same wind turbines, with both techniques revealing the presence of wake meandering behind all three turbines. The spectral analysis performed with the spatial and temporal signals obtained from these two measurement techniques indicates a Strouhal number of ≈ 0.20 - 0.22 based on the characteristic wake-meandering frequency, the rotor diameter and the flow speed at hub height.

Critical Behavior in Cellular Automata Animal Disease Transmission Model

NASA Astrophysics Data System (ADS)

Morley, P. D.; Chang, Julius

Using cellular automata model, we simulate the British Government Policy (BGP) in the 2001 foot and mouth epidemic in Great Britain. When clinical symptoms of the disease appeared in a farm, there is mandatory slaughter (culling) of all livestock in an infected premise (IP). Those farms in the neighboring of an IP (contiguous premise, CP), are also culled, aka nearest neighbor interaction. Farms where the disease may be prevalent from animal, human, vehicle or airborne transmission (dangerous contact, DC), are additionally culled, aka next-to-nearest neighbor interactions and lightning factor. The resulting mathematical model possesses a phase transition, whereupon if the physical disease transmission kernel exceeds a critical value, catastrophic loss of animals ensues. The nonlocal disease transport probability can be as low as 0.01% per day and the disease can still be in the high mortality phase. We show that the fundamental equation for sustainable disease transport is the criticality equation for neutron fission cascade. Finally, we calculate that the percentage of culled animals that are actually healthy is ≈30%.

The economic benefits of disease triggered early harvest: A case study of pancreas disease in farmed Atlantic salmon from Norway.

PubMed

Pettersen, J M; Rich, K M; Jensen, B Bang; Aunsmo, A

2015-10-01

Pancreas disease (PD) is an important viral disease in Norwegian, Scottish and Irish aquaculture causing biological losses in terms of reduced growth, mortality, increased feed conversion ratio, and carcass downgrading. We developed a bio-economic model to investigate the economic benefits of a disease triggered early harvesting strategy to control PD losses. In this strategy, the salmon farm adopts a PCR (Polymerase Chain Reaction) diagnostic screening program to monitor the virus levels in stocks. Virus levels are used to forecast a clinical outbreak of pancreas disease, which then initiates a prescheduled harvest of the stock to avoid disease losses. The model is based on data inputs from national statistics, literature, company data, and an expert panel, and use stochastic simulations to account for the variation and/or uncertainty associated with disease effects and selected production expenditures. With the model, we compared the impacts of a salmon farm undergoing prescheduled harvest versus the salmon farm going through a PD outbreak. We also estimated the direct costs of a PD outbreak as the sum of biological losses, treatment costs, prevention costs, and other additional costs, less the costs of insurance pay-outs. Simulation results suggests that the economic benefit from a prescheduled harvest is positive once the average salmon weight at the farm has reached 3.2kg or more for an average Norwegian salmon farm stocked with 1,000,000smolts and using average salmon sales prices for 2013. The direct costs from a PD outbreak occurring nine months (average salmon weight 1.91kg) after sea transfer and using 2013 sales prices was on average estimated at NOK 55.4 million (5%, 50% and 90% percentile: 38.0, 55.8 and 72.4) (NOK=€0.128 in 2013). Sensitivity analyses revealed that the losses from a PD outbreak are sensitive to feed- and salmon sales prices, and that high 2013 sales prices contributed to substantial losses associated with a PD outbreak. Copyright © 2015 Elsevier B.V. All rights reserved.

Farming the mitochondrial ancestor as a model of endosymbiotic establishment by natural selection.

PubMed

Zachar, István; Szilágyi, András; Számadó, Szabolcs; Szathmáry, Eörs

2018-02-13

The origin of mitochondria was a major evolutionary transition leading to eukaryotes, and is a hotly debated issue. It is unknown whether mitochondria were acquired early or late, and whether it was captured via phagocytosis or syntrophic integration. We present dynamical models to directly simulate the emergence of mitochondria in an ecoevolutionary context. Our results show that regulated farming of prey bacteria and delayed digestion can facilitate the establishment of stable endosymbiosis if prey-rich and prey-poor periods alternate. Stable endosymbiosis emerges without assuming any initial metabolic benefit provided by the engulfed partner, in a wide range of parameters, despite that during good periods farming is costly. Our approach lends support to the appearance of mitochondria before any metabolic coupling has emerged, but after the evolution of primitive phagocytosis by the urkaryote. Copyright © 2018 the Author(s). Published by PNAS.

Phytoplankton dynamics in the Gulf of Aqaba (Eilat, Red Sea): a simulation study of mariculture effects.

PubMed

Laiolo, Leonardo; Barausse, Alberto; Dubinsky, Zvy; Palmeri, Luca; Goffredo, Stefano; Kamenir, Yury; Al-Najjar, Tariq; Iluz, David

2014-09-15

The northern Gulf of Aqaba is an oligotrophic water body hosting valuable coral reefs. In the Gulf, phytoplankton dynamics are driven by an annual cycle of stratification and mixing. Superimposed on that fairly regular pattern was the establishment of a shallow-water fish-farm initiative that increased gradually until its activity was terminated in June 2008. Nutrient, water temperature, irradiation, phytoplankton data gathered in the area during the years 2007-2009, covering the peak of the fish-farm activity and its cessation, were analyzed by means of statistical analyses and ecological models of phytoplankton dynamics. Two datasets, one from an open water station and one next to the fish farms, were used. Results show that nutrient concentrations and, consequently, phytoplankton abundance and seasonal succession were radically altered by the pollution originating from the fish-farm in the sampling station closer to it, and also that the fish-farm might even have influenced the open water station. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cost analysis of immunisation against east coast fever on smallholder dairy farms in Kenya.

PubMed

Muraguri, G R; Mbogo, S K; McHardy, N; Kariuki, D P

1998-03-27

A spreadsheet model was developed and used to estimate the total cost of immunising cattle against East Coast fever (ECF) based on the infection-and-treatment method. Using data from an immunisation trial carried out on 102 calves and yearlings on 64 farms in the Githunguri division, Kiambu district, Kenya, a reference base scenario of a mean herd of five animals, a 10% rate of reaction to immunisation and a 2-day interval monitoring regimen (a total of 10 farm visits) was simulated. Under these conditions, the mean cost of immunisation per animal was US$16.48 (Ksh 955.78); this was equivalent to US$82.39 (Ksh 4778.90) per five-animal farm. A commonly reported reactor rate of 3% would decrease the cost of US$14.63 (Ksh 848.29) per animal. Reducing the number of farm monitoring visits from 10 to 7 would reduce the total cost by 10%, justified if farmers are trained to undertake some of the monitoring work. The fixed costs were 53% of the total cost of immunisation per farm. The cost of immunisation decreased with increasing number of animals per farm, showing economies of scale.

AN EVALUATION OF HANFORD SITE TANK FARM SUBSURFACE CONTAMINATION FY2007

DOE Office of Scientific and Technical Information (OSTI.GOV)

MANN, F.M.

2007-07-10

The Tank Farm Vadose Zone (TFVZ) Project conducts activities to characterize and analyze the long-term environmental and human health impacts from tank waste releases to the vadose zone. The project also implements interim measures to mitigate impacts, and plans the remediation of waste releases from tank farms and associated facilities. The scope of this document is to report data needs that are important to estimating long-term human health and environmental risks. The scope does not include technologies needed to remediate contaminated soils and facilities, technologies needed to close tank farms, or management and regulatory decisions that will impact remediation andmore » closure. This document is an update of ''A Summary and Evaluation of Hanford Site Tank Farm Subsurface Contamination''. That 1998 document summarized knowledge of subsurface contamination beneath the tank farms at the time. It included a preliminary conceptual model for migration of tank wastes through the vadose zone and an assessment of data and analysis gaps needed to update the conceptual model. This document provides a status of the data and analysis gaps previously defined and discussion of the gaps and needs that currently exist to support the stated mission of the TFVZ Project. The first data-gaps document provided the basis for TFVZ Project activities over the previous eight years. Fourteen of the nineteen knowledge gaps identified in the previous document have been investigated to the point that the project defines the current status as acceptable. In the process of filling these gaps, significant accomplishments were made in field work and characterization, laboratory investigations, modeling, and implementation of interim measures. The current data gaps are organized in groups that reflect Components of the tank farm vadose zone conceptual model: inventory, release, recharge, geohydrology, geochemistry, and modeling. The inventory and release components address residual wastes that will remain in the tanks and tank-farm infrastructure after closure and potential losses from leaks during waste retrieval. Recharge addresses the impacts of current conditions in the tank farms (i.e. gravel covers that affect infiltration and recharge) as well as the impacts of surface barriers. The geohydrology and geochemistry components address the extent of the existing subsurface contaminant inventory and drivers and pathways for contaminants to be transported through the vadose zone and groundwater. Geochemistry addresses the mobility of key reactive contaminants such as uranium. Modeling addresses conceptual models and how they are simulated in computers. The data gaps will be used to provide input to planning (including the upcoming C Farm Data Quality Objective meetings scheduled this year).« less

Modeling of phosphorus loads in sugarcane in a low-relief landscape using ontology-based simulation.

PubMed

Kwon, Ho-Young; Grunwald, Sabine; Beck, Howard W; Jung, Yunchul; Daroub, Samira H; Lang, Timothy A; Morgan, Kelly T

2010-01-01

Water flow and P dynamics in a low-relief landscape manipulated by extensive canal and ditch drainage systems were modeled utilizing an ontology-based simulation model. In the model, soil water flux and processes between three soil inorganic P pools (labile, active, and stable) and organic P are represented as database objects. And user-defined relationships among objects are used to automatically generate computer code (Java) for running the simulation of discharge and P loads. Our objectives were to develop ontology-based descriptions of soil P dynamics within sugarcane- (Saccharum officinarum L.) grown farm basins of the Everglades Agricultural Area (EAA) and to calibrate and validate such processes with water quality monitoring data collected at one farm basin (1244 ha). In the calibration phase (water year [WY] 99-00), observed discharge totaled 11,114 m3 ha(-1) and dissolved P 0.23 kg P ha(-1); and in the validation phase (WY 02-03), discharge was 10,397 m3 ha(-1) and dissolved P 0.11 kg P ha(-). During WY 99-00 the root mean square error (RMSE) for monthly discharge was 188 m3 ha(-1) and for monthly dissolved P 0.0077 kg P ha(-1); whereas during WY 02-03 the RMSE for monthly discharge was 195 m3 ha(-1) and monthly dissolved P 0.0022 kg P ha(-1). These results were confirmed by Nash-Sutcliffe Coefficient of 0.69 (calibration) and 0.81 (validation) comparing measured and simulated P loads. The good model performance suggests that our model has promise to simulate P dynamics, which may be useful as a management tool to reduce P loads in other similar low-relief areas.

A regional assessment of the cost and effectiveness of mitigation measures for reducing nutrient losses to water and greenhouse gas emissions to air from pastoral farms.

PubMed

Vibart, Ronaldo; Vogeler, Iris; Dennis, Samuel; Kaye-Blake, William; Monaghan, Ross; Burggraaf, Vicki; Beautrais, Josef; Mackay, Alec

2015-06-01

Using a novel approach that links geospatial land resource information with individual farm-scale simulation, we conducted a regional assessment of nitrogen (N) and phosphorous (P) losses to water and greenhouse gas (GHG) emissions to air from the predominant mix of pastoral industries in Southland, New Zealand. An evaluation of the cost-effectiveness of several nutrient loss mitigation strategies applied at the farm-scale, set primarily for reducing N and P losses and grouped by capital cost and potential ease of adoption, followed an initial baseline assessment. Grouped nutrient loss mitigation strategies were applied on an additive basis on the assumption of full adoption, and were broadly identified as 'improved nutrient management' (M1), 'improved animal productivity' (M2), and 'restricted grazing' (M3). Estimated annual nitrate-N leaching losses occurring under representative baseline sheep and beef (cattle) farms, and representative baseline dairy farms for the region were 10 ± 2 and 32 ± 6 kg N/ha (mean ± standard deviation), respectively. Both sheep and beef and dairy farms were responsive to N leaching loss mitigation strategies in M1, at a low cost per kg N-loss mitigated. Only dairy farms were responsive to N leaching loss abatement from adopting M2, at no additional cost per kg N-loss mitigated. Dairy farms were also responsive to N leaching loss abatement from adopting M3, but this reduction came at a greater cost per kg N-loss mitigated. Only dairy farms were responsive to P-loss mitigation strategies, in particular by adopting M1. Only dairy farms were responsive to GHG abatement; greater abatement was achieved by the most intensified dairy farm system simulated. Overall, M1 provided for high levels of regional scale N- and P-loss abatement at a low cost per farm without affecting overall farm production, M2 provided additional N-loss abatement but only marginal P-loss abatement, whereas M3 provided the greatest N-loss abatement, but delivered no additional P abatement, and came at a large financial cost to farmers, sheep and beef farmers in particular. The modelling approach provides a farm-scale framework that can be extended to other regions to accommodate different farm production systems and performances, capturing the interactions between farm types, land use capabilities and production levels, as these influence nutrient losses and GHG emissions, and the effectiveness of mitigation strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modelling the failure behaviour of wind turbines

NASA Astrophysics Data System (ADS)

Faulstich, S.; Berkhout, V.; Mayer, J.; Siebenlist, D.

2016-09-01

Modelling the failure behaviour of wind turbines is an essential part of offshore wind farm simulation software as it leads to optimized decision making when specifying the necessary resources for the operation and maintenance of wind farms. In order to optimize O&M strategies, a thorough understanding of a wind turbine's failure behaviour is vital and is therefore being developed at Fraunhofer IWES. Within this article, first the failure models of existing offshore O&M tools are presented to show the state of the art and strengths and weaknesses of the respective models are briefly discussed. Then a conceptual framework for modelling different failure mechanisms of wind turbines is being presented. This framework takes into account the different wind turbine subsystems and structures as well as the failure modes of a component by applying several influencing factors representing wear and break failure mechanisms. A failure function is being set up for the rotor blade as exemplary component and simulation results have been compared to a constant failure rate and to empirical wind turbine fleet data as a reference. The comparison and the breakdown of specific failure categories demonstrate the overall plausibility of the model.

NREL Software Models Performance of Wind Plants (Fact Sheet)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

2015-01-01

This NREL Highlight is being developed for the 2015 February Alliance S&T Meeting, and describes NREL's Simulator for Offshore Wind Farm Applications (SOWFA) software in collaboration with Norway-based Statoil, to optimize layouts and controls of wind plants arrays.

Modeling Agricultural Watersheds with the Soil and Water Assessment Tool (SWAT): Calibration and Validation with a Novel Procedure for Spatially Explicit HRUs.

PubMed

Teshager, Awoke Dagnew; Gassman, Philip W; Secchi, Silvia; Schoof, Justin T; Misgna, Girmaye

2016-04-01

Applications of the Soil and Water Assessment Tool (SWAT) model typically involve delineation of a watershed into subwatersheds/subbasins that are then further subdivided into hydrologic response units (HRUs) which are homogeneous areas of aggregated soil, landuse, and slope and are the smallest modeling units used within the model. In a given standard SWAT application, multiple potential HRUs (farm fields) in a subbasin are usually aggregated into a single HRU feature. In other words, the standard version of the model combines multiple potential HRUs (farm fields) with the same landuse/landcover, soil, and slope, but located at different places of a subbasin (spatially non-unique), and considers them as one HRU. In this study, ArcGIS pre-processing procedures were developed to spatially define a one-to-one match between farm fields and HRUs (spatially unique HRUs) within a subbasin prior to SWAT simulations to facilitate input processing, input/output mapping, and further analysis at the individual farm field level. Model input data such as landuse/landcover (LULC), soil, crop rotation, and other management data were processed through these HRUs. The SWAT model was then calibrated/validated for Raccoon River watershed in Iowa for 2002-2010 and Big Creek River watershed in Illinois for 2000-2003. SWAT was able to replicate annual, monthly, and daily streamflow, as well as sediment, nitrate and mineral phosphorous within recommended accuracy in most cases. The one-to-one match between farm fields and HRUs created and used in this study is a first step in performing LULC change, climate change impact, and other analyses in a more spatially explicit manner.

Modeling Agricultural Watersheds with the Soil and Water Assessment Tool (SWAT): Calibration and Validation with a Novel Procedure for Spatially Explicit HRUs

NASA Astrophysics Data System (ADS)

Teshager, Awoke Dagnew; Gassman, Philip W.; Secchi, Silvia; Schoof, Justin T.; Misgna, Girmaye

2016-04-01

Applications of the Soil and Water Assessment Tool (SWAT) model typically involve delineation of a watershed into subwatersheds/subbasins that are then further subdivided into hydrologic response units (HRUs) which are homogeneous areas of aggregated soil, landuse, and slope and are the smallest modeling units used within the model. In a given standard SWAT application, multiple potential HRUs (farm fields) in a subbasin are usually aggregated into a single HRU feature. In other words, the standard version of the model combines multiple potential HRUs (farm fields) with the same landuse/landcover, soil, and slope, but located at different places of a subbasin (spatially non-unique), and considers them as one HRU. In this study, ArcGIS pre-processing procedures were developed to spatially define a one-to-one match between farm fields and HRUs (spatially unique HRUs) within a subbasin prior to SWAT simulations to facilitate input processing, input/output mapping, and further analysis at the individual farm field level. Model input data such as landuse/landcover (LULC), soil, crop rotation, and other management data were processed through these HRUs. The SWAT model was then calibrated/validated for Raccoon River watershed in Iowa for 2002-2010 and Big Creek River watershed in Illinois for 2000-2003. SWAT was able to replicate annual, monthly, and daily streamflow, as well as sediment, nitrate and mineral phosphorous within recommended accuracy in most cases. The one-to-one match between farm fields and HRUs created and used in this study is a first step in performing LULC change, climate change impact, and other analyses in a more spatially explicit manner.

Let's put this in perspective: using dynamic simulation modelling to assess the impacts of farm-scale land management change on catchment-scale water quality

NASA Astrophysics Data System (ADS)

Rivers, Mark; Clarendon, Simon; Coles, Neil

2013-04-01

Natural Resource Management and Agri-industry development groups in Australia have invested considerable resources into the investigation of the economic, social and, particularly, environmental impacts of varying farming activities in a "catchment context". This research has resulted in the development of a much-improved understanding of the likely impacts of changed management practices at the farm-scale as well as the development of a number of conceptual models which place farming within this broader catchment context. The project discussed in this paper transformed a conceptual model of dairy farm phosphorus (P) management and transport processes into a more temporally and spatially dynamic model. This was then loaded with catchment-specific data and used as a "policy support tool" to allow the Australian dairy industry to examine the potential farm and catchment-scale impacts of varying dairy farm management practices within some key dairy farming regions. Models were developed, validated and calibrated using "STELLA©" dynamic modelling software for three catchments in which dairy is perceived as a significant land use. The models describe P movement and cycling within and through dairy farms in great detail and also estimate P transport through major source, sink and flow sectors of the catchments. A series of scenarios were executed for all three catchments which examined three main "groups" of tests: changes to farm P input rates; implementation of perceived environmental "Best Management Practices" (BMPs), and; changes to land use mosaics. Modifications to actual P input rates into dairy farms (not surprisingly) had a major effect on nutrient transport within and from the farms with a significant rise in nutrient loss rates at all scales with increasing fertiliser use. More surprisingly, however, even extensive environmental BMP implementation did not have marked effects on off-farm nutrient loss rates. On and off-farm riparian management implemented over entire catchments, for example, only reduced P losses by approximately 20%. Most importantly, changes to land use mosaics within the catchments provided great insight into the relative roles within the catchment P system of the various land uses. While dairying uses large amounts of P, the effects that dairy farm management can have at the catchment scale when these farms represent only a small proportion of the landscape are limited. The most important conclusions from the research are that: • While State and regional environmental management and regulatory agencies continue to set optimistic goals for water quality protection, this research shows that these targets are not achievable within current landscape paradigms even after broadscale BMP implementation, and that either these targets must be re-considered or that significant land use change (rather than simply improved management within current systems) must occur to meet the targets. • Catchment-scale effects of P losses at the farm scale are a complex function of P-use efficiency, landscape position and landscape footprint. Simply targetting those landuses perceived to have high nutrient loss rates does not adequately address the problem. • Catchment P management must be considered in a more inclusive and holistic way, and these assessments should be used to inform future planning policies and development plans if environmental goals as well as community expectations about the productive use of agricultural land are to be met.

Stability Augmentation of Wind Farm using Variable Speed Permanent Magnet Synchronous Generator

NASA Astrophysics Data System (ADS)

Rosyadi, Marwan; Muyeen, S. M.; Takahashi, Rion; Tamura, Junji

This paper presents a new control strategy of variable speed permanent magnet wind generator for stability augmentation of wind farm including fixed speed wind turbine with Induction Generator (IG). A new control scheme is developed for two levels back-to-back converters of Permanent Magnet Synchronous Generator (PMSG), by which both active and reactive powers delivered to the grid can be controlled easily. To avoid the converter damage, the DC link protection controller is also proposed in order to protect the dc link circuit during fault condition. To evaluate the control capability of the proposed controllers, simulations are performed on two model systems composed of wind farms connected to an infinite bus. From transient and steady state analyses by using PSCAD/EMTDC, it is concluded that the proposed control scheme is very effective to improve the stability of wind farm for severe network disturbance and randomly fluctuating wind speed.

SIMS(DAIRY): a modelling framework to identify sustainable dairy farms in the UK. Framework description and test for organic systems and N fertiliser optimisation.

PubMed

Del Prado, A; Misselbrook, T; Chadwick, D; Hopkins, A; Dewhurst, R J; Davison, P; Butler, A; Schröder, J; Scholefield, D

2011-09-01

Multiple demands are placed on farming systems today. Society, national legislation and market forces seek what could be seen as conflicting outcomes from our agricultural systems, e.g. food quality, affordable prices, a healthy environmental, consideration of animal welfare, biodiversity etc., Many of these demands, or desirable outcomes, are interrelated, so reaching one goal may often compromise another and, importantly, pose a risk to the economic viability of the farm. SIMS(DAIRY), a farm-scale model, was used to explore this complexity for dairy farm systems. SIMS(DAIRY) integrates existing approaches to simulate the effect of interactions between farm management, climate and soil characteristics on losses of nitrogen, phosphorus and carbon. The effects on farm profitability and attributes of biodiversity, milk quality, soil quality and animal welfare are also included. SIMS(DAIRY) can also be used to optimise fertiliser N. In this paper we discuss some limitations and strengths of using SIMS(DAIRY) compared to other modelling approaches and propose some potential improvements. Using the model we evaluated the sustainability of organic dairy systems compared with conventional dairy farms under non-optimised and optimised fertiliser N use. Model outputs showed for example, that organic dairy systems based on grass-clover swards and maize silage resulted in much smaller total GHG emissions per l of milk and slightly smaller losses of NO(3) leaching and NO(x) emissions per l of milk compared with the grassland/maize-based conventional systems. These differences were essentially because the conventional systems rely on indirect energy use for 'fixing' N compared with biological N fixation for the organic systems. SIMS(DAIRY) runs also showed some other potential benefits from the organic systems compared with conventional systems in terms of financial performance and soil quality and biodiversity scores. Optimisation of fertiliser N timings and rates showed a considerable scope to reduce the (GHG emissions per l milk too). Copyright © 2011 Elsevier B.V. All rights reserved.

Effect of inter-annual variability in pasture growth and irrigation response on farm productivity and profitability based on biophysical and farm systems modelling.

PubMed

Vogeler, Iris; Mackay, Alec; Vibart, Ronaldo; Rendel, John; Beautrais, Josef; Dennis, Samuel

2016-09-15

Farm system and nutrient budget models are increasingly being used in analysis to inform on farm decision making and evaluate land use policy options at regional scales. These analyses are generally based on the use of average annual pasture yields. In New Zealand (NZ), like in many countries, there is considerable inter-annual variation in pasture growth rates, due to climate. In this study a modelling approach was used to (i) include inter-annual variability as an integral part of the analysis and (ii) test the approach in an economic analysis of irrigation in a case study within the Hawkes Bay Region of New Zealand. The Agricultural Production Systems Simulator (APSIM) was used to generate pasture dry matter yields (DMY) for 20 different years and under both dryland and irrigation. The generated DMY were linked to outputs from farm-scale modelling for both Sheep and Beef Systems (Farmaxx Pro) and Dairy Systems (Farmax® Dairy Pro) to calculate farm production over 20 different years. Variation in DMY and associated livestock production due to inter-annual variation in climate was large, with a coefficient of variations up to 20%. Irrigation decreased this inter-annual variation. On average irrigation, with unlimited available water, increased income by $831 to 1195/ha, but when irrigation was limited to 250mm/ha/year income only increased by $525 to 883/ha. Using pasture responses in individual years to capturing the inter-annual variation, rather than the pasture response averaged over 20years resulted in lower financial benefits. In the case study income from irrigation based on an average year were 10 to >20% higher compared with those obtained from individual years. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigation of thermolytic hydrogen generation rate of tank farm simulated and actual waste

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martino, C.; Newell, D.; Woodham, W.

To support resolution of Potential Inadequacies in the Safety Analysis for the Savannah River Site (SRS) Tank Farm, Savannah River National Laboratory conducted research to determine the thermolytic hydrogen generation rate (HGR) with simulated and actual waste. Gas chromatography methods were developed and used with air-purged flow systems to quantify hydrogen generation from heated simulated and actual waste at rates applicable to the Tank Farm Documented Safety Analysis (DSA). Initial simulant tests with a simple salt solution plus sodium glycolate demonstrated the behavior of the test apparatus by replicating known HGR kinetics. Additional simulant tests with the simple salt solutionmore » excluding organics apart from contaminants provided measurement of the detection and quantification limits for the apparatus with respect to hydrogen generation. Testing included a measurement of HGR on actual SRS tank waste from Tank 38. A final series of measurements examined HGR for a simulant with the most common SRS Tank Farm organics at temperatures up to 140 °C. The following conclusions result from this testing.« less

Control strategies for wind farm power optimization: LES study

NASA Astrophysics Data System (ADS)

Ciri, Umberto; Rotea, Mario; Leonardi, Stefano

2017-11-01

Turbines in wind farms operate in off-design conditions as wake interactions occur for particular wind directions. Advanced wind farm control strategies aim at coordinating and adjusting turbine operations to mitigate power losses in such conditions. Coordination is achieved by controlling on upstream turbines either the wake intensity, through the blade pitch angle or the generator torque, or the wake direction, through yaw misalignment. Downstream turbines can be adapted to work in waked conditions and limit power losses, using the blade pitch angle or the generator torque. As wind conditions in wind farm operations may change significantly, it is difficult to determine and parameterize the variations of the coordinated optimal settings. An alternative is model-free control and optimization of wind farms, which does not require any parameterization and can track the optimal settings as conditions vary. In this work, we employ a model-free optimization algorithm, extremum-seeking control, to find the optimal set-points of generator torque, blade pitch and yaw angle for a three-turbine configuration. Large-Eddy Simulations are used to provide a virtual environment to evaluate the performance of the control strategies under realistic, unsteady incoming wind. This work was supported by the National Science Foundation, Grants No. 1243482 (the WINDINSPIRE project) and IIP 1362033 (I/UCRC WindSTAR). TACC is acknowledged for providing computational time.

Process-based Modeling of Ammonia Emission from Beef Cattle Feedyards with the Integrated Farm Systems Model.

PubMed

Waldrip, Heidi M; Rotz, C Alan; Hafner, Sasha D; Todd, Richard W; Cole, N Andy

2014-07-01

Ammonia (NH) volatilization from manure in beef cattle feedyards results in loss of agronomically important nitrogen (N) and potentially leads to overfertilization and acidification of aquatic and terrestrial ecosystems. In addition, NH is involved in the formation of atmospheric fine particulate matter (PM), which can affect human health. Process-based models have been developed to estimate NH emissions from various livestock production systems; however, little work has been conducted to assess their accuracy for large, open-lot beef cattle feedyards. This work describes the extension of an existing process-based model, the Integrated Farm Systems Model (IFSM), to include simulation of N dynamics in this type of system. To evaluate the model, IFSM-simulated daily per capita NH emission rates were compared with emissions data collected from two commercial feedyards in the Texas High Plains from 2007 to 2009. Model predictions were in good agreement with observations and were sensitive to variations in air temperature and dietary crude protein concentration. Predicted mean daily NH emission rates for the two feedyards had 71 to 81% agreement with observations. In addition, IFSM estimates of annual feedyard emissions were within 11 to 24% of observations, whereas a constant emission factor currently in use by the USEPA underestimated feedyard emissions by as much as 79%. The results from this study indicate that IFSM can quantify average feedyard NH emissions, assist with emissions reporting, provide accurate information for legislators and policymakers, investigate methods to mitigate NH losses, and evaluate the effects of specific management practices on farm nutrient balances. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Landscape structure and management alter the outcome of a pesticide ERA: Evaluating impacts of endocrine disruption using the ALMaSS European Brown Hare model.

PubMed

Topping, Chris J; Dalby, Lars; Skov, Flemming

2016-01-15

There is a gradual change towards explicitly considering landscapes in regulatory risk assessment. To realise the objective of developing representative scenarios for risk assessment it is necessary to know how detailed a landscape representation is needed to generate a realistic risk assessment, and indeed how to generate such landscapes. This paper evaluates the contribution of landscape and farming components to a model based risk assessment of a fictitious endocrine disruptor on hares. In addition, we present methods and code examples for generation of landscape structures and farming simulation from data collected primarily for EU agricultural subsidy support and GIS map data. Ten different Danish landscapes were generated and the ERA carried out for each landscape using two different assumed toxicities. The results showed negative impacts in all cases, but the extent and form in terms of impacts on abundance or occupancy differed greatly between landscapes. A meta-model was created, predicting impact from landscape and farming characteristics. Scenarios based on all combinations of farming and landscape for five landscapes representing extreme and middle impacts were created. The meta-models developed from the 10 real landscapes failed to predict impacts for these 25 scenarios. Landscape, farming, and the emergent density of hares all influenced the results of the risk assessment considerably. The study indicates that prediction of a reasonable worst case scenario is difficult from structural, farming or population metrics; rather the emergent properties generated from interactions between landscape, management and ecology are needed. Meta-modelling may also fail to predict impacts, even when restricting inputs to combinations of those used to create the model. Future ERA may therefore need to make use of multiple scenarios representing a wide range of conditions to avoid locally unacceptable risks. This approach could now be feasible Europe wide given the landscape generation methods presented.

Surrogate based wind farm layout optimization using manifold mapping

NASA Astrophysics Data System (ADS)

Kaja Kamaludeen, Shaafi M.; van Zuijle, Alexander; Bijl, Hester

2016-09-01

High computational cost associated with the high fidelity wake models such as RANS or LES serves as a primary bottleneck to perform a direct high fidelity wind farm layout optimization (WFLO) using accurate CFD based wake models. Therefore, a surrogate based multi-fidelity WFLO methodology (SWFLO) is proposed. The surrogate model is built using an SBO method referred as manifold mapping (MM). As a verification, optimization of spacing between two staggered wind turbines was performed using the proposed surrogate based methodology and the performance was compared with that of direct optimization using high fidelity model. Significant reduction in computational cost was achieved using MM: a maximum computational cost reduction of 65%, while arriving at the same optima as that of direct high fidelity optimization. The similarity between the response of models, the number of mapping points and its position, highly influences the computational efficiency of the proposed method. As a proof of concept, realistic WFLO of a small 7-turbine wind farm is performed using the proposed surrogate based methodology. Two variants of Jensen wake model with different decay coefficients were used as the fine and coarse model. The proposed SWFLO method arrived at the same optima as that of the fine model with very less number of fine model simulations.

High Performance Computing for Modeling Wind Farms and Their Impact

NASA Astrophysics Data System (ADS)

Mavriplis, D.; Naughton, J. W.; Stoellinger, M. K.

2016-12-01

As energy generated by wind penetrates further into our electrical system, modeling of power production, power distribution, and the economic impact of wind-generated electricity is growing in importance. The models used for this work can range in fidelity from simple codes that run on a single computer to those that require high performance computing capabilities. Over the past several years, high fidelity models have been developed and deployed on the NCAR-Wyoming Supercomputing Center's Yellowstone machine. One of the primary modeling efforts focuses on developing the capability to compute the behavior of a wind farm in complex terrain under realistic atmospheric conditions. Fully modeling this system requires the simulation of continental flows to modeling the flow over a wind turbine blade, including down to the blade boundary level, fully 10 orders of magnitude in scale. To accomplish this, the simulations are broken up by scale, with information from the larger scales being passed to the lower scale models. In the code being developed, four scale levels are included: the continental weather scale, the local atmospheric flow in complex terrain, the wind plant scale, and the turbine scale. The current state of the models in the latter three scales will be discussed. These simulations are based on a high-order accurate dynamic overset and adaptive mesh approach, which runs at large scale on the NWSC Yellowstone machine. A second effort on modeling the economic impact of new wind development as well as improvement in wind plant performance and enhancements to the transmission infrastructure will also be discussed.

Groundwater economics: An object-oriented foundation for integrated studies of irrigated agricultural systems

USDA-ARS?s Scientific Manuscript database

An integrated foundation is presented to study the impacts of external forcings on irrigated agricultural systems. Individually, models are presented that simulate groundwater hydrogeology and econometric farm level crop choices and irrigated water use. The natural association between groundwater we...

Field Scale Monitoring and Modeling of Water and Chemical Transfer in the Vadose Zone

USDA-ARS?s Scientific Manuscript database

Natural resource systems involve highly complex interactions of soil-plant-atmosphere-management components that are extremely difficult to quantitatively describe. Computer simulations for prediction and management of watersheds, water supply areas, and agricultural fields and farms have become inc...

Economic and financial viability of small-scale dairy systems in central Mexico: economic scenario 2010-2018.

PubMed

Posadas-Domínguez, R R; Callejas-Juárez, N; Arriaga-Jordán, C M; Martínez-Castañeda, F E

2016-12-01

A simulation Monte Carlo model was used to assess the economic and financial viability of 130 small-scale dairy farms in central Mexico, through a Representative Small-Scale Dairy Farm. Net yields were calculated for a 9-year planning horizon by means of simulated values for the distribution of input and product prices taking 2010 as base year and considering four scenarios which were compared against the scenario of actual production. The other scenarios were (1) total hiring in of needed labour; (2) external purchase of 100 % of inputs and (3) withdrawal of subsidies to production. A stochastic modelling approach was followed to determine the scenario with the highest economic and financial viability. Results show a viable economic and financial situation for the real production scenario, as well as the scenarios for total hiring of labour and of withdrawal of subsidies, but the scenario when 100 % of feed inputs for the herd are bought-in was not viable.

Simulating nitrogen budgets in complex farming systems using INCA: calibration and scenario analyses for the Kervidy catchment (W. France)

NASA Astrophysics Data System (ADS)

Durand, P.

The integrated nitrogen model INCA (Integrated Nitrogen in Catchments) was used to analyse the nitrogen dynamics in a small rural catchment in Western France. The agrosystem studied is very complex, with: extensive use of different organic fertilisers, a variety of crop rotations, a structural excess of nitrogen (i.e. more animal N produced by the intensive farming than the N requirements of the crops and pastures), and nitrate retention in both hydrological stores and riparian zones. The original model features were adapted here to describe this complexity. The calibration results are satisfactory, although the daily variations in stream nitrate are not simulated in detail. Different climate scenarios, based on observed climate records, were tested; all produced a worsening of the pollution in the short term. Scenarios of alternative agricultural practices (reduced fertilisation and catch crops) were also analysed, suggesting that a reduction by 40% of the fertilisation combined with the introduction of catch crops would be necessary to stop the degradation of water quality.

Modelling the far field hydro-environmental impacts of tidal farms - A focus on tidal regime, inter-tidal zones and flushing

NASA Astrophysics Data System (ADS)

Nash, S.; O'Brien, N.; Olbert, A.; Hartnett, M.

2014-10-01

The introduction of tidal stream turbines into water bodies can have an impact on the environment due to changes in the hydrodynamic flow fields resulting from the extraction of energy by the tidal turbines. Water levels, tidal currents and flushing characteristics could potentially be significantly altered with the introduction of tidal turbine farms, which could lead to possible loss of habitat and a change in the tidal regime. Therefore, planning of tidal turbines field deployments must take into account possible hydro-environmental impacts. This paper describes research undertaken by the authors in the Shannon Estuary to predict changes in the tidal regime and flushing characteristics, with the introduction of tidal turbine farms of different array configurations. The model was simulated using a 2D hydrodynamic model that was modified to incorporate the effects of tidal turbine fields. Water levels are shown to have been affected with the inclusion of turbines, especially in areas upstream of the turbine farm where inter-tidal zones could become predominately inundated resulting in loss of habitat in the estuary. Flushing parameters were also shown to be altered with the inclusion of turbines, with residence time shown to be increased, which could change pollutant transport in the region.

Egg production forecasting: Determining efficient modeling approaches.

PubMed

Ahmad, H A

2011-12-01

Several mathematical or statistical and artificial intelligence models were developed to compare egg production forecasts in commercial layers. Initial data for these models were collected from a comparative layer trial on commercial strains conducted at the Poultry Research Farms, Auburn University. Simulated data were produced to represent new scenarios by using means and SD of egg production of the 22 commercial strains. From the simulated data, random examples were generated for neural network training and testing for the weekly egg production prediction from wk 22 to 36. Three neural network architectures-back-propagation-3, Ward-5, and the general regression neural network-were compared for their efficiency to forecast egg production, along with other traditional models. The general regression neural network gave the best-fitting line, which almost overlapped with the commercial egg production data, with an R(2) of 0.71. The general regression neural network-predicted curve was compared with original egg production data, the average curves of white-shelled and brown-shelled strains, linear regression predictions, and the Gompertz nonlinear model. The general regression neural network was superior in all these comparisons and may be the model of choice if the initial overprediction is managed efficiently. In general, neural network models are efficient, are easy to use, require fewer data, and are practical under farm management conditions to forecast egg production.

ARRAY OPTIMIZATION FOR TIDAL ENERGY EXTRACTION IN A TIDAL CHANNEL – A NUMERICAL MODELING ANALYSIS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Zhaoqing; Wang, Taiping; Copping, Andrea

This paper presents an application of a hydrodynamic model to simulate tidal energy extraction in a tidal dominated estuary in the Pacific Northwest coast. A series of numerical experiments were carried out to simulate tidal energy extraction with different turbine array configurations, including location, spacing and array size. Preliminary model results suggest that array optimization for tidal energy extraction in a real-world site is a very complex process that requires consideration of multiple factors. Numerical models can be used effectively to assist turbine siting and array arrangement in a tidal turbine farm for tidal energy extraction.

[Epidemiological and financial considerations for the control of Neospora caninum on Swiss dairy farms].

PubMed

Häsler, B; Stärk, K; Gottstein, B; Reist, M

2008-06-01

Neospora caninum is widely recognized as one of the most important abortifacients in cattle and causes substantial financial losses to bovine livestock production. This study aimed to calculate the losses caused by N. caninum on Swiss dairy farms and to evaluate the efficacy and profitability of the control strategies culling, not breeding replacements and chemotherapy of calves on farm level. Three different farm sizes with high, medium and low herd prevalences were defined. Epidemiological and financial models were used to simulate the effect of control strategies on the prevalence over time and to perform a cost-benefit analysis. The median annual losses on farm level ranged between CHF 3094.- (= Euro 1875; 60 dairy cattle, high prevalence) and CHF 134.- (= Euro 81; 15 dairy cattle, low prevalence). Culling of animals that had any abortion or a N. caninum abortion, or not breeding replacements from such animals, respectively, were neither effective nor profitable. Only the strategy "not breeding replacements from N. caninum seropositive cows" on farms with a high prevalence was financially attractive. The strategy "chemotherapy of calves" should be re-evaluated as soon as new data regarding the efficacy of treatment and a corresponding protocol have been scientifically validated.

Economic evaluation of the Programs Rede Farmácia de Minas do SUS versus Farmácia Popular do Brasil.

PubMed

Garcia, Marina Morgado; Guerra, Augusto Afonso; Acúrcio, Francisco de Assis

2017-01-01

We conducted an economic assessment of the Pharmaceutical Assistance - Rede Farmácia de Minas Gerais-RFMG and Farmácia Popular do Brasil-FPB to ascertain which of the two models stands out as the most efficient. To do this, a model, which consisted of a study of incurred costs in both programs, up to the dispensing of medicine to citizens, was developed. The uncertainties of the proposed model were tested using the Monte Carlo method. If the entire population initially estimated in the RFMG were attended in the FPB, there would be an additional cost of R$ 139,324,050.19. The sensitivity analysis appeared to be favorable to the RFMG. A total of 10000 simulations were carried out, resulting in a median value of R$ 114,053,709.99 for the RFMG and R$ 254,106,120.65 for the FPB. The current National Drug Policy emphasizes the need to strengthen pharmaceutical services beyond the mere acquisition and delivery of pharmaceutical products. The public healthcare service model, consistent with the principles and guidelines of the SUS, seems to be more appropriate in ensuring complete and universal quality healthcare services to the citizens. The economic study conducted reinforces this fact, as it appears to be a more efficient alternative of the direct use of resources in the public health network.

Simulation of Nitrogen and Phosphorus Load Runoff by a GIS-based Distributed Model for Chikugo River Watershed

NASA Astrophysics Data System (ADS)

Iseri, Haruka; Hiramatsu, Kazuaki; Harada, Masayoshi

A distributed model was developed in order to simulate the process of nitrogen and phosphorus load runoff in the semi-urban watershed of the Chikugo River, Japan. A grid of cells 1km in size was laid over the study area, and several input variables for each cell area including DEM, land use and statistical data were extracted by GIS. In the process of water runoff, hydrograph calculated at Chikugo Barrage was in close agreement with the observed one, which achieved Nash-Sutcliffe coefficient of 0.90. In addition, the model simulated reasonably well the movement of TN and TP at each station. The model was also used to analyze three scenarios based on the watershed management: (1) reduction of nutrient loads from livestock farm, (2) improvement of septic tanks' wastewater treatment system and (3) application of purification function of paddy fields. As a result, effectiveness of management strategy in each scenario depended on land use patterns. The reduction rates of nutrient load effluent in scenarios (1) and (3) were higher than that in scenario (2). The present result suggests that an appropriate management of livestock farm together with the effective use of paddy environment would have significant effects on the reduction of nutrient loads. A suitable management strategy should be planned based on the land use pattern in the watershed.

Simulating spatial adaption of groundwater pumping on seawater intrusion in coastal regions

NASA Astrophysics Data System (ADS)

Grundmann, Jens; Ladwig, Robert; Schütze, Niels; Walther, Marc

2016-04-01

Coastal aquifer systems are used intensively to meet the growing demands for water in those regions. They are especially at risk for the intrusion of seawater due to aquifer overpumping, limited groundwater replenishment and unsustainable groundwater management which in turn also impacts the social and economical development of coastal regions. One example is the Al-Batinah coastal plain in northern Oman where irrigated agriculture is practiced by lots of small scaled farms in different distances from the sea, each of them pumping their water from coastal aquifer. Due to continuous overpumping and progressing saltwater intrusion farms near the coast had to close since water for irrigation got too saline. For investigating appropriate management options numerical density dependent groundwater modelling is required which should also portray the adaption of groundwater abstraction schemes on the water quality. For addressing this challenge a moving inner boundary condition is implemented in the numerical density dependent groundwater model which adjusts the locations for groundwater abstraction according to the position of the seawater intrusion front controlled by thresholds of relative chloride concentration. The adaption process is repeated for each management cycle within transient model simulations and allows for considering feedbacks with the consumers e.g. the agriculture by moving agricultural farms more inland or towards the sea if more fertile soils at the coast could be recovered. For finding optimal water management strategies efficiently, the behaviour of the numerical groundwater model for different extraction and replenishment scenarios is approximated by an artificial neural network using a novel approach for state space surrogate model development. Afterwards the derived surrogate is coupled with an agriculture module within a simulation based water management optimisation framework to achieve optimal cropping pattern and water abstraction schemes regarding multiple objectives like aquifer sustainability and profitable agriculture. Results obtained for the above mentioned region show that the surrogate model has a very good interpolation capability i.e. it is able to reproduce unknown states obtained by numerical model simulations within the range of its training data. Furthermore, the importance of portraying the adaptive behaviour of farmers on water quality is underlined to develop management scenarios more realistically. However, results of a stop pumping scenario show that it is not possible to push back an advanced seawater intrusion in a time period of 200 years. Therefore, combinations of technical and adaptive measures are required.

Simulated Impact of Climate Change on Fremont Native American Maize Farming in Utah at the MCA-LIA Transition, ca. 12-14th c. CE

NASA Astrophysics Data System (ADS)

Thomson, M. J.; MacDonald, G. M.

2016-12-01

We present the results of a computational crop modeling experiment for ancient Fremont Native American Zea mays farming in the Uinta Basin, Utah, at the Medieval Climate Anomaly to Little Ice Age (MCA-LIA) transition, ca. 850-1450 CE. This period coincides with the rapid disappearance of complex Native American cultures from the American Southwest. The crop model (the Environment Policy Impact Calculator, EPIC) was driven by statistically downscaled precipitation, temperature and shortwave radiative flux from the Community Earth System Model Last Millennium Ensemble (CESM LME). We found that maize yield responded to changes in the model-reconstructed temperature and precipitation; and periods of reduced maize yields corresponded to the abandonment of higher elevation Fremont 14C-dated archaeological sites. EPIC produces good agreement between modeled and historically reported maize yields for the 19th century.

A stochastic dynamic model of a dairy farm to evaluate the technical and economic performance under different scenarios.

PubMed

Calsamiglia, S; Astiz, S; Baucells, J; Castillejos, L

2018-05-23

Dairy farms need to improve their competitiveness through decisions that are often difficult to evaluate because they are highly dependent on many economic and technical factors. The objective of this project was to develop a stochastic and dynamic mathematical model to simulate the functioning of a dairy farm to evaluate the effect of changes in technical or economic factors on performance and profitability. Submodels were developed for reproduction, feeding, diseases, heifers, environmental factors, facilities, management, and economics. All these submodels were simulated on an animal-by-animal and day-by-day basis. Default values for all variables are provided, but the user can change them. The outcome provides a list of technical and economic indicators essential for the decision-making process. Performance of the program was verified by evaluating the effects and sensitivity analysis of different scenarios in 20 different dairy farms. As an example, a case study of a dairy farm with 300 cows producing 40 L/d and a 12% pregnancy rate (PR) was used. The effect of using a time-fixed artificial insemination (TFAI) protocol in the first insemination at 77 d in milk, with 45 and 40% conception rates for first-lactation and older cows, respectively, and a cost of €13 was explored. During the 5-yr simulation, the TFAI increased PR (12 to 17%) and milk yield per milking cow (39.8 to 41.2 L/d) and reduced days to first AI (93 to 74), days open (143 to 116), and the proportion of problem cows (24.3 to 15.9%). In the TFAI, cows were dried 30 d earlier, resulting in more dry cows, and a smaller difference in milk yield by present cows (35.5 vs 36.0 L/d for control and TFAI, respectively). A longer productive life (2.56 vs. 2.79 yr) with shorter lactations in TFIA resulted in less first-lactation cows (42 vs 36%), 32 more calvings per year, and, therefore, more cases of postpartum diseases. Total (32.5 to 29.9%) and reproductive (10.5 vs 6.8%) culling rates decreased in TFIA. Overall, the net margin was €245 and €309/cow per year in control and TFIA, respectively. The net margin of applying TFAI decreased as PR of the farm increased, with limited benefit of TFAI at a PR of 30%. The model provides a powerful web-based tool to explore the short- and medium-term consequences of technical and economic decisions on the economic sustainability of dairy farms. © 2018, The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Simulation-optimization aids in resolving water conflict: Temecula Basin, Southern California

USGS Publications Warehouse

Hanson, Randall T.; Faunt, Claudia C.; Schmid, Wolfgang; Lear, Jonathan

2014-01-01

The productive agricultural areas of Pajaro Valley, California have exclusively relied on ground water from coastal aquifers in central Monterey Bay. As part of the Basin Management Plan (BMP), the Pajaro Valley Water Management Agency (PVWMA) is developing additional local supplies to replace coastal pumpage, which is causing seawater intrusion. The BMP includes an aquifer storage and recovery (ASR) system, which captures and stores local winter runoff, and supplies it to growers later in the growing season in lieu of ground-water pumpage. A Coastal Distribution System (CDS) distributes water from the ASR and other supplemental sources. A detailed model of the Pajaro Valley is being used to simulate the coupled supply and demand components of irrigated agriculture from 1963 to 2006. Recent upgrades to the Farm Process in MODFLOW (MF2K-FMP) allow simulating the effects of ASR deliveries and reduced pumping for farms in subregions connected to the CDS. The BMP includes a hierarchy of monthly supply alternatives, including a recovery well field around the ASR system, a supplemental wellfield, and onsite farm supply wells. The hierarchy of delivery requirements is used by MF2K-FMP to estimate the effects of these deliveries on coastal ground-water pumpage and recovery of water levels. This integrated approach can be used to assess the effectiveness of the BMP under variable climatic conditions, and to test the impacts of more complete subscription by coastal farmers to the CDS deliveries. The model will help managers assess the effects of new BMP components to further reduce pumpage and seawater intrusion.

Effects of stored feed cropping systems and farm size on the profitability of Maine organic dairy farm simulations.

PubMed

Hoshide, A K; Halloran, J M; Kersbergen, R J; Griffin, T S; DeFauw, S L; LaGasse, B J; Jain, S

2011-11-01

United States organic dairy production has increased to meet the growing demand for organic milk. Despite higher prices received for milk, organic dairy farmers have come under increasing financial stress due to increases in concentrated feed prices over the past few years, which can make up one-third of variable costs. Market demand for milk has also leveled in the last year, resulting in some downward pressure on prices paid to dairy farmers. Organic dairy farmers in the Northeast United States have experimented with growing different forage and grain crops to maximize on-farm production of protein and energy to improve profitability. Three representative organic feed systems were simulated using the integrated farm system model for farms with 30, 120, and 220 milk cows. Increasing intensity of equipment use was represented by organic dairy farms growing only perennial sod (low) to those with corn-based forage systems, which purchase supplemental grain (medium) or which produce and feed soybeans (high). The relative profitability of these 3 organic feed systems was strongly dependent on dairy farm size. From results, we suggest smaller organic dairy farms can be more profitable with perennial sod-based rather than corn-based forage systems due to lower fixed costs from using only equipment associated with perennial forage harvest and storage. The largest farm size was more profitable using a corn-based system due to greater economies of scale for growing soybeans, corn grain, winter cereals, and corn silages. At an intermediate farm size of 120 cows, corn-based forage systems were more profitable if perennial sod was not harvested at optimum quality, corn was grown on better soils, or if milk yield was 10% higher. Delayed harvest decreased the protein and energy content of perennial sod crops, requiring more purchased grain to balance the ration and resulting in lower profits. Corn-based systems were less affected by lower perennial forage quality, as corn silage is part of the forage base. Growing on better soils increased corn yields more than perennial forage yields. Large corn-based organic dairy farms that produced and fed soybeans minimized off-farm grain purchases and were the most profitable among large farms. Although perennial sod-based systems purchased more grain, these organic systems were more profitable under timely forage harvest, decreased soil quality, and relatively lower purchased energy prices and higher protein supplement prices. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

NetFlow Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corbet Jr., Thomas F; Beyeler, Walter E; Vanwestrienen, Dirk

NetFlow Dynamics is a web-accessible analysis environment for simulating dynamic flows of materials on model networks. Performing a simulation requires both the NetFlow Dynamics application and a network model which is a description of the structure of the nodes and edges of a network including the flow capacity of each edge and the storage capacity of each node, and the sources and sinks of the material flowing on the network. NetFlow Dynamics consists of databases for storing network models, algorithms to calculate flows on networks, and a GIS-based graphical interface for performing simulations and viewing simulation results. Simulated flows aremore » dynamic in the sense that flows on each edge of the network and inventories at each node change with time and can be out of equilibrium with boundary conditions. Any number of network models could be simulated using Net Flow Dynamics. To date, the models simulated have been models of petroleum infrastructure. The main model has been the National Transportation Fuels Model (NTFM), a network of U.S. oil fields, transmission pipelines, rail lines, refineries, tank farms, and distribution terminals. NetFlow Dynamics supports two different flow algorithms, the Gradient Flow algorithm and the Inventory Control algorithm, that were developed specifically for the NetFlow Dynamics application. The intent is to add additional algorithms in the future as needed. The ability to select from multiple algorithms is desirable because a single algorithm never covers all analysis needs. The current algorithms use a demand-driven capacity-constrained formulation which means that the algorithms strive to use all available capacity and stored inventory to meet desired flows to sinks, subject to the capacity constraints of each network component. The current flow algorithms are best suited for problems in which a material flows on a capacity-constrained network representing a supply chain in which the material supplied can be stored at each node of the network. In the petroleum models, the flowing materials are crude oil and refined products that can be stored at tank farms, refineries, or terminals (i.e. the nodes of the network). Examples of other network models that could be simulated are currency flowing in a financial network, agricultural products moving to market, or natural gas flowing on a pipeline network.« less

Offshore Wind Energy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strach-Sonsalla, Mareike; Stammler, Matthias; Wenske, Jan

In 1991, the Vindeby Offshore Wind Farm, the first offshore wind farm in the world, started feeding electricity to the grid off the coast of Lolland, Denmark. Since then, offshore wind energy has developed from this early experiment to a multibillion dollar market and an important pillar of worldwide renewable energy production. Unit sizes grew from 450 kW at Vindeby to the 7.5 MW-class offshore wind turbines (OWT ) that are currently (by October 2014) in the prototyping phase. This chapter gives an overview of the state of the art in offshore wind turbine (OWT) technology and introduces the principlesmore » of modeling and simulating an OWT. The OWT components -- including the rotor, nacelle, support structure, control system, and power electronics -- are introduced, and current technological challenges are presented. The OWT system dynamics and the environment (wind and ocean waves) are described from the perspective of OWT modelers and designers. Finally, an outlook on future technology is provided. The descriptions in this chapter are focused on a single OWT -- more precisely, a horizontal-axis wind turbine -- as a dynamic system. Offshore wind farms and wind farm effects are not described in detail in this chapter, but an introduction and further references are given.« less

Wind farms production: Control and prediction

NASA Astrophysics Data System (ADS)

El-Fouly, Tarek Hussein Mostafa

Wind energy resources, unlike dispatchable central station generation, produce power dependable on external irregular source and that is the incident wind speed which does not always blow when electricity is needed. This results in the variability, unpredictability, and uncertainty of wind resources. Therefore, the integration of wind facilities to utility electrical grid presents a major challenge to power system operator. Such integration has significant impact on the optimum power flow, transmission congestion, power quality issues, system stability, load dispatch, and economic analysis. Due to the irregular nature of wind power production, accurate prediction represents the major challenge to power system operators. Therefore, in this thesis two novel models are proposed for wind speed and wind power prediction. One proposed model is dedicated to short-term prediction (one-hour ahead) and the other involves medium term prediction (one-day ahead). The accuracy of the proposed models is revealed by comparing their results with the corresponding values of a reference prediction model referred to as the persistent model. Utility grid operation is not only impacted by the uncertainty of the future production of wind farms, but also by the variability of their current production and how the active and reactive power exchange with the grid is controlled. To address this particular task, a control technique for wind turbines, driven by doubly-fed induction generators (DFIGs), is developed to regulate the terminal voltage by equally sharing the generated/absorbed reactive power between the rotor-side and the gridside converters. To highlight the impact of the new developed technique in reducing the power loss in the generator set, an economic analysis is carried out. Moreover, a new aggregated model for wind farms is proposed that accounts for the irregularity of the incident wind distribution throughout the farm layout. Specifically, this model includes the wake effect and the time delay of the incident wind speed of the different turbines on the farm, and to simulate the fluctuation in the generated power more accurately and more closer to real-time operation. Recently, wind farms with considerable output power ratings have been installed. Their integrating into the utility grid will substantially affect the electricity markets. This thesis investigates the possible impact of wind power variability, wind farm control strategy, wind energy penetration level, wind farm location, and wind power prediction accuracy on the total generation costs and close to real time electricity market prices. These issues are addressed by developing a single auction market model for determining the real-time electricity market prices.

Numerical analysis of the wake of a 10kW HAWT

NASA Astrophysics Data System (ADS)

Gong, S. G.; Deng, Y. B.; Xie, G. L.; Zhang, J. P.

2017-01-01

With the rising of wind power industry and the ever-growing scale of wind farm, the research for the wake performance of wind turbine has an important guiding significance for the overall arrangement of wind turbines in the large wind farm. The wake simulation model of 10kW horizontal-axis wind turbine is presented on the basis of Averaged Navier-Stokes (RANS) equations and the RNG k-ε turbulence model for applying to the rotational fluid flow. The sliding mesh technique in ANSYS CFX software is used to solve the coupling equation of velocity and pressure. The characters of the average velocity in the wake zone under rated inlet wind speed and different rotor rotational speeds have been investigated. Based on the analysis results, it is proposed that the horizontal spacing between the wind turbines is less than two times radius of rotor, and its longitudinal spacing is less than five times of radius. And other results have also been obtained, which are of great importance for large wind farms.

Investigation of the disposal of dead pigs by pig farmers in mainland China by simulation experiment.

PubMed

Wu, Linhai; Xu, Guoyan; Li, Qingguang; Hou, Bo; Hu, Wuyang; Wang, Jianhua

2017-01-01

Dead pigs are a major waste by-product of pig farming. Thus, safe disposal of dead pigs is important to the protection of consumer health and the ecological environment by preventing marketing of slaughtered and processed dead pigs and improper dumping of dead pigs. In this study, a probability model was constructed for the disposal of dead pigs by pig farmers by selecting factors affecting disposal. To that end, we drew on the definition and meaning of behavior probability based on survey data collected from 654 pig farmers in Funing County, Jiangsu Province, China. Moreover, the role of influencing factors in pig farmers' behavioral choices regarding the disposal of dead pigs was simulated by simulation experiment. The results indicated that years of farming had a positive impact on pig farmers' choice of negative disposal of dead pigs. Moreover, there was not a simple linear relationship between scale of farming and pig farmers' behavioral choices related to the disposal of dead pigs. The probability for farmers to choose the safe disposal of dead pigs increased with the improvement of their knowledge of government policies and relevant laws and regulations. Pig farmers' behavioral choice about the disposal of dead pigs was also affected by government subsidy policies, regulation, and punishment. Government regulation and punishment were more effective than subsidy. The findings of our simulation experiment provide important decision-making support for the governance in preventing the marketing of dead pigs at the source.

Wind Farm Flow Modeling using an Input-Output Reduced-Order Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Annoni, Jennifer; Gebraad, Pieter; Seiler, Peter

Wind turbines in a wind farm operate individually to maximize their own power regardless of the impact of aerodynamic interactions on neighboring turbines. There is the potential to increase power and reduce overall structural loads by properly coordinating turbines. To perform control design and analysis, a model needs to be of low computational cost, but retains the necessary dynamics seen in high-fidelity models. The objective of this work is to obtain a reduced-order model that represents the full-order flow computed using a high-fidelity model. A variety of methods, including proper orthogonal decomposition and dynamic mode decomposition, can be used tomore » extract the dominant flow structures and obtain a reduced-order model. In this paper, we combine proper orthogonal decomposition with a system identification technique to produce an input-output reduced-order model. This technique is used to construct a reduced-order model of the flow within a two-turbine array computed using a large-eddy simulation.« less

Incorporating a prediction of postgrazing herbage mass into a whole-farm model for pasture-based dairy systems.

PubMed

Gregorini, P; Galli, J; Romera, A J; Levy, G; Macdonald, K A; Fernandez, H H; Beukes, P C

2014-07-01

The DairyNZ whole-farm model (WFM; DairyNZ, Hamilton, New Zealand) consists of a framework that links component models for animal, pastures, crops, and soils. The model was developed to assist with analysis and design of pasture-based farm systems. New (this work) and revised (e.g., cow, pasture, crops) component models can be added to the WFM, keeping the model flexible and up to date. Nevertheless, the WFM does not account for plant-animal relationships determining herbage-depletion dynamics. The user has to preset the maximum allowable level of herbage depletion [i.e., postgrazing herbage mass (residuals)] throughout the year. Because residuals have a direct effect on herbage regrowth, the WFM in its current form does not dynamically simulate the effect of grazing pressure on herbage depletion and consequent effect on herbage regrowth. The management of grazing pressure is a key component of pasture-based dairy systems. Thus, the main objective of the present work was to develop a new version of the WFM able to predict residuals, and thereby simulate related effects of grazing pressure dynamically at the farm scale. This objective was accomplished by incorporating a new component model into the WFM. This model represents plant-animal relationships, for example sward structure and herbage intake rate, and resulting level of herbage depletion. The sensitivity of the new version of the WFM was evaluated and then the new WFM was tested against an experimental data set previously used to evaluate the WFM and to illustrate the adequacy and improvement of the model development. Key outputs variables of the new version pertinent to this work (milk production, herbage dry matter intake, intake rate, harvesting efficiency, and residuals) responded acceptably to a range of input variables. The relative prediction errors for monthly and mean annual residual predictions were 20 and 5%, respectively. Monthly predictions of residuals had a line bias (1.5%), with a proportion of square root of mean square prediction error (RMSPE) due to random error of 97.5%. Predicted monthly herbage growth rates had a line bias of 2%, a proportion of RMSPE due to random error of 96%, and a concordance correlation coefficient of 0.87. Annual herbage production was predicted with an RMSPE of 531 (kg of herbage dry matter/ha per year), a line bias of 11%, a proportion of RMSPE due to random error of 80%, and relative prediction errors of 2%. Annual herbage dry matter intake per cow and hectare, both per year, were predicted with RMSPE, relative prediction error, and concordance correlation coefficient of 169 and 692kg of dry matter, 3 and 4%, and 0.91 and 0.87, respectively. These results indicate that predictions of the new WFM are relatively accurate and precise, with a conclusion that incorporating a plant-animal relationship model into the WFM allows for dynamic predictions of residuals and more realistic simulations of the effect of grazing pressure on herbage production and intake at the farm level without the intervention from the user. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Groundwater response to changing water-use practices in sloping aquifers using convolution of transient response functions

USDA-ARS?s Scientific Manuscript database

An integrated foundation is presented to study the impacts of external forcings on irrigated agricultural systems. Individually, models are presented that simulate groundwater hydrogeology and econometric farm level crop choices and irrigated water use. The natural association between groundwater we...

A multi-analysis approach for space-time and economic evaluation of risks related with livestock diseases: the example of FMD in Peru.

PubMed

Martínez-López, B; Ivorra, B; Fernández-Carrión, E; Perez, A M; Medel-Herrero, A; Sánchez-Vizcaíno, F; Gortázar, C; Ramos, A M; Sánchez-Vizcaíno, J M

2014-04-01

This study presents a multi-disciplinary decision-support tool, which integrates geo-statistics, social network analysis (SNA), spatial-stochastic spread model, economic analysis and mapping/visualization capabilities for the evaluation of the sanitary and socio-economic impact of livestock diseases under diverse epidemiologic scenarios. We illustrate the applicability of this tool using foot-and-mouth disease (FMD) in Peru as an example. The approach consisted on a flexible, multistep process that may be easily adapted based on data availability. The first module (mI) uses a geo-statistical approach for the estimation (if needed) of the distribution and abundance of susceptible population (in the example here, cattle, swine, sheep, goats, and camelids) at farm-level in the region or country of interest (Peru). The second module (mII) applies SNA for evaluating the farm-to-farm contact patterns and for exploring the structure and frequency of between-farm animal movements as a proxy for potential disease introduction or spread. The third module (mIII) integrates mI-II outputs into a spatial-stochastic model that simulates within- and between-farm FMD-transmission. The economic module (mIV) connects outputs from mI-III to provide an estimate of associated direct and indirect costs. A visualization module (mV) is also implemented to graph and map the outputs of module I-IV. After 1000 simulated epidemics, the mean (95% probability interval) number of outbreaks, infected animals, epidemic duration, and direct costs were 37 (1, 1164), 2152 (1, 13, 250), 63 days (0, 442), and US$ 1.2 million (1072, 9.5 million), respectively. Spread of disease was primarily local (<4.5km), but geolocation and type of index farm strongly influenced the extent and spatial patterns of an epidemic. The approach is intended to support decisions in the last phase of the FMD eradication program in Peru, in particular to inform and support the implementation of risk-based surveillance and livestock insurance systems that may help to prevent and control potential FMD virus incursions into Peru. Copyright © 2014 Elsevier B.V. All rights reserved.

Could Crop Roughness Impact the Wind Resource at Agriculturally Productive Wind Farm Sites?

NASA Astrophysics Data System (ADS)

Vanderwende, B. J.; Lundquist, J. K.

2014-12-01

The high concentration of both large-scale agriculture and wind power production in the United States Midwest region raises new questions concerning the interaction of the two activities. For instance, it is known from internal boundary layer theory that changes in the roughness of the land-surface resulting from crop choices could modify the momentum field aloft. Upward propagation of such an effect might impact the properties of the winds encountered by modern turbines, which typically span a layer from about 40 to 120 meters above the surface. As direct observation of such interaction would require impractical interference in the planting schedules of farmers, we use numerical modeling to quantify the magnitude of crop-roughness effects. To simulate a collocated farm and turbine array, we use version 3.4.1 of the Weather Research and Forecasting model (WRF). The hypothetical farm is inserted near the real location of the 2013 Crop Wind Energy Experiment (CWEX). Reanalyses provide representative initial and boundary conditions. A month-long period spanning August 2013 is used to evaluate the differences in flows above corn (maize) and soybean crops at the mature, reproductive stage. Simulations are performed comparing the flow above each surface regime, both in the absence and presence of a wind farm, which consists of a parameterized 11x11 array of 1.8 MW Vestas V90 turbines. Appreciable differences in rotor-layer wind speeds emerge. The use of soybeans results in an increase in wind speeds and a corresponding reduction in rotor-layer shear when compared to corn. Despite the turbulent nature of flow within a wind farm, high stability reduces the impact of crop roughness on the flow aloft, particularly in the upper portion of the rotor disk. We use these results to estimate the economic impact of crop selection on wind power producers.

Modeling, analysis, control and design application guidelines of Doubly Fed Induction Generator (DFIG) for wind power applications

NASA Astrophysics Data System (ADS)

Masaud, Tarek

Double Fed Induction Generators (DFIG) has been widely used for the past two decades in large wind farms. However, there are many open-ended problems yet to be solved before they can be implemented in some specific applications. This dissertation deals with the general analysis, modeling, control and applications of the DFIG for large wind farm applications. A detailed "d-q" model of DFIG along with other applications is simulated using the MATLAB/Simulink platform. The simulation results have been discussed in detail in both sub-synchronous and super-synchronous mode of operation. An improved vector control strategy based on the rotor flux oriented vector control has been proposed to control the active power output of the DFIG. The new vector control strategy is compared with the stator flux oriented vector control which is commonly used. It is observed that the new improved vector control method provides a better active power tracking accuracy compare with the stator flux oriented vector control. The behavior of the DFIG -based wind farm under the various grid disturbances is also studied in this dissertation. The implementation of the Flexible AC Transmission System devices (FACTS) to overcome the voltage stability issue for such applications is investigated. The study includes the implementation of both a static synchronous compensator (STATCOM), and the static VAR compensator (SVC) as dynamic reactive power compensators at the point of common coupling to support DFIG-based wind farm during disturbances. Integrating FACTS protect the grid connected DFIG-based wind farm from going offline during and after the disturbances. It is found that the both devices improve the transient performance and therefore helps the wind turbine generator system to remain in service during grid faults. A comparison between the performance of the two devices in terms of the amount of reactive power injected, time response and the application cost has been discussed in this dissertation. Finally, the integration of the battery energy storage system (BESS) into a grid connected DFIG- based wind turbine as a proposed solution to smooth out the output power during wind speed variations is also addressed.

Representative Agricultural Pathways and Climate Impact Assessment for Pacific Northwest Agricultural Systems

NASA Astrophysics Data System (ADS)

MU, J.; Antle, J. M.; Zhang, H.; Capalbo, S. M.; Eigenbrode, S.; Kruger, C.; Stockle, C.; Wolfhorst, J. D.

2013-12-01

Representative Agricultural Pathways (RAPs) are projections of plausible future biophysical and socio-economic conditions used to carry out climate impact assessments for agriculture. The development of RAPs iss motivated by the fact that the various global and regional models used for agricultural climate change impact assessment have been implemented with individualized scenarios using various data and model structures, often without transparent documentation or public availability. These practices have hampered attempts at model inter-comparison, improvement, and synthesis of model results across studies. This paper aims to (1) present RAPs developed for the principal wheat-producing region of the Pacific Northwest, and to (2) combine these RAPs with downscaled climate data, crop model simulations and economic model simulations to assess climate change impacts on winter wheat production and farm income. This research was carried out as part of a project funded by the USDA known as the Regional Approaches to Climate Change in the Pacific Northwest (REACCH). The REACCH study region encompasses the major winter wheat production area in Pacific Northwest and preliminary research shows that farmers producing winter wheat could benefit from future climate change. However, the future world is uncertain in many dimensions, including commodity and input prices, production technology, and policies, as well as increased probability of disturbances (pests and diseases) associated with a changing climate. Many of these factors cannot be modeled, so they are represented in the regional RAPS. The regional RAPS are linked to global agricultural and shared social-economic pathways, and used along with climate change projections to simulate future outcomes for the wheat-based farms in the REACCH region.

Assessment of soil water, carbon and nitrogen cycling in reseeded grassland on the North Wyke Farm Platform using a process-based model.

PubMed

Li, Yuefen; Liu, Yi; Harris, Paul; Sint, Hadewij; Murray, Phil J; Lee, Michael R F; Wu, Lianhai

2017-12-15

The North Wyke Farm Platform (NWFP) generates large volumes of temporally-indexed data that provides a valuable test-bed for agricultural mathematical models in temperate grasslands. In our study, we used the primary datasets generated from the NWFP (https://nwfp.rothamsted.ac.uk/) to validate the SPACSYS model in terms of the dynamics of water loss and forage dry matter yield estimated through cutting. The SPACSYS model is capable of simulating soil water, carbon (C) and nitrogen (N) balance in the soil-plant-atmosphere system. The validated model was then used to simulate the responses of soil water, C and N to reseeding grass cultivars with either high sugar (Lolium perenne L. cv. AberMagic) or deep rooting (Festulolium cv. Prior) traits. Simulation results demonstrated that the SPACSYS model could predict reliably soil water, C and N cycling in reseeded grassland. Compared to AberMagic, the Prior grass could fix more C in the second year following reseeding, whereas less C was lost through soil respiration in the first transition year. In comparison to the grass cultivar of the permanent pasture that existed before reseeding, both grasses reduced N losses through runoff and contributed to reducing water loss, especially Prior in relation to the latter. The SPACSYS model could predict these differences as supported by the rich dataset from the NWFP, providing a tool for future predictions on less characterized pasture. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Wind-tunnel experiments of scalar transport in aligned and staggered wind farms

NASA Astrophysics Data System (ADS)

Zhang, W.; Markfort, C. D.; Porté-Agel, F.

2012-04-01

Wind energy is the fastest growing renewable energy worldwide, and it is expected that many more large-scale wind farms will be built and will cover a significant portion of land and ocean surfaces. By extracting kinetic energy from the atmospheric boundary layer, wind farms may affect the exchange/transport of momentum, heat and moisture between the atmosphere and land surface. To ensure the long-term sustainability of wind energy, it is important to understand the influence of large-scale wind farms on land-atmosphere interaction. Knowledge of this impact will also be useful to improve parameterizations of wind farms in numerical prediction tools, such as large-scale weather models and large-eddy simulation. Here, we present wind-tunnel measurements of the surface scalar (heat) flux from model wind farms, consisting of more than 10 rows of wind turbines, in a turbulent boundary layer with a surface heat source. Spatially distributed surface heat flux was obtained in idealized aligned and staggered wind farm layouts, having the same turbine distribution density. Measurements, using surface-mounted heat flux sensors, were taken at the 11th out of 12 rows of wind turbines, where the mean flow achieves a quasi-equilibrium state. In the aligned farm, there exist two distinct regions of increased and decreased surface heat flux on either side of turbine columns. The regions are correlated with coherent wake rotation in the turbine-array. On the upwelling side there is decreased flux, while on the downwelling side cool air moves towards the surface causing increased flux. For the staggered farm, the surface heat flux exhibits a relatively uniform distribution and an overall reduction with respect to the boundary layer flow, except in the vicinity of the turbine tower. This observation is also supported by near-surface temperature and turbulent heat flux measured using a customized x-wire/cold-wire. The overall surface heat flux, relative to that of the boundary layer flow without wind turbines, is reduced by approximately 4% in the staggered wind farm and remains nearly the same in the aligned wind farm.

A Quantitative Study of Vertical Replenishment and its Contribution to Momentum Recovery for a Large Offshore Windfarm

NASA Astrophysics Data System (ADS)

Gupta, T.; Baidya Roy, S.; Miller, L.

2017-12-01

With rapid increase in the installed wind capacity around the globe, it is important and interesting to understand the processes involved in wind farm-atmospheric boundary layer interactions. A wind turbine extracts energy from the mean flow and converts it into electrical energy, thereby reducing the mean kinetic energy available. The corresponding reduction in momentum triggers vertical mixing that transports high-momentum air from aloft to the wind turbine layer thereby replenishing the lost momentum, at least partially. This study investigates the phenomenon of vertical replenishment and quantifies its contribution in the momentum recovery as a function of various factors including installed capacity (MW/km2), depth of the wind farm (km) and climatology of the area. Numerical experiments are conducted using the WRF mesoscale model to simulate wind turbine-boundary layer interactions in a hypothetical large off-shore wind farm located deep in the Arabian Sea off the western coast of India. WRF is equipped with a wind turbine parameterization and is capable of simulating both the momentum reduction and vertical replenishment phenomena. It is found that the downward turbulent flux is able to replenish about 66% of momentum lost because of wind turbines. Additionally, the feedback leads to an average increase of 1.5% in generated power capacity in the wind farm. These results indicate that when the momentum deficit occurs, the vertical replenishment in form of turbulent flux tries to dampen the momentum loss, hence, acting as a negative feedback in the wind farm.

Numerical modelling of organic waste dispersion from fjord located fish farms

NASA Astrophysics Data System (ADS)

Ali, Alfatih; Thiem, Øyvind; Berntsen, Jarle

2011-07-01

In this study, a three-dimensional particle tracking model coupled to a terrain following ocean model is used to investigate the dispersion and the deposition of fish farm particulate matter (uneaten food and fish faeces) on the seabed due to tidal currents. The particle tracking model uses the computed local flow field for advection of the particles and random movement to simulate the turbulent diffusion. Each particle is given a settling velocity which may be drawn from a probability distribution according to settling velocity measurements of faecal and feed pellets. The results show that the maximum concentration of organic waste for fast sinking particles is found under the fish cage and continue monotonically decreasing away from the cage area. The maximum can split into two maximum peaks located at both sides of the centre of the fish cage area in the current direction. This process depends on the sinking time (time needed for a particle to settle at the bottom), the tidal velocity and the fish cage size. If the sinking time is close to a multiple of the tidal period, the maximum concentration point will be under the fish cage irrespective of the tide strength. This is due to the nature of the tidal current first propagating the particles away and then bringing them back when the tide reverses. Increasing the cage size increases the likelihood for a maximum waste accumulation beneath the fish farm, and larger farms usually means larger biomasses which can make the local pollution even more severe. The model is validated by using an analytical model which uses an exact harmonic representation of the tidal current, and the results show an excellent agreement. This study shows that the coupled ocean and particle model can be used in more realistic applications to help estimating the local environmental impact due to fish farms.

Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

NASA Astrophysics Data System (ADS)

Lee, Joseph C. Y.; Lundquist, Julie K.

2017-11-01

Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind-turbine wakes. This paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind-downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.

Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

DOE PAGES

Lee, Joseph C. Y.; Lundquist, Julie K.

2017-11-23

Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind-turbine wakes. Our paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustratemore » with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind–downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.« less

Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Joseph C. Y.; Lundquist, Julie K.

Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind-turbine wakes. Our paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustratemore » with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind–downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.« less

Dutch dairy farms after milk quota abolition: Economic and environmental consequences of a new manure policy.

PubMed

Klootwijk, C W; Van Middelaar, C E; Berentsen, P B M; de Boer, I J M

2016-10-01

The abolition of the Dutch milk quota system has been accompanied by the introduction of a new manure policy to limit phosphate production (i.e., excretion via manure) on expanding dairy farms. The objective of this study was to evaluate the effect of these recent policy changes on the farm structure, management, labor income, nitrogen and phosphate surpluses, and greenhouse gas emissions of an average Dutch dairy farm. The new manure policy requires that any increase in phosphate production be partly processed and partly applied to additional farmland. In addition, phosphate quotas have been introduced. Herein, we used a whole-farm optimization model to simulate an average farm before and after quota abolition and introduction of the new manure policy. The objective function of the model maximized labor income. We combined the model with a farm nutrient balance and life-cycle assessment to determine environmental impact. Based on current prices, increasing the number of cows after quota abolition was profitable until manure processing or additional land was required to comply with the new manure policy. Manure processing involved treatment so that phosphate was removed from the national manure market. Farm intensity in terms of milk per hectare increased by about 4%, from 13,578kg before quota abolition to 14,130kg after quota abolition. Labor income increased by €505/yr. When costs of manure processing decreased from €13 to €8/t of manure or land costs decreased from €1,187 to €573/ha, farm intensity could increase up to 20% until the phosphate quota became limiting. Farms that had already increased their barn capacity to prepare for expansion after milk quota abolition could benefit from purchasing extra phosphate quota to use their full barn capacity. If milk prices increased from €355 to €420/t, farms could grow unlimited, provided that the availability of external inputs such as labor, land, barn capacity, feed, and phosphate quota at current prices were also unlimited. The milk quota abolition, accompanied by a new manure policy, will slightly increase nutrient losses per hectare, due to an increase in farm intensity. Greenhouse gas emissions per unit of milk will hardly change, so at a given milk production per cow, total greenhouse gas emissions will increase linearly with an increase in the number of cows. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Real time implementation and control validation of the wind energy conversion system

NASA Astrophysics Data System (ADS)

Sattar, Adnan

The purpose of the thesis is to analyze dynamic and transient characteristics of wind energy conversion systems including the stability issues in real time environment using the Real Time Digital Simulator (RTDS). There are different power system simulation tools available in the market. Real time digital simulator (RTDS) is one of the powerful tools among those. RTDS simulator has a Graphical User Interface called RSCAD which contains detail component model library for both power system and control relevant analysis. The hardware is based upon the digital signal processors mounted in the racks. RTDS simulator has the advantage of interfacing the real world signals from the external devices, hence used to test the protection and control system equipments. Dynamic and transient characteristics of the fixed and variable speed wind turbine generating systems (WTGSs) are analyzed, in this thesis. Static Synchronous Compensator (STATCOM) as a flexible ac transmission system (FACTS) device is used to enhance the fault ride through (FRT) capability of the fixed speed wind farm. Two level voltage source converter based STATCOM is modeled in both VSC small time-step and VSC large time-step of RTDS. The simulation results of the RTDS model system are compared with the off-line EMTP software i.e. PSCAD/EMTDC. A new operational scheme for a MW class grid-connected variable speed wind turbine driven permanent magnet synchronous generator (VSWT-PMSG) is developed. VSWT-PMSG uses fully controlled frequency converters for the grid interfacing and thus have the ability to control the real and reactive powers simultaneously. Frequency converters are modeled in the VSC small time-step of the RTDS and three phase realistic grid is adopted with RSCAD simulation through the use of optical analogue digital converter (OADC) card of the RTDS. Steady state and LVRT characteristics are carried out to validate the proposed operational scheme. Simulation results show good agreement with real time simulation software and thus can be used to validate the controllers for the real time operation. Integration of the Battery Energy Storage System (BESS) with wind farm can smoothen its intermittent power fluctuations. The work also focuses on the real time implementation of the Sodium Sulfur (NaS) type BESS. BESS is integrated with the STATCOM. The main advantage of this system is that it can also provide the reactive power support to the system along with the real power exchange from BESS unit. BESS integrated with STATCOM is modeled in the VSC small time-step of the RTDS. The cascaded vector control scheme is used for the control of the STATCOM and suitable control is developed to control the charging/discharging of the NaS type BESS. Results are compared with Laboratory standard power system software PSCAD/EMTDC and the advantages of using RTDS in dynamic and transient characteristics analyses of wind farm are also demonstrated clearly.

Real-time simulation of a Doubly-Fed Induction Generator based wind power system on eMEGASimRTM Real-Time Digital Simulator

NASA Astrophysics Data System (ADS)

Boakye-Boateng, Nasir Abdulai

The growing demand for wind power integration into the generation mix prompts the need to subject these systems to stringent performance requirements. This study sought to identify the required tools and procedures needed to perform real-time simulation studies of Doubly-Fed Induction Generator (DFIG) based wind generation systems as basis for performing more practical tests of reliability and performance for both grid-connected and islanded wind generation systems. The author focused on developing a platform for wind generation studies and in addition, the author tested the performance of two DFIG models on the platform real-time simulation model; an average SimpowerSystemsRTM DFIG wind turbine, and a detailed DFIG based wind turbine using ARTEMiSRTM components. The platform model implemented here consists of a high voltage transmission system with four integrated wind farm models consisting in total of 65 DFIG based wind turbines and it was developed and tested on OPAL-RT's eMEGASimRTM Real-Time Digital Simulator.

The Development of a Virtual Farm for Applications in Elementary Science Education

ERIC Educational Resources Information Center

Tarng, Wernhuar; Chang, Mei-Yu; Ou, Kuo-Liang; Yu, Kein-Fu; Hsieh, Kuen-Rong

2012-01-01

The goal of this study is to develop a virtual farm for educational applications. Users can play the role of a farmer by planting vegetables and raising poultry on the virtual farm to observe their growth through online learning activities. The virtual farm possesses educational and entertaining functions, and it is designed by simulating the real…

Feeding strategy, nitrogen cycling, and profitability of dairy farms.

PubMed

Rotz, C A; Satter, L D; Mertens, D R; Muck, R E

1999-12-01

On a typical dairy farm today, large amounts of N are imported as feed supplements and fertilizer. If this N is not recycled through crop growth, it can lead to large losses to the atmosphere and ground water. More efficient use of protein feed supplements can potentially reduce the import of N in feeds, excretion of N in manure, and losses to the environment. A simulation study with a dairy farm model (DAFOSYM) illustrated that more efficient feeding and use of protein supplements increased farm profit and reduced N loss from the farm. Compared to soybean meal as the sole protein supplement, use of soybean meal along with a less rumen degradable protein feed reduced volatile N loss by 13 to 34 kg/ha of cropland with a small reduction in N leaching loss (about 1 kg/ha). Using the more expensive but less degradable protein supplement along with soybean meal improved net return by $46 to $69/cow per year, dependent on other management strategies of the farm. Environmental and economic benefits from more efficient supplementation of protein were generally greater with more animals per unit of land, higher milk production, more sandy soils, or a daily manure hauling strategy. Relatively less benefit was obtained when either alfalfa or corn silage was the sole forage on the farm or when relatively high amounts of forage were used in animal rations.

Landscape Level Carbon and Water Balances and Agricultural Production in Mountainous Terrain of the Haean Basin, South Korea

NASA Astrophysics Data System (ADS)

Lee, B.; Geyer, R.; Seo, B.; Lindner, S.; Walther, G.; Tenhunen, J. D.

2009-12-01

The process-based spatial simulation model PIXGRO was used to estimate gross primary production, ecosystem respiration, net ecosystem CO2 exchange and water use by forest and crop fields of Haean Basin, South Korea at landscape scale. Simulations are run for individual years from early spring to late fall, providing estimates for dry land crops and rice paddies with respect to carbon gain, biomass and leaf area development, allocation of photoproducts to the belowground ecosystem compartment, and harvest yields. In the case of deciduous oak forests, gas exchange is estimated, but spatial simulation of growth over the single annual cycles is not included. Spatial parameterization of the model is derived for forest LAI based on remote sensing, for forest and cropland fluxes via eddy covariance and chamber studies, for soil characteristics by generalization from spatial surveys, for climate drivers by generalizing observations at ca. 20 monitoring stations distributed throughout the basin and along the elevation gradient from 500 to 1000 m, and for incident radiation via modelling of the radiation components in complex terrain. Validation of the model is being carried out at point scale based on comparison of model output at selected locations with observations as well as with known trends in ecosystem response documented in the literature. The resulting modelling tool is useful for estimation of ecosystem services at landscape scale, first expressed as kg ha-1 crop yield, but via future cooperative studies also in terms of monetary gain to individual farms and farming cooperatives applying particular management strategies.

Coevolution of farming and private property during the early Holocene.

PubMed

Bowles, Samuel; Choi, Jung-Kyoo

2013-05-28

The advent of farming around 12 millennia ago was a cultural as well as technological revolution, requiring a new system of property rights. Among mobile hunter-gatherers during the late Pleistocene, food was almost certainly widely shared as it was acquired. If a harvested crop or the meat of a domesticated animal were to have been distributed to other group members, a late Pleistocene would-be farmer would have had little incentive to engage in the required investments in clearing, cultivation, animal tending, and storage. However, the new property rights that farming required--secure individual claims to the products of one's labor--were infeasible because most of the mobile and dispersed resources of a forager economy could not cost-effectively be delimited and defended. The resulting chicken-and-egg puzzle might be resolved if farming had been much more productive than foraging, but initially it was not. Our model and simulations explain how, despite being an unlikely event, farming and a new system of farming-friendly property rights nonetheless jointly emerged when they did. This Holocene revolution was not sparked by a superior technology. It occurred because possession of the wealth of farmers--crops, dwellings, and animals--could be unambiguously demarcated and defended. This facilitated the spread of new property rights that were advantageous to the groups adopting them. Our results thus challenge unicausal models of historical dynamics driven by advances in technology, population pressure, or other exogenous changes. Our approach may be applied to other technological and institutional revolutions such as the 18th- and 19th-century industrial revolution and the information revolution today.

Coevolution of farming and private property during the early Holocene

PubMed Central

Bowles, Samuel; Choi, Jung-Kyoo

2013-01-01

The advent of farming around 12 millennia ago was a cultural as well as technological revolution, requiring a new system of property rights. Among mobile hunter–gatherers during the late Pleistocene, food was almost certainly widely shared as it was acquired. If a harvested crop or the meat of a domesticated animal were to have been distributed to other group members, a late Pleistocene would-be farmer would have had little incentive to engage in the required investments in clearing, cultivation, animal tending, and storage. However, the new property rights that farming required—secure individual claims to the products of one’s labor—were infeasible because most of the mobile and dispersed resources of a forager economy could not cost-effectively be delimited and defended. The resulting chicken-and-egg puzzle might be resolved if farming had been much more productive than foraging, but initially it was not. Our model and simulations explain how, despite being an unlikely event, farming and a new system of farming-friendly property rights nonetheless jointly emerged when they did. This Holocene revolution was not sparked by a superior technology. It occurred because possession of the wealth of farmers—crops, dwellings, and animals—could be unambiguously demarcated and defended. This facilitated the spread of new property rights that were advantageous to the groups adopting them. Our results thus challenge unicausal models of historical dynamics driven by advances in technology, population pressure, or other exogenous changes. Our approach may be applied to other technological and institutional revolutions such as the 18th- and 19th-century industrial revolution and the information revolution today. PMID:23671111

Parallel stochastic simulation of macroscopic calcium currents.

PubMed

González-Vélez, Virginia; González-Vélez, Horacio

2007-06-01

This work introduces MACACO, a macroscopic calcium currents simulator. It provides a parameter-sweep framework which computes macroscopic Ca(2+) currents from the individual aggregation of unitary currents, using a stochastic model for L-type Ca(2+) channels. MACACO uses a simplified 3-state Markov model to simulate the response of each Ca(2+) channel to different voltage inputs to the cell. In order to provide an accurate systematic view for the stochastic nature of the calcium channels, MACACO is composed of an experiment generator, a central simulation engine and a post-processing script component. Due to the computational complexity of the problem and the dimensions of the parameter space, the MACACO simulation engine employs a grid-enabled task farm. Having been designed as a computational biology tool, MACACO heavily borrows from the way cell physiologists conduct and report their experimental work.

Dynamic energy budget model: a monitoring tool for growth and reproduction performance of Mytilus galloprovincialis in Bizerte Lagoon (Southwestern Mediterranean Sea).

PubMed

Béjaoui-Omri, Amel; Béjaoui, Béchir; Harzallah, Ali; Aloui-Béjaoui, Nejla; El Bour, Monia; Aleya, Lotfi

2014-11-01

Mussel farming is the main economic activity in Bizerte Lagoon, with a production that fluctuates depending on environmental factors. In the present study, we apply a bioenergetic growth model to the mussel Mytilus galloprovincialis, based on dynamic energy budget (DEB) theory which describes energy flux variation through the different compartments of the mussel body. Thus, the present model simulates both mussel growth and sexual cycle steps according to food availability and water temperature and also the effect of climate change on mussel behavior and reproduction. The results point to good concordance between simulations and growth parameters (metric length and weight) for mussels in the lagoon. A heat wave scenario was also simulated using the DEB model, which highlighted mussel mortality periods during a period of high temperature.

Development of a decision support system for small reservoir irrigation systems in rainfed and drought prone areas.

PubMed

Balderama, Orlando F

2010-01-01

An integrated computer program called Cropping System and Water Management Model (CSWM) with a three-step feature (expert system-simulation-optimization) was developed to address a range of decision support for rainfed farming, i.e. crop selection, scheduling and optimisation. The system was used for agricultural planning with emphasis on sustainable agriculture in the rainfed areas through the use of small farm reservoirs for increased production and resource conservation and management. The application of the model was carried out using crop, soil, and climate and water resource data from the Philippines. Primarily, four sets of data representing the different rainfall classification of the country were collected, analysed, and used as input in the model. Simulations were also done on date of planting, probabilities of wet and dry period and with various capacities of the water reservoir used for supplemental irrigation. Through the analysis, useful information was obtained to determine suitable crops in the region, cropping schedule and pattern appropriate to the specific climate conditions. In addition, optimisation of the use of the land and water resources can be achieved in areas partly irrigated by small reservoirs.

Numerical and Experimental Methods for Wake Flow Analysis in Complex Terrain

NASA Astrophysics Data System (ADS)

Castellani, Francesco; Astolfi, Davide; Piccioni, Emanuele; Terzi, Ludovico

2015-06-01

Assessment and interpretation of the quality of wind farms power output is a non-trivial task, which poses at least three main challenges: reliable comprehension of free wind flow, which is stretched to the limit on very complex terrains, realistic model of how wake interactions resemble on the wind flow, awareness of the consequences on turbine control systems, including alignment patterns to the wind and, consequently, power output. The present work deals with an onshore wind farm in southern Italy, which has been a test case of IEA- Task 31 Wakebench project: 17 turbines, with 2.3 MW of rated power each, are sited on a very complex terrain. A cluster of machines is investigated through numerical and experimental methods: CFD is employed for simulating wind fields and power extraction, as well as wakes, are estimated through the Actuator Disc model. SCADA data mining techniques are employed for comparison between models and actual performances. The simulations are performed both on the real terrain and on flat terrain, in order to disentangle the effects of complex flow and wake effects. Attention is devoted to comparison between actual alignment patterns of the cluster of turbines and predicted flow deviation.

Simulation of wind turbine wakes using the actuator line technique

PubMed Central

Sørensen, Jens N.; Mikkelsen, Robert F.; Henningson, Dan S.; Ivanell, Stefan; Sarmast, Sasan; Andersen, Søren J.

2015-01-01

The actuator line technique was introduced as a numerical tool to be employed in combination with large eddy simulations to enable the study of wakes and wake interaction in wind farms. The technique is today largely used for studying basic features of wakes as well as for making performance predictions of wind farms. In this paper, we give a short introduction to the wake problem and the actuator line methodology and present a study in which the technique is employed to determine the near-wake properties of wind turbines. The presented results include a comparison of experimental results of the wake characteristics of the flow around a three-bladed model wind turbine, the development of a simple analytical formula for determining the near-wake length behind a wind turbine and a detailed investigation of wake structures based on proper orthogonal decomposition analysis of numerically generated snapshots of the wake. PMID:25583862

An R package for simulating growth and organic wastage in aquaculture farms in response to environmental conditions and husbandry practices

PubMed Central

Baldan, Damiano; Porporato, Erika Maria Diletta; Pastres, Roberto

2018-01-01

A new R software package, RAC, is presented. RAC allows to simulate the rearing cycle of 4 species, finfish and shellfish, highly important in terms of production in the Mediterranean Sea. The package works both at the scale of the individual and of the farmed population. Mathematical models included in RAC were all validated in previous works, and account for growth and metabolism, based on input data characterizing the forcing functions—water temperature, and food quality/quantity. The package provides a demo dataset of forcings for each species, as well as a typical set of husbandry parameters for Mediterranean conditions. The present work illustrates RAC main features, and its current capabilities/limitations. Three test cases are presented as a proof of concept of RAC applicability, and to demonstrate its potential for integrating different open products nowadays provided by remote sensing and operational oceanography. PMID:29723208

Data Farming in Support of NATO

DTIC Science & Technology

2014-03-01

What are your national/international experiences on data farming ? • Finland : Technology forecasting, indirect fire studies (19,000 different...from the military bringing their questions to the data farming community. • Which simulation systems have been used in the past? • Finland : SANDIS...sponsors. • Do you have standardized procedures to conduct a data farming experiment? • Finland : No standard procedure (ad hoc at the moment, still

Understanding Large Wind Farm Impacts on Regional Climate and Vegetation Growth from Observational and Modeling Perspectives

NASA Astrophysics Data System (ADS)

Xia, Geng

In the most recent decade, wind energy has experienced exponential growth worldwide and this rapid increase is expected to continue, particularly over farmlands in the United States. This poses an important question regarding whether the widespread deployment of wind turbines (WTs) will influence surface/near-surface microclimate and vegetation growth. In this dissertation, I investigate the potential wind farm (WF) impacts on regional climate and vegetation growth from both observational and modeling perspectives. High resolution satellite, radiosonde and field observations are used to determine the magnitude and variability of WF-induced changes on surface/near-surface temperatures while the Weather Research and Forecasting (WRF) model is used to simulate these changes in real-world WFs at regional scales and to uncover the physical processes behind the simulated temperature changes. First, the primary physical mechanisms controlling the seasonal and diurnal variations of WF impacts on land surface temperature (LST) are investigated by analyzing both satellite data and field observations. It is found that the turbine-induced turbulent kinetic energy (TKE) relative to the background TKE determines the magnitude and variability of such impacts. In addition, atmospheric stability also matters in determining the sign and strength of the net downward heat transport as well as the magnitude of the background TKE. Second, the WRF's ability in simulating the observed WF impacts on LST is examined by conducting real-world WF experiments driven by realistic initial and boundary conditions. Overall, the WRF model can moderately reproduce the observed spatiotemporal variations of the background LST but has difficulties in reproducing such variations for the turbine-induced LST change signals at pixel levels. However, the model is still able to reproduce the coherent and consistent responses of the observed WF-induced LST changes at regional scales. Third, the spatiotemporal characteristics of the simulated temperature changes as well as the relevant physical processes responsible for such changes are further investigated using the WRF model. It is found that (i) the WF-induced sensible heat flux change is the dominant surface forcing responsible for the simulated temperature changes; (ii) the WF-induced temperature changes are not only restricted at the surface but also can extend vertically to the hub-height level and horizontally spread 60 km in the downwind direction; (iii) the vertical divergence of heat flux from the planetary boundary layer scheme and the resolved temperature advection are the two most likely physical processes behind the simulated temperature changes. Finally, the possible WF impacts on vegetation growth are also investigated using high resolution ( 250m) satellite derived vegetation indices (VI) over two well-studied large WF regions. Results indicate that the WFs have insignificant or no detectable impacts on local vegetation growth. At the pixel level, the VI changes demonstrate a random nature and have no spatial coupling with the WF layout. At the regional level, there is no systematic shift in vegetation greenness between the pre- and post-turbine periods. At interannual and seasonal time scales, there are no confident vegetation changes over wind farm pixels relative to non-wind farm pixels. Most importantly, the majority of the VI changes are within the data uncertainty, suggesting that the WF impacts on vegetation, if any, cannot be separated confidently from the data noise.

Empirical Analysis of Farm Credit Risk under the Structure Model

ERIC Educational Resources Information Center

Yan, Yan

2009-01-01

The study measures farm credit risk by using farm records collected by Farm Business Farm Management (FBFM) during the period 1995-2004. The study addresses the following questions: (1) whether farm's financial position is fully described by the structure model, (2) what are the determinants of farm capital structure under the structure model, (3)…

Impacts of a large array of offshore wind farms on precipitation during hurricane Harvey

NASA Astrophysics Data System (ADS)

Pan, Y.; Archer, C. L.

2017-12-01

Hurricane Harvey brought to the Texas coast possibly the heaviest rain ever recorded in U.S. history, which then caused flooding at unprecedented levels. Previous studies have shown that large arrays of offshore wind farms can extract kinetic energy from a hurricane and thus reduce the wind and storm surge. This study will quantitatively test weather the offshore turbines may also affect precipitation patterns. The Weather Research Forecast model is employed to model Harvey and the offshore wind farms are parameterized as elevated drag and turbulence kinetic energy sources. The turbines (7.8 MW Enercon-126 with rotor diameter D=127 m) are placed along the coast of Texas and Louisiana within 100 km from the shore, where the water depth is below 200 meters. Three spacing between turbines are considered (with the number of turbines in parenthesis): 7D×7D (149,936), 9D×9D (84,339), and 11D×11D (56,226). A fourth case (9D×9D) with a smaller area and thus less turbines (33,363) is added to the simulations to emphasize the impacts of offshore turbines installed specifically to protect the city of Houston, which was flooded heavily during hurricane Harvey. The model is integrated for 24 hours from 00UTC Aug 26th, 2017 to 00UTC Aug 27th, 2017. Model results indicate that the offshore wind farms have a strong impact on the distribution of 24-hour accumulated precipitation, with an obvious decrease onshore, downstream of the wind farms, and an increase in the offshore areas, upstream of or within the wind farms. A sector covering the metro-Houston area is chosen to study the sensitivity of the four different wind farm layouts. The spatial-average 24-hour accumulated precipitation is decreased by 37%, 28%, 20% and 25% respectively for the four cases. Compared with the control case with no wind turbines, increased horizontal wind divergence and lower vertical velocity are found where the precipitation is reduced onshore, whereas increased horizontal wind convergence and higher vertical velocity occur upstream or within the offshore wind farms. These preliminary results suggest that large arrays of offshore wind turbines can effectively protect the coast from heavy rain during hurricanes and that smart layouts with fewer turbines over smaller areas can be almost as effective as those with more turbines over larger areas.

Simulation of thermal environment in a three-layer vinyl greenhouse by natural ventilation control

NASA Astrophysics Data System (ADS)

Jin, Tea-Hwan; Shin, Ki-Yeol; Yoon, Si-Won; Im, Yong-Hoon; Chang, Ki-Chang

2017-11-01

A high energy, efficient, harmonious, ecological greenhouse has been highlighted by advanced future agricultural technology recently. This greenhouse is essential for expanding the production cycle toward growth conditions through combined thermal environmental control. However, it has a negative effect on farming income via huge energy supply expenses. Because not only production income, but operating costs related to thermal load for thermal environment control is important in farming income, it needs studies such as a harmonious ecological greenhouse using natural ventilation control. This study is simulated for energy consumption and thermal environmental conditions in a three-layered greenhouse by natural ventilation using window opening. A virtual 3D model of a three-layered greenhouse was designed based on the real one in the Gangneung area. This 3D model was used to calculate a thermal environment state such as indoor temperature, relative humidity, and thermal load in the case of a window opening rate from 0 to 100%. There was also a heat exchange operated for heating or cooling controlled by various setting temperatures. The results show that the cooling load can be reduced by natural ventilation control in the summer season, and the heat exchange capacity for heating can also be simulated for growth conditions in the winter season.

[Development of APSIM (agricultural production systems simulator) and its application].

PubMed

Shen, Yuying; Nan, Zhibiao; Bellotti, Bill; Robertson, Michael; Chen, Wen; Shao, Xinqing

2002-08-01

Soil-crop simulator model is an effective tool for providing decision on agricultural management. APSIM (Agricultural Production Systems Simulator) was developed to simulate the biophysical process in farming system, and particularly in the economic and ecological features of the systems under climatic risk. The current literatures revealed that APSIM could be applied in wide zone, including temperate continental, temperate maritime, sub-tropic and arid climate, and Mediterranean climates, with the soil type of clay, duplex soil, vertisol, silt sandy, silt loam and silt clay loam. More than 20 crops have been simulated well. APSIM is powerful on describing crop structure, crop sequence, yield prediction, and quality control as well as erosion estimation under different planting pattern.

Effectiveness of Simulated Interventions in Reducing the Estimated Prevalence of Salmonella in UK Pig Herds

PubMed Central

Berriman, Alexander D. C.; Clancy, Damian; Clough, Helen E.; Armstrong, Derek; Christley, Robert M.

2013-01-01

Salmonella spp are a major foodborne zoonotic cause of human illness. Consumption of pork products is believed to be a major source of human salmonellosis and Salmonella control throughout the food-chain is recommended. A number of on-farm interventions have been proposed, and some have been implemented in order to try to achieve Salmonella control. In this study we utilize previously developed models describing Salmonella dynamics to investigate the potential effects of a range of these on-farm interventions. As the models indicated that the number of bacteria shed in the faeces of an infectious animal was a key factor, interventions applied within a high-shedding scenario were also analysed. From simulation of the model, the probability of infection after Salmonella exposure was found to be a key driver of Salmonella transmission. The model also highlighted that minimising physiological stress can have a large effect but only when shedding levels are not excessive. When shedding was high, weekly cleaning and disinfection was not effective in Salmonella control. However it is possible that cleaning may have an effect if conducted more often. Furthermore, separating infectious animals, shedding bacteria at a high rate, from the rest of the population was found to be able to minimise the spread of Salmonella. PMID:23840399

"A New Life in the Countryside Awaits": Interactive Lessons in the Rural Utopia in "Farming" Simulation Games

ERIC Educational Resources Information Center

Cole, Matthew; Stewart, Kate

2017-01-01

This paper critically analyses the legitimation of exploitative human-nonhuman animal relations in online "farming" simulation games, especially the game Hay Day. The analysis contributes to a wider project of critical analyses of popular culture representations of nonhuman animals. The paper argues that legitimation is effected in Hay…

Adaptation of farming practices could buffer effects of climate change on northern prairie wetlands

USGS Publications Warehouse

Voldseth, R.A.; Johnson, W.C.; Guntenspergen, G.R.; Gilmanov, T.; Millett, B.V.

2009-01-01

Wetlands of the Prairie Pothole Region of North America are vulnerable to climate change. Adaptation of farming practices to mitigate adverse impacts of climate change on wetland water levels is a potential watershed management option. We chose a modeling approach (WETSIM 3.2) to examine the effects of changes in climate and watershed cover on the water levels of a semi-permanent wetland in eastern South Dakota. Land-use practices simulated were unmanaged grassland, grassland managed with moderately heavy grazing, and cultivated crops. Climate scenarios were developed by adjusting the historical climate in combinations of 2??C and 4??C air temperature and ??10% precipitation. For these climate change scenarios, simulations of land use that produced water levels equal to or greater than unmanaged grassland under historical climate were judged to have mitigative potential against a drier climate. Water levels in wetlands surrounded by managed grasslands were significantly greater than those surrounded by unmanaged grassland. Management reduced both the proportion of years the wetland went dry and the frequency of dry periods, producing the most dynamic vegetation cycle for this modeled wetland. Both cultivated crops and managed grassland achieved water levels that were equal or greater than unmanaged grassland under historical climate for the 2??C rise in air temperature, and the 2??C rise plus 10% increase in precipitation scenarios. Managed grassland also produced water levels that were equal or greater than unmanaged grassland under historical climate for the 4??C rise plus 10% increase in precipitation scenario. Although these modeling results stand as hypotheses, they indicate that amelioration potential exists for a change in climate up to an increase of 2??C or 4??C with a concomitant 10% increase in precipitation. Few empirical data exist to verify the results of such land-use simulations; however, adaptation of farming practices is one possible mitigation avenue available for prairie wetlands. ?? 2009, The Society of Wetland Scientists.

A Multiscale Nested Modeling Framework to Simulate the Interaction of Surface Gravity Waves with Nonlinear Internal Gravity Waves

DTIC Science & Technology

2015-09-30

Meneveau, C., and L. Shen (2014), Large-eddy simulation of offshore wind farm , Physics of Fluids, 26, 025101. Zhang, Z., Fringer, O.B., and S.R...being centimeter scale, surface mixed layer processes arising from the combined actions of tides, winds and mesoscale currents. Issues related to...the internal wave field and how it impacts the surface waves. APPROACH We are focusing on the problem of modification of the wind -wave field

Evaluation model of wind energy resources and utilization efficiency of wind farm

NASA Astrophysics Data System (ADS)

Ma, Jie

2018-04-01

Due to the large amount of abandoned winds in wind farms, the establishment of a wind farm evaluation model is particularly important for the future development of wind farms In this essay, consider the wind farm's wind energy situation, Wind Energy Resource Model (WERM) and Wind Energy Utilization Efficiency Model(WEUEM) are established to conduct a comprehensive assessment of the wind farm. Wind Energy Resource Model (WERM) contains average wind speed, average wind power density and turbulence intensity, which assessed wind energy resources together. Based on our model, combined with the actual measurement data of a wind farm, calculate the indicators using the model, and the results are in line with the actual situation. We can plan the future development of the wind farm based on this result. Thus, the proposed establishment approach of wind farm assessment model has application value.

Evaluating expansion strategies for startup European Union dairy farm businesses.

PubMed

McDonald, R; Shalloo, L; Pierce, K M; Horan, B

2013-06-01

A stochastic whole-farm simulation model was used to examine alternative strategies for new entrant dairy farmers to grow and develop dairy farm businesses in the context of European Union (EU) milk quota abolition in 2015. Six alternative strategies were compared: remain static, natural growth expansion, waiting until after EU milk quota abolition to expand, a full-scale expansion strategy without milk quotas and not incurring super levy penalties, a full-scale expansion strategy with milk quotas and incurring super levy penalties, and once-a-day milking until EU milk quota abolition, followed by full-scale expansion. Each discrete whole farm investment strategy was evaluated over a 15-yr period (2013-2027) using multiple financial stability and risk indicators, including overall discounted farm business profitability, net worth change, return on investment, and financial risk. The results of this study indicate that, although associated with increased risk, dairy farm expansion will ensure the future profitability of the farm business. Within the context of EU milk quotas until 2015, the most attractive expansion strategy is to increase cow numbers while avoiding super levy fines using once-a-day milking techniques, increasing to the full capacity of the dairy farm once milk quotas are removed. In contrast, the results also indicate that dairy farms that remain static will experience a significant reduction in farm profitability in the coming year due to production cost inflation. Cash flow deficits were observed during the initial year of expansion and, therefore, rapidly expanding dairy farm businesses require a significant cash reserve to alleviate business risk during the initial year of expansion. The results of this analysis also indicate that dairy farm businesses that expand using lower cost capital investments and avoid milk quota super levy fines significantly reduce the financial risks associated with expansion. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A novel iterative mixed model to remap three complex orthopedic traits in dogs

PubMed Central

Huang, Meng; Hayward, Jessica J.; Corey, Elizabeth; Garrison, Susan J.; Wagner, Gabriela R.; Krotscheck, Ursula; Hayashi, Kei; Schweitzer, Peter A.; Lust, George; Boyko, Adam R.; Todhunter, Rory J.

2017-01-01

Hip dysplasia (HD), elbow dysplasia (ED), and rupture of the cranial (anterior) cruciate ligament (RCCL) are the most common complex orthopedic traits of dogs and all result in debilitating osteoarthritis. We reanalyzed previously reported data: the Norberg angle (a quantitative measure of HD) in 921 dogs, ED in 113 cases and 633 controls, and RCCL in 271 cases and 399 controls and their genotypes at ~185,000 single nucleotide polymorphisms. A novel fixed and random model with a circulating probability unification (FarmCPU) function, with marker-based principal components and a kinship matrix to correct for population stratification, was used. A Bonferroni correction at p<0.01 resulted in a P< 6.96 ×10−8. Six loci were identified; three for HD and three for RCCL. An associated locus at CFA28:34,369,342 for HD was described previously in the same dogs using a conventional mixed model. No loci were identified for RCCL in the previous report but the two loci for ED in the previous report did not reach genome-wide significance using the FarmCPU model. These results were supported by simulation which demonstrated that the FarmCPU held no power advantage over the linear mixed model for the ED sample but provided additional power for the HD and RCCL samples. Candidate genes for HD and RCCL are discussed. When using FarmCPU software, we recommend a resampling test, that a positive control be used to determine the optimum pseudo quantitative trait nucleotide-based covariate structure of the model, and a negative control be used consisting of permutation testing and the identical resampling test as for the non-permuted phenotypes. PMID:28614352

Full-Scale Field Test of Wake Steering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fleming, Paul; Annoni, Jennifer; Scholbrock, Andrew

Wind farm control, in which turbine controllers are coordinated to improve farmwide performance, is an active field of research. One form of wind farm control is wake steering, in which a turbine is yawed to the inflow to redirect its wake away from downstream turbines. Wake steering has been studied in depth in simulations as well as in wind tunnels and scaled test facilities. This work performs a field test of wake steering on a full-scale turbine. In the campaign, the yaw controller of the turbine has been set to track different yaw misalignment set points while a nacelle-mounted lidarmore » scans the wake at several ranges downwind. The lidar measurements are combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast. In conclusion, these measurements are then compared to the predictions of a wind farm control-oriented model of wakes.« less

Processor farming in two-level analysis of historical bridge

NASA Astrophysics Data System (ADS)

Krejčí, T.; Kruis, J.; Koudelka, T.; Šejnoha, M.

2017-11-01

This contribution presents a processor farming method in connection with a multi-scale analysis. In this method, each macro-scopic integration point or each finite element is connected with a certain meso-scopic problem represented by an appropriate representative volume element (RVE). The solution of a meso-scale problem provides then effective parameters needed on the macro-scale. Such an analysis is suitable for parallel computing because the meso-scale problems can be distributed among many processors. The application of the processor farming method to a real world masonry structure is illustrated by an analysis of Charles bridge in Prague. The three-dimensional numerical model simulates the coupled heat and moisture transfer of one half of arch No. 3. and it is a part of a complex hygro-thermo-mechanical analysis which has been developed to determine the influence of climatic loading on the current state of the bridge.

Full-Scale Field Test of Wake Steering

DOE PAGES

Fleming, Paul; Annoni, Jennifer; Scholbrock, Andrew; ...

2017-06-13

Wind farm control, in which turbine controllers are coordinated to improve farmwide performance, is an active field of research. One form of wind farm control is wake steering, in which a turbine is yawed to the inflow to redirect its wake away from downstream turbines. Wake steering has been studied in depth in simulations as well as in wind tunnels and scaled test facilities. This work performs a field test of wake steering on a full-scale turbine. In the campaign, the yaw controller of the turbine has been set to track different yaw misalignment set points while a nacelle-mounted lidarmore » scans the wake at several ranges downwind. The lidar measurements are combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast. In conclusion, these measurements are then compared to the predictions of a wind farm control-oriented model of wakes.« less

Data Farming and the Exploration of Inter-Agency, Inter-Disciplinary, and International "What If?" Questions

NASA Technical Reports Server (NTRS)

Anderson, Steve; Horne, Gary; Meyer, Ted; Triola, Larry

2012-01-01

Data farming uses simulation modeling, high performance computing, and analysis to examine questions of interest with large possibility spaces.This methodology allows for the examination of whole landscapes of potential outcomes and provides the capability of executing enough experiments so that outlets might be captured and examined for insights. This capability may be quite informative when used to examine the plethora of "What if?" questions that result when examining potential scenarios that our forces may face in the uncertain world of the future. Many of theses scenarios most certainly will be challenging and solutions may depend on interagency and international collaboration as well as the need for inter-disciplinary scientific inquiry preceding these events. In this paper, we describe data farming and illustrate it in the context of application to questions inherent to military decision-making as we consider alternate future scenarios.

An Adaptive Coordinated Control for an Offshore Wind Farm Connected VSC Based Multi-Terminal DC Transmission System

NASA Astrophysics Data System (ADS)

Kumar, M. Ajay; Srikanth, N. V.

2015-01-01

The voltage source converter (VSC) based multiterminal high voltage direct current (MTDC) transmission system is an interesting technical option to integrate offshore wind farms with the onshore grid due to its unique performance characteristics and reduced power loss via extruded DC cables. In order to enhance the reliability and stability of the MTDC system, an adaptive neuro fuzzy inference system (ANFIS) based coordinated control design has been addressed in this paper. A four terminal VSC-MTDC system which consists of an offshore wind farm and oil platform is implemented in MATLAB/ SimPowerSystems software. The proposed model is tested under different fault scenarios along with the converter outage and simulation results show that the novel coordinated control design has great dynamic stabilities and also the VSC-MTDC system can supply AC voltage of good quality to offshore loads during the disturbances.

Economic and environmental feasibility of a perennial cow dairy farm.

PubMed

Rotz, C A; Zartman, D L; Crandall, K L

2005-08-01

More efficient and economical production systems are needed to improve the sustainability of dairy farms. One concept to consider is using perennial cows. Perennial cows are those that maintain a relatively high milk production for >or=2 yr without going through the typical dry period followed by calving. Farm records show that some cows have produced over 20 kg/d after 4 yr of continuous lactation. A farm simulation model was used to evaluate the long-term performance, environmental impact, and economics of a conceptual perennial cow production system on a typical dairy farm in Pennsylvania. Compared with a traditional 100-cow farm with replacement heifers produced on the farm, a perennial herd of 100 cows and purchased replacements provided environmental benefit but sustained a substantial economic loss. However, increasing the perennial herd to 128 cows better utilized the feed produced on the farm. Compared with the traditional 100-cow farm, use of the perennial 128-cow herd reduced supplemental protein and mineral feed purchases by 38%, increased annual milk sales by 21%, reduced nitrogen losses by 17%, maintained a phosphorus balance, and increased annual net return to farm management by 3200 dollars. A traditional 120-cow dairy farm with purchased replacements also used a similar amount of farm-produced feed. Compared with this option, the farm with 128 perennial cows reduced protein and mineral feed purchases by 36%, maintained similar annual milk sales, increased manure production by 7%, reduced N losses by 10%, and increased annual net return by 12,700 dollars. The economic feasibility of the perennial-cow dairy farm was very sensitive to the milk production maintained by the perennial herd and market prices for milk and perennial replacement animals. The analysis was relatively insensitive to the assumed useful life of perennial cows as long as they could be maintained in the herd for at least 3 yr. Thus, a perennial cow production system can improve the economic and environmental sustainability of a traditional dairy farm if a similar level in annual milk production per cow can be maintained.

Direct and indirect impacts of crop-livestock organization on mixed crop-livestock systems sustainability: a model-based study.

PubMed

Sneessens, I; Veysset, P; Benoit, M; Lamadon, A; Brunschwig, G

2016-11-01

Crop-livestock production is claimed more sustainable than specialized production systems. However, the presence of controversial studies suggests that there must be conditions of mixing crop and livestock productions to allow for higher sustainable performances. Whereas previous studies focused on the impact of crop-livestock interactions on performances, we posit here that crop-livestock organization is a key determinant of farming system sustainability. Crop-livestock organization refers to the percentage of the agricultural area that is dedicated to each production. Our objective is to investigate if crop-livestock organization has both a direct and an indirect impact on mixed crop-livestock (MC-L) sustainability. In that objective, we build a whole-farm model parametrized on representative French sheep and crop farming systems in plain areas (Vienne, France). This model permits simulating contrasted MC-L systems and their subsequent sustainability through the following indicators of performance: farm income, production, N balance, greenhouse gas (GHG) emissions (/kg product) and MJ consumption (/kg product). Two MC-L systems were simulated with contrasted crop-livestock organizations (MC20-L80: 20% of crops; MC80-L20: 80% of crops). A first scenario - constraining no crop-livestock interactions in both MC-L systems - permits highlighting that crop-livestock organization has a significant direct impact on performances that implies trade-offs between objectives of sustainability. Indeed, the MC80-L20 system is showing higher performances for farm income (+44%), livestock production (+18%) and crop GHG emissions (-14%) whereas the MC20-L80 system has a better N balance (-53%) and a lower livestock MJ consumption (-9%). A second scenario - allowing for crop-livestock interactions in both MC20-L80 and MC80-L20 systems - stated that crop-livestock organization has a significant indirect impact on performances. Indeed, even if crop-livestock interactions permit improving performances, crop-livestock organization influences the capacity of MC-L systems to benefit from crop-livestock interactions. As a consequence, we observed a decreasing performance trade-off between MC-L systems for farm income (-4%) and crop GHG emissions (-10%) whereas the gap increases for nitrogen balance (+23%), livestock production (+6%) - MJ consumption (+16%) - GHG emissions (+5%) and crop MJ consumption (+5%). However, the indirect impact of crop-livestock organization doesn't reverse the trend of trade-offs between objectives of sustainability determined by the direct impact of crop-livestock organization. As a conclusion, crop-livestock organization is a key factor that has to be taken into account when studying the sustainability of mixed crop-livestock systems.

Simulation for Grid Connected Wind Turbines with Fluctuating

NASA Astrophysics Data System (ADS)

Ye, Ying; Fu, Yang; Wei, Shurong

This paper establishes the whole dynamic model of wind turbine generator system which contains the wind speed model and DFIG wind turbines model .A simulation sample based on the mathematical models is built by using MATLAB in this paper. Research are did on the performance characteristics of doubly-fed wind generators (DFIG) which connected to power grid with three-phase ground fault and the disturbance by gust and mixed wind. The capacity of the wind farm is 9MW which consists of doubly-fed wind generators (DFIG). Simulation results demonstrate that the three-phase ground fault occurs on grid side runs less affected on the stability of doubly-fed wind generators. However, as a power source, fluctuations of the wind speed will run a large impact on stability of double-fed wind generators. The results also show that if the two disturbances occur in the meantime, the situation will be very serious.

SIMULATION OF NITROUS OXIDE EMISSIONS FROM DAIRY FARMS TO ASSESS GREENHOUSE GAS REDUCTION STRATEGIES

USDA-ARS?s Scientific Manuscript database

Farming practices can have a large impact on the net emission of greenhouse gases including carbon dioxide, methane, and nitrous oxide (N**2O). The primary sources of N**2O from dairy farms are nitrification and denitrification processes in soil, with smaller contributions from manure storage and ba...

SIMULATION OF CARBON DIOXIDE EMISSIONS FROM DAIRY FARMS TO ASSESS GREENHOUSE GAS REDUCTION STRATEGIES

USDA-ARS?s Scientific Manuscript database

Farming practices can have a large impact on the soil carbon cycle and the resulting net emission of greenhouse gases including carbon dioxide (CO**2), methane and nitrous oxide. Primary sources of CO**2 emission on dairy farms are soil, plant, and animal respiration with smaller contributions from ...

Collaborations Move Industry Forward, Prove Mutually Beneficial | News |

Science.gov Websites

features collaboration between NREL and GE Global Research, which is advancing its use of NREL's Simulator researchers to better understand wind farm flow physics so future wind farms can be more optimally designed Colorado will join in interpreting the data. "Wind farm control is garnering interest across the

Flow adjustment inside large finite-size wind farms approaching the infinite wind farm regime

NASA Astrophysics Data System (ADS)

Wu, Ka Ling; Porté-Agel, Fernando

2017-04-01

Due to the increasing number and the growing size of wind farms, the distance among them continues to decrease. Thus, it is necessary to understand how these large finite-size wind farms and their wakes could interfere the atmospheric boundary layer (ABL) dynamics and adjacent wind farms. Fully-developed flow inside wind farms has been extensively studied through numerical simulations of infinite wind farms. The transportation of momentum and energy is only vertical and the advection of them is neglected in these infinite wind farms. However, less attention has been paid to examine the length of wind farms required to reach such asymptotic regime and the ABL dynamics in the leading and trailing edges of the large finite-size wind farms. Large eddy simulations are performed in this study to investigate the flow adjustment inside large finite-size wind farms in conventionally-neutral boundary layer with the effect of Coriolis force and free-atmosphere stratification from 1 to 5 K/km. For the large finite-size wind farms considered in the present work, when the potential temperature lapse rate is 5 K/km, the wind farms exceed the height of the ABL by two orders of magnitude for the incoming flow inside the farms to approach the fully-developed regime. An entrance fetch of approximately 40 times of the ABL height is also required for such flow adjustment. At the fully-developed flow regime of the large finite-size wind farms, the flow characteristics match those of infinite wind farms even though they have different adjustment length scales. The role of advection at the entrance and exit regions of the large finite-size wind farms is also examined. The interaction between the internal boundary layer developed above the large finite-size wind farms and the ABL under different potential temperature lapse rates are compared. It is shown that the potential temperature lapse rate plays a role in whether the flow inside the large finite-size wind farms adjusts to the fully-developed flow regime. The flow characteristics of the wake of these large finite-size wind farms are reported to forecast the effect of large finite-size wind farms on adjacent wind farms. A power deficit as large as 8% is found at a distance of 10 km downwind from the large finite-size wind farms.

Evaluation of strategies for the eradication of Pseudorabies virus (Aujeszky's disease) in commercial swine farms in Chiang-Mai and Lampoon Provinces, Thailand, using a simulation disease spread model.

PubMed

Ketusing, N; Reeves, A; Portacci, K; Yano, T; Olea-Popelka, F; Keefe, T; Salman, M

2014-04-01

Several strategies for eradicating Pseudorabies virus (Aujeszky's disease) in Chiang-Mai and Lampoon Provinces, Thailand, were compared using a computer simulation model, the North American Animal Disease Spread Model (NAADSM). The duration of the outbreak, the number of affected herds and the number of destroyed herds were compared during these simulated outbreaks. Depopulation, zoning for restricted movement and improved detection and vaccination strategies were assessed. The most effective strategies to eradicate Pseudorabies as per the findings from this study are applying depopulation strategies with MOVEMENT RESTRICTIONS in 3-, 8- and 16-km ZONES surrounding infected herds and enhancing the eradication with vaccination campaign on 16-km radius surrounding infected herds. © 2012 Blackwell Verlag GmbH.

Comparison of simulations of land-use specific water demand and irrigation water supply by MF-FMP and IWFM

USGS Publications Warehouse

Schmid, Wolfgang; Dogural, Emin; Hanson, Randall T.; Kadir, Tariq; Chung, Francis

2011-01-01

Two hydrologic models, MODFLOW with the Farm Process (MF-FMP) and the Integrated Water Flow Model (IWFM), are compared with respect to each model’s capabilities of simulating land-use hydrologic processes, surface-water routing, and groundwater flow. Of major concern among the land-use processes was the consumption of water through evaporation and transpiration by plants. The comparison of MF-FMP and IWFM was conducted and completed using a realistic hypothetical case study. Both models simulate the water demand for water-accounting units resulting from evapotranspiration and inefficiency losses and, for irrigated units, the supply from surface-water deliveries and groundwater pumpage. The MF-FMP simulates reductions in evapotranspiration owing to anoxia and wilting, and separately considers land-use-related evaporation and transpiration; IWFM simulates reductions in evapotranspiration related to the depletion of soil moisture. The models simulate inefficiency losses from precipitation and irrigation water applications to runoff and deep percolation differently. MF-FMP calculates the crop irrigation requirement and total farm delivery requirement, and then subtracts inefficiency losses from runoff and deep percolation. In IWFM, inefficiency losses to surface runoff from irrigation and precipitation are computed and subtracted from the total irrigation and precipitation before the crop irrigation requirement is estimated. Inefficiency losses in terms of deep percolation are computed simultaneously with the crop irrigation requirement. The seepage from streamflow routing also is computed differently and can affect certain hydrologic settings and magnitudes ofstreamflow infiltration. MF-FMP assumes steady-state conditions in the root zone; therefore, changes in soil moisture within the root zone are not calculated. IWFM simulates changes in the root zone in both irrigated and non-irrigated natural vegetation. Changes in soil moisture are more significant for non-irrigated natural vegetation areas than in the irrigated areas. Therefore, to facilitate the comparison of models, the changes in soil moisture are only simulated by IWFM for the natural vegetation areas, and soil-moisture parameters in irrigated regions in IWFM were specified at constant values . The IWFM total simulated changes in soil moisture that are related to natural vegetation areas vary from stress period to stress period but are small over the entire two-year period of simulation. In the hypothetical case study, IWFM simulates more evapotranspiration and return flows and less streamflow infiltration than MF-FMP. This causes more simulated surface-water diversions upstream and less simulated water available to downstream farms in IWFM compared to MF-FMP. The evapotranspiration simulated by the two models is well correlated even though the quantity is different. The different approaches used to simulate soil moisture, evapotranspiration, and inefficient losses yield different results for deep percolation and pumpage. In IWFM, deep percolation is a function of soil moisture; therefore, the constant soil-moisture requirement for irrigated regions, assumed for this comparison, results in a constant deep percolation rate. This led to poor correlation with the variable deep percolation rates simulated in MF-FMP, where the deep percolation rate, a fraction of inefficiency losses from precipitation and irrigation, is a function of quasi-steady state infiltration for each soil type and a function of groundwater head. Similarly, the larger simulated evapotranspiration in IWFM is mainly responsible for larger simulated groundwater pumpage demands and related lower groundwater levels in IWFM compared to MF-FMP. Because of the differences in features between MF-FMP and IWFM, the user may find that for certain hydrologic settings one model is better suited than the other. The performance of MF-FMP and IWFM in this particular hypothetical test case, with a fixed framework composed of common initial and boundary conditions and input parameter values, does not necessarily predict the performance of MF-FMP and IWFM in a real-world situation with variable framework and parameter values. These differences may affect the evaluation of policies, projects, or water-balance analysis for some hydrologic settings. Generally, both models are powerful tools that simulate a connected system of aquifer, stream networks, land surface, root zone, and runoff processes. MF-FMP simulated the hypothetical test case in about 4 minutes compared to about 58 minutes for IWFM.

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

PubMed

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

Estimating the effect of mastitis on the profitability of Irish dairy farms.

PubMed

Geary, U; Lopez-Villalobos, N; Begley, N; McCoy, F; O'Brien, B; O'Grady, L; Shalloo, L

2012-07-01

The objective of this paper was to estimate the effect of the costs of mastitis on the profitability of Irish dairy farms as indicated by various ranges of bulk milk somatic cell count (BMSCC). Data were collected from 4 sources and included milk production losses, cases treated, and on-farm practices around mastitis management. The Moorepark Dairy Systems Model, which simulates dairying systems inside the farm gate, was used to carry out the analysis. The cost components of mastitis that affect farm profitability and that were included in the model were milk losses, culling, diagnostic testing, treatment, veterinary attention, discarded milk, and penalties. Farms were grouped by 5 BMSCC thresholds of ≤ 100,000, 100,001-200,000, 200,001-300,000, 300,001-400,000, and > 400,000 cells/mL. The ≤ 100,000 cells/mL threshold was taken as the baseline and the other 4 thresholds were compared relative to this baseline. For a 40-ha farm, the analysis found that as BMSCC increased, milk receipts decreased from €148,843 at a BMSCC <100,000 cells/mL to €138,573 at a BMSCC > 400,000 cells/mL. In addition, as BMSCC increased, livestock receipts increased by 17%, from €43,304 at a BMSCC <100,000 cells/mL to €50,519 at a BMSCC > 400,000 cells/mL. This reflected the higher replacement rates as BMSCC increased and the associated cull cow value. Total farm receipts decreased from €192,147 at the baseline (< 100,000 cells/mL) to €189,091 at a BMSCC > 400,000 cells/mL. Total farm costs increased as BMSCC increased, reflecting treatment, veterinary, diagnostic testing, and replacement heifer costs. At the baseline, total farm costs were €161,085, increasing to €177,343 at a BMSCC > 400,000 cells/mL. Net farm profit decreased as BMSCC increased, from €31,252/yr at the baseline to €11,748/yr at a BMSCC > 400,000 cells/mL. This analysis highlights the impact that mastitis has on the profitability of Irish dairy farms. The analysis presented here can be used to develop a "cost of mastitis" tool for use on Irish dairy farms to motivate farmers to acknowledge the scale of the problem, realize the value of improving mastitis control, and implement effective mastitis control practices. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Gravity Waves and Wind-Farm Efficiency in Neutral and Stable Conditions

NASA Astrophysics Data System (ADS)

Allaerts, Dries; Meyers, Johan

2018-02-01

We use large-eddy simulations (LES) to investigate the impact of stable stratification on gravity-wave excitation and energy extraction in a large wind farm. To this end, the development of an equilibrium conventionally neutral boundary layer into a stable boundary layer over a period of 8 h is considered, using two different cooling rates. We find that turbulence decay has considerable influence on the energy extraction at the beginning of the boundary-layer transition, but afterwards, energy extraction is dominated by geometrical and jet effects induced by an inertial oscillation. It is further shown that the inertial oscillation enhances gravity-wave excitation. By comparing LES results with a simple one-dimensional model, we show that this is related to an interplay between wind-farm drag, variations in the Froude number and the dispersive effects of vertically-propagating gravity waves. We further find that the pressure gradients induced by gravity waves lead to significant upstream flow deceleration, reducing the average turbine output compared to a turbine in isolated operation. This leads us to the definition of a non-local wind-farm efficiency, next to a more standard wind-farm wake efficiency, and we show that both can be of the same order of magnitude. Finally, an energy flux analysis is performed to further elucidate the effect of gravity waves on the flow in the wind farm.

Application of MODFLOW’s farm process to California’s Central Valley

USGS Publications Warehouse

Faunt, Claudia; Hanson, Randall T.; Schmid, Wolfgang; Belitz, Kenneth

2008-01-01

landscape processes. The FMP provides coupled simulation of the ground-water and surface-water components of the hydrologic cycle for irrigated and non-irrigated areas. A dynamic allocation of ground-water recharge and ground-water pumping is simulated on the basis of residual crop-water demand after surface-water deliveries and root uptake from shallow ground water. The FMP links with the Streamflow Routing Package SFR1) to facilitate the simulated conveyance of surface-water deliveries. Ground-water Pumpage through both single-aquifer and multi-node wells, irrigation return flow, and variable irrigation efficiencies also are simulated by the FMP. The simulated deliveries and ground-water pumpage in the updated model reflect climatic differences, differences among defined water-balance regions, and changes in the waterdelivery system, during the 1961–2003 simulation period. The model is designed to accept forecasts from Global Climate Models (GCMs) to simulate the potential effects on surface-water delivery, ground-water pumpage, and ground-water storage in response to climate change. The model provides a detailed transient analysis of changes in ground-water availability in relation to climatic variability, urbanization, and changes in irrigated agriculture.

Security, protection, and control of power systems with large-scale wind power penetration

NASA Astrophysics Data System (ADS)

Acharya, Naresh

As the number of wind generation facilities in the utility system is fast increasing, many issues associated with their integration into the power system are beginning to emerge. Of the various issues, this dissertation deals with the development of new concepts and computational methods to handle the transmission issues and voltage issues caused by large-scale integration of wind turbines. This dissertation also formulates a probabilistic framework for the steady-state security assessment of wind power incorporating the forecast uncertainty and correlation. Transmission issues are mainly related to the overloading of transmission lines, when all the wind power generated cannot be delivered in full due to prior outage conditions. To deal with this problem, a method to curtail the wind turbine outputs through Energy Management System facilities in the on-line operational environment is proposed. The proposed method, which is based on linear optimization, sends the calculated control signals via the Supervisory Control and Data Acquisition system to wind farm controllers. The necessary ramping of the wind farm outputs is implemented either by the appropriate blade pitch angle control at the turbine level or by switching a certain number of turbines. The curtailment strategy is tested with an equivalent system model of MidAmerican Energy Company. The results show that the line overload in high wind areas can be alleviated by controlling the outputs of the wind farms step-by-step over an allowable period of time. A low voltage event during a system fault can cause a large number of wind turbines to trip, depending on voltages at the wind turbine terminals during the fault and the under-voltage protection setting of wind turbines. As a result, an N-1 contingency may evolve into an N-(K+1) contingency, where K is the number of wind farms tripped due to low voltage conditions. Losing a large amount of wind power following a line contingency might lead to system instabilities. It is important for the system operator to be aware of such limiting events during system operation and be prepared to take proper control actions. This can be achieved by incorporating the wind farm tripping status for each contingency as part of the static security assessment. A methodology to calculate voltages at the wind farm buses during a worst case line fault is proposed, which, along with the protection settings of wind turbines, can be used to determine the tripping of wind farms. The proposed algorithm is implemented in MATLAB and tested with MidAmerican Energy reduced network. The result shows that a large amount of wind capacity can be tripped due to a fault in the lines. Therefore, the technique will find its application in the static security assessment where each line fault can be associated with the tripping of wind farms as determined from the proposed method. A probabilistic framework to handle the uncertainty in day-ahead forecast error in order to correctly assess the steady-state security of the power system is presented. Stochastic simulations are conducted by means of Latin hypercube sampling along with the consideration of correlations. The correlation is calculated from the historical distribution of wind power forecast errors. The results from the deterministic simulation based on point forecast and the stochastic simulation show that security assessment based solely on deterministic simulations can lead to incorrect assessment of system security. With stochastic simulations, each outcome can be assigned a probability and the decision regarding control actions can be made based on the associated probability.

One-Water Hydrologic Flow Model (MODFLOW-OWHM)

USGS Publications Warehouse

Hanson, Randall T.; Boyce, Scott E.; Schmid, Wolfgang; Hughes, Joseph D.; Mehl, Steffen W.; Leake, Stanley A.; Maddock, Thomas; Niswonger, Richard G.

2014-01-01

The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model (IHM) that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. Conjunctive use is the combined use of groundwater and surface water. MF-OWHM allows the simulation, analysis, and management of nearly all components of human and natural water movement and use in a physically-based supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 (MF-FMP2) combined with Local Grid Refinement (LGR) for embedded models to allow use of the Farm Process (FMP) and Streamflow Routing (SFR) within embedded grids. MF-OWHM also includes new features such as the Surface-water Routing Process (SWR), Seawater Intrusion (SWI), and Riparian Evapotrasnpiration (RIP-ET), and new solvers such as Newton-Raphson (NWT) and nonlinear preconditioned conjugate gradient (PCGN). This IHM also includes new connectivities to expand the linkages for deformation-, flow-, and head-dependent flows. Deformation-dependent flows are simulated through the optional linkage to simulated land subsidence with a vertically deforming mesh. Flow-dependent flows now include linkages between the new SWR with SFR and FMP, as well as connectivity with embedded models for SFR and FMP through LGR. Head-dependent flows now include a modified Hydrologic Flow Barrier Package (HFB) that allows optional transient HFB capabilities, and the flow between any two layers that are adjacent along a depositional or erosional boundary or displaced along a fault. MF-OWHM represents a complete operational hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for consumption by irrigated agriculture, but also of water used in urban areas and by natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply-constrained conditions. From large- to small-scale settings, MF-OWHM has the unique set of capabilities to simulate and analyze historical, present, and future conjunctive-use conditions. MF-OWHM is especially useful for the analysis of agricultural water use where few data are available for pumpage, land use, or agricultural information. The features presented in this IHM include additional linkages with SFR, SWR, Drain-Return (DRT), Multi-Node Wells (MNW1 and MNW2), and Unsaturated-Zone Flow (UZF). Thus, MF-OWHM helps to reduce the loss of water during simulation of the hydrosphere and helps to account for “all of the water everywhere and all of the time.” In addition to groundwater, surface-water, and landscape budgets, MF-OWHM provides more options for observations of land subsidence, hydraulic properties, and evapotranspiration (ET) than previous models. Detailed landscape budgets combined with output of estimates of actual evapotranspiration facilitates linkage to remotely sensed observations as input or as additional observations for parameter estimation or water-use analysis. The features of FMP have been extended to allow for temporally variable water-accounting units (farms) that can be linked to land-use models and the specification of both surface-water and groundwater allotments to facilitate sustainability analysis and connectivity to the Groundwater Management Process (GWM). An example model described in this report demonstrates the application of MF-OWHM with the addition of land subsidence and a vertically deforming mesh, delayed recharge through an unsaturated zone, rejected infiltration in a riparian area, changes in demand caused by deficiency in supply, and changes in multi-aquifer pumpage caused by constraints imposed through the Farm Process and the MNW2 Package, and changes in surface water such as runoff, streamflow, and canal flows through SFR and SWR linkages.

Modelling tidal current energy extraction in large area using a three-dimensional estuary model

NASA Astrophysics Data System (ADS)

Chen, Yaling; Lin, Binliang; Lin, Jie

2014-11-01

This paper presents a three-dimensional modelling study for simulating tidal current energy extraction in large areas, with a momentum sink term being added into the momentum equations. Due to the limits of computational capacity, the grid size of the numerical model is generally much larger than the turbine rotor diameter. Two models, i.e. a local grid refinement model and a coarse grid model, are employed and an idealized estuary is set up. The local grid refinement model is constructed to simulate the power generation of an isolated turbine and its impacts on hydrodynamics. The model is then used to determine the deployment of turbine farm and quantify a combined thrust coefficient for multiple turbines located in a grid element of coarse grid model. The model results indicate that the performance of power extraction is affected by array deployment, with more power generation from outer rows than inner rows due to velocity deficit influence of upstream turbines. Model results also demonstrate that the large-scale turbine farm has significant effects on the hydrodynamics. The tidal currents are attenuated within the turbine swept area, and both upstream and downstream of the array. While the currents are accelerated above and below turbines, which is contributed to speeding up the wake mixing process behind the arrays. The water levels are heightened in both low and high water levels as the turbine array spanning the full width of estuary. The magnitude of water level change is found to increase with the array expansion, especially at the low water level.

Automatic milking systems, farm size, and milk production.

PubMed

Rotz, C A; Coiner, C U; Soder, K J

2003-12-01

Automatic milking systems (AMS) offer relief from the demanding routine of milking. Although many AMS are in use in Europe and a few are used in the United States, the potential benefit for American farms is uncertain. A farm-simulation model was used to determine the long-term, whole-farm effect of implementing AMS on farm sizes of 30 to 270 cows. Highest farm net return to management and unpaid factors was when AMS were used at maximal milking capacity. Adding stalls to increase milking frequency and possibly increase production generally did not improve net return. Compared with new traditional milking systems, the greatest potential economic benefit was a single-stall AMS on a farm size of 60 cows at a moderate milk production level (8600 kg/cow). On other farm sizes using single-stall type robotic units, losses in annual net return of 0 dollars to 300 dollars/cow were projected, with the greatest losses on larger farms and at high milk production (10,900 kg/cow). Systems with one robot serving multiple stalls provided a greater net return than single-stall systems, and this net return was competitive with traditional parlors for 50- to 130-cow farm sizes. The potential benefit of AMS was improved by 100 dollars/cow per year if the AMS increased production an additional 5%. A 20% reduction in initial equipment cost or doubling milking labor cost also improved annual net return of an AMS by up to 100 dollars/cow. Annual net return was reduced by 110 dollars/cow, though, if the economic life of the AMS was reduced by 3 yr for a more rapid depreciation than that normally used with traditional milking systems. Thus, under current assumptions, the economic return for an AMS was similar to that of new parlor systems on smaller farms when the milking capacity of the AMS was well matched to herd size and milk production level.

Can tidal energy farms create temperature fronts in the coastal ocean?

NASA Astrophysics Data System (ADS)

Shapiro, G. I.

2012-04-01

Although an industrial scale tidal farm comprising a large set of submerged turbines has not been built yet, tidal power is considered to be one of potential sources of renewable energy in the future. For example, India plans to install a 50MW tidal farm in the Gulf of Kutch which could be further expanded to deliver more than 200MW. As tidal stream generators extract kinetic energy from the ocean currents, they change the circulation pattern and hence affect the marine environment. Recent research has shown ( Shapiro, 2011, Neill et al., 2009) that a tidal farm can modify currents and sediment transport outside the farm as far as up to a hundred kilometres. This paper studies the potential effect of a tidal farm on the temperature structure in a shallow sea using a 3D ocean model POLCOMS which was modified to include effects of kinetic energy extraction as detailed in (Shapiro, 2011). The model is set up in the Celtic Sea known for its high levels of tidal energy. The model is driven by 15 tidal constituents and the meteo forcing. Effects of tidal farms of varying sizes and power capacities (from 50 MW to 1500MW) have been studied during summer months. The simulated farms are placed in various locations north of the Cornish coast. It has been shown that even smaller farms can modify temperature distribution as far as a few tens of kilometres from the farm, and sometimes generate localised temperature fronts. This effect is particularly strong during the month of June when the fronts penetrate from surface to the seabed. The fronts are more pronounced during the spring tides, however they are still seen during the neaps. As the seasonal thermocline strengthens towards the end of summer, the fronts are mostly seen in the upper ocean layer, with warmer waters in the area of the farm and cooler waters outside the farm. The physical mechanism of front generation is linked to abrupt changes in the current patterns due to energy extraction from the ocean. The currents inside the farm become weaker, whilst the currents outside the farm ( at a scale comparable to the baroclinic Rossby radius) become stronger. Such stronger currents enhance the mixing of the water column outside the farm, and weaker currents inside the farm reduce turbulent mixing and facilitate formation of a stronger thermocline. The overall effect is generally similar to the formation of fronts between tidally mixed and stratified areas of a shallow sea (Simpson and Hunter, 1974). Effect of geometrically smaller farms is less pronounced as the water particles travel in and out the affected zone during the tidal cycle (over the length of the tidal excursion) and hence are influenced by the above mechanism only during a proportion of the tidal cycle. Reduced vertical mixing within the area of the farm and positive heat balance explains higher temperatures at the surface. In the beginning of summer when thermal stratification is relatively week, the thermocline is significantly altered and the fronts propagate to a greater depth. Development of a stronger thermocline towards the end of summer inhibits the effect of mixing and the fluctuations of the depth of the upper mixed layer due to energy extraction are suppressed .

Off-farm applications of solar energy in agriculture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berry, R.E.

1980-01-01

Food processing applications make up almost all present off-farm studies of solar energy in agriculture. Research, development and demonstration projects on solar food processing have shown significant progress over the past 3 years. Projects have included computer simulation and mathematical models, hardware and process development for removing moisture from horticultural or animal products, integration of energy conservation with solar energy augmentation in conventional processes, and commercial scale demonstrations. The demonstration projects include solar heated air for drying prunes and raisins, soy beans and onions/garlic; and solar generated steam for orange juice pasteurization. Several new and planned projects hold considerable promisemore » for commerical exploitation in future food processes.« less

RANS simulations of wind turbine wakes: optimal tuning of turbulence closure and aerodynamic loads from LiDAR and SCADA data

NASA Astrophysics Data System (ADS)

Letizia, Stefano; Puccioni, Matteo; Zhan, Lu; Viola, Francesco; Camarri, Simone; Iungo, Giacomo Valerio

2017-11-01

Numerical simulations of wakes produced by utility-scale wind turbines still present challenges related to the variability of the atmospheric conditions and, in the most of the cases, the lack of information about the geometry and aerodynamic performance of the wind turbine blades. In order to overcome the mentioned difficulties, we propose a RANS solver for which turbine aerodynamic forcing and turbulence closure are calibrated through LiDAR and SCADA data acquired for an onshore wind farm. The wind farm under examination is located in North Texas over a relatively flat terrain. The experimental data are leveraged to maximize accuracy of the RANS predictions in terms of wake velocity field and power capture for different atmospheric stability conditions and settings of the wind turbines. The optimization of the RANS parameters is performed through an adjoint-RANS formulation and a gradient-based procedure. The optimally-tuned aerodynamic forcing and turbulence closure are then analyzed in order to investigate effects of the atmospheric stability on the evolution of wind turbine wakes and power performance. The proposed RANS solver has low computational costs comparable to those of wake engineering models, which make it a compelling tool for wind farm control and optimization. Acknowledgments: NSF I/UCRC WindSTAR IIP 1362033 and TACC.

Biological exhaust air treatment systems as a potential microbial risk for farm animals assessed with a computer simulation.

PubMed

Seedorf, Jens

2013-09-01

Livestock operations are under increasing pressure to fulfil minimum environmental requirements and avoid polluting the atmosphere. In regions with high farm animal densities, new farm buildings receive building permission only when biological exhaust air treatment systems (BEATS) are in place, such as biofilters. However, it is currently unknown whether BEATS can harbour pathogens such as zoonotic agents, which are potentially emitted via the purified gas. Because BEATS are located very close to the livestock building, it is assumed that BEATS-related microorganisms are aerially transported to farm animals via the inlet system of the ventilation system. To support this hypothesis, a computer simulation was applied to calculate the wind field around a facility consisting of a virtual livestock house and an adjacent biofilter. Under the chosen wind conditions (speed and direction), it can be shown that turbulences and eddies may occur in the near surrounding of a livestock building with an adjacent biofilter. Consequently, this might cause the entry of the released biofilter's purified gas into the barn, including possible microorganisms within this purified gas. If field investigations verify the results of the simulations, counter-measures must be taken to ensure biosecurity on farms with BEATS. © 2013 Society of Chemical Industry.

The Impact of Input and Output Prices on The Household Economic Behavior of Rice-Livestock Integrated Farming System (Rlifs) and Non Rlifs Farmers

NASA Astrophysics Data System (ADS)

Lindawati, L.; Kusnadi, N.; Kuntjoro, S. U.; Swastika, D. K. S.

2018-02-01

Integrated farming system is a system that emphasized linkages and synergism of farming units waste utilization. The objective of the study was to analyze the impact of input and output prices on both Rice Livestock Integrated Farming System (RLIFS) and non RLIFS farmers. The study used econometric model in the form of a simultaneous equations system consisted of 36 equations (18 behavior and 18 identity equations). The impact of changes in some variables was obtained through simulation of input and output prices on simultaneous equations. The results showed that the price increasing of the seed, SP-36, urea, medication/vitamins, manure, bran, straw had negative impact on production of the rice, cow, manure, bran, straw and household income. The decrease in the rice and cow production, production input usage, allocation of family labor, rice and cow business income was greater in RLIFS than non RLIFS farmers. The impact of rising rice and cow cattle prices in the two groups of farmers was not too much different because (1) farming waste wasn’t used effectively (2) manure and straw had small proportion of production costs. The increase of input and output price didn’t have impact on production costs and household expenditures on RLIFS.

Comparing offshore wind farm wake observed from satellite SAR and wake model results

NASA Astrophysics Data System (ADS)

Bay Hasager, Charlotte

2014-05-01

Offshore winds can be observed from satellite synthetic aperture radar (SAR). In the FP7 EERA DTOC project, the European Energy Research Alliance project on Design Tools for Offshore Wind Farm Clusters, there is focus on mid- to far-field wind farm wakes. The more wind farms are constructed nearby other wind farms, the more is the potential loss in annual energy production in all neighboring wind farms due to wind farm cluster effects. It is of course dependent upon the prevailing wind directions and wind speed levels, the distance between the wind farms, the wind turbine sizes and spacing. Some knowledge is available within wind farm arrays and in the near-field from various investigations. There are 58 offshore wind farms in the Northern European seas grid connected and in operation. Several of those are spaced near each other. There are several twin wind farms in operation including Nysted-1 and Rødsand-2 in the Baltic Sea, and Horns Rev 1 and Horns Rev 2, Egmond aan Zee and Prinses Amalia, and Thompton 1 and Thompton 2 all in the North Sea. There are ambitious plans of constructing numerous wind farms - great clusters of offshore wind farms. Current investigation of offshore wind farms includes mapping from high-resolution satellite SAR of several of the offshore wind farms in operation in the North Sea. Around 20 images with wind farm wake cases have been retrieved and processed. The data are from the Canadian RADARSAT-1/-2 satellites. These observe in microwave C-band and have been used for ocean surface wind retrieval during several years. The satellite wind maps are valid at 10 m above sea level. The wakes are identified in the raw images as darker areas downwind of the wind farms. In the SAR-based wind maps the wake deficit is found as areas of lower winds downwind of the wind farms compared to parallel undisturbed flow in the flow direction. The wind direction is clearly visible from lee effects and wind streaks in the images. The wind farm wake cases are modeled by various types of wake models. In the EERA DTOC project the model suite consists of engineering models (Ainslie, DWM, GLC, PARK, WASP/NOJ), simplified CFD models (FUGA, FarmFlow), full CFD models (CRES-flowNS, RANS), mesoscale model (SKIRON, WRF) and coupled meso-scale and microscale models. The comparison analysis between the satellite wind wake and model results will be presented and discussed. It is first time a comprehensive analysis is performed on this subject. The topic gains increasing importance because there is a growing need to precisely model also mid- and far-field wind farms wakes for development and planning of offshore wind farm clusters.

Production and feeding strategies for phosphorus management on dairy farms.

PubMed

Rotz, C A; Sharpley, A N; Satter, L D; Gburek, W J; Sanderson, M A

2002-11-01

Long-term accumulation of soil phosphorus (P) is becoming a concern on some watersheds heavily populated with animal feeding facilities, including dairy farms. Management changes in crop production and feeding may help reduce the accumulation of excess P, but farm profitability must be maintained or improved to assure adoption of such changes. Whole-farm simulation was used to evaluate the long-term effects of changes in feeding, cropping, and other production strategies on P loading and the economics of 100-cow and 800-cow dairy farms in southeastern New York. Simulated farms maintained a long-term P balance if the following occurred: 1) animals were fed to meet recommended minimum amounts of dietary P, 2) the cropping strategy and land base supplied all of the forage needed, 3) all animals were fed a high forage diet, and 4) replacement heifers were produced on the farm to utilize more forage. The most easily implemented change was to reduce the supplemental mineral P fed to that required to meet current NRC recommended amounts, and this provided an annual increase in farm profit of about $22/cow. Intensifying the use of grassland and improving grazing practices increased profit along with a small reduction in excess P. Conversion from dairy production to heifer raising or expansion from 100 cows to a 250-cow "state-of-the-art" confinement facility (with a 70% increase in land area) were also profitable options. These options provided a long-term P balance for the farm as long as the production and use of forage was maximized and minimum dietary P amounts were those recommended by the NRC. Thus, management changes can be made to prevent the long-term accumulation of soil P on dairy farms while improving farm profitability.

Modelling impacts of offshore wind farms on trophic web: the Courseulles-sur-Mer case study

NASA Astrophysics Data System (ADS)

Raoux, Aurore; Pezy, Jean-Philippe; Dauvin, Jean-Claude; Tecchio, samuele; Degraer, Steven; Wilhelmsson, Dan; Niquil, Nathalie

2016-04-01

The French government is planning the construction of three offshore wind farms in Normandy. These offshore wind farms will integrate into an ecosystem already subject to a growing number of anthropogenic disturbances such as transportation, fishing, sediment deposit, and sediment extraction. The possible effects of this cumulative stressors on ecosystem functioning are still unknown, but they could impact their resilience, making them susceptible to changes from one stable state to another. Understanding the behaviour of these marine coastal complex systems is essential in order to anticipate potential state changes, and to implement conservation actions in a sustainable manner. Currently, there are no global and integrated studies on the effects of construction and exploitation of offshore wind farms. Moreover, approaches are generally focused on the conservation of some species or groups of species. Here, we develop a holistic and integrated view of ecosystem impacts through the use of trophic webs modelling tools. Trophic models describe the interaction between biological compartments at different trophic levels and are based on the quantification of flow of energy and matter in ecosystems. They allow the application of numerical methods for the characterization of emergent properties of the ecosystem, also called Ecological Network Analysis (ENA). These indices have been proposed as ecosystem health indicators as they have been demonstrated to be sensitive to different impacts on marine ecosystems. We present here in detail the strategy for analysing the potential environmental impacts of the construction of the Courseulles-sur-Mer offshore wind farm (Bay of Seine) such as the reef effect through the use of the Ecopath with Ecosim software. Similar Ecopath simulations will be made in the future on the Le Tréport offshore wind farm site. Results will contribute to a better knowledge of the impacts of the offshore wind farms on ecosystems. They also allow to define recommendations for environmental managers and industry in terms of monitoring the effects of Marine Renewable Energy, not only locally, but also on other sites, national and European levels. Finally, this approach could contribute to a better social acceptability of Marine Renewable Energy projects allowing a holistic vision of all pressures on ecosystems. Keywords: Marine Renewable Energies, trophic model Contact author: Aurore Raoux, UNICAEN, raoux.aurore@gmail.com

Within-farm transmission dynamics of foot and mouth disease as revealed by the 2001 epidemic in Great Britain.

PubMed

Chis Ster, Irina; Dodd, Peter J; Ferguson, Neil M

2012-08-01

This paper uses statistical and mathematical models to examine the potential impact of within-farm transmission dynamics on the spread of the 2001 foot and mouth disease (FMD) outbreak in Great Britain. We partly parameterize a simple within farm transmission model using data from experimental studies of FMD pathogenesis, embed this model within an existing between-farm transmission model, and then estimate unknown parameters (such as the species-specific within-farm reproduction number) from the 2001 epidemic case data using Markov Chain Monte-Carlo (MCMC) methods. If the probability of detecting an infected premises depends on farm size and species mix then the within-farm species specific basic reproduction ratios for baseline models are estimated to be 21 (16, 25) and 14 (10, 19) for cattle and sheep, respectively. Alternatively, if detection is independent of farm size, then the corresponding estimates are 49 (41, 61) and 10 (1.4, 21). Both model variants predict that the average fraction of total farm infectiousness accumulated prior to detection of infection on an IP is about 30-50% in cattle or mixed farms. The corresponding estimate for sheep farms depended more on the detection model, being 65-80% if detection was linked to the farms' characteristics, but only 25% if not. We highlighted evidence which reinforces the role of within-farm dynamics in contributing to the long tail of the 2001 epidemic. Copyright © 2012 Elsevier B.V. All rights reserved.

Wake flow control using a dynamically controlled wind turbine

NASA Astrophysics Data System (ADS)

Castillo, Ricardo; Wang, Yeqin; Pol, Suhas; Swift, Andy; Hussain, Fazle; Westergaard, Carsten; Texas Tech University Team

2016-11-01

A wind tunnel based "Hyper Accelerated Wind Farm Kinematic-Control Simulator" (HAWKS) is being built at Texas Tech University to emulate controlled wind turbine flow physics. The HAWKS model turbine has pitch, yaw and speed control which is operated in real model time, similar to that of an equivalent full scale turbine. Also, similar to that of a full scale wind turbine, the controls are developed in a Matlab Simulink environment. The current diagnostic system consists of power, rotor position, rotor speed measurements and PIV wake characterization with four cameras. The setup allows up to 7D downstream of the rotor to be mapped. The purpose of HAWKS is to simulate control strategies at turnaround times much faster than CFD and full scale testing. The fundamental building blocks of the simulator have been tested, and demonstrate wake steering for both static and dynamic turbine actuation. Parameters which have been studied are yaw, rotor speed and combinations hereof. The measured wake deflections for static yaw cases are in agreement with previously reported research implying general applicability of the HAWKS platform for the purpose of manipulating the wake. In this presentation the general results will be introduced followed by an analysis of the wake turbulence and coherent structures when comparing static and dynamic flow cases. The outcome of such studies could ultimately support effective wind farm wake flow control strategies. Texas Emerging Technology Fund (ETF).

Integrating gene flow, crop biology, and farm management in on-farm conservation of avocado (Persea americana, Lauraceae).

PubMed

Birnbaum, Kenneth; Desalle, Rob; Peters, Charles M; Benfey, Philip N

2003-11-01

Maintaining crop diversity on farms where cultivars can evolve is a conservation goal, but few tools are available to assess the long-term maintenance of genetic diversity on farms. One important issue for on-farm conservation is gene flow from crops with a narrow genetic base into related populations that are genetically diverse. In a case study of avocado (Persea americana var. americana) in one of its centers of diversity (San Jerónimo, Costa Rica), we used 10 DNA microsatellite markers in a parentage analysis to estimate gene flow from commercialized varieties into a traditional crop population. Five commercialized genotypes comprised nearly 40% of orchard trees, but they contributed only about 14.5% of the gametes to the youngest cohort of trees. Although commercialized varieties and the diverse population were often planted on the same farm, planting patterns appeared to keep the two types of trees separated on small scales, possibly explaining the limited gene flow. In a simulation that combined gene flow estimates, crop biology, and graft tree management, loss of allelic diversity was less than 10% over 150 yr, and selection was effective in retaining desirable alleles in the diverse subpopulation. Simulations also showed that, in addition to gene flow, managing the genetic makeup and life history traits of the invasive commercialized varieties could have a significant impact on genetic diversity in the target population. The results support the feasibility of on-farm crop conservation, but simulations also showed that higher levels of gene flow could lead to severe losses of genetic diversity even if farmers continue to plant diverse varieties.

Simulation of wind turbine wakes using the actuator line technique.

PubMed

Sørensen, Jens N; Mikkelsen, Robert F; Henningson, Dan S; Ivanell, Stefan; Sarmast, Sasan; Andersen, Søren J

2015-02-28

The actuator line technique was introduced as a numerical tool to be employed in combination with large eddy simulations to enable the study of wakes and wake interaction in wind farms. The technique is today largely used for studying basic features of wakes as well as for making performance predictions of wind farms. In this paper, we give a short introduction to the wake problem and the actuator line methodology and present a study in which the technique is employed to determine the near-wake properties of wind turbines. The presented results include a comparison of experimental results of the wake characteristics of the flow around a three-bladed model wind turbine, the development of a simple analytical formula for determining the near-wake length behind a wind turbine and a detailed investigation of wake structures based on proper orthogonal decomposition analysis of numerically generated snapshots of the wake. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Large-eddy simulation of wind turbine wake interactions on locally refined Cartesian grids

NASA Astrophysics Data System (ADS)

Angelidis, Dionysios; Sotiropoulos, Fotis

2014-11-01

Performing high-fidelity numerical simulations of turbulent flow in wind farms remains a challenging issue mainly because of the large computational resources required to accurately simulate the turbine wakes and turbine/turbine interactions. The discretization of the governing equations on structured grids for mesoscale calculations may not be the most efficient approach for resolving the large disparity of spatial scales. A 3D Cartesian grid refinement method enabling the efficient coupling of the Actuator Line Model (ALM) with locally refined unstructured Cartesian grids adapted to accurately resolve tip vortices and multi-turbine interactions, is presented. Second order schemes are employed for the discretization of the incompressible Navier-Stokes equations in a hybrid staggered/non-staggered formulation coupled with a fractional step method that ensures the satisfaction of local mass conservation to machine zero. The current approach enables multi-resolution LES of turbulent flow in multi-turbine wind farms. The numerical simulations are in good agreement with experimental measurements and are able to resolve the rich dynamics of turbine wakes on grids containing only a small fraction of the grid nodes that would be required in simulations without local mesh refinement. This material is based upon work supported by the Department of Energy under Award Number DE-EE0005482 and the National Science Foundation under Award number NSF PFI:BIC 1318201.

The profitability of automatic milking on Dutch dairy farms.

PubMed

Bijl, R; Kooistra, S R; Hogeveen, H

2007-01-01

Several studies have reported on the profitability of automatic milking based on different simulation models, but a data-based study using actual farm data has been lacking. The objective of this study was to analyze the profitability of dairy farms having an automatic milking system (AMS) compared with farms using a conventional milking system (CMS) based on real accounting data. In total, 62 farms (31 using an AMS and 31 using a CMS) were analyzed for the year 2003 in a case control study. Differences between the years 2002 and 2003 also were analyzed by comparing a subgroup of 16 farms with an AMS and 16 farms with a CMS. Matching was based on the time of investment in a milking system (same year), the total milk production per year, and intensity of land use (kg/ha). Results from 2003 showed that the farms with an AMS used, on average, 29% less labor than farms with a CMS. In contrast, farms using a CMS grew faster (37,132 kg of milk quota and 5 dairy cows) than farms with an AMS (-3,756 kg milk quota and 0.5 dairy cows) between 2002 and 2003. Dairy farmers with a CMS had larger (euro7,899) revenues than those with an AMS. However, no difference in the margin on dairy production was detected, partly because of numerically greater (euro6,822) variable costs on CMS farms. Dairy farms were compared financially based on the amount of money that was available for rent, depreciation, interest, labor, and profit (RDILP). The CMS farms had more money (euro15,566) available for RDILP than the AMS farms. This difference was caused by larger fixed costs (excluding labor) for the AMS farms, larger contractor costs (euro6,422), and larger costs for gas, water, and electricity (euro1,549). Differences in costs for contractors and for gas, water, and electricity were statistically significant. When expressed per full-time employee, AMS farms had greater revenues, margins, and gross margins per full-time employee than did CMS farms. This resulted in a substantially greater (but not statistically significant) RDILP per full-time employee (euro12,953) for AMS farms compared with CMS farms. Depreciation and interest costs for automatic milking were not available but were calculated based on several assumptions. Assuming larger purchase costs and a shorter depreciation time for AMS than for CMS, costs for depreciation and interest were larger for AMS farms than for CMS farms. Larger fixed costs should be compensated for by the amount of labor that has become available after introducing the milking robot. Therefore, farm managers should decide whether the extra time acquired by automatic milking balances against the extra costs associated with an AMS.

Disease prevention versus data privacy: using landcover maps to inform spatial epidemic models.

PubMed

Tildesley, Michael J; Ryan, Sadie J

2012-01-01

The availability of epidemiological data in the early stages of an outbreak of an infectious disease is vital for modelers to make accurate predictions regarding the likely spread of disease and preferred intervention strategies. However, in some countries, the necessary demographic data are only available at an aggregate scale. We investigated the ability of models of livestock infectious diseases to predict epidemic spread and obtain optimal control policies in the event of imperfect, aggregated data. Taking a geographic information approach, we used land cover data to predict UK farm locations and investigated the influence of using these synthetic location data sets upon epidemiological predictions in the event of an outbreak of foot-and-mouth disease. When broadly classified land cover data were used to create synthetic farm locations, model predictions deviated significantly from those simulated on true data. However, when more resolved subclass land use data were used, moderate to highly accurate predictions of epidemic size, duration and optimal vaccination and ring culling strategies were obtained. This suggests that a geographic information approach may be useful where individual farm-level data are not available, to allow predictive analyses to be carried out regarding the likely spread of disease. This method can also be used for contingency planning in collaboration with policy makers to determine preferred control strategies in the event of a future outbreak of infectious disease in livestock.

Disease Prevention versus Data Privacy: Using Landcover Maps to Inform Spatial Epidemic Models

PubMed Central

Tildesley, Michael J.; Ryan, Sadie J.

2012-01-01

The availability of epidemiological data in the early stages of an outbreak of an infectious disease is vital for modelers to make accurate predictions regarding the likely spread of disease and preferred intervention strategies. However, in some countries, the necessary demographic data are only available at an aggregate scale. We investigated the ability of models of livestock infectious diseases to predict epidemic spread and obtain optimal control policies in the event of imperfect, aggregated data. Taking a geographic information approach, we used land cover data to predict UK farm locations and investigated the influence of using these synthetic location data sets upon epidemiological predictions in the event of an outbreak of foot-and-mouth disease. When broadly classified land cover data were used to create synthetic farm locations, model predictions deviated significantly from those simulated on true data. However, when more resolved subclass land use data were used, moderate to highly accurate predictions of epidemic size, duration and optimal vaccination and ring culling strategies were obtained. This suggests that a geographic information approach may be useful where individual farm-level data are not available, to allow predictive analyses to be carried out regarding the likely spread of disease. This method can also be used for contingency planning in collaboration with policy makers to determine preferred control strategies in the event of a future outbreak of infectious disease in livestock. PMID:23133352

Using Reconstructed POD Modes as Turbulent Inflow for LES Wind Turbine Simulations

NASA Astrophysics Data System (ADS)

Nielson, Jordan; Bhaganagar, Kiran; Juttijudata, Vejapong; Sirisup, Sirod

2016-11-01

Currently, in order to get realistic atmospheric effects of turbulence, wind turbine LES simulations require computationally expensive precursor simulations. At times, the precursor simulation is more computationally expensive than the wind turbine simulation. The precursor simulations are important because they capture turbulence in the atmosphere and as stated above, turbulence impacts the power production estimation. On the other hand, POD analysis has been shown to be capable of capturing turbulent structures. The current study was performed to determine the plausibility of using lower dimension models from POD analysis of LES simulations as turbulent inflow to wind turbine LES simulations. The study will aid the wind energy community by lowering the computational cost of full scale wind turbine LES simulations, while maintaining a high level of turbulent information and being able to quickly apply the turbulent inflow to multi turbine wind farms. This will be done by comparing a pure LES precursor wind turbine simulation with simulations that use reduced POD mod inflow conditions. The study shows the feasibility of using lower dimension models as turbulent inflow of LES wind turbine simulations. Overall the power production estimation and velocity field of the wind turbine wake are well captured with small errors.

Towards practical application of sensors for monitoring animal health; design and validation of a model to detect ketosis.

PubMed

Steensels, Machteld; Maltz, Ephraim; Bahr, Claudia; Berckmans, Daniel; Antler, Aharon; Halachmi, Ilan

2017-05-01

The objective of this study was to design and validate a mathematical model to detect post-calving ketosis. The validation was conducted in four commercial dairy farms in Israel, on a total of 706 multiparous Holstein dairy cows: 203 cows clinically diagnosed with ketosis and 503 healthy cows. A logistic binary regression model was developed, where the dependent variable is categorical (healthy/diseased) and a set of explanatory variables were measured with existing commercial sensors: rumination duration, activity and milk yield of each individual cow. In a first validation step (within-farm), the model was calibrated on the database of each farm separately. Two thirds of the sick cows and an equal number of healthy cows were randomly selected for model validation. The remaining one third of the cows, which did not participate in the model validation, were used for model calibration. In order to overcome the random selection effect, this procedure was repeated 100 times. In a second (between-farms) validation step, the model was calibrated on one farm and validated on another farm. Within-farm accuracy, ranging from 74 to 79%, was higher than between-farm accuracy, ranging from 49 to 72%, in all farms. The within-farm sensitivities ranged from 78 to 90%, and specificities ranged from 71 to 74%. The between-farms sensitivities ranged from 65 to 95%. The developed model can be improved in future research, by employing other variables that can be added; or by exploring other models to achieve greater sensitivity and specificity.

Impacts of vegetation change on groundwater recharge

NASA Astrophysics Data System (ADS)

Bond, W. J.; Verburg, K.; Smith, C. J.

2003-12-01

Vegetation change is the accepted cause of increasing river salt concentrations and the salinisation of millions of hectares of farm land in Australia. Replacement of perennial native vegetation by annual crops and pastures following European settlement has altered the water balance causing increased groundwater recharge and mobilising the naturally saline groundwater. The Redesigning Agriculture for Australian Landscapes Program, of which the work described here is a part, was established to develop agricultural practices that are more attuned to the delicate water balance described above. Results of field measurements will be presented that contrast the water balance characteristics of native vegetation with those of conventional agricultural plants, and indicate the functional characteristics required of new agricultural practices to reduce recharge. New agricultural practices may comprise different management of current crops and pastures, or may involve introducing totally new species. In either case, long-term testing is required to examine their impact on recharge over a long enough climate record to encompass the natural variability of rainfall that is characteristic of most Australian farming regions. Field experimentation therefore needs to be complemented and extended by computer simulation. This requires a modelling approach that is more robust than conventional crop modelling because (a) it needs to be sensitive enough to predict small changes in the residual recharge term, (b) it needs to be able to simulate a variety of vegetation in different sequences, (c) it needs to be able to simulate continuously for several decades of input data, and (d) it therefore needs to be able to simulate the period between crops, which often has a critical impact on recharge. The APSIM simulation framework will be used to illustrate these issues and to explore the effect of different vegetation combinations on recharge.

Usability of NASA Satellite Imagery-Based Daily Solar Radiation for Crop Yield Simulation and Management Decisions

NASA Astrophysics Data System (ADS)

Yang, H.; Cassman, K. G.; Stackhouse, P. W.; Hoell, J. M.

2007-12-01

We tested the usability of NASA satellite imagery-based daily solar radiation for farm-specific crop yield simulation and management decisions using the Hybrid-Maize model (www.hybridmaize.unl.edu). Solar radiation is one of the key inputs for crop yield simulation. Farm-specific crop management decisions using simulation models require long-term (i.e., 20 years or longer) daily local weather data including solar radiation for assessing crop yield potential and its variation, optimizing crop planting date, and predicting crop yield in a real time mode. Weather stations that record daily solar radiation have sparse coverage and many of them have record shorter than 15 years. Based on satellite imagery and other remote sensed information, NASA has provided estimates of daily climatic data including solar radiation at a resolution of 1 degree grid over the earth surface from 1983 to 2005. NASA is currently continuing to update the database and has plans to provide near real-time data in the future. This database, which is free to the public at http://power.larc.nasa.gov, is a potential surrogate for ground- measured climatic data for farm-specific crop yield simulation and management decisions. In this report, we quantified (1) the similarities between NASA daily solar radiation and ground-measured data atr 20 US sites and four international sites, and (2) the accuracy and precision of simulated corn yield potential and its variability using NASA solar radiation coupled with other weather data from ground measurements. The 20 US sites are in the western Corn Belt, including Iowa, South Dakota, Nebraska, and Kansas. The four international sites are Los Banos in the Philippines, Beijing in China, Cali in Columbia, and Ibatan in Nigeria. Those sites were selected because of their high quality weather record and long duration (more than 20 years on average). We found that NASA solar radiation was highly significantly correlated (mean r2 =0.88**) with the ground measurements at the 20 US sites, while the correlation was poor (mean r2=0.55**, though significant) at the four international sites. At the 20 US sites, the mean root mean square error (RMSE) between NASA solar radiation and the ground data was 2.7 MJ/m2/d, or 19% of the mean daily ground data. At the four international sites, the mean RMSE was 4.0 MJ/m2/d, or 25% of the mean daily ground value. Large differences between NASA solar radiation and the ground data were likely associated with tropical environment or significant variation in elevation within a short distance. When using NASA solar radiation coupled with other weather data from ground measurements, the simulated corn yields were highly significantly correlated (mean r2=0.85**) with those using complete ground weather data at the 20 US sites, while the correlation (mean r2=0.48**) was poor at the four international sites. The mean RMSE between the simulated corn yields of the two batches was 0.50 Mg/ha, or 3% of the mean absolute value using the ground data. At the four international sites, the RMSE of the simulated yields was 1.5 Mg/ha, or 13% of the mean absolute value using the ground data. We conclude that the NASA satellite imagery-based daily solar radiation is a reasonably reliable surrogate for the ground observations for farm-specific crop yield simulation and management decisions, especially at locations where ground-measured solar radiation is unavailable.

Electromagnetic Simulation of the Near-Field Distribution around a Wind Farm

DOE PAGES

Yang, Shang-Te; Ling, Hao

2013-01-01

An efficienmore » t approach to compute the near-field distribution around and within a wind farm under plane wave excitation is proposed. To make the problem computationally tractable, several simplifying assumptions are made based on the geometry problem. By comparing the approximations against full-wave simulations at 500 MHz, it is shown that the assumptions do not introduce significant errors into the resulting near-field distribution. The near fields around a 3 × 3 wind farm are computed using the developed methodology at 150 MHz, 500 MHz, and 3 GHz. Both the multipath interference patterns and the forward shadows are predicted by the proposed method.« less

Quantifying array losses due to spacing and staggering in offshore wind farms (Invited)

NASA Astrophysics Data System (ADS)

Archer, C. L.; Mirzaeisefat, S.; Lee, S.; Xie, S.

2013-12-01

The layout of wind turbines can have an impact on the power production of a wind farm. Design variables that define the layout of wind turbines within a wind farm include: orientation of the rows with respect to the prevailing wind direction, size and shape of the wind farm, spacing between turbines, and alignment of the turbines (i.e., whether in-line or staggered with one another). There are no universal layout recommendations for offshore wind farms, partly because isolating the contribution of each individual design variable is impossible at existing offshore wind farms, where multiple effects overlap non-linearly on one another, and partly because analyzing the sensitivity to design variables requires sophisticated and computer-intensive numerical codes, such as large-eddy simulations (LES), that can simulate the small-scale turbulent features of turbine wakes. The National Renewable Energy Laboratory (NREL) developed the only publicly available and open-source LES code that is capable of resolving wind turbine blades as rotating actuator lines (not fixed disks), includes both neutral and unstable atmospheric conditions (stable case is currently under development), and does not rely on periodic boundary conditions. This code, named Simulator for Offshore/Onshore Wind Farm Applications (SOWFA), is based on OpenFOAM and has been used successfully in the past for turbulent wake simulations. Here we address the issue of quantifying two design variables: turbine spacing (both along and across the prevailing wind direction) and alignment (in-line or staggered for consecutive rows). SOWFA is used to simulate an existing offshore wind farm in Lillgrund (Sweden), consisting of 48 Siemens 2.3 MW turbines with spacing of 3.2D across and 4.3D along the prevailing wind direction and without staggering, where D is the turbine diameter (93 m). This spacing is exceptionally tight, to our knowledge the tightest of all modern wind farms. While keeping the area and the shape of the farm constant, we design several new Lillgrund farm layouts with and without staggering, with increased spacing in each direction individually and in both directions together, and with various wind directions and atmospheric stabilities. We found that the average wind power generated per turbine is increased by ~32% (from 696 kW to 922 kW) if both staggering and doubling of the across-spacing are implemented simultaneously in a neutral stability case. Wake losses are quantified in terms of average power in the first (upwind) row of wind turbines in the control case, representative of the power that could be generated if there were no wakes, over the average power of all the wind turbines in the farm. Wake losses at Lillgrund are relatively high due to the tight packing, of the order of 35%, but smart combinations of staggering and doubling of turbine spacing can reduce them to 15%-26%. In summary, we provide estimates of the losses/gains associated with individual and combined changes in two design variables, spacing and staggering, under various atmospheric stabilities, wind directions, and wind speeds. These estimates will be useful to the wind industry to optimize a wind project because the effects of alternative layouts can be quantified quickly with respect to total power, capacity factor, and number of wind turbines, all of which can ultimately be converted to actual costs or savings.

Quantifying array losses due to spacing and staggering in offshore wind farms (Invited)

NASA Astrophysics Data System (ADS)

Archer, C. L.; Mirzaeisefat, S.; Lee, S.; Xie, S.

2011-12-01

The layout of wind turbines can have an impact on the power production of a wind farm. Design variables that define the layout of wind turbines within a wind farm include: orientation of the rows with respect to the prevailing wind direction, size and shape of the wind farm, spacing between turbines, and alignment of the turbines (i.e., whether in-line or staggered with one another). There are no universal layout recommendations for offshore wind farms, partly because isolating the contribution of each individual design variable is impossible at existing offshore wind farms, where multiple effects overlap non-linearly on one another, and partly because analyzing the sensitivity to design variables requires sophisticated and computer-intensive numerical codes, such as large-eddy simulations (LES), that can simulate the small-scale turbulent features of turbine wakes. The National Renewable Energy Laboratory (NREL) developed the only publicly available and open-source LES code that is capable of resolving wind turbine blades as rotating actuator lines (not fixed disks), includes both neutral and unstable atmospheric conditions (stable case is currently under development), and does not rely on periodic boundary conditions. This code, named Simulator for Offshore/Onshore Wind Farm Applications (SOWFA), is based on OpenFOAM and has been used successfully in the past for turbulent wake simulations. Here we address the issue of quantifying two design variables: turbine spacing (both along and across the prevailing wind direction) and alignment (in-line or staggered for consecutive rows). SOWFA is used to simulate an existing offshore wind farm in Lillgrund (Sweden), consisting of 48 Siemens 2.3 MW turbines with spacing of 3.2D across and 4.3D along the prevailing wind direction and without staggering, where D is the turbine diameter (93 m). This spacing is exceptionally tight, to our knowledge the tightest of all modern wind farms. While keeping the area and the shape of the farm constant, we design several new Lillgrund farm layouts with and without staggering, with increased spacing in each direction individually and in both directions together, and with various wind directions and atmospheric stabilities. We found that the average wind power generated per turbine is increased by ~32% (from 696 kW to 922 kW) if both staggering and doubling of the across-spacing are implemented simultaneously in a neutral stability case. Wake losses are quantified in terms of average power in the first (upwind) row of wind turbines in the control case, representative of the power that could be generated if there were no wakes, over the average power of all the wind turbines in the farm. Wake losses at Lillgrund are relatively high due to the tight packing, of the order of 35%, but smart combinations of staggering and doubling of turbine spacing can reduce them to 15%-26%. In summary, we provide estimates of the losses/gains associated with individual and combined changes in two design variables, spacing and staggering, under various atmospheric stabilities, wind directions, and wind speeds. These estimates will be useful to the wind industry to optimize a wind project because the effects of alternative layouts can be quantified quickly with respect to total power, capacity factor, and number of wind turbines, all of which can ultimately be converted to actual costs or savings.

Prediction of far-field wind turbine noise propagation with parabolic equation.

PubMed

Lee, Seongkyu; Lee, Dongjai; Honhoff, Saskia

2016-08-01

Sound propagation of wind farms is typically simulated by the use of engineering tools that are neglecting some atmospheric conditions and terrain effects. Wind and temperature profiles, however, can affect the propagation of sound and thus the perceived sound in the far field. A better understanding and application of those effects would allow a more optimized farm operation towards meeting noise regulations and optimizing energy yield. This paper presents the parabolic equation (PE) model development for accurate wind turbine noise propagation. The model is validated against analytic solutions for a uniform sound speed profile, benchmark problems for nonuniform sound speed profiles, and field sound test data for real environmental acoustics. It is shown that PE provides good agreement with the measured data, except upwind propagation cases in which turbulence scattering is important. Finally, the PE model uses computational fluid dynamics results as input to accurately predict sound propagation for complex flows such as wake flows. It is demonstrated that wake flows significantly modify the sound propagation characteristics.

Modeling of In-stream Tidal Energy Development and its Potential Effects in Tacoma Narrows, Washington, USA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Zhaoqing; Wang, Taiping; Copping, Andrea E.

Understanding and providing proactive information on the potential for tidal energy projects to cause changes to the physical system and to key water quality constituents in tidal waters is a necessary and cost-effective means to avoid costly regulatory involvement and late stage surprises in the permitting process. This paper presents a modeling study for evaluating the tidal energy extraction and its potential impacts on the marine environment in a real world site - Tacoma Narrows of Puget Sound, Washington State, USA. An unstructured-grid coastal ocean model, fitted with a module that simulates tidal energy devices, was applied to simulate themore » tidal energy extracted by different turbine array configurations and the potential effects of the extraction at local and system-wide scales in Tacoma Narrows and South Puget Sound. Model results demonstrated the advantage of an unstructured-grid model for simulating the far-field effects of tidal energy extraction in a large model domain, as well as assessing the near-field effect using a fine grid resolution near the tidal turbines. The outcome shows that a realistic near-term deployment scenario extracts a very small fraction of the total tidal energy in the system and that system wide environmental effects are not likely; however, near-field effects on the flow field and bed shear stress in the area of tidal turbine farm are more likely. Model results also indicate that from a practical standpoint, hydrodynamic or water quality effects are not likely to be the limiting factor for development of large commercial-scale tidal farms. Results indicate that very high numbers of turbines are required to significantly alter the tidal system; limitations on marine space or other environmental concerns are likely to be reached before reaching these deployment levels. These findings show that important information obtained from numerical modeling can be used to inform regulatory and policy processes for tidal energy development.« less

Managing aquatic parasites for reduced drug resistance: lessons from the land.

PubMed

McEwan, Gregor F; Groner, Maya L; Burnett, Danielle L; Fast, Mark D; Revie, Crawford W

2016-12-01

Atlantic salmon farming is one of the largest aquaculture industries in the world. A major problem in salmon farms is the sea louse ectoparasite Lepeophtheirus salmonis, which can cause stress, secondary infection and sometimes mortality in the salmon host. Sea lice have substantial impacts on farm economics and potentially nearby wild salmonid populations. The most common method of controlling sea louse infestations is application of chemicals. However, most farming regions worldwide have observed resistance to the small set of treatment chemicals that are available. Despite this, there has been little investigation of treatment strategies for managing resistance in aquaculture. In this article, we compare four archetypical treatment strategies inspired by agriculture, where the topic has a rich history of study, and add a fifth strategy common in aquaculture. We use an agent-based model (ABM) to simulate these strategies and their varying applications of chemicals over time and space. We analyse the ABM output to compare how the strategies perform in controlling louse abundance, number of treatments required and levels of resistance in the sea louse population. Our results indicated that among the approaches considered applying chemicals in combination was the most effective over the long term. © 2016 The Author(s).

Lewis Research Center studies of multiple large wind turbine generators on a utility network

NASA Technical Reports Server (NTRS)

Gilbert, L. J.; Triezenberg, D. M.

1979-01-01

A NASA-Lewis program to study the anticipated performance of a wind turbine generator farm on an electric utility network is surveyed. The paper describes the approach of the Lewis Wind Energy Project Office to developing analysis capabilities in the area of wind turbine generator-utility network computer simulations. Attention is given to areas such as, the Lewis Purdue hybrid simulation, an independent stability study, DOE multiunit plant study, and the WEST simulator. Also covered are the Lewis mod-2 simulation including analog simulation of a two wind turbine system and comparison with Boeing simulation results, and gust response of a two machine model. Finally future work to be done is noted and it is concluded that the study shows little interaction between the generators and between the generators and the bus.

Exploring agent-level calculations of risk and returns in relation to observed land-use changes in the US Great Plains, 1870–1940

PubMed Central

Sylvester, Kenneth M.; Brown, Daniel G.; Leonard, Susan H.; Merchant, Emily; Hutchins, Meghan

2015-01-01

Land-use change in the U.S. Great Plains since agricultural settlement in the second half of the nineteenth century has been well documented. While aggregate historical trends are easily tracked, the decision-making of individual farmers is difficult to reconstruct. We use an agent-based model to tell the history of the settlement of the West by simulating farm-level agricultural decision making based on historical data about prices, yields, farming costs, and environmental conditions. The empirical setting for the model is the period between 1875 and 1940 in two townships in Kansas, one in the shortgrass region and the other in the mixed grass region. Annual historical data on yields and prices determine profitability of various land uses and thereby inform decision-making, in conjunction with the farmer’s previous experience and randomly assigned levels of risk aversion. Results illustrating the level of agreement between model output and unique and detailed household-level records of historical land use and farm size suggest that economic behavior and natural endowments account for land change processes to some degree, but are incomplete. Discrepancies are examined to identify missing processes through model experiments, in which we adjust input and output prices, crop yields, agent memory, and risk aversion. These analyses demonstrate how agent-based modeling can be a useful laboratory for thinking about social and economic behavior in the past. PMID:25729323

A mechanistic model for spread of livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) within a pig herd

PubMed Central

Toft, Nils; Boklund, Anette; Espinosa-Gongora, Carmen; Græsbøll, Kaare; Larsen, Jesper; Halasa, Tariq

2017-01-01

Before an efficient control strategy for livestock-associated methicillin resistant Staphylococcus aureus (LA-MRSA) in pigs can be decided upon, it is necessary to obtain a better understanding of how LA-MRSA spreads and persists within a pig herd, once it is introduced. We here present a mechanistic stochastic discrete-event simulation model for spread of LA-MRSA within a farrow-to-finish sow herd to aid in this. The model was individual-based and included three different disease compartments: susceptible, intermittent or persistent shedder of MRSA. The model was used for studying transmission dynamics and within-farm prevalence after different introductions of LA-MRSA into a farm. The spread of LA-MRSA throughout the farm mainly followed the movement of pigs. After spread of LA-MRSA had reached equilibrium, the prevalence of LA-MRSA shedders was predicted to be highest in the farrowing unit, independent of how LA-MRSA was introduced. LA-MRSA took longer to spread to the whole herd if introduced in the finisher stable, rather than by gilts in the mating stable. The more LA-MRSA positive animals introduced, the shorter time before the prevalence in the herd stabilised. Introduction of a low number of intermittently shedding pigs was predicted to frequently result in LA-MRSA fading out. The model is a potential decision support tool for assessments of short and long term consequences of proposed intervention strategies or surveillance options for LA-MRSA within pig herds. PMID:29182655

Impacts of past and future climate change on wind energy resources in the United States

NASA Astrophysics Data System (ADS)

McCaa, J. R.; Wood, A.; Eichelberger, S.; Westrick, K.

2009-12-01

The links between climate change and trends in wind energy resources have important potential implications for the wind energy industry, and have received significant attention in recent studies. We have conducted two studies that provide insights into the potential for climate change to affect future wind power production. In one experiment, we projected changes in power capacity for a hypothetical wind farm located near Kennewick, Washington, due to greenhouse gas-induced climate change, estimated using a set of regional climate model simulations. Our results show that the annual wind farm power capacity is projected to decrease 1.3% by 2050. In a wider study focusing on wind speed instead of power, we analyzed projected changes in wind speed from 14 different climate simulations that were performed in support of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). Our results show that the predicted ensemble mean changes in annual mean wind speeds are expected to be modest. However, seasonal changes and changes predicted by individual models are large enough to affect the profitability of existing and future wind projects. The majority of the model simulations reveal that near-surface wind speed values are expected to shift poleward in response to the IPCC A2 emission scenario, particularly during the winter season. In the United States, most models agree that the mean annual wind speed values will increase in a region extending from the Great Lakes southward across the Midwest and into Texas. Decreased values, though, are predicted across most of the western United States. However, these predicted changes have a strong seasonal dependence, with wind speed increases over most of the United States during the winter and decreases over the northern United States during the summer.

Estimating the economic impact of subclinical ketosis in dairy cattle using a dynamic stochastic simulation model.

PubMed

Mostert, P F; Bokkers, E A M; van Middelaar, C E; Hogeveen, H; de Boer, I J M

2018-01-01

The objective of this study was to estimate the economic impact of subclinical ketosis (SCK) in dairy cows. This metabolic disorder occurs in the period around calving and is associated with an increased risk of other diseases. Therefore, SCK affects farm productivity and profitability. Estimating the economic impact of SCK may make farmers more aware of this problem, and can improve their decision-making regarding interventions to reduce SCK. We developed a dynamic stochastic simulation model that enables estimating the economic impact of SCK and related diseases (i.e. mastitis, metritis, displaced abomasum, lameness and clinical ketosis) occurring during the first 30 days after calving. This model, which was applied to a typical Dutch dairy herd, groups cows according to their parity (1 to 5+), and simulates the dynamics of SCK and related diseases, and milk production per cow during one lactation. The economic impact of SCK and related diseases resulted from a reduced milk production, discarded milk, treatment costs, costs from a prolonged calving interval and removal (culling or dying) of cows. The total costs of SCK were €130 per case per year, with a range between €39 and €348 (5 to 95 percentiles). The total costs of SCK per case per year, moreover, increased from €83 per year in parity 1 to €175 in parity 3. Most cows with SCK, however, had SCK only (61%), and costs were €58 per case per year. Total costs of SCK per case per year resulted for 36% from a prolonged calving interval, 24% from reduced milk production, 19% from treatment, 14% from discarded milk and 6% from removal. Results of the sensitivity analysis showed that the disease incidence, removal risk, relations of SCK with other diseases and prices of milk resulted in a high variation of costs of SCK. The costs of SCK, therefore, might differ per farm because of farm-specific circumstances. Improving data collection on the incidence of SCK and related diseases, and on consequences of diseases can further improve economic estimations.

The greenhouse gas balance of European grasslands.

PubMed

Chang, Jinfeng; Ciais, Philippe; Viovy, Nicolas; Vuichard, Nicolas; Sultan, Benjamin; Soussana, Jean-François

2015-10-01

The greenhouse gas (GHG) balance of European grasslands (EU-28 plus Norway and Switzerland), including CO2 , CH4 and N2 O, is estimated using the new process-based biogeochemical model ORCHIDEE-GM over the period 1961-2010. The model includes the following: (1) a mechanistic representation of the spatial distribution of management practice; (2) management intensity, going from intensively to extensively managed; (3) gridded simulation of the carbon balance at ecosystem and farm scale; and (4) gridded simulation of N2 O and CH4 emissions by fertilized grassland soils and livestock. The external drivers of the model are changing animal numbers, nitrogen fertilization and deposition, land-use change, and variable CO2 and climate. The carbon balance of European grassland (NBP) is estimated to be a net sink of 15 ± 7 g C m(-2 ) year(-1) during 1961-2010, equivalent to a 50-year continental cumulative soil carbon sequestration of 1.0 ± 0.4 Pg C. At the farm scale, which includes both ecosystem CO2 fluxes and CO2 emissions from the digestion of harvested forage, the net C balance is roughly halved, down to a small sink, or nearly neutral flux of 8 g C m(-2 ) year(-1) . Adding CH4 and N2 O emissions to net ecosystem exchange to define the ecosystem-scale GHG balance, we found that grasslands remain a net GHG sink of 19 ± 10 g C-CO2 equiv. m(-2 ) year(-1) , because the CO2 sink offsets N2 O and grazing animal CH4 emissions. However, when considering the farm scale, the GHG balance (NGB) becomes a net GHG source of -50 g C-CO2 equiv. m(-2 ) year(-1) . ORCHIDEE-GM simulated an increase in European grassland NBP during the last five decades. This enhanced NBP reflects the combination of a positive trend of net primary production due to CO2 , climate and nitrogen fertilization and the diminishing requirement for grass forage due to the Europe-wide reduction in livestock numbers. © 2015 John Wiley & Sons Ltd.

Array Effects in Large Wind Farms. Cooperative Research and Development Final Report, CRADA Number CRD-09-343

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moriarty, Patrick

2016-02-23

The effects of wind turbine wakes within operating wind farms have a substantial impact on the overall energy production from the farm. The current generation of models drastically underpredicts the impact of these wakes leading to non-conservative estimates of energy capture and financial losses to wind farm operators and developers. To improve these models, detailed research of operating wind farms is necessary. Rebecca Barthelmie of Indiana University is a world leader of wind farm wakes effects and would like to partner with NREL to help improve wind farm modeling by gathering additional wind farm data, develop better models and increasemore » collaboration with European researchers working in the same area. This is currently an active area of research at NREL and the capabilities of both parties should mesh nicely.« less

A simulation-based approach for evaluating and comparing the environmental footprints of beef production systems.

PubMed

Rotz, C A; Isenberg, B J; Stackhouse-Lawson, K R; Pollak, E J

2013-11-01

A methodology was developed and used to determine environmental footprints of beef cattle produced at the U.S. Meat Animal Research Center (MARC) in Clay Center, NE, with the goal of quantifying improvements achieved over the past 40 yr. Information for MARC operations was gathered and used to establish parameters representing their production system with the Integrated Farm System Model. The MARC farm, cow-calf, and feedlot operations were each simulated over recent historical weather to evaluate performance, environmental impact, and economics. The current farm operation included 841 ha of alfalfa and 1,160 ha of corn to produce feed predominately for the beef herd of 5,500 cows, 1,180 replacement cattle, and 3,724 cattle finished per year. Spring and fall cow-calf herds were fed on 9,713 ha of pastureland supplemented through the winter with hay and silage produced by the farm operation. Feedlot cattle were backgrounded for 3 mo on hay and silage with some grain and finished over 7 mo on a diet high in corn and wet distillers grain. For weather year 2011, simulated feed production and use, energy use, and production costs were within 1% of actual records. A 25-yr simulation of their current production system gave an average annual carbon footprint of 10.9±0.6 kg of CO2 equivalent units per kg BW sold, and the energy required to produce that beef (energy footprint) was 26.5±4.5 MJ/kg BW. The annual water required (water footprint) was 21,300±5,600 L/kg BW sold, and the water footprint excluding precipitation was 2,790±910 L/kg BW. The simulated annual cost of producing their beef was US$2.11±0.05/kg BW. Simulation of the production practices of 2005 indicated that the inclusion of distillers grain in animal diets has had a relatively small effect on environmental footprints except that reactive nitrogen loss has increased 10%. Compared to 1970, the carbon footprint of the beef produced has decreased 6% with no change in the energy footprint, a 3% reduction in the reactive nitrogen footprint, and a 6% reduction in the real cost of production. The water footprint, excluding precipitation, has increased 42% due to greater use of irrigated corn production. This proven methodology provides a means for developing the production data needed to support regional and national full life cycle assessments of the sustainability of beef.

Farms, Families, and Markets: New Evidence on Completeness of Markets in Agricultural Settings

PubMed Central

LaFave, Daniel; Thomas, Duncan

2016-01-01

The farm household model has played a central role in improving the understanding of small-scale agricultural households and non-farm enterprises. Under the assumptions that all current and future markets exist and that farmers treat all prices as given, the model simplifies households’ simultaneous production and consumption decisions into a recursive form in which production can be treated as independent of preferences of household members. These assumptions, which are the foundation of a large literature in labor and development, have been tested and not rejected in several important studies including Benjamin (1992). Using multiple waves of longitudinal survey data from Central Java, Indonesia, this paper tests a key prediction of the recursive model: demand for farm labor is unrelated to the demographic composition of the farm household. The prediction is unambiguously rejected. The rejection cannot be explained by contamination due to unobserved heterogeneity that is fixed at the farm level, local area shocks or farm-specific shocks that affect changes in household composition and farm labor demand. We conclude that the recursive form of the farm household model is not consistent with the data. Developing empirically tractable models of farm households when markets are incomplete remains an important challenge. PMID:27688430

Irrigation Dynamics and Tactics - Developing a Sustainable and Profitable Irrigation Strategy for Agricultural Areas

NASA Astrophysics Data System (ADS)

Van Opstal, J.; Neale, C. M. U.; Lecina, S.

2014-12-01

Irrigation management is a dynamic process that adapts according to weather conditions and water availability, as well as socio-economic influences. The goal of water users is to adapt their management to achieve maximum profits. However, these decisions should take into account the environmental impact on the surroundings. Agricultural irrigation systems need to be viewed as a system that is an integral part of a watershed. Therefore changes in the infrastructure, operation and management of an irrigated area, has an impact on the water quantity and quality available for other water users. A strategy can be developed for decision-makers using an irrigation system modelling tool. Such a tool can simulate the impact of the infrastructure, operation and management of an irrigation area on its hydrology and agricultural productivity. This combination of factors is successfully simulated with the Ador model, which is able to reproduce on-farm irrigation and water delivery by a canal system. Model simulations for this study are supported with spatial analysis tools using GIS and remote sensing. Continuous measurements of drainage water will be added to indicate the water quality aspects. The Bear River Canal Company located in Northern Utah (U.S.A.) is used as a case study for this research. The irrigation area encompasses 26,000 ha and grows mainly alfalfa, grains, corn and onions. The model allows the simulation of different strategies related to water delivery, on-farm water use, crop rotations, and reservoirs and networks capacities under different weather and water availability conditions. Such changes in the irrigation area will have consequences for farmers in the study area regarding crop production, and for downstream users concerning both the quantity and quality of outflows. The findings from this study give insight to decision-makers and water users for changing irrigation water delivery strategies to improve the sustainability and profitability of agriculture in the future.

An AgMIP framework for improved agricultural representation in integrated assessment models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruane, Alex C.; Rosenzweig, Cynthia; Asseng, Senthold

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agriculturalmore » Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications.« less

An AgMIP framework for improved agricultural representation in integrated assessment models

NASA Astrophysics Data System (ADS)

Ruane, Alex C.; Rosenzweig, Cynthia; Asseng, Senthold; Boote, Kenneth J.; Elliott, Joshua; Ewert, Frank; Jones, James W.; Martre, Pierre; McDermid, Sonali P.; Müller, Christoph; Snyder, Abigail; Thorburn, Peter J.

2017-12-01

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agricultural Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications.

Soaring Migratory Birds Avoid Wind Farm in the Isthmus of Tehuantepec, Southern Mexico

PubMed Central

Villegas-Patraca, Rafael; Cabrera-Cruz, Sergio A.; Herrera-Alsina, Leonel

2014-01-01

The number of wind farms operating in the Isthmus of Tehuantepec, southern Mexico, has rapidly increased in recent years; yet, this region serves as a major migration route for various soaring birds, including Turkey Vultures (Cathartes aura) and Swainson's Hawks (Buteo swainsoni). We analyzed the flight trajectories of soaring migrant birds passing the La Venta II wind farm during the two migratory seasons of 2011, to determine whether an avoidance pattern existed or not. We recorded three polar coordinates for the flight path of migrating soaring birds that were detected using marine radar, plotted the flight trajectories and estimated the number of trajectories that intersected the polygon defined by the wind turbines of La Venta II. Finally, we estimated the actual number of intersections per kilometer and compared this value with the null distributions obtained by running 10,000 simulations of our datasets. The observed number of intersections per kilometer fell within or beyond the lower end of the null distributions in the five models proposed for the fall season and in three of the four models proposed for the spring season. Flight trajectories had a non-random distribution around La Venta II, suggesting a strong avoidance pattern during fall and a possible avoidance pattern during spring. We suggest that a nearby ridgeline plays an important role in this pattern, an issue that may be incorporated into strategies to minimize the potential negative impacts of future wind farms on soaring birds. Studies evaluating these issues in the Isthmus of Tehuantepec have not been previously published; hence this work contributes important baseline information about the movement patterns of soaring birds and its relationship to wind farms in the region. PMID:24647442

Soaring migratory birds avoid wind farm in the Isthmus of Tehuantepec, southern Mexico.

PubMed

Villegas-Patraca, Rafael; Cabrera-Cruz, Sergio A; Herrera-Alsina, Leonel

2014-01-01

The number of wind farms operating in the Isthmus of Tehuantepec, southern Mexico, has rapidly increased in recent years; yet, this region serves as a major migration route for various soaring birds, including Turkey Vultures (Cathartes aura) and Swainson's Hawks (Buteo swainsoni). We analyzed the flight trajectories of soaring migrant birds passing the La Venta II wind farm during the two migratory seasons of 2011, to determine whether an avoidance pattern existed or not. We recorded three polar coordinates for the flight path of migrating soaring birds that were detected using marine radar, plotted the flight trajectories and estimated the number of trajectories that intersected the polygon defined by the wind turbines of La Venta II. Finally, we estimated the actual number of intersections per kilometer and compared this value with the null distributions obtained by running 10,000 simulations of our datasets. The observed number of intersections per kilometer fell within or beyond the lower end of the null distributions in the five models proposed for the fall season and in three of the four models proposed for the spring season. Flight trajectories had a non-random distribution around La Venta II, suggesting a strong avoidance pattern during fall and a possible avoidance pattern during spring. We suggest that a nearby ridgeline plays an important role in this pattern, an issue that may be incorporated into strategies to minimize the potential negative impacts of future wind farms on soaring birds. Studies evaluating these issues in the Isthmus of Tehuantepec have not been previously published; hence this work contributes important baseline information about the movement patterns of soaring birds and its relationship to wind farms in the region.

Investment appraisal of technology innovations on dairy farm electricity consumption.

PubMed

Upton, J; Murphy, M; De Boer, I J M; Groot Koerkamp, P W G; Berentsen, P B M; Shalloo, L

2015-02-01

The aim of this study was to conduct an investment appraisal for milk-cooling, water-heating, and milk-harvesting technologies on a range of farm sizes in 2 different electricity-pricing environments. This was achieved by using a model for electricity consumption on dairy farms. The model simulated the effect of 6 technology investment scenarios on the electricity consumption and electricity costs of the 3 largest electricity-consuming systems within the dairy farm (i.e., milk-cooling, water-heating, and milking machine systems). The technology investment scenarios were direct expansion milk-cooling, ice bank milk-cooling, milk precooling, solar water-heating, and variable speed drive vacuum pump-milking systems. A dairy farm profitability calculator was combined with the electricity consumption model to assess the effect of each investment scenario on the total discounted net income over a 10-yr period subsequent to the investment taking place. Included in the calculation were the initial investments, which were depreciated to zero over the 10-yr period. The return on additional investment for 5 investment scenarios compared with a base scenario was computed as the investment appraisal metric. The results of this study showed that the highest return on investment figures were realized by using a direct expansion milk-cooling system with precooling of milk to 15°C with water before milk entry to the storage tank, heating water with an electrical water-heating system, and using standard vacuum pump control on the milking system. Return on investment figures did not exceed the suggested hurdle rate of 10% for any of the ice bank scenarios, making the ice bank system reliant on a grant aid framework to reduce the initial capital investment and improve the return on investment. The solar water-heating and variable speed drive vacuum pump scenarios failed to produce positive return on investment figures on any of the 3 farm sizes considered on either the day and night tariff or the flat tariff, even when the technology costs were reduced by 40% in a sensitivity analysis of technology costs. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A comparison of methods for assessing power output in non-uniform onshore wind farms

DOE PAGES

Staid, Andrea; VerHulst, Claire; Guikema, Seth D.

2017-10-02

Wind resource assessments are used to estimate a wind farm's power production during the planning process. It is important that these estimates are accurate, as they can impact financing agreements, transmission planning, and environmental targets. Here, we analyze the challenges in wind power estimation for onshore farms. Turbine wake effects are a strong determinant of farm power production. With given input wind conditions, wake losses typically cause downstream turbines to produce significantly less power than upstream turbines. These losses have been modeled extensively and are well understood under certain conditions. Most notably, validation of different model types has favored offshoremore » farms. Models that capture the dynamics of offshore wind conditions do not necessarily perform equally as well for onshore wind farms. We analyze the capabilities of several different methods for estimating wind farm power production in 2 onshore farms with non-uniform layouts. We compare the Jensen model to a number of statistical models, to meteorological downscaling techniques, and to using no model at all. In conclusion, we show that the complexities of some onshore farms result in wind conditions that are not accurately modeled by the Jensen wake decay techniques and that statistical methods have some strong advantages in practice.« less

A comparison of methods for assessing power output in non-uniform onshore wind farms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Staid, Andrea; VerHulst, Claire; Guikema, Seth D.

Wind resource assessments are used to estimate a wind farm's power production during the planning process. It is important that these estimates are accurate, as they can impact financing agreements, transmission planning, and environmental targets. Here, we analyze the challenges in wind power estimation for onshore farms. Turbine wake effects are a strong determinant of farm power production. With given input wind conditions, wake losses typically cause downstream turbines to produce significantly less power than upstream turbines. These losses have been modeled extensively and are well understood under certain conditions. Most notably, validation of different model types has favored offshoremore » farms. Models that capture the dynamics of offshore wind conditions do not necessarily perform equally as well for onshore wind farms. We analyze the capabilities of several different methods for estimating wind farm power production in 2 onshore farms with non-uniform layouts. We compare the Jensen model to a number of statistical models, to meteorological downscaling techniques, and to using no model at all. In conclusion, we show that the complexities of some onshore farms result in wind conditions that are not accurately modeled by the Jensen wake decay techniques and that statistical methods have some strong advantages in practice.« less

A review of network analysis terminology and its application to foot-and-mouth disease modelling and policy development.

PubMed

Dubé, C; Ribble, C; Kelton, D; McNab, B

2009-04-01

Livestock movements are important in spreading infectious diseases and many countries have developed regulations that require farmers to report livestock movements to authorities. This has led to the availability of large amounts of data for analysis and inclusion in computer simulation models developed to support policy formulation. Social network analysis has become increasingly popular to study and characterize the networks resulting from the movement of livestock from farm-to-farm and through other types of livestock operations. Network analysis is a powerful tool that allows one to study the relationships created among these operations, providing information on the role that they play in acquiring and spreading infectious diseases, information that is not readily available from more traditional livestock movement studies. Recent advances in the study of real-world complex networks are now being applied to veterinary epidemiology and infectious disease modelling and control. A review of the principles of network analysis and of the relevance of various complex network theories to infectious disease modelling and control is presented in this paper.

Modelling farm vulnerability to flooding: A step toward vulnerability mitigation policies appraisal

NASA Astrophysics Data System (ADS)

Brémond, P.; Abrami, G.; Blanc, C.; Grelot, F.

2009-04-01

Recent catastrophic flood events such as Elbe in 2002 or Rhône in 2003 have shown limits of flood management policies relying on dykes protection: worsening of flood impacts downstream, increased damage by dykes rupture. Those events, among others, contributes to radical changes on the philosophy of flood prevention, with the promotion of new orientations for mitigating flood exposition. Two new trends may have a significant impact on rural areas: floodplain restoration and vulnerability mitigation. The Rhône River program, which is an contract of objectives signed between French Government and local collectivites, is highly illustrative of these new trends and their impact on agricultural sector. In this program, it appears that areas to be concerned by floodplain restoration are agricultural ones, because their supposed vulnerability to flood is expected to be less important to urban areas. As a consequence, agricultural sector is particularly concerned by planned actions on mitigation of assets vulnerability, an important part of the program (financial support of European Union of 7.5 Million euros). Mitigation of agricultural assets vulnerability reveals particularly interesting for two following reasons. Firstly, it is a way to maintain agricultural activities in floodplains yet existing, without promoting flood protection. Secondly, in case of floodplain restoration, vulnerability mitigation is a way for local authorities to compensate over-flooding impacts. In practice, local authorities may financially support farmers for implementing measures to mitigate their farm vulnerability. On the Rhône River, an important work has already been done to identify farm vulnerability to flooding, and propose measures to mitigate it. More than 3 000 farms exposed to flood risk have been identified representing 88 690 ha of agricultural areas which is estimated to generate damage between 400 and 800 Million euros depending on the season of occurrence for a catastrophic flood. In the case of farm activities, vulnerability mitigation consists in implementing measures which can be: physical (equipment or electric power system elevation), organizational (emergency or recovery plan) or financial (insurance). These measures aim at decreasing the total damage incurred by farmers in case of flooding. For instance, if equipment is elevated, it will not suffer direct damage such as degradation. As a consequence, equipment will be available to continue production or recovery tasks, thus, avoiding indirect damage such as delays, indebtedness… The effects of these policies on farms, in particular vulnerability mitigation cannot be appraised using current methodologies mainly because they do not consider farm as a whole and focus on direct damage at the land plot scale (loss of yield). Moreover, since vulnerability mitigation policies are quite recent, few examples of implementation exist and no feedback experience can be processed. Meanwhile, decision makers and financial actors require more justification of the efficiency of public fund by economic appraisal of the projects. On the Rhône River, decision makers asked for an economic evaluation of the program of farm vulnerability mitigation they plan to implement. This implies to identify the effects of the measures to mitigate farm vulnerability, and to classify them by comparing their efficacy (avoided damage) and their cost of implementation. In this presentation, we propose and discuss a conceptual model of vulnerability at the farm scale. The modelling, in Unified Modelling Language, enabled to represent the ties between spatial, organizational and temporal dimensions, which are central to understanding of farm vulnerability and resilience to flooding. Through this modelling, we encompass three goals: To improve the comprehension of farm vulnerability and create a framework that allow discussion with experts of different disciplines as well as with local farmers; To identify data which are needed to implement the model and to collect them, specifically using the focus group method; Based on the conceptual model, to program a mathematical model which will be used to simulate damage (direct and indirect) on farm due to flood. This last objective should enable us to appraise policy to mitigate vulnerability which is planned to be implemented on Rhône River at the individual and regional scale. Finally, we discuss the possibility to use the UML modelling to develop a multi-agent system approach which could be interesting to take into account ties between farmers (solidarity, loan of equipment) or systemic effects due to the damage incurred by economic partners (loss of market share). Keywords vulnerability, UML modelling, farming systems, flood, mitigation policy, economic valuation

Could Crop Height Affect the Wind Resource at Agriculturally Productive Wind Farm Sites?

NASA Astrophysics Data System (ADS)

Vanderwende, Brian; Lundquist, Julie K.

2016-03-01

The collocation of cropland and wind turbines in the US Midwest region introduces complex meteorological interactions that could influence both agriculture and wind-power production. Crop management practices may affect the wind resource through alterations of land-surface properties. We use the weather research and forecasting (WRF) model to estimate the impact of crop height variations on the wind resource in the presence of a large turbine array. A hypothetical wind farm consisting of 121 1.8-MW turbines is represented using the WRF model wind-farm parametrization. We represent the impact of selecting soybeans rather than maize by altering the aerodynamic roughness length in a region approximately 65 times larger than that occupied by the turbine array. Roughness lengths of 0.1 and 0.25 m represent the mature soy crop and a mature maize crop, respectively. In all but the most stable atmospheric conditions, statistically significant hub-height wind-speed increases and rotor-layer wind-shear reductions result from switching from maize to soybeans. Based on simulations for the entire month of August 2013, wind-farm energy output increases by 14 %, which would yield a significant monetary gain. Further investigation is required to determine the optimal size, shape, and crop height of the roughness modification to maximize the economic benefit and minimize the cost of such crop-management practices. These considerations must be balanced by other influences on crop choice such as soil requirements and commodity prices.

Could crop height affect the wind resource at agriculturally productive wind farm sites?

DOE PAGES

Vanderwende, Brian; Lundquist, Julie K.

2015-11-07

The collocation of cropland and wind turbines in the US Midwest region introduces complex meteorological interactions that could influence both agriculture and wind-power production. Crop management practices may affect the wind resource through alterations of land-surface properties. We use the weather research and forecasting (WRF) model to estimate the impact of crop height variations on the wind resource in the presence of a large turbine array. A hypothetical wind farm consisting of 121 1.8-MW turbines is represented using the WRF model wind-farm parametrization. We represent the impact of selecting soybeans rather than maize by altering the aerodynamic roughness length inmore » a region approximately 65 times larger than that occupied by the turbine array. Roughness lengths of 0.1 and 0.25 m represent the mature soy crop and a mature maize crop, respectively. In all but the most stable atmospheric conditions, statistically significant hub-height wind-speed increases and rotor-layer wind-shear reductions result from switching from maize to soybeans. Based on simulations for the entire month of August 2013, wind-farm energy output increases by 14 %, which would yield a significant monetary gain. Further investigation is required to determine the optimal size, shape, and crop height of the roughness modification to maximize the economic benefit and minimize the cost of such crop-management practices. As a result, these considerations must be balanced by other influences on crop choice such as soil requirements and commodity prices.« less

Could crop height affect the wind resource at agriculturally productive wind farm sites?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vanderwende, Brian; Lundquist, Julie K.

The collocation of cropland and wind turbines in the US Midwest region introduces complex meteorological interactions that could influence both agriculture and wind-power production. Crop management practices may affect the wind resource through alterations of land-surface properties. We use the weather research and forecasting (WRF) model to estimate the impact of crop height variations on the wind resource in the presence of a large turbine array. A hypothetical wind farm consisting of 121 1.8-MW turbines is represented using the WRF model wind-farm parametrization. We represent the impact of selecting soybeans rather than maize by altering the aerodynamic roughness length inmore » a region approximately 65 times larger than that occupied by the turbine array. Roughness lengths of 0.1 and 0.25 m represent the mature soy crop and a mature maize crop, respectively. In all but the most stable atmospheric conditions, statistically significant hub-height wind-speed increases and rotor-layer wind-shear reductions result from switching from maize to soybeans. Based on simulations for the entire month of August 2013, wind-farm energy output increases by 14 %, which would yield a significant monetary gain. Further investigation is required to determine the optimal size, shape, and crop height of the roughness modification to maximize the economic benefit and minimize the cost of such crop-management practices. As a result, these considerations must be balanced by other influences on crop choice such as soil requirements and commodity prices.« less

Near real time wind energy forecasting incorporating wind tunnel modeling

NASA Astrophysics Data System (ADS)

Lubitz, William David

A series of experiments and investigations were carried out to inform the development of a day-ahead wind power forecasting system. An experimental near-real time wind power forecasting system was designed and constructed that operates on a desktop PC and forecasts 12--48 hours in advance. The system uses model output of the Eta regional scale forecast (RSF) to forecast the power production of a wind farm in the Altamont Pass, California, USA from 12 to 48 hours in advance. It is of modular construction and designed to also allow diagnostic forecasting using archived RSF data, thereby allowing different methods of completing each forecasting step to be tested and compared using the same input data. Wind-tunnel investigations of the effect of wind direction and hill geometry on wind speed-up above a hill were conducted. Field data from an Altamont Pass, California site was used to evaluate several speed-up prediction algorithms, both with and without wind direction adjustment. These algorithms were found to be of limited usefulness for the complex terrain case evaluated. Wind-tunnel and numerical simulation-based methods were developed for determining a wind farm power curve (the relation between meteorological conditions at a point in the wind farm and the power production of the wind farm). Both methods, as well as two methods based on fits to historical data, ultimately showed similar levels of accuracy: mean absolute errors predicting power production of 5 to 7 percent of the wind farm power capacity. The downscaling of RSF forecast data to the wind farm was found to be complicated by the presence of complex terrain. Poor results using the geostrophic drag law and regression methods motivated the development of a database search method that is capable of forecasting not only wind speeds but also power production with accuracy better than persistence.

An integrated modeling method for wind turbines

NASA Astrophysics Data System (ADS)

Fadaeinedjad, Roohollah

To study the interaction of the electrical, mechanical, and aerodynamic aspects of a wind turbine, a detailed model that considers all these aspects must be used. A drawback of many studies in the area of wind turbine simulation is that either a very simple mechanical model is used with a detailed electrical model, or vice versa. Hence the interactions between electrical and mechanical aspects of wind turbine operation are not accurately taken into account. In this research, it will be shown that a combination of different simulation packages, namely TurbSim, FAST, and Simulink can be used to model the aerodynamic, mechanical, and electrical aspects of a wind turbine in detail. In this thesis, after a review of some wind turbine concepts and software tools, a simulation structure is proposed for studying wind turbines that integrates the mechanical and electrical components of a wind energy conversion device. Based on the simulation structure, a comprehensive model for a three-bladed variable speed wind turbine with doubly-fed induction generator is developed. Using the model, the impact of a voltage sag on the wind turbine tower vibration is investigated under various operating conditions such as power system short circuit level, mechanical parameters, and wind turbine operating conditions. It is shown how an electrical disturbance can cause more sustainable tower vibrations under high speed and turbulent wind conditions, which may disrupt the operation of pitch control system. A similar simulation structure is used to model a two-bladed fixed speed wind turbine with an induction generator. An extension of the concept is introduced by adding a diesel generator system. The model is utilized to study the impact of the aeroelastic aspects of wind turbine (i.e. tower shadow, wind shears, yaw error, turbulence, and mechanical vibrations) on the power quality of a stand-alone wind-diesel system. Furthermore, an IEEE standard flickermeter model is implemented in a Simulink environment to study the flicker contribution of the wind turbine in the wind-diesel system. By using a new wind power plant representation method, a large wind farm (consisting of 96 fixed speed wind turbines) is modelled to study the power quality of wind power system. The flicker contribution of wind farm is also studied with different wind turbine numbers, using the flickermeter model. Keywords. Simulink, FAST, TurbSim, AreoDyn, wind energy, doubly-fed induction generator, variable speed wind turbine, voltage sag, tower vibration, power quality, flicker, fixed speed wind turbine, wind shear, tower shadow, and yaw error.

[Severe clinical problems lasting several weeks on a multiplier pig farm: what if it had been classical swine fever?].

PubMed

Backer, Jantien; Spierenburg, Marcel; van der Spek, Arco; Elbers, Armin

2010-10-15

In the Spring of 2009, a veterinarian reported suspected classical swine fever (CSF) on a multiplier pig farm in the southern part of The Netherlands (close to the Belgian border). Over a 5-week period there had been a number of sick sows and an excessively high percentage of stillborn and preterm piglets. Sick animals were treated with anti-inflammatory drugs and antibiotics, but did not respond as well as anticipated. A visiting specialist team from the Food Safety Authority could not exclude CSF as the cause of the clinical problems and sent blood samples to the reference laboratory in Lelystad for a PCR test on CSF antigen. Fortunately, test results obtained 6 hours later were negative for CSF, and the disease control measures were lifted. It later appeared that porcine reproductive and respiratory syndrome (PRRSV) might have been responsible for the problems. But what if CSF had caused the clinical problems? A CSF-transmission model was used to simulate CSF outbreaks dependent on the duration of the high-risk period (HRP). As the duration of the HRP increased, there was an exponential growth in the number of pig farms infected during this period. Simulations also showed that with a longer HRP, the virus spread over greater distances from the source herd. It was also investigated whether a possible CSF outbreak could be detected on the basis of an increased mortality and hence increased number of cadavers sent to a rendering plant. However, the calculated mortality incidence was not sensitive enough to serve as an alarm signal. It is recommended that CSF-exclusion diagnostics be used much earlier in similar clinical situations on pig farms.

Identification of Deleterious Mutations in Myostatin Gene of Rohu Carp (Labeo rohita) Using Modeling and Molecular Dynamic Simulation Approaches

PubMed Central

Rasal, Kiran Dashrath; Chakrapani, Vemulawada; Patra, Swagat Kumar; Mohapatra, Shibani D.; Nayak, Swapnarani; Jena, Sasmita; Sundaray, Jitendra Kumar; Jayasankar, Pallipuram; Barman, Hirak Kumar

2016-01-01

The myostatin (MSTN) is a known negative growth regulator of skeletal muscle. The mutated myostatin showed a double-muscular phenotype having a positive significance for the farmed animals. Consequently, adequate information is not available in the teleosts, including farmed rohu carp, Labeo rohita. In the absence of experimental evidence, computational algorithms were utilized in predicting the impact of point mutation of rohu myostatin, especially its structural and functional relationships. The four mutations were generated at different positions (p.D76A, p.Q204P, p.C312Y, and p.D313A) of MSTN protein of rohu. The impacts of each mutant were analyzed using SIFT, I-Mutant 2.0, PANTHER, and PROVEAN, wherein two substitutions (p.D76A and p.Q204P) were predicted as deleterious. The comparative structural analysis of each mutant protein with the native was explored using 3D modeling as well as molecular-dynamic simulation techniques. The simulation showed altered dynamic behaviors concerning RMSD and RMSF, for either p.D76A or p.Q204P substitution, when compared with the native counterpart. Interestingly, incorporated two mutations imposed a significant negative impact on protein structure and stability. The present study provided the first-hand information in identifying possible amino acids, where mutations could be incorporated into MSTN gene of rohu carp including other carps for undertaking further in vivo studies. PMID:27019850

Identification of Deleterious Mutations in Myostatin Gene of Rohu Carp (Labeo rohita) Using Modeling and Molecular Dynamic Simulation Approaches.

PubMed

Rasal, Kiran Dashrath; Chakrapani, Vemulawada; Patra, Swagat Kumar; Mohapatra, Shibani D; Nayak, Swapnarani; Jena, Sasmita; Sundaray, Jitendra Kumar; Jayasankar, Pallipuram; Barman, Hirak Kumar

2016-01-01

The myostatin (MSTN) is a known negative growth regulator of skeletal muscle. The mutated myostatin showed a double-muscular phenotype having a positive significance for the farmed animals. Consequently, adequate information is not available in the teleosts, including farmed rohu carp, Labeo rohita. In the absence of experimental evidence, computational algorithms were utilized in predicting the impact of point mutation of rohu myostatin, especially its structural and functional relationships. The four mutations were generated at different positions (p.D76A, p.Q204P, p.C312Y, and p.D313A) of MSTN protein of rohu. The impacts of each mutant were analyzed using SIFT, I-Mutant 2.0, PANTHER, and PROVEAN, wherein two substitutions (p.D76A and p.Q204P) were predicted as deleterious. The comparative structural analysis of each mutant protein with the native was explored using 3D modeling as well as molecular-dynamic simulation techniques. The simulation showed altered dynamic behaviors concerning RMSD and RMSF, for either p.D76A or p.Q204P substitution, when compared with the native counterpart. Interestingly, incorporated two mutations imposed a significant negative impact on protein structure and stability. The present study provided the first-hand information in identifying possible amino acids, where mutations could be incorporated into MSTN gene of rohu carp including other carps for undertaking further in vivo studies.

Dairy goat demography and Q fever infection dynamics

PubMed Central

2013-01-01

Between 2007 and 2009, the largest human Q fever epidemic ever described occurred in the Netherlands. The source was traced back to dairy goat farms, where abortion storms had been observed since 2005. Since one putative cause of these abortion storms is the intensive husbandry systems in which the goats are kept, the objective of this study was to assess whether these could be explained by herd size, reproductive pattern and other demographic aspects of Dutch dairy goat herds alone. We adapted an existing, fully parameterized simulation model for Q fever transmission in French dairy cattle herds to represent the demographics typical for Dutch dairy goat herds. The original model represents the infection dynamics in a herd of 50 dairy cows after introduction of a single infected animal; the adapted model has 770 dairy goats. For a full comparison, herds of 770 cows and 50 goats were also modeled. The effects of herd size and goat versus cattle demographics on the probability of and time to extinction of the infection, environmental bacterial load and abortion rate were studied by simulation. The abortion storms could not be fully explained by demographics alone. Adequate data were lacking at the moment to attribute the difference to characteristics of the pathogen, host, within-herd environment, or a combination thereof. The probability of extinction was higher in goat herds than in cattle herds of the same size. The environmental contamination was highest within cattle herds, which may be taken into account when enlarging cattle farming systems. PMID:23621908

Dairy goat demography and Q fever infection dynamics.

PubMed

Hogerwerf, Lenny; Courcoul, Aurélie; Klinkenberg, Don; Beaudeau, François; Vergu, Elisabeta; Nielen, Mirjam

2013-04-26

Between 2007 and 2009, the largest human Q fever epidemic ever described occurred in the Netherlands. The source was traced back to dairy goat farms, where abortion storms had been observed since 2005. Since one putative cause of these abortion storms is the intensive husbandry systems in which the goats are kept, the objective of this study was to assess whether these could be explained by herd size, reproductive pattern and other demographic aspects of Dutch dairy goat herds alone. We adapted an existing, fully parameterized simulation model for Q fever transmission in French dairy cattle herds to represent the demographics typical for Dutch dairy goat herds. The original model represents the infection dynamics in a herd of 50 dairy cows after introduction of a single infected animal; the adapted model has 770 dairy goats. For a full comparison, herds of 770 cows and 50 goats were also modeled. The effects of herd size and goat versus cattle demographics on the probability of and time to extinction of the infection, environmental bacterial load and abortion rate were studied by simulation. The abortion storms could not be fully explained by demographics alone. Adequate data were lacking at the moment to attribute the difference to characteristics of the pathogen, host, within-herd environment, or a combination thereof. The probability of extinction was higher in goat herds than in cattle herds of the same size. The environmental contamination was highest within cattle herds, which may be taken into account when enlarging cattle farming systems.

Optimizing bulk milk dioxin monitoring based on costs and effectiveness.

PubMed

Lascano-Alcoser, V H; Velthuis, A G J; van der Fels-Klerx, H J; Hoogenboom, L A P; Oude Lansink, A G J M

2013-07-01

Dioxins are environmental pollutants, potentially present in milk products, which have negative consequences for human health and for the firms and farms involved in the dairy chain. Dioxin monitoring in feed and food has been implemented to detect their presence and estimate their levels in food chains. However, the costs and effectiveness of such programs have not been evaluated. In this study, the costs and effectiveness of bulk milk dioxin monitoring in milk trucks were estimated to optimize the sampling and pooling monitoring strategies aimed at detecting at least 1 contaminated dairy farm out of 20,000 at a target dioxin concentration level. Incidents of different proportions, in terms of the number of contaminated farms, and concentrations were simulated. A combined testing strategy, consisting of screening and confirmatory methods, was assumed as well as testing of pooled samples. Two optimization models were built using linear programming. The first model aimed to minimize monitoring costs subject to a minimum required effectiveness of finding an incident, whereas the second model aimed to maximize the effectiveness for a given monitoring budget. Our results show that a high level of effectiveness is possible, but at high costs. Given specific assumptions, monitoring with 95% effectiveness to detect an incident of 1 contaminated farm at a dioxin concentration of 2 pg of toxic equivalents/g of fat [European Commission's (EC) action level] costs €2.6 million per month. At the same level of effectiveness, a 73% cost reduction is possible when aiming to detect an incident where 2 farms are contaminated at a dioxin concentration of 3 pg of toxic equivalents/g of fat (EC maximum level). With a fixed budget of €40,000 per month, the probability of detecting an incident with a single contaminated farm at a dioxin concentration equal to the EC action level is 4.4%. This probability almost doubled (8.0%) when aiming to detect the same incident but with a dioxin concentration equal to the EC maximum level. This study shows that the effectiveness of finding an incident depends not only on the ratio at which, for testing, collected truck samples are mixed into a pooled sample (aiming at detecting certain concentration), but also the number of collected truck samples. In conclusion, the optimal cost-effective monitoring depends on the number of contaminated farms and the concentration aimed at detection. The models and study results offer quantitative support to risk managers of food industries and food safety authorities. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

IEA-Task 31 WAKEBENCH: Towards a protocol for wind farm flow model evaluation. Part 2: Wind farm wake models

NASA Astrophysics Data System (ADS)

Moriarty, Patrick; Sanz Rodrigo, Javier; Gancarski, Pawel; Chuchfield, Matthew; Naughton, Jonathan W.; Hansen, Kurt S.; Machefaux, Ewan; Maguire, Eoghan; Castellani, Francesco; Terzi, Ludovico; Breton, Simon-Philippe; Ueda, Yuko

2014-06-01

Researchers within the International Energy Agency (IEA) Task 31: Wakebench have created a framework for the evaluation of wind farm flow models operating at the microscale level. The framework consists of a model evaluation protocol integrated with a web-based portal for model benchmarking (www.windbench.net). This paper provides an overview of the building-block validation approach applied to wind farm wake models, including best practices for the benchmarking and data processing procedures for validation datasets from wind farm SCADA and meteorological databases. A hierarchy of test cases has been proposed for wake model evaluation, from similarity theory of the axisymmetric wake and idealized infinite wind farm, to single-wake wind tunnel (UMN-EPFL) and field experiments (Sexbierum), to wind farm arrays in offshore (Horns Rev, Lillgrund) and complex terrain conditions (San Gregorio). A summary of results from the axisymmetric wake, Sexbierum, Horns Rev and Lillgrund benchmarks are used to discuss the state-of-the-art of wake model validation and highlight the most relevant issues for future development.

Do differences in food web structure between organic and conventional farms affect the ecosystem service of pest control?

PubMed

Macfadyen, Sarina; Gibson, Rachel; Polaszek, Andrew; Morris, Rebecca J; Craze, Paul G; Planqué, Robert; Symondson, William O C; Memmott, Jane

2009-03-01

While many studies have demonstrated that organic farms support greater levels of biodiversity, it is not known whether this translates into better provision of ecosystem services. Here we use a food-web approach to analyse the community structure and function at the whole-farm scale. Quantitative food webs from 10 replicate pairs of organic and conventional farms showed that organic farms have significantly more species at three trophic levels (plant, herbivore and parasitoid) and significantly different network structure. Herbivores on organic farms were attacked by more parasitoid species on organic farms than on conventional farms. However, differences in network structure did not translate into differences in robustness to simulated species loss and we found no difference in percentage parasitism (natural pest control) across a variety of host species. Furthermore, a manipulative field experiment demonstrated that the higher species richness of parasitoids on the organic farms did not increase mortality of a novel herbivore used to bioassay ecosystem service. The explanation for these differences is likely to include inherent differences in management strategies and landscape structure between the two farming systems.

Lessons Learned Developing an Extension-Based Training Program for Farm Labor Supervisors

ERIC Educational Resources Information Center

Roka, Fritz M.; Thissen, Carlene A.; Monaghan, Paul F.; Morera, Maria C.; Galindo-Gonzalez, Sebastian; Tovar-Aguilar, Jose Antonio

2017-01-01

This article outlines a four-step model for developing a training program for farm labor supervisors. The model draws on key lessons learned during the development of the University of Florida Institute of Food and Agricultural Sciences Farm Labor Supervisor Training program. The program is designed to educate farm supervisors on farm labor laws…

Impact of Offshore Wind Power Integrated by VSC-HVDC on Power Angle Stability of Power Systems

NASA Astrophysics Data System (ADS)

Lu, Haiyang; Tang, Xisheng

2017-05-01

Offshore wind farm connected to grid by VSC-HVDC loses frequency support for power system, so adding frequency control in wind farm and VSC-HVDC system is an effective measure, but it will change wind farm VSC-HVDC’s transient stability on power system. Through theoretical analysis, concluding the relationship between equivalent mechanical power and electromagnetic power of two-machine system with the active power of wind farm VSC-HVDC, then analyzing the impact of wind farm VSC-HVDC with or without frequency control and different frequency control parameters on angle stability of synchronous machine by EEAC. The validity of theoretical analysis has been demonstrated through simulation in PSCAD/EMTDC.

Optimizing productivity, herd structure, environmental performance, and profitability of dairy cattle herds.

PubMed

Liang, D; Cabrera, V E

2015-04-01

This study used the Integrated Farm System Model to simulate the whole farm performance of a representative Wisconsin dairy farm and predict its economic and environmental outputs based on 25 yr of daily local weather data (1986 to 2010). The studied farm, located in southern Wisconsin, had 100 milking cows and 100 ha of cropland with no replacement heifers kept on the farm. Sensitivity analyses were conducted to test the effect of management strategies on energy-corrected milk production (ECM; 4.0% fat and 3.5% protein), net return to management, and greenhouse gas (GHG; including biogenic CO2) emission. The management strategies included (1) target milk production, for which the model optimized available resources to attain, and (2) herd structure, represented by the percentage of first-lactation cows. Weather conditions affected the outputs by changing the farm quantity and the quality of produced feed resources. As expected, when target milk production increased, the ECM increased positively and linearly to a certain level, and then it increased nonlinearly at a decreasing rate, constrained by available feed nutrients. Thereafter, the ECM reached the maximum potential milk production and remained flat regardless of higher target milk production input. Greenhouse gas emissions decreased between 3.4 and 7.3% at different first-lactation cow percentages. As the first-lactation cow percent increased from 15 to 45% in 5% intervals, GHG increased between 9.4 and 11.3% at different levels of target milk production. A high percentage of first-lactation cows reduced the maximum potential milk production. Net return to management had a similar changing trend as ECM. As the target milk production increased from 9,979 to 11,793 kg, the net return to management increased between 31 and 46% at different first-lactation cow percentages. Results revealed a win-win situation when increasing milk production or improving herd structure, which concurrently increased farm net return to management and decreased GHG emissions. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

An individual-based population dynamic model for estimating biomass yield and nutrient fluxes through an off-shore mussel ( Mytilus galloprovincialis) farm

NASA Astrophysics Data System (ADS)

Brigolin, Daniele; Maschio, Gabriele Dal; Rampazzo, Federico; Giani, Michele; Pastres, Roberto

2009-04-01

The fluxes of carbon, nitrogen and phosphorus through an off-shore long-line Mytilus galloprovincialis farm during a typical rearing cycle were estimated by combining a simple population dynamic model, based on a new individual model, and a set of field data, concerning the composition of the seston, as well as that of mussel meat and faeces. The individual model, based on an energy budget, was validated against a set of original field data, which were purposely collected from July 2006 to May 2007 in the North-Western Adriatic Sea (Italy) and was further tested using historical data. The model was upscaled to the population level by means of a set of Monte Carlo simulations, which were used for estimating the size structure of the population. The daily fluxes of C, N and P associated with mussel filtration, excretion and faeces and pseudo-faeces production were integrated over the 10-month-long rearing cycle and compared with the total amount of C, N and P removed by harvesting. The results indicate that the individual model compares well with an existing literature model and provides reliable estimations of the growth of mussel specimen over a range of trophic conditions which are typical of the Northern Adriatic Sea coastal area. The results of the budget calculation indicate that, even though the harvest represents a net removal of phosphorus and nitrogen from the ecosystem, the mussel farm increases the retention time of both nutrients in the coastal area, via the deposition of faeces and pseudo-faeces on the sea-bed. In fact, the amount of nitrogen associated with deposition is approximately twice the harvested one and the amount of phosphorus is approximately five times higher. These findings are in qualitative agreement with the results of literature budget and model calculations carried out in a temperate coastal embayment. This agreement suggests that the proper assessment of the overall effect of long-line mussel farming on both the benthic and pelagic ecosystem asks for an integrated modelling approach, which should include the dynamic of early diagenesis processes, as well as of that of nutrients released from the surface sediment.

The role of turbulent mixing in wind turbine wake recovery and wind array performance

NASA Astrophysics Data System (ADS)

Fruh, Wolf-Gerrit; Creech, Angus; Maguire, Eoghan

2014-05-01

The effect of wind turbine wakes in large offshore wind energy arrays can be a substantial factor in affecting the performance of turbines inside the array. Turbulent mixing plays a key role in the wake recovery, having a significant effect on the length over which the wake is strong enough to affect the performance other turbines significantly. We aim to highlight how turbulence affects wind turbine wakes, first by examining a high resolution CFD model of a single turbine wake validated by LIDAR measurements [1], and secondly with a much larger CFD simulation of Lillgrund offshore wind farm, validated with SCADA data [2]. By comparing the decay rates behind single turbines in environments of different surrounding surface features, ranging from ideal free-slip wind tunnels to mixed-vegetation hills, we suggest that the decay rate of turbine wakes are enhanced by free-stream turbulence, created by topography and ground features. In the context of Lillgrund wind farm, observations and computational results suggest that the wakes created by the turbines in the leading row facing the wind decay much slower than those in second row, or further into the turbine array. This observation can be explained by the diffusive action of upwind turbulence breaking up the wake generated by a turbine rotor. Angus CW Creech, Wolf-Gerrit Früh, Peter Clive (2012). Actuator volumes and hradaptive methods for threedimensional simulation of wind turbine wakes and performance. Wind Energy Vol.15, 847 - 863. Angus C.W. Creech, Wolf-Gerrit Früh, A. Eoghan Maguire (2013). High-resolution CFD modelling of Lillgrund Wind farm. Renewable Energies and Power Quality Journal, Vol. 11

Perturbations to the Spatial and Temporal Characteristics of the Diurnally-Varying Atmospheric Boundary Layer Due to an Extensive Wind Farm

NASA Astrophysics Data System (ADS)

Sharma, V.; Parlange, M. B.; Calaf, M.

2017-02-01

The effect of extensive terrestrial wind farms on the spatio-temporal structure of the diurnally-evolving atmospheric boundary layer is explored. High-resolution large-eddy simulations of a realistic diurnal cycle with an embedded wind farm are performed. Simulations are forced by a constant geostrophic velocity with time-varying surface boundary conditions derived from a selected period of the CASES-99 field campaign. Through analysis of the bulk statistics of the flow as a function of height and time, it is shown that extensive wind farms shift the inertial oscillations and the associated nocturnal low-level jet vertically upwards by approximately 200 m; cause a three times stronger stratification between the surface and the rotor-disk region, and as a consequence, delay the formation and growth of the convective boundary layer (CBL) by approximately 2 h. These perturbations are shown to have a direct impact on the potential power output of an extensive wind farm with the displacement of the low-level jet causing lower power output during the night as compared to the day. The low-power regime at night is shown to persist for almost 2 h beyond the morning transition due to the reduced growth of the CBL. It is shown that the wind farm induces a deeper entrainment region with greater entrainment fluxes. Finally, it is found that the diurnally-averaged effective roughness length for wind farms is much lower than the reference value computed theoretically for neutral conditions.

Computer simulation of wolf-removal strategies for animal-damage control

USGS Publications Warehouse

Haight, R.G.; Travis, L.E.; Nimerfro, K.; Mech, L.D.

2002-01-01

Because of the sustained growth of the gray wolf (Canis lupus) population in the western Great Lakes region of the United States, management agencies are anticipating gray wolf removal from the federal endangered species list and are proposing strategies for wolf management. Strategies are needed that would balance public demand for wolf conservation with demand for protection against wolf depredation on livestock, poultry, and pets. We used a stochastic, spatially structured, individually based simulation model of a hypothetical wolf population, representing a small subset of the western Great Lakes wolves, to predict the relative performance of 3 wolf-removal strategies. Those strategies included reactive management (wolf removal occurred in summer after depredation), preventive management (wolves removed in winter from territories with occasional depredation), and population-size management (wolves removed annually in winter from all territories near farms). Performance measures included number of depredating packs and wolves removed, cost, and population size after 20 years. We evaluated various scenarios about immigration, trapping success, and likelihood of packs engaging in depredation. Four robust results emerged from the simulations: 1) each strategy reduced depredation by at least 40% compared with no action, 2) preventive and population-size management removed fewer wolves than reactive management because wolves were removed in winter before pups were born, 3)population-size management was least expensive because repeated annual removal kept most territories near farms free of wolves, and 4) none of the strategies threatened wolf populations unless they were isolated because wolf removal took place near farms and not in wild areas. For isolated populations, reactive management alone ensured conservation and reduced depredation. Such results can assist decision makers in managing gray wolves in the western Great Lakes states.

Stochastic bio-economic modeling of mastitis in Ethiopian dairy farms.

PubMed

Getaneh, Abraham Mekibeb; Mekonnen, Sefinew Alemu; Hogeveen, Henk

2017-03-01

Mastitis is an inflammation of the mammary gland that is considered to be one of the most frequent and costly diseases in the dairy industry. Also in Ethiopia, bovine mastitis is one of the most frequently encountered diseases of dairy cows. However, there was no study, so far, regarding the costs of clinical mastitis and only two studies were reported on costs of subclinical mastitis. Presenting an appropriate and complete study of the costs of mastitis will help farmers in making management decisions for mastitis control. The objective of this study was to estimate the economic effects of mastitis on Ethiopian market-oriented dairy farms. Market-oriented dairy farming is driven by making profits through selling milk in the market on a regular basis. A dynamic stochastic Monte-Carlo simulation model (bio-economic model) was developed taking into account both clinical and subclinical mastitis. Production losses, culling, veterinarian costs, treatment, discarded milk, and labour were the main cost factors which were modeled in this study. The annual incidence of clinical mastitis varied from 0 to 50% with a mean annual incidence of 21.6%, whereas the mean annual incidence of subclinical mastitis was 36.2% which varied between 0 and 75%. The total costs due to mastitis for a default farm size of 8 lactating cows were 6,709 ETB per year (838 ETB per cow per year). The costs varied considerably, with 5th and 95th percentiles of 109 ETB and 22,009 ETB, respectively. The factor most contributing to the total annual cost of mastitis was culling. On average a clinical case costs 3,631 ETB, varying from 0 to 12,401, whereas a sub clinical case costs 147 ETB, varying from 0 to 412. The sensitivity analysis showed that the total costs at the farm level were most sensitive for variation in the probability of occurrence of clinical mastitis and the probability of culling. This study helps farmers to raise awareness about the actual costs of mastitis and motivate them to timely treat and/or take preventive measures. As a results, the dairy industry will improve. Copyright © 2017 Elsevier B.V. All rights reserved.

Hydrology and Soil Erosion in Tropical Rainforests and Pasture Lands on the Atherton Tablelands, North Queensland, Australia - a rainfall simulator study

NASA Astrophysics Data System (ADS)

Joanne, Joanne; Ciesiolka, Cyril

2010-05-01

The Barron and Johnstone Rivers rise in the basaltic Atherton Tableland, North Queensland, Australia, and flow into the Coral Sea and Great Barrier Reef World Heritage Area (GBRWHA). Natural rainforest in this region was cleared for settlement in the early 20th century. Rapid decline in soil fertility during the 1940's and 50's forced landholders to turn to pasture based industries from row crop agriculture. Since then, these pasture based industries have intensified. The intensified land use has been linked to increases in sediment and nutrient levels in terrestrial runoff and identified as a major environmental threat to the GBRWHA, which has raised alarm for the tourist industry and resource managers. Studies linking land-use to pollutant discharge are often based on measurements and modelling of end of catchment measurements of water quality. Whilst such measurements can be a reasonable indicator of the effects of land use on pollutant discharge to waterways, they are often a gross assessment. This project used rainfall simulations to investigate the relationship between land use and management with sources and sinks of runoff and soil erosion within the Barron and Johnstone Rivers catchments. Rainfall simulations were conducted and pollutant loads measured in natural rainforest, as well as dairy and beef farming systems. The dairy farming systems included an effluent fed pasture, a high mineral fertilizer and supplementary irrigation farm, and a rainfed organic pasture that relied on tropical legumes and introduced grasses and returned organic material to the soil. One of the beef farming systems used a 7-10 day rotation with a low fertilizer regime (kikuyu mostly), while the other, used a long period- two paddock-rotation with no fertiliser and paspalum pastures. The rainforests were generally small isolated enclaves with a well developed shrub layer (1-3 m), and a presence of scattered, deciduous trees. Simulations were carried out on sites which were observed to be part of a drainage network and which were typical of the surrounding hillslopes. A 13 m long by 2 m wide portable rainfall simulator was used to produce rainfall associated with high intensity events. The simulator consisted of six A-frame modules with spray nozzles (equipped with pressure gauges) that operated in an oscillating movement. Rainfall from the simulator was measured using seven dynamically calibrated pluviometers (~0.1mm/tip) and 26 rain gauges (100mm diameter, muslin covered). Runoff volume was recorded using a tipping bucket mechanism. Samples were collected at three minute intervals and used to calculate soil loss using standard methods. At sites where there was a high rate of infiltration a catena effect on runoff could be discerned. Highest runoff volumes tended to be generated on the midslope, rectilinear segments of the hillslope. However some of the sites exhibited effects from indurated laterite layers, exfiltration areas, and small areas of unweathered basalt veneered by a surface ferrasol. All sites had high levels of vegetative cover but large differences in biomass. While runoff and soil erosion were not significantly correlated with vegetative cover, a useful relationship was found when cover was multiplied by biomass. The rate of soil loss from intensive dairying was less than from the intensive beef grazing sites and cattle tracks. However, because deposition from these point sources occurred it became difficult to verify whether contributions from overland flow to the stream were significant. Observations of farm dam overflows near to the simulation sites confirmed the significant subsurface flows that diluted sediment concentrations in the local waterways. Overall, the results indicated that to reduce sediment loss farms must be designed and managed according to landscape features. In order to better understand runoff and sediment delivery it would be necessary to measure volumes and rates through a 'nested' catchment approach so that stream channel contributions could be quantified.

A modeling study on the hydrodynamics of a coastal embayment occupied by mussel farms (Ria de Ares-Betanzos, NW Iberian Peninsula)

NASA Astrophysics Data System (ADS)

Duarte, Pedro; Alvarez-Salgado, Xosé Antón; Fernández-Reiriz, Maria José; Piedracoba, Silvia; Labarta, Uxío

2014-06-01

The present study suggests that both under upwelling and downwelling winds, the residual circulation of Ria de Ares-Betanzos remains positive with a strong influence from river discharge and a positive feedback from wind, unlike what is generally accepted for Galician rias. Furthermore, mussel cultivation areas may reduce residual velocities by almost 40%, suggesting their potential feedbacks on food replenishment for cultivated mussels. The Ria de Ares-Betanzos is a partially stratified estuary in the NW Iberian upwelling system where blue mussels are extensively cultured on hanging ropes. This type of culture depends to a large extent on water circulation and residence times, since mussels feed on suspended particles. Therefore, understanding the role of tides, continental runoff, and winds on the circulation of this embayment has important practical applications. Furthermore, previous works have emphasized the potential importance of aquaculture leases on water circulation within coastal ecosystems, with potential negative feedbacks on production carrying capacity. Here we implemented and validated a 3D hydrodynamic numerical model for the Ria de Ares-Betanzos to (i) evaluate the relative importance of the forcing agents on the circulation within the ria and (ii) estimate the importance of culture leases on circulation patterns at the scale of the mussel farms from model simulations. The model was successfully validated with empirical current velocity data collected during July and October 2007 using an assortment of efficiency criteria. Model simulations were carried out to isolate the effects of wind and river flows on circulation patterns.

Real time wind farm emulation using SimWindFarm toolbox

NASA Astrophysics Data System (ADS)

Topor, Marcel

2016-06-01

This paper presents a wind farm emulation solution using an open source Matlab/Simulink toolbox and the National Instruments cRIO platform. This work is based on the Aeolus SimWindFarm (SWF) toolbox models developed at Aalborg university, Denmark. Using the Matlab Simulink models developed in SWF, the modeling code can be exported to a real time model using the NI Veristand model framework and the resulting code is integrated as a hardware in the loop control on the NI 9068 platform.

Testing the robustness of optimal access vessel fleet selection for operation and maintenance of offshore wind farms

DOE PAGES

Sperstad, Iver Bakken; Stålhane, Magnus; Dinwoodie, Iain; ...

2017-09-23

Optimising the operation and maintenance (O&M) and logistics strategy of offshore wind farms implies the decision problem of selecting the vessel fleet for O&M. Different strategic decision support tools can be applied to this problem, but much uncertainty remains regarding both input data and modelling assumptions. Our paper aims to investigate and ultimately reduce this uncertainty by comparing four simulation tools, one mathematical optimisation tool and one analytic spreadsheet-based tool applied to select the O&M access vessel fleet that minimizes the total O&M cost of a reference wind farm. The comparison shows that the tools generally agree on the optimalmore » vessel fleet, but only partially agree on the relative ranking of the different vessel fleets in terms of total O&M cost. The robustness of the vessel fleet selection to various input data assumptions was tested, and the ranking was found to be particularly sensitive to the vessels' limiting significant wave height for turbine access. Also the parameter with the greatest discrepancy between the tools, implies that accurate quantification and modelling of this parameter is crucial. The ranking is moderately sensitive to turbine failure rates and vessel day rates but less sensitive to electricity price and vessel transit speed.« less

Testing the robustness of optimal access vessel fleet selection for operation and maintenance of offshore wind farms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sperstad, Iver Bakken; Stålhane, Magnus; Dinwoodie, Iain

Optimising the operation and maintenance (O&M) and logistics strategy of offshore wind farms implies the decision problem of selecting the vessel fleet for O&M. Different strategic decision support tools can be applied to this problem, but much uncertainty remains regarding both input data and modelling assumptions. Our paper aims to investigate and ultimately reduce this uncertainty by comparing four simulation tools, one mathematical optimisation tool and one analytic spreadsheet-based tool applied to select the O&M access vessel fleet that minimizes the total O&M cost of a reference wind farm. The comparison shows that the tools generally agree on the optimalmore » vessel fleet, but only partially agree on the relative ranking of the different vessel fleets in terms of total O&M cost. The robustness of the vessel fleet selection to various input data assumptions was tested, and the ranking was found to be particularly sensitive to the vessels' limiting significant wave height for turbine access. Also the parameter with the greatest discrepancy between the tools, implies that accurate quantification and modelling of this parameter is crucial. The ranking is moderately sensitive to turbine failure rates and vessel day rates but less sensitive to electricity price and vessel transit speed.« less

Optimal supplementary frequency controller design using the wind farm frequency model and controller parameters stability region.

PubMed

Toulabi, Mohammadreza; Bahrami, Shahab; Ranjbar, Ali Mohammad

2018-03-01

In most of the existing studies, the frequency response in the variable speed wind turbines (VSWTs) is simply realized by changing the torque set-point via appropriate inputs such as frequency deviations signal. However, effective dynamics and systematic process design have not been comprehensively discussed yet. Accordingly, this paper proposes a proportional-derivative frequency controller and investigates its performance in a wind farm consisting of several VSWTs. A band-pass filter is deployed before the proposed controller to avoid responding to either steady state frequency deviations or high rate of change of frequency. To design the controller, the frequency model of the wind farm is first characterized. The proposed controller is then designed based on the obtained open loop system. The stability region associated with the controller parameters is analytically determined by decomposing the closed-loop system's characteristic polynomial into the odd and even parts. The performance of the proposed controller is evaluated through extensive simulations in MATLAB/Simulink environment in a power system comprising a high penetration of VSWTs equipped with the proposed controller. Finally, based on the obtained feasible area and appropriate objective function, the optimal values associated with the controller parameters are determined using the genetic algorithm (GA). Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Mobilizing local innovation capacity through a simulation game in a participatory research project on agricultural innovation in El Brahmi irrigation scheme (Tunisia).

NASA Astrophysics Data System (ADS)

Dolinska, Aleksandra; d'Aquino, Patrick; Imache, Amar; Dionnet, Mathieu; Rougier, Jean-Emmanuel

2015-04-01

In the framework of the European Union and African Union cooperative research to increase Food production in irrigated farming systems in Africa (EAU4Food project) we conducted a participatory research on the possible innovative practices to increase production of dairy farms in the irrigation scheme El Brahmi in Tunisia in the face of changing economic, political and environmental conditions. Our aim was to find effective research method to stimulate farmers' participation in the innovation process. Although the capacities of farmers in producing knowledge and in innovating are recognized and the shift from the linear model of technology transfer towards more participatory approaches to innovation is postulated, in which the role of researchers changes from providing solutions towards supporting farmers in finding their own solutions, in practice, the position of farmers in shaping innovation practice and process remains weak. After a series of participatory workshops and in-depth interviews with the actors of the local innovation system we developed and tested a simple open simulation game Laitconomie for farmers. The game proved to be effective in increasing our understanding of the system as the farmers were adding new elements and rules while playing, and in mobilizing farmers' knowledge (including tacit knowledge) in the simulated innovation process. The result reported by the participants was learning how to improve farm management, soil fertility management and cow nutrition practices. Some of the participants used the game as a decision support tool. While our game and its scope were modest and mobilized only two types of players (farmers and extension agent), open simulation proved to be a useful tool to analyze a local innovation system. Designing similar type of tools that would mobilize more diverse players and hence have a larger scope can be imagined.

Wind Power Curve Modeling Using Statistical Models: An Investigation of Atmospheric Input Variables at a Flat and Complex Terrain Wind Farm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wharton, S.; Bulaevskaya, V.; Irons, Z.

The goal of our FY15 project was to explore the use of statistical models and high-resolution atmospheric input data to develop more accurate prediction models for turbine power generation. We modeled power for two operational wind farms in two regions of the country. The first site is a 235 MW wind farm in Northern Oklahoma with 140 GE 1.68 turbines. Our second site is a 38 MW wind farm in the Altamont Pass Region of Northern California with 38 Mitsubishi 1 MW turbines. The farms are very different in topography, climatology, and turbine technology; however, both occupy high wind resourcemore » areas in the U.S. and are representative of typical wind farms found in their respective areas.« less

Spatial structure of kinetic energy spectra in LES simulations of flow in an offshore wind farm

NASA Astrophysics Data System (ADS)

Fruh, Wolf-Gerrit; Creech, Angus

2017-04-01

The evolution of wind turbine and wind farm wakes was investigated numerically for the case of Lillgrund wind farm consisting of a tightly packed array of 48 turbines. The simulations for a number of wind directions at a free wind speed of just under the rated wind speed in a neutrally stable atmosphere were carried out using Large-Eddy Simulations with the adaptive Finite-Element CFD solver Fluidity. The results were interpolated from the irregularly spaced mesh nodes onto a regular grid with comparable spatial resolution at horizontal slices at various heights. To investigate the development of the wake as the flow evolves through the array, spectra of the kinetic energy in sections perpendicular to the wind directions within the wake and to the sides of the array were calculated. This paper will present the key features and spectral slopes of the flow as a function of downstream distance from the front turbine through and beyond the array. The main focus will be on the modification of the spectra as the flow crosses a row of turbines followed by its decay in the run-up to the next row, but we will also present to wake decay of the wind farm wake downstream of the array.

Effect of fertility on the economics of pasture-based dairy systems.

PubMed

Shalloo, L; Cromie, A; McHugh, N

2014-05-01

There are significant costs associated with reproductive inefficiency in pasture-based dairy herds. This study has quantified the economic effect of a number of key variables associated with reproductive inefficiency in a dairy herd and related them to 6-week calving rate for both cows and heifers. These variables include: increased culling costs, the effects of sub optimum calving dates, increased labour costs and increased artificial insemination (AI) and intervention costs. The Moorepark Dairy Systems Model which is a stochastic budgetary simulation model was used to simulate the overall economic effect at farm level. The effect of change in each of the components was simulated in the model and the costs associated with each component was quantified. An analysis of national data across a 4-year period using the Irish Cattle Breeding Federation database was used to quantify the relationship between the 6-week calving rate of a herd with survivability (%), calving interval (days) and the level of AI usage. The costs associated with increased culling (%), calving date slippage (day), increased AI and intervention costs (0.1 additional inseminations), as well as, increased labour costs (10%) were quantified as €13.68, €3.86, €4.56 and €29.6/cow per year. There was a statistically significant association between the 6-week calving rate and survivability, calving interval and AI usage at farm level. A 1% change in 6-week calving rate was associated with €9.26/cow per annum for cows and €3.51/heifer per annum for heifers. This study does not include the indirect costs such as reduced potential for expansion, increased costs associated with failing to maintain a closed herd as well as the unrealised potential within the herd.

A socio-hydrologic model of coupled water-agriculture dynamics with emphasis on farm size.

NASA Astrophysics Data System (ADS)

Brugger, D. R.; Maneta, M. P.

2015-12-01

Agricultural land cover dynamics in the U.S. are dominated by two trends: 1) total agricultural land is decreasing and 2) average farm size is increasing. These trends have important implications for the future of water resources because 1) growing more food on less land is due in large part to increased groundwater withdrawal and 2) larger farms can better afford both more efficient irrigation and more groundwater access. However, these large-scale trends are due to individual farm operators responding to many factors including climate, economics, and policy. It is therefore difficult to incorporate the trends into watershed-scale hydrologic models. Traditional scenario-based approaches are valuable for many applications, but there is typically no feedback between the hydrologic model and the agricultural dynamics and so limited insight is gained into the how agriculture co-evolves with water resources. We present a socio-hydrologic model that couples simplified hydrologic and agricultural economic dynamics, accounting for many factors that depend on farm size such as irrigation efficiency and returns to scale. We introduce an "economic memory" (EM) state variable that is driven by agricultural revenue and affects whether farms are sold when land market values exceed expected returns from agriculture. The model uses a Generalized Mixture Model of Gaussians to approximate the distribution of farm sizes in a study area, effectively lumping farms into "small," "medium," and "large" groups that have independent parameterizations. We apply the model in a semi-arid watershed in the upper Columbia River Basin, calibrating to data on streamflow, total agricultural land cover, and farm size distribution. The model is used to investigate the sensitivity of the coupled system to various hydrologic and economic scenarios such as increasing market value of land, reduced surface water availability, and increased irrigation efficiency in small farms.

Vineyard management in virtual reality: autonomous control of a transformable drone

NASA Astrophysics Data System (ADS)

Griffiths, H.; Shen, H.; Li, N.; Rojas, S.; Perkins, N.; Liu, M.

2017-05-01

Grape vines are susceptible to many diseases. Routine scouting is critically important to keep vineyards in healthy condition. Currently, scouting relies on experienced farm workers to inspect acres of land while arduously filling out reports to document crop health conditions. This process is both labor and time consuming. Using drones to assist farm workers in scouting has great potential to improve the efficiency of vineyard management. Due to the complexity in grape farm disease detection, the drones are normally used to detect suspicious areas to help farm workers to prioritize scouting activities. Operations still rely heavily on humans for further inspection to be certain about the health conditions of the vines. This paper introduces an autonomous transition flight control method for a transformable drone, which is suitable for the future virtual presence of humans in further inspecting suspicious areas. The transformable drone adopts a tilt-rotor mechanism to automatically switch between hover and horizontal flight modes, following commands from virtual reality devices held in the ground control station. The conceptual design and transformation dynamics of the drone will be first discussed, followed by a model predictive control system developed to automatically control the transition flight. Simulation is also provided to show the effectiveness of the proposed control system.

Can biosecurity and local network properties predict pathogen species richness in the salmonid industry?

PubMed

Yatabe, Tadaishi; More, Simon J; Geoghegan, Fiona; McManus, Catherine; Hill, Ashley E; Martínez-López, Beatriz

2018-01-01

Salmonid farming in Ireland is mostly organic, which implies limited disease treatment options. This highlights the importance of biosecurity for preventing the introduction and spread of infectious agents. Similarly, the effect of local network properties on infection spread processes has rarely been evaluated. In this paper, we characterized the biosecurity of salmonid farms in Ireland using a survey, and then developed a score for benchmarking the disease risk of salmonid farms. The usefulness and validity of this score, together with farm indegree (dichotomized as ≤ 1 or > 1), were assessed through generalized Poisson regression models, in which the modeled outcome was pathogen richness, defined here as the number of different diseases affecting a farm during a year. Seawater salmon (SW salmon) farms had the highest biosecurity scores with a median (interquartile range) of 82.3 (5.4), followed by freshwater salmon (FW salmon) with 75.2 (8.2), and freshwater trout (FW trout) farms with 74.8 (4.5). For FW salmon and trout farms, the top ranked model (in terms of leave-one-out information criteria, looic) was the null model (looic = 46.1). For SW salmon farms, the best ranking model was the full model with both predictors and their interaction (looic = 33.3). Farms with a higher biosecurity score were associated with lower pathogen richness, and farms with indegree > 1 (i.e. more than one fish supplier) were associated with increased pathogen richness. The effect of the interaction between these variables was also important, showing an antagonistic effect. This would indicate that biosecurity effectiveness is achieved through a broader perspective on the subject, which includes a minimization in the number of suppliers and hence in the possibilities for infection to enter a farm. The work presented here could be used to elaborate indicators of a farm's disease risk based on its biosecurity score and indegree, to inform risk-based disease surveillance and control strategies for private and public stakeholders.

Nesting large-eddy simulations within mesoscale simulations for wind energy applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lundquist, J K; Mirocha, J D; Chow, F K

2008-09-08

With increasing demand for more accurate atmospheric simulations for wind turbine micrositing, for operational wind power forecasting, and for more reliable turbine design, simulations of atmospheric flow with resolution of tens of meters or higher are required. These time-dependent large-eddy simulations (LES), which resolve individual atmospheric eddies on length scales smaller than turbine blades and account for complex terrain, are possible with a range of commercial and open-source software, including the Weather Research and Forecasting (WRF) model. In addition to 'local' sources of turbulence within an LES domain, changing weather conditions outside the domain can also affect flow, suggesting thatmore » a mesoscale model provide boundary conditions to the large-eddy simulations. Nesting a large-eddy simulation within a mesoscale model requires nuanced representations of turbulence. Our group has improved the Weather and Research Forecasting model's (WRF) LES capability by implementing the Nonlinear Backscatter and Anisotropy (NBA) subfilter stress model following Kosovic (1997) and an explicit filtering and reconstruction technique to compute the Resolvable Subfilter-Scale (RSFS) stresses (following Chow et al, 2005). We have also implemented an immersed boundary method (IBM) in WRF to accommodate complex terrain. These new models improve WRF's LES capabilities over complex terrain and in stable atmospheric conditions. We demonstrate approaches to nesting LES within a mesoscale simulation for farms of wind turbines in hilly regions. Results are sensitive to the nesting method, indicating that care must be taken to provide appropriate boundary conditions, and to allow adequate spin-up of turbulence in the LES domain.« less

Active Power Control of Waked Wind Farms: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fleming, Paul A; van Wingerden, Jan-Willem; Pao, Lucy

Active power control can be used to balance the total power generated by wind farms with the power consumed on the electricity grid. With the increasing penetration levels of wind energy, there is an increasing need for this ancillary service. In this paper, we show that the tracking of a certain power reference signal provided by the transmission system operator can be significantly improved by using feedback control at the wind farm level. We propose a simple feedback control law that significantly improves the tracking behavior of the total power output of the farm, resulting in higher performance scores. Themore » effectiveness of the proposed feedback controller is demonstrated using high-fidelity computational fluid dynamics simulations of a small wind farm.« less

Potential economic benefits of adapting agricultural production systems to future climate change

USGS Publications Warehouse

Fagre, Daniel B.; Pederson, Gregory; Bengtson, Lindsey E.; Prato, Tony; Qui, Zeyuan; Williams, Jimmie R.

2010-01-01

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960–2005) and future climate period (2006–2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO2 emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs to future climate change is advantageous (i.e., NFI with adaptation is superior to NFI without adaptation based on SERF), in six of the nine cases in which adaptation is advantageous, NFI with adaptation in the future climate period is inferior to NFI in the historical climate period. Therefore, adaptation of APSs to future climate change in Flathead Valley is insufficient to offset the adverse impacts on NFI of such change.

Potential economic benefits of adapting agricultural production systems to future climate change.

PubMed

Prato, Tony; Zeyuan, Qiu; Pederson, Gregory; Fagre, Dan; Bengtson, Lindsey E; Williams, Jimmy R

2010-03-01

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960-2005) and future climate period (2006-2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO(2) emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs to future climate change is advantageous (i.e., NFI with adaptation is superior to NFI without adaptation based on SERF), in six of the nine cases in which adaptation is advantageous, NFI with adaptation in the future climate period is inferior to NFI in the historical climate period. Therefore, adaptation of APSs to future climate change in Flathead Valley is insufficient to offset the adverse impacts on NFI of such change.

Impact of increasing milk production on whole farm environmental management

USDA-ARS?s Scientific Manuscript database

Increasing herd milk production can provide both economic benefit to the producer and environmental benefit to society. Simulated dairy farms with average annual herd productions from 16,000 to 30,000 lb/cow illustrate that increasing milk yield per cow improves feed efficiency, reduces feed costs a...

Computer simulation of energy use, greenhouse gas emissions and process economics of the fluid milk process

USDA-ARS?s Scientific Manuscript database

On-farm activities associated with fluid milk production contribute approximately 70% of total greenhouse gas (GHG) emissions while off-farm activities arising from milk processing, packaging, and refrigeration, contribute the remainder in the form of energy-related carbon dioxide (CO2) emissions. W...

Simulating landscape catena effects in no-till dryland agroecosystems using GPFARM

USDA-ARS?s Scientific Manuscript database

Alternative agricultural management systems in the semi-arid Great Plains are receiving increasing attention. GPFARM is a farm/ranch decision support system (DSS) designed to assist in strategic management planning for land units from the field to the whole-farm level. This study evaluated the site...

Review of Reactive Power Dispatch Strategies for Loss Minimization in a DFIG-based Wind Farm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Baohua; Hu, Weihao; Hou, Peng

This study reviews and compares the performance of reactive power dispatch strategies for the loss minimization of Doubly Fed Induction Generator (DFIG)-based Wind Farms (WFs). Twelve possible combinations of three WF level reactive power dispatch strategies and four Wind Turbine (WT) level reactive power control strategies are investigated. All of the combined strategies are formulated based on the comprehensive loss models of WFs, including the loss models of DFIGs, converters, filters, transformers, and cables of the collection system. Optimization problems are solved by a Modified Particle Swarm Optimization (MPSO) algorithm. The effectiveness of these strategies is evaluated by simulations onmore » a carefully designed WF under a series of cases with different wind speeds and reactive power requirements of the WF. The wind speed at each WT inside the WF is calculated using the Jensen wake model. The results show that the best reactive power dispatch strategy for loss minimization comes when the WF level strategy and WT level control are coordinated and the losses from each device in the WF are considered in the objective.« less

Review of Reactive Power Dispatch Strategies for Loss Minimization in a DFIG-based Wind Farm

DOE PAGES

Zhang, Baohua; Hu, Weihao; Hou, Peng; ...

2017-06-27

This study reviews and compares the performance of reactive power dispatch strategies for the loss minimization of Doubly Fed Induction Generator (DFIG)-based Wind Farms (WFs). Twelve possible combinations of three WF level reactive power dispatch strategies and four Wind Turbine (WT) level reactive power control strategies are investigated. All of the combined strategies are formulated based on the comprehensive loss models of WFs, including the loss models of DFIGs, converters, filters, transformers, and cables of the collection system. Optimization problems are solved by a Modified Particle Swarm Optimization (MPSO) algorithm. The effectiveness of these strategies is evaluated by simulations onmore » a carefully designed WF under a series of cases with different wind speeds and reactive power requirements of the WF. The wind speed at each WT inside the WF is calculated using the Jensen wake model. The results show that the best reactive power dispatch strategy for loss minimization comes when the WF level strategy and WT level control are coordinated and the losses from each device in the WF are considered in the objective.« less

The Development of a Model Design to Assess Instruction in Farm Management in Terms of Economic Returns and the Understanding of Economic Principles.

ERIC Educational Resources Information Center

Rolloff, John August

The records of 27 farm operators participating in farm business analysis programs in 5 Ohio schools were studied to develop and test a model for determining the influence of the farm business analysis phase of vocational agriculture instruction in farm management. Economic returns were measured as ratios between 1965 program inputs and outputs…

Multi-agent modelling framework for water, energy and other resource networks

NASA Astrophysics Data System (ADS)

Knox, S.; Selby, P. D.; Meier, P.; Harou, J. J.; Yoon, J.; Lachaut, T.; Klassert, C. J. A.; Avisse, N.; Mohamed, K.; Tomlinson, J.; Khadem, M.; Tilmant, A.; Gorelick, S.

2015-12-01

Bespoke modelling tools are often needed when planning future engineered interventions in the context of various climate, socio-economic and geopolitical futures. Such tools can help improve system operating policies or assess infrastructure upgrades and their risks. A frequently used approach is to simulate and/or optimise the impact of interventions in engineered systems. Modelling complex infrastructure systems can involve incorporating multiple aspects into a single model, for example physical, economic and political. This presents the challenge of combining research from diverse areas into a single system effectively. We present the Pynsim 'Python Network Simulator' framework, a library for building simulation models capable of representing, the physical, institutional and economic aspects of an engineered resources system. Pynsim is an open source, object oriented code aiming to promote integration of different modelling processes through a single code library. We present two case studies that demonstrate important features of Pynsim's design. The first is a large interdisciplinary project of a national water system in the Middle East with modellers from fields including water resources, economics, hydrology and geography each considering different facets of a multi agent system. It includes: modelling water supply and demand for households and farms; a water tanker market with transfer of water between farms and households, and policy decisions made by government institutions at district, national and international level. This study demonstrates that a well-structured library of code can provide a hub for development and act as a catalyst for integrating models. The second focuses on optimising the location of new run-of-river hydropower plants. Using a multi-objective evolutionary algorithm, this study analyses different network configurations to identify the optimal placement of new power plants within a river network. This demonstrates that Pynsim can be used to evaluate a multitude of topologies for identifying the optimal location of infrastructure investments. Pynsim is available on GitHub or via standard python installer packages such as pip. It comes with several examples and online documentation, making it attractive for those less experienced in software engineering.

Pathways to sustainable intensification through crop water management

NASA Astrophysics Data System (ADS)

MacDonald, Graham K.; D'Odorico, Paolo; Seekell, David A.

2016-09-01

How much could farm water management interventions increase global crop production? This is the central question posed in a global modelling study by Jägermeyr et al (2016 Environ. Res. Lett. 11 025002). They define the biophysical realm of possibility for future gains in crop production related to agricultural water practices—enhancing water availability to crops and expanding irrigation by reducing non-productive water consumption. The findings of Jägermeyr et al offer crucial insight on the potential for crop water management to sustainably intensify agriculture, but they also provide a benchmark to consider the broader role of sustainable intensification targets in the global food system. Here, we reflect on how the global crop water management simulations of Jägermeyr et al could interact with: (1) farm size at more local scales, (2) downstream water users at the river basin scale, as well as (3) food trade and (4) demand-side food system strategies at the global scale. Incorporating such cross-scale linkages in future research could highlight the diverse pathways needed to harness the potential of farm-level crop water management for a more productive and sustainable global food system.

Observations of Near-Surface Relative Humidity in a Wind Turbine Array Boundary Layer Using an Instrumented Unmanned Aerial System

NASA Astrophysics Data System (ADS)

Adkins, K. A.; Sescu, A.

2016-12-01

Simulation and modeling have shown that wind farms have an impact on the near-surface atmospheric boundary layer (ABL) as turbulent wakes generated by the turbines enhance vertical mixing. These changes alter downstream atmospheric properties. With a large portion of wind farms hosted within an agricultural context, changes to the environment can potentially have secondary impacts such as to the productivity of crops. With the exception of a few observational data sets that focus on the impact to near-surface temperature, little to no observational evidence exists. These few studies also lack high spatial resolution due to their use of a limited number of meteorological towers or remote sensing techniques. This study utilizes an instrumented small unmanned aerial system (sUAS) to gather in-situ field measurements from two Midwest wind farms, focusing on the impact that large utility-scale wind turbines have on relative humidity. Wind turbines are found to differentially alter the relative humidity in the downstream, spanwise and vertical directions under a variety of atmospheric stability conditions.

Modelling the Wind-Borne Spread of Highly Pathogenic Avian Influenza Virus between Farms

PubMed Central

Ssematimba, Amos; Hagenaars, Thomas J.; de Jong, Mart C. M.

2012-01-01

A quantitative understanding of the spread of contaminated farm dust between locations is a prerequisite for obtaining much-needed insight into one of the possible mechanisms of disease spread between farms. Here, we develop a model to calculate the quantity of contaminated farm-dust particles deposited at various locations downwind of a source farm and apply the model to assess the possible contribution of the wind-borne route to the transmission of Highly Pathogenic Avian Influenza virus (HPAI) during the 2003 epidemic in the Netherlands. The model is obtained from a Gaussian Plume Model by incorporating the dust deposition process, pathogen decay, and a model for the infection process on exposed farms. Using poultry- and avian influenza-specific parameter values we calculate the distance-dependent probability of between-farm transmission by this route. A comparison between the transmission risk pattern predicted by the model and the pattern observed during the 2003 epidemic reveals that the wind-borne route alone is insufficient to explain the observations although it could contribute substantially to the spread over short distance ranges, for example, explaining 24% of the transmission over distances up to 25 km. PMID:22348042

Modelling the wind-borne spread of highly pathogenic avian influenza virus between farms.

PubMed

Ssematimba, Amos; Hagenaars, Thomas J; de Jong, Mart C M

2012-01-01

A quantitative understanding of the spread of contaminated farm dust between locations is a prerequisite for obtaining much-needed insight into one of the possible mechanisms of disease spread between farms. Here, we develop a model to calculate the quantity of contaminated farm-dust particles deposited at various locations downwind of a source farm and apply the model to assess the possible contribution of the wind-borne route to the transmission of Highly Pathogenic Avian Influenza virus (HPAI) during the 2003 epidemic in the Netherlands. The model is obtained from a Gaussian Plume Model by incorporating the dust deposition process, pathogen decay, and a model for the infection process on exposed farms. Using poultry- and avian influenza-specific parameter values we calculate the distance-dependent probability of between-farm transmission by this route. A comparison between the transmission risk pattern predicted by the model and the pattern observed during the 2003 epidemic reveals that the wind-borne route alone is insufficient to explain the observations although it could contribute substantially to the spread over short distance ranges, for example, explaining 24% of the transmission over distances up to 25 km.

Assessment of 1.5°C and 2°C climate change scenarios impact on wheat production in Tunisia

NASA Astrophysics Data System (ADS)

Bergaoui, karim; Belhaj Fraj, Makram; Zaaboul, Rashyd; Allen, Myles; Mitchell, Dann; Schleussner, Carl-Friedrich; Saeed, Fahad; Mc Donnell, Rachael

2017-04-01

Wheat is the main staple crop in North Africa region and contributes the most to food security. It is almost entirely grown under rainfed conditions and its yield is highly impacted by the climate variability, e. g. dry winters, a late autumn or late spring. Irregular rainfall or drought events particularly at key stages of the growing season, lead to both early and terminal wheat stresses and high inter-year variation in yield. The goal of this study was to explore the impacts of future climate on wheat production in Tunisia using an ensemble of regional bias corrected climate models outputs for the 1.5°C and 2°C warming above the pre-industrial levels. By examining the outputs on wheat yield levels the study would help answer the question of whether the ambitious climate change mitigation efforts involved in stabilizing temperatures at 1.5°C would bring the cereal yields needed in North Africa. Tunisia was chosen as the focus country because its wheat systems are found across a wide diversity in biophysical and farming conditions so giving insight on more localized effects. Data availability across a wide range of wheat management systems from subsistence farming systems to highly mechanized agribusinesses also supported work here as model results could be readily validated for the historical period. Two scenarios were obtained using the RCP2.6 as boundary conditions for 1.5 scenario and a weighted combination of RCP2.6 and RCP4.5 for the 2°C scenario using their respective CO2 levels in the future. We calibrated and validated a dynamical crop model, DSSAT, to simulate the national wheat production and to understand the impact of drought on growth and development that causes yield variation. DSSAT simulations were driven by CHIRPS and ERA-Interim reanalysis data as daily climate forcings. The simulations were validated in a set of farmer fields which were representative of the dominant cropping systems in the country. Then, the model was validated with 10 years' state-level production data. Finally, we forced the crop model with HAPPI bias corrected outputs using ISI-MIP approach where the trend and the long-term mean are well represented and we assessed the impact of each scenario on the wheat production at the national level. The results highlighted a difference in wheat yield in some biophysical areas and farming systems. This insight is important as countries develop mitigation and adaptation strategies as the impact costs can be included.

Comparing model-based predictions of a wind turbine wake to LiDAR measurements in complex terrain

NASA Astrophysics Data System (ADS)

Kay, Andrew; Jones, Paddy; Boyce, Dean; Bowman, Neil

2013-04-01

The application of remote sensing techniques to the measurement of wind characteristics offers great potential to accurately predict the atmospheric boundary layer flow (ABL) and its interactions with wind turbines. An understanding of these interactions is important for optimizing turbine siting in wind farms and improving the power performance and lifetime of individual machines. In particular, Doppler wind Light Detection and Ranging (LiDAR) can be used to remotely measure the wind characteristics (speed, direction and turbulence intensity) approaching a rotor. This information can be utilised to improve turbine lifetime (advanced detection of incoming wind shear, wind veer and extreme wind conditions, such as gusts) and optimise power production (improved yaw, pitch and speed control). LiDAR can also make detailed measurements of the disturbed wind profile in the wake, which can damage surrounding turbines and reduce efficiency. These observational techniques can help engineers better understand and model wakes to optimize turbine spacing in large wind farms, improving efficiency and reducing the cost of energy. NEL is currently undertaking research to measure the disturbed wind profile in the wake of a 950 kW wind turbine using a ZephIR Dual Mode LiDAR at its Myres Hill wind turbine test site located near Glasgow, Scotland. Myres Hill is moderately complex terrain comprising deep peat, low lying grass and heathers, localised slopes and nearby forest, approximately 2 km away. Measurements have been obtained by vertically scanning at 10 recorded heights across and above the rotor plane to determine the wind speed, wind direction and turbulence intensity profiles. Measurement stations located at various rotor diameters downstream of the turbine were selected in an attempt to capture the development of the wake and its recovery towards free stream conditions. Results of the measurement campaign will also highlight how the wake behaves as a result of sudden gusts or rapid changes in wind direction. NEL has carried out simulations to model the wake of the turbine using Computational Fluid Dynamics (CFD) software provided by ANSYS Inc. The model incorporates a simple actuator disk concept to model the turbine and its wake, typical of that used in many commercial wind farm optimization tools. The surrounding terrain, including the forestry is modelled allowing an investigation of the wake-terrain interactions occurring across the site. The overall aim is to compare the LiDAR measurements with simulated data to assess the quality of the model and its sensitivity to variables such as mesh size and turbulence/forestry modelling techniques. Knowledge acquired from the study will help to define techniques for combining LiDAR measurements with CFD modelling to improve predictions of wake losses in large wind farms and hence, energy production. In addition, the impact of transient wind conditions on the results of predictions based on idealised, steady state models has been examined.

Adding Complex Terrain and Stable Atmospheric Condition Capability to the OpenFOAM-based Flow Solver of the Simulator for On/Offshore Wind Farm Applications (SOWFA): Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Churchfield, M. J.; Sang, L.; Moriarty, P. J.

This paper describes changes made to NREL's OpenFOAM-based wind plant aerodynamics solver such that it can compute the stably stratified atmospheric boundary layer and flow over terrain. Background about the flow solver, the Simulator for Off/Onshore Wind Farm Applications (SOWFA) is given, followed by details of the stable stratification/complex terrain modifications to SOWFA, along with somepreliminary results calculations of a stable atmospheric boundary layer and flow over a simply set of hills.

Adding Complex Terrain and Stable Atmospheric Condition Capability to the Simulator for On/Offshore Wind Farm Applications (SOWFA) (Presentation)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Churchfield, M. J.

This presentation describes changes made to NREL's OpenFOAM-based wind plant aerodynamics solver so that it can compute the stably stratified atmospheric boundary layer and flow over terrain. Background about the flow solver, the Simulator for Off/Onshore Wind Farm Applications (SOWFA) is given, followed by details of the stable stratification/complex terrain modifications to SOWFA, along with some preliminary results calculations of a stable atmospheric boundary layer and flow over a simple set of hills.

Modeling Commercial Freshwater Turtle Production on US Farms for Pet and Meat Markets

PubMed Central

Mali, Ivana; Wang, Hsiao-Hsuan; Grant, William E.; Feldman, Mark; Forstner, Michael R. J.

2015-01-01

Freshwater turtles are being exploited for meat, eggs, traditional medicine, and pet trade. As a response, turtle farming became a booming aquaculture industry in the past two decades, specifically in the southeastern states of the United States of America (US) and across Southeast Asia. However, US turtle farms are currently producing turtles only for the pet trade while commercial trappers remain focused on catching the largest individuals from the wild. In our analyses we have created a biological and economic model that describes farming operations on a representative turtle farm in Louisiana. We first modeled current production of hatchling and yearling red-eared slider turtles (Trachemys scripta elegans) (i.e., traditional farming) for foreign and domestic pet markets, respectively. We tested the possibility of harvesting adult turtles from the breeding stock for sale to meat markets to enable alternative markets for the farmers, while decreasing the continued pressures on wild populations (i.e., non-traditional farming). Our economic model required current profit requirements of ~$13/turtle or ~$20.31/kg of meat from non-traditional farming in order to acquire the same profit as traditional farming, a value which currently exceeds market values of red-eared sliders. However, increasing competition with Asian turtle farms and decreasing hatchling prices may force the shift in the US toward producing turtles for meat markets. In addition, our model can be modified and applied to more desirable species on the meat market once more knowledge is acquired about species life histories and space requirements under farmed conditions. PMID:26407157

Modeling Commercial Freshwater Turtle Production on US Farms for Pet and Meat Markets.

PubMed

Mali, Ivana; Wang, Hsiao-Hsuan; Grant, William E; Feldman, Mark; Forstner, Michael R J

2015-01-01

Freshwater turtles are being exploited for meat, eggs, traditional medicine, and pet trade. As a response, turtle farming became a booming aquaculture industry in the past two decades, specifically in the southeastern states of the United States of America (US) and across Southeast Asia. However, US turtle farms are currently producing turtles only for the pet trade while commercial trappers remain focused on catching the largest individuals from the wild. In our analyses we have created a biological and economic model that describes farming operations on a representative turtle farm in Louisiana. We first modeled current production of hatchling and yearling red-eared slider turtles (Trachemys scripta elegans) (i.e., traditional farming) for foreign and domestic pet markets, respectively. We tested the possibility of harvesting adult turtles from the breeding stock for sale to meat markets to enable alternative markets for the farmers, while decreasing the continued pressures on wild populations (i.e., non-traditional farming). Our economic model required current profit requirements of ~$13/turtle or ~$20.31/kg of meat from non-traditional farming in order to acquire the same profit as traditional farming, a value which currently exceeds market values of red-eared sliders. However, increasing competition with Asian turtle farms and decreasing hatchling prices may force the shift in the US toward producing turtles for meat markets. In addition, our model can be modified and applied to more desirable species on the meat market once more knowledge is acquired about species life histories and space requirements under farmed conditions.

Data-driven RANS for simulations of large wind farms

NASA Astrophysics Data System (ADS)

Iungo, G. V.; Viola, F.; Ciri, U.; Rotea, M. A.; Leonardi, S.

2015-06-01

In the wind energy industry there is a growing need for real-time predictions of wind turbine wake flows in order to optimize power plant control and inhibit detrimental wake interactions. To this aim, a data-driven RANS approach is proposed in order to achieve very low computational costs and adequate accuracy through the data assimilation procedure. The RANS simulations are implemented with a classical Boussinesq hypothesis and a mixing length turbulence closure model, which is calibrated through the available data. High-fidelity LES simulations of a utility-scale wind turbine operating with different tip speed ratios are used as database. It is shown that the mixing length model for the RANS simulations can be calibrated accurately through the Reynolds stress of the axial and radial velocity components, and the gradient of the axial velocity in the radial direction. It is found that the mixing length is roughly invariant in the very near wake, then it increases linearly with the downstream distance in the diffusive region. The variation rate of the mixing length in the downstream direction is proposed as a criterion to detect the transition between near wake and transition region of a wind turbine wake. Finally, RANS simulations were performed with the calibrated mixing length model, and a good agreement with the LES simulations is observed.

Lidar-based wake tracking for closed-loop wind farm control

NASA Astrophysics Data System (ADS)

Raach, Steffen; Schlipf, David; Cheng, Po Wen

2016-09-01

This work presents two advancements towards closed-loop wake redirecting of a wind turbine. First, a model-based estimation approach is presented which uses a nacelle-based lidar system facing downwind to obtain information about the wake. A reduced order wake model is described which is then used in the estimation to track the wake. The tracking is demonstrated with lidar measurement data from an offshore campaign and with simulated lidar data from a SOWFA simulation. Second, a controller for closed-loop wake steering is presented. It uses the wake tracking information to set the yaw actuator of the wind turbine to redirect the wake to a desired position. Altogether, this paper aims to present the concept of closed-loop wake redirecting and gives a possible solution to it.

Great Lakes O shore Wind Project: Utility and Regional Integration Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sajadi, Amirhossein; Loparo, Kenneth A.; D'Aquila, Robert

This project aims to identify transmission system upgrades needed to facilitate offshore wind projects as well as operational impacts of offshore generation on operation of the regional transmission system in the Great Lakes region. A simulation model of the US Eastern Interconnection was used as the test system as a case study for investigating the impact of the integration of a 1000MW offshore wind farm operating in Lake Erie into FirstEnergy/PJM service territory. The findings of this research provide recommendations on offshore wind integration scenarios, the locations of points of interconnection, wind profile modeling and simulation, and computational methods tomore » quantify performance, along with operating changes and equipment upgrades needed to mitigate system performance issues introduced by an offshore wind project.« less

Can biosecurity and local network properties predict pathogen species richness in the salmonid industry?

PubMed Central

More, Simon J.; Geoghegan, Fiona; McManus, Catherine; Hill, Ashley E.; Martínez-López, Beatriz

2018-01-01

Salmonid farming in Ireland is mostly organic, which implies limited disease treatment options. This highlights the importance of biosecurity for preventing the introduction and spread of infectious agents. Similarly, the effect of local network properties on infection spread processes has rarely been evaluated. In this paper, we characterized the biosecurity of salmonid farms in Ireland using a survey, and then developed a score for benchmarking the disease risk of salmonid farms. The usefulness and validity of this score, together with farm indegree (dichotomized as ≤ 1 or > 1), were assessed through generalized Poisson regression models, in which the modeled outcome was pathogen richness, defined here as the number of different diseases affecting a farm during a year. Seawater salmon (SW salmon) farms had the highest biosecurity scores with a median (interquartile range) of 82.3 (5.4), followed by freshwater salmon (FW salmon) with 75.2 (8.2), and freshwater trout (FW trout) farms with 74.8 (4.5). For FW salmon and trout farms, the top ranked model (in terms of leave-one-out information criteria, looic) was the null model (looic = 46.1). For SW salmon farms, the best ranking model was the full model with both predictors and their interaction (looic = 33.3). Farms with a higher biosecurity score were associated with lower pathogen richness, and farms with indegree > 1 (i.e. more than one fish supplier) were associated with increased pathogen richness. The effect of the interaction between these variables was also important, showing an antagonistic effect. This would indicate that biosecurity effectiveness is achieved through a broader perspective on the subject, which includes a minimization in the number of suppliers and hence in the possibilities for infection to enter a farm. The work presented here could be used to elaborate indicators of a farm’s disease risk based on its biosecurity score and indegree, to inform risk-based disease surveillance and control strategies for private and public stakeholders. PMID:29381760

Power Flow Simulations of a More Renewable California Grid Utilizing Wind and Solar Insolation Forecasting

NASA Astrophysics Data System (ADS)

Hart, E. K.; Jacobson, M. Z.; Dvorak, M. J.

2008-12-01

Time series power flow analyses of the California electricity grid are performed with extensive addition of intermittent renewable power. The study focuses on the effects of replacing non-renewable and imported (out-of-state) electricity with wind and solar power on the reliability of the transmission grid. Simulations are performed for specific days chosen throughout the year to capture seasonal fluctuations in load, wind, and insolation. Wind farm expansions and new wind farms are proposed based on regional wind resources and time-dependent wind power output is calculated using a meteorological model and the power curves of specific wind turbines. Solar power is incorporated both as centralized and distributed generation. Concentrating solar thermal plants are modeled using local insolation data and the efficiencies of pre-existing plants. Distributed generation from rooftop PV systems is included using regional insolation data, efficiencies of common PV systems, and census data. The additional power output of these technologies offsets power from large natural gas plants and is balanced for the purposes of load matching largely with hydroelectric power and by curtailment when necessary. A quantitative analysis of the effects of this significant shift in the electricity portfolio of the state of California on power availability and transmission line congestion, using a transmission load-flow model, is presented. A sensitivity analysis is also performed to determine the effects of forecasting errors in wind and insolation on load-matching and transmission line congestion.

Targeting the impact of agri-environmental policy - Future scenarios in two less favoured areas in Portugal.

PubMed

Jones, Nadia; Fleskens, Luuk; Stroosnijder, Leo

2016-10-01

Targeting agri-environmental measures (AEM) improves their effectiveness in the delivery of public goods, provided the necessary coordination with other incentives. In less favoured areas (LFA) measures focusing on the conservation of extensive farming contribute to sustainable land management in these areas. In this paper we investigate the implementation of a possible AEM supporting the improvement of permanent pastures coordinated with the extensive livestock and single farm payments actually in place. Through applying a spatially-explicit mixed integer optimisation model we simulate future land use scenarios for two less favoured areas in Portugal (Centro and Alentejo) considering two policy scenarios: a 'targeted AEM', and a 'non-targeted AEM'. We then compare the results with a 'basic policy' option (reflecting a situation without AEM). This is done with regard to landscape-scale effects on the reduction of fire hazard and erosion risk, as well as effects on farm income. The results show that an AEM for permanent pastures would be more cost-effective for erosion and fire hazard mitigation if implemented within a spatially targeted framework. However when cost-effectiveness is assessed with other indicators (e.g. net farm income and share of grazing livestock) 'non-targeted AEM' implementation delivers the best outcome in Alentejo. In Centro the implementation of an AEM involves important losses of income compared to the 'basic policy'. 'Targeted AEM' tends to favour farms in very marginal conditions, i.e. targeting is demonstrated to perform best in landscapes where spatial heterogeneity is higher. The results also show the risk of farm abandonment in the two studied less favoured areas: in all three scenarios more than 30% of arable land is deemed to be abandoned. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modelling Nitrogen Cycling in a Mariculture Ecosystem as a Tool to Evaluate its Outflow

NASA Astrophysics Data System (ADS)

Lefebvre, S.; Bacher, C.; Meuret, A.; Hussenot, J.

2001-03-01

A model was constructed to describe an intensive mariculture ecosystem growing sea bass ( Dicentrarchus labrax), located in the salt marshes of the Fiers d'Ars Bay on the French Atlantic coast, in order to assess nitrogen cycling within the system and nitrogen outflow from the system. The land-based system was separated into three main compartments: a seawater reservoir, fish ponds and a lagoon (sedimentation pond). Three submodels were built for simulation purposes: (1) a hydrological submodel which simulated water exchange; (2) a fish growth and excretion bioenergetic submodel; and (3) a nitrogen compound transformation and loss submodel (i.e. ammonification, nitrification and assimilation processes). A two-year sampling period of nitrogen water quality concentrations and fish growth was used to validate the model. The model fitted the observations of dissolved nitrogen components, fish growth and water fluxes on a daily basis in all the compartments. The dissolved inorganic nitrogen ranged widely and over time from 0·5 to 9 g N m -3within the system, depending on seawater supply and water temperature, without affecting fish growth. Fish feed was the most important input of nitrogen into the system. The mean average input of nitrogen in the feed was 205 kg N day -1, of which 19% was retained by fish, 4% accumulated in the sediment and 61% flowed from the system as dissolved components. The farm represented about 25% of the total dissolved nitrogen export from the bay, although the farm surface area was 100 times smaller than that of the bay.

An economic analysis of hyperketonemia testing and propylene glycol treatment strategies in early lactation dairy cattle.

PubMed

McArt, J A A; Nydam, D V; Oetzel, G R; Guard, C L

2014-11-01

The purpose was to develop stochastic economic models which address variation in disease risks and costs in order to evaluate different simulated on-farm testing and propylene glycol (PG) treatment strategies based on herd hyperketonemia (HYK) incidence during the first 30 DIM. Data used in model development concerning the difference in health and production consequences between HYK and non-ketotic cows were based on results from 10 studies representing over 13,000 cows from 833 dairy farms in North America, Canada, and Europe. Inputs for PG associated variables were based on a large field trial using cows from 4 free-stall dairy herds (2 in New York and 2 in Wisconsin). Four simulated on-farm testing and treatment strategies were analyzed at herd HYK incidences ranging from 5% to 80% and included: 1) treating all cows with 5d of PG starting at 5 DIM, 2) testing all cows for HYK 1 day per week (e.g. Mondays) from 3 to 16 DIM and treating all positive cows with 5d of oral PG, 3) testing all cows for HYK 2 days per week (e.g. Mondays and Thursdays) from 3 to 9 DIM and treating all positive cows with 5d of oral PG, and 4) testing all cows for HYK 3 days per week (e.g. Mondays, Wednesdays, and Fridays) from 3 to 16 DIM and treating all positive cows with 5d of oral PG. Cost-benefit analysis included the costs associated with labor to test cows, β-hydroxybutyrate test strips, labor to treat cows, PG, and the associated gain in milk production, decrease in DA and early removal risks of PG treated HYK positive cows compared to non-treated HYK positive cows. Stochastic models were developed to account for variability in the distribution of input variables. Per 100 fresh cows in a herd with an HYK incidence of 40%, the mean economic benefits of the 4 different strategies were $1088, $744, $1166, and $760, respectively. Testing cows 2 days per week from 3 to 9 DIM was the most cost-effective strategy for herds with HYK incidences between 15% and 50%; above 50%, treating all fresh cows with 5d of PG was the most cost-effective strategy. These results show that for herds similar to those used in model, when herd HYK incidences rise above 25%, almost any HYK testing and treatment protocol will be economically beneficial for the farm. Copyright © 2014 Elsevier B.V. All rights reserved.

Turbulent flow and scalar transport in a large wind farm

NASA Astrophysics Data System (ADS)

Porte-Agel, F.; Markfort, C. D.; Zhang, W.

2012-12-01

Wind energy is one of the fastest growing sources of renewable energy world-wide, and it is expected that many more large-scale wind farms will be built and cover a significant portion of land and ocean surfaces. By extracting kinetic energy from the atmospheric boundary layer and converting it to electricity, wind farms may affect the transport of momentum, heat, moisture and trace gases (e.g. CO_2) between the atmosphere and the land surface locally and globally. Understanding wind farm-atmosphere interaction is complicated by the effects of turbine array configuration, wind farm size, land-surface characteristics, and atmospheric thermal stability. A wind farm of finite length may be modeled as an added roughness or as a canopy in large-scale weather and climate models. However, it is not clear which analogy is physically more appropriate. Also, surface scalar flux is affected by wind farms and needs to be properly parameterized in meso-scale and/or high-resolution numerical models. Experiments involving model wind farms, with perfectly aligned and staggered configurations, having the same turbine distribution density, were conducted in a thermally-controlled boundary-layer wind tunnel. A neutrally stratified turbulent boundary layer was developed with a surface heat source. Measurements of the turbulent flow and fluxes over and through the wind farm were made using a custom x-wire/cold-wire anemometer; and surface scalar flux was measured with an array of surface-mounted heat flux sensors far within the quasi-developed region of the wind-farm. The turbulence statistics exhibit similar properties to those of canopy-type flows, but retain some characteristics of surface-layer flows in a limited region above the wind farms as well. The flow equilibrates faster and the overall momentum absorption is higher for the staggered compared to the aligned farm, which is consistent with canopy scaling and leads to a larger effective roughness. Although the overall surface heat flux change produced by the wind farms is found to be small, with a net reduction of 4% for the staggered wind farm and nearly zero change for the aligned wind farm, the highly heterogeneous spatial distribution of the surface heat flux, dependent on wind farm layout, is significant. This comprehensive first wind-tunnel dataset on turbulent flow and scalar transport in wind farms will be further used to develop and validate new parameterizations of surface fluxes in numerical models.

Quantifying the economic importance of irrigation water reuse in a Chilean watershed using an integrated agent-based model

NASA Astrophysics Data System (ADS)

Arnold, R. T.; Troost, Christian; Berger, Thomas

2015-01-01

Irrigation with surface water enables Chilean agricultural producers to generate one of the country's most important economic exports. The Chilean water code established tradable water rights as a mechanism to allocate water amongst farmers and other water-use sectors. It remains contested whether this mechanism is effective and many authors have raised equity concerns regarding its impact on water users. For example, speculative hoarding of water rights in expectations of their increasing value has been described. This paper demonstrates how farmers can hoard water rights as a risk management strategy for variable water supply, for example, due to the cycles of El Niño or as consequence of climate change. While farmers with insufficient water rights can rely on unclaimed water during conditions of normal water availability, drought years overproportionally impact on their supply of irrigation water and thereby farm profitability. This study uses a simulation model that consists of a hydrological balance model component and a multiagent farm decision and production component. Both model components are parameterized with empirical data, while uncertain parameters are calibrated. The study demonstrates a thorough quantification of parameter uncertainty, using global sensitivity analysis and multiple behavioral parameter scenarios.

Groundwater economics: An object-oriented foundation for integrated studies of irrigated agricultural systems

NASA Astrophysics Data System (ADS)

Steward, David R.; Peterson, Jeffrey M.; Yang, Xiaoying; Bulatewicz, Tom; Herrera-Rodriguez, Mauricio; Mao, Dazhi; Hendricks, Nathan

2009-05-01

An integrated foundation is presented to study the impacts of external forcings on irrigated agricultural systems. Individually, models are presented that simulate groundwater hydrogeology and econometric farm level crop choices and irrigated water use. The natural association between groundwater wells and agricultural parcels is employed to couple these models using geographic information science technology and open modeling interface protocols. This approach is used to study the collective action problem of the common pool. Three different policies (existing, regulation, and incentive based) are studied in the semiarid grasslands overlying the Ogallala Aquifer in the central United States. Results show that while regulation using the prior appropriation doctrine and incentives using a water buy-back program may each achieve the same level of water savings across the study region, each policy has a different impact on spatial patterns of groundwater declines and farm level economic activity. This represents the first time that groundwater and econometric models of irrigated agriculture have been integrated at the well-parcel level and provides methods for scientific investigation of this coupled natural-human system. Results are useful for science to inform decision making and public policy debate.

Fatigue minimising power reference control of a de-rated wind farm

NASA Astrophysics Data System (ADS)

Jensen, T. N.; Knudsen, T.; Bak, T.

2016-09-01

Modern wind farms (cluster of wind turbines) can be required to control the total power output to meet a set-point, and would then profit by minimising the structural loads and thereby the cost of energy. In this paper, we propose a new control strategy for a derated wind farm with the objective of maintaining a desired reference power production for the wind farm, while minimising the sum of fatigues on the wind turbines in steady-state. The controller outputs a vector of power references for the individual turbines. It exploits the positive correlation between fatigue and added turbulence to minimise fatigue indirectly by minimising the added turbulence. Simulated results for a wind farm with three turbines demonstrate the efficacy of the proposed solution by assessing the damage equivalent loads.

CWEX: Crop/wind-energy experiment: Observations of surface-layer, boundary-layer and mesoscale interactions with a wind farm

USDA-ARS?s Scientific Manuscript database

Large wind turbines perturb mean and turbulent wind characteristics, which modify fluxes between the vegetated surface and the lower boundary layer. While simulations have suggested that wind farms could create significant changes in surface fluxes of heat, momentum, moisture, and CO2 over hundreds ...

Crop/Wind-energy Experiment (CWEX): Observations of surface-layer, boundary-layer and mesoscale interactions with a wind farm

USDA-ARS?s Scientific Manuscript database

Perturbations of mean and turbulent wind characteristics by large wind turbines modify fluxes between the vegetated surface and the lower boundary layer. While simulations have suggested that wind farms could significantly change surface fluxes of heat, momentum, moisture, and CO2 over hundreds of s...

Development of FAST.Farm: A New Multiphysics Engineering Tool for Wind Farm Design and Analysis: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jonkman, Jason; Annoni, Jennifer; Hayman, Greg

2017-01-01

This paper presents the development of FAST.Farm, a new multiphysics tool applicable to engineering problems in research and industry involving wind farm performance and cost optimization that is needed to address the current underperformance, failures, and expenses plaguing the wind industry. Achieving wind cost-of-energy targets - which requires improvements in wind farm performance and reliability, together with reduced uncertainty and expenditures - has been eluded by the complicated nature of the wind farm design problem, especially the sophisticated interaction between atmospheric phenomena and wake dynamics and array effects. FAST.Farm aims to balance the need for accurate modeling of the relevantmore » physics for predicting power performance and loads while maintaining low computational cost to support a highly iterative and probabilistic design process and system-wide optimization. FAST.Farm makes use of FAST to model the aero-hydro-servo-elastics of distinct turbines in the wind farm, and it is based on some of the principles of the Dynamic Wake Meandering (DWM) model, but avoids many of the limitations of existing DWM implementations.« less

Applying Dynamic Energy Budget (DEB) theory to simulate growth and bio-energetics of blue mussels under low seston conditions

NASA Astrophysics Data System (ADS)

Rosland, R.; Strand, Ø.; Alunno-Bruscia, M.; Bacher, C.; Strohmeier, T.

2009-08-01

A Dynamic Energy Budget (DEB) model for simulation of growth and bioenergetics of blue mussels ( Mytilus edulis) has been tested in three low seston sites in southern Norway. The observations comprise four datasets from laboratory experiments (physiological and biometrical mussel data) and three datasets from in situ growth experiments (biometrical mussel data). Additional in situ data from commercial farms in southern Norway were used for estimation of biometrical relationships in the mussels. Three DEB parameters (shape coefficient, half saturation coefficient, and somatic maintenance rate coefficient) were estimated from experimental data, and the estimated parameters were complemented with parameter values from literature to establish a basic parameter set. Model simulations based on the basic parameter set and site specific environmental forcing matched fairly well with observations, but the model was not successful in simulating growth at the extreme low seston regimes in the laboratory experiments in which the long period of negative growth caused negative reproductive mass. Sensitivity analysis indicated that the model was moderately sensitive to changes in the parameter and initial conditions. The results show the robust properties of the DEB model as it manages to simulate mussel growth in several independent datasets from a common basic parameter set. However, the results also demonstrate limitations of Chl a as a food proxy for blue mussels and limitations of the DEB model to simulate long term starvation. Future work should aim at establishing better food proxies and improving the model formulations of the processes involved in food ingestion and assimilation. The current DEB model should also be elaborated to allow shrinking in the structural tissue in order to produce more realistic growth simulations during long periods of starvation.

Brazilian Soybean Production: Emergy Analysis with an Expanded Scope

ERIC Educational Resources Information Center

Ortega, Enrique; Cavalett, Otavio; Bonifacio, Robert; Watanabe, Marcos

2005-01-01

This article offers the results of emergy analysis used to evaluate four different soybean production systems in Brazil that were divided into two main categories: biological models (organic and ecological farms) and industrial models (green-revolution chemical farms and herbicide with no-tillage farms). The biological models show better…

Self-similarity and flow characteristics of vertical-axis wind turbine wakes: an LES study

NASA Astrophysics Data System (ADS)

Abkar, Mahdi; Dabiri, John O.

2017-04-01

Large eddy simulation (LES) is coupled with a turbine model to study the structure of the wake behind a vertical-axis wind turbine (VAWT). In the simulations, a tuning-free anisotropic minimum dissipation model is used to parameterise the subfilter stress tensor, while the turbine-induced forces are modelled with an actuator line technique. The LES framework is first validated in the simulation of the wake behind a model straight-bladed VAWT placed in the water channel and then used to study the wake structure downwind of a full-scale VAWT sited in the atmospheric boundary layer. In particular, the self-similarity of the wake is examined, and it is found that the wake velocity deficit can be well characterised by a two-dimensional multivariate Gaussian distribution. By assuming a self-similar Gaussian distribution of the velocity deficit, and applying mass and momentum conservation, an analytical model is developed and tested to predict the maximum velocity deficit downwind of the turbine. Also, a simple parameterisation of VAWTs for LES with very coarse grid resolutions is proposed, in which the turbine is modelled as a rectangular porous plate with the same thrust coefficient. The simulation results show that, after some downwind distance (x/D ≈ 6), both actuator line and rectangular porous plate models have similar predictions for the mean velocity deficit. These results are of particular importance in simulations of large wind farms where, due to the coarse spatial resolution, the flow around individual VAWTs is not resolved.

Trade-offs between pasture production and farmland bird conservation: exploration of options using a dynamic farm model.

PubMed

Sabatier, R; Teillard, F; Rossing, W A H; Doyen, L; Tichit, M

2015-05-01

In European grassland landscapes, grazing and mowing play a key role for the maintenance of high-quality habitats that host important bird populations. As grasslands are also key resources for cattle feeding, there is a need to develop management strategies that achieve the double objective of production and biodiversity conservation. The objective of this study was to use a modelling approach to generate recognisable patterns of bird dynamics in farms composed of different land use proportions, and to compare their production and ecological dimensions. We developed a dynamic model, which linked grassland management to bird population dynamics at the field and farm levels. The model was parameterised for two types of suckling farms corresponding to contrasting levels of grassland intensification and for two bird species of high conservation value. A viability algorithm was used to define and assess viable management strategies for production and ecological performance so as to draw the shape of the relationship between both types of performances for the two types of farms. Our results indicated that, at the farm level, there was a farming system effect with a negative and non-linear relationship linking performance. Improving bird population maintenance was less costly in extensive farms compared with intensive farms. At the field level, the model predicted the timing and intensity of land use, maximising either production or ecological performance. The results suggested that multi-objective grassland management would benefit from public policies that consider levels of organisation higher than the field level, such as the farm or the landscape.

Simple Patchy-Based Simulators Used to Explore Pondscape Systematic Dynamics

PubMed Central

Fang, Wei-Ta; Chou, Jui-Yu; Lu, Shiau-Yun

2014-01-01

Thousands of farm ponds disappeared on the tableland in Taoyuan County, Taiwan since 1920s. The number of farm ponds that have disappeared is 1,895 (37%), 2,667 ponds remain (52%), and only 537 (11%) new ponds were created within a 757 km2 area in Taoyuan, Taiwan between 1926 and 1960. In this study, a geographic information system (GIS) and logistic stepwise regression model were used to detect pond-loss rates and to understand the driving forces behind pondscape changes. The logistic stepwise regression model was used to develop a series of relationships between pondscapes affected by intrinsic driving forces (patch size, perimeter, and patch shape) and external driving forces (distance from the edge of the ponds to the edges of roads, rivers, and canals). The authors concluded that the loss of ponds was caused by pond intrinsic factors, such as pond perimeter; a large perimeter increases the chances of pond loss, but also increases the possibility of creating new ponds. However, a large perimeter is closely associated with circular shapes (lower value of the mean pond-patch fractal dimension [MPFD]), which characterize the majority of newly created ponds. The method used in this study might be helpful to those seeking to protect this unique landscape by enabling the monitoring of patch-loss problems by using simple patchy-based simulators. PMID:24466281

Large-Eddy Simulation of Atmospheric Boundary-Layer Flow Through a Wind Farm Sited on Topography

NASA Astrophysics Data System (ADS)

Shamsoddin, Sina; Porté-Agel, Fernando

2017-04-01

Large-eddy simulation (LES) has recently been well validated and applied in the context of wind turbines over flat terrain; however, to date its accuracy has not been tested systematically in the case of turbine-wake flows over topography. Here, we investigate the wake flow in a wind farm situated on hilly terrain using LES for a case where wind-tunnel experimental data are available. To this end, first boundary-layer flow is simulated over a two-dimensional hill in order to characterize the spatial distribution of the mean velocity and the turbulence statistics. A flow simulation is then performed through a wind farm consisting of five horizontal-axis wind turbines sited over the same hill in an aligned layout. The resulting flow characteristics are compared with the former case, i.e., without wind turbines. To assess the validity of the simulations, the results are compared with the wind-tunnel measurements. It is found that LES can reproduce the flow field effectively, and, specifically, the speed-up over the hilltop and the velocity deficit and turbulence intensity enhancement induced by the turbines are well captured by the simulations. Besides, the vertical profiles of the mean velocity and turbulence intensity at different streamwise positions match well those for the experiment. In addition, another numerical experiment is carried out to show how higher (and more realistic) thrust coefficients of the turbines lead to stronger wakes and, at the same time, higher turbulence intensities.

Saturn Apollo Program

NASA Image and Video Library

1963-05-10

The Marshall Space Flight Center (MSFC) played a crucial role in the development of the huge Saturn rockets that delivered humans to the moon in the 1960s. Many unique facilities existed at MSFC for the development and testing of the Saturn rockets. Affectionately nicknamed “The Arm Farm”, the Random Motion/ Lift-Off Simulator was one of those unique facilities. This facility was developed to test the swingarm mechanisms that were used to hold the rocket in position until lift-off. The Arm Farm provided the capability of testing the detachment and reconnection of various arms under brutally realistic conditions. The 18-acre facility consisted of more than a half dozen arm test positions and one position for testing access arms used by the Apollo astronauts. Each test position had two elements: a vehicle simulator for duplicating motions during countdown and launch; and a section duplicating the launch tower. The vehicle simulator duplicated the portion of the vehicle skin that contained the umbilical connections and personnel access hatches. Driven by a hydraulic servo system, the vehicle simulator produced relative motion between the vehicle and tower. On the Arm Farm, extreme environmental conditions (such as a launch scrub during an approaching Florida thunderstorm) could be simulated. The dramatic scenes that the Marshall engineers and technicians created at the Arm Farm permitted the gathering of crucial technical and engineering data to ensure a successful real time launch from the Kennedy Space Center.

Saturn Apollo Program

NASA Image and Video Library

1967-07-28

The Marshall Space Flight Center (MSFC) played a crucial role in the development of the huge Saturn rockets that delivered humans to the moon in the 1960s. Many unique facilities existed at MSFC for the development and testing of the Saturn rockets. Affectionately nicknamed “The Arm Farm”, the Random Motion/ Lift-Off Simulator was one of those unique facilities. This facility was developed to test the swingarm mechanisms that were used to hold the rocket in position until lift-off. The Arm Farm provided the capability of testing the detachment and reconnection of various arms under brutally realistic conditions. The 18-acre facility consisted of more than a half dozen arm test positions and one position for testing access arms used by the Apollo astronauts. Each test position had two elements: a vehicle simulator for duplicating motions during countdown and launch; and a section duplicating the launch tower. The vehicle simulator duplicated the portion of the vehicle skin that contained the umbilical connections and personnel access hatches. Driven by a hydraulic servo system, the vehicle simulator produced relative motion between the vehicle and tower. On the Arm Farm, extreme environmental conditions (such as a launch scrub during an approaching Florida thunderstorm) could be simulated. The dramatic scenes that the Marshall engineers and technicians created at the Arm Farm permitted the gathering of crucial technical and engineering data to ensure a successful real time launch from the Kennedy Space Center.

Developing COMET-Farm and the DayCent Model for California Specialty Crops

NASA Astrophysics Data System (ADS)

Steenwerth, K. L.; Barker, X. Z.; Carlson, M.; Killian, K.; Easter, M.; Swan, A.; Thompson, L.; Williams, S.; Paustian, K.

2016-12-01

Specialty crops are hugely important to the agricultural economy of California, which grows over 400 specialty crops and produces at least a third of the nations' vegetables and more than two thirds of its fruit and nut tree crops. Since the passage of AB32 Global Warming Solutions Act in 2006, the state has made strong investments in reducing greenhouse gas emissions and developing climate adaptation solutions. Most recently, Governor J. Brown (CA) has issued an executive order to establish reductions to 40% below 1990 levels. While agriculture in California is not regulated for greenhouse gas emissions under AB32, efforts are being made to develop tools to support practices that can enhance soil health and reduce greenhouse gas emissions. USDA-NRCS supports one such tool known as COMET-Farm, which is intended for future use with incentive programs and soil conservation plans managed by the agency. The underlying model that that simulates entity-scale greenhouse gas emissions in COMET-Farm is DayCent. Members of the California Climate Hub are collaborating with the Natural Resource Ecology Laboratory at Colorado State University in Fort Collins, CO to develop DayCent for 15 California specialty crops. These specialty crops include woody perennials like stone fruit like almonds and peaches, walnuts, citrus, wine grapes, raisins and table grapes. Annual specialty crops include cool season vegetables like lettuce and broccoli, tomatoes, and strawberries. DayCent has been parameterized for these crops using existing published and unpublished studies. Practice based information has also been gathered in consultation with growers. Aspects of the model have been developed for woody biomass production and competition between herbaceous vegetation and woody perennial crops. We will report on model performance for these crops and opportunities for model improvement.

Exploring economically and environmentally viable northeastern US dairy farm strategies for coping with rising corn grain prices.

PubMed

Ghebremichael, L T; Veith, T L; Cerosaletti, P E; Dewing, D E; Rotz, C A

2009-08-01

In 2008, corn grain prices rose $115/t of DM above the 2005 average. Such an increase creates tight marginal profits for small (<100) and medium-sized (100 to 199) dairy farms in the northeastern United States importing corn grain as animal feed supplement. Particularly in New York State, dairy farmers are attempting to avoid or minimize profit losses by growing more corn silage and reducing corn grain purchases. This study applies the Integrated Farm Systems Model to 1 small and 1 medium-sized New York State dairy farm to predict 1) sediment and P loss impacts from expanding corn fields, 2) benefits of no-till or cover cropping on corn fields, and 3) alternatives to the economic challenge of the current farming system as the price ratio of milk to corn grain continues to decline. Based on the simulation results, expanding corn silage production by 3% of the cultivated farm area increased sediment and sediment-bound P losses by 41 and 18%, respectively. Implementing no-till controlled about 84% of the erosion and about 75% of the sediment-bound P that would have occurred from the conventionally tilled, expanded corn production scenario. Implementing a conventionally tilled cover crop with the conventionally tilled, expanded corn production scenario controlled both erosion and sediment-bound P, but to a lesser extent than no-till corn with no cover crop. However, annual farm net return using cover crops was slightly less than when using no-till. Increasing on-farm grass productivity while feeding cows a high-quality, high-forage diet and precise dietary P levels offered dual benefits: 1) improved farm profitability from reduced purchases of dietary protein and P supplements, and 2) decreased runoff P losses from reduced P-levels in applied manure. Moreover, alternatives such as growing additional small grains on marginal lands and increasing milk production levels demonstrated great potential in increasing farm profitability. Overall, it is crucial that conservation measures such as no-till and cover cropping be implemented on new or existing corn lands as these areas often pose the highest threat for P losses through runoff. Although alternatives that would likely provide the largest net profit were evaluated one at a time to better quantify their individual impacts, combinations of these strategies, such as no-till corn plus a minimum-till cover crop, are recommended whenever feasible.

Hybrid RANS-LES using high order numerical methods

NASA Astrophysics Data System (ADS)

Henry de Frahan, Marc; Yellapantula, Shashank; Vijayakumar, Ganesh; Knaus, Robert; Sprague, Michael

2017-11-01

Understanding the impact of wind turbine wake dynamics on downstream turbines is particularly important for the design of efficient wind farms. Due to their tractable computational cost, hybrid RANS/LES models are an attractive framework for simulating separation flows such as the wake dynamics behind a wind turbine. High-order numerical methods can be computationally efficient and provide increased accuracy in simulating complex flows. In the context of LES, high-order numerical methods have shown some success in predictions of turbulent flows. However, the specifics of hybrid RANS-LES models, including the transition region between both modeling frameworks, pose unique challenges for high-order numerical methods. In this work, we study the effect of increasing the order of accuracy of the numerical scheme in simulations of canonical turbulent flows using RANS, LES, and hybrid RANS-LES models. We describe the interactions between filtering, model transition, and order of accuracy and their effect on turbulence quantities such as kinetic energy spectra, boundary layer evolution, and dissipation rate. This work was funded by the U.S. Department of Energy, Exascale Computing Project, under Contract No. DE-AC36-08-GO28308 with the National Renewable Energy Laboratory.

Assessing the impact of marine wind farms on birds through movement modelling.

PubMed

Masden, Elizabeth A; Reeve, Richard; Desholm, Mark; Fox, Anthony D; Furness, Robert W; Haydon, Daniel T

2012-09-07

Advances in technology and engineering, along with European Union renewable energy targets, have stimulated a rapid growth of the wind power sector. Wind farms contribute to carbon emission reductions, but there is a need to ensure that these structures do not adversely impact the populations that interact with them, particularly birds. We developed movement models based on observed avoidance responses of common eider Somateria mollissima to wind farms to predict, and identify potential measures to reduce, impacts. Flight trajectory data that were collected post-construction of the Danish Nysted offshore wind farm were used to parameterize competing models of bird movements around turbines. The model most closely fitting the observed data incorporated individual variation in the minimum distance at which birds responded to the turbines. We show how such models can contribute to the spatial planning of wind farms by assessing their extent, turbine spacing and configurations on the probability of birds passing between the turbines. Avian movement models can make new contributions to environmental assessments of wind farm developments, and provide insights into how to reduce impacts that can be identified at the planning stage.

Prospects for generating electricity by large onshore and offshore wind farms

NASA Astrophysics Data System (ADS)

Volker, Patrick J. H.; Hahmann, Andrea N.; Badger, Jake; Jørgensen, Hans E.

2017-03-01

The decarbonisation of energy sources requires additional investments in renewable technologies, including the installation of onshore and offshore wind farms. For wind energy to remain competitive, wind farms must continue to provide low-cost power even when covering larger areas. Inside very large wind farms, winds can decrease considerably from their free-stream values to a point where an equilibrium wind speed is reached. The magnitude of this equilibrium wind speed is primarily dependent on the balance between turbine drag force and the downward momentum influx from above the wind farm. We have simulated for neutral atmospheric conditions, the wind speed field inside different wind farms that range from small (25 km2) to very large (105 km2) in three regions with distinct wind speed and roughness conditions. Our results show that the power density of very large wind farms depends on the local free-stream wind speed, the surface characteristics, and the turbine density. In onshore regions with moderate winds the power density of very large wind farms reaches 1 W m-2, whereas in offshore regions with very strong winds it exceeds 3 W m-2. Despite a relatively low power density, onshore regions with moderate winds offer potential locations for very large wind farms. In offshore regions, clusters of smaller wind farms are generally preferable; under very strong winds also very large offshore wind farms become efficient.

Coupling of a distributed stakeholder-built system dynamics socio-economic model with SAHYSMOD for sustainable soil salinity management. Part 2: Model coupling and application

NASA Astrophysics Data System (ADS)

Inam, Azhar; Adamowski, Jan; Prasher, Shiv; Halbe, Johannes; Malard, Julien; Albano, Raffaele

2017-08-01

Many simulation models focus on simulating a single physical process and do not constitute balanced representations of the physical, social and economic components of a system. The present study addresses this challenge by integrating a physical (P) model (SAHYSMOD) with a group (stakeholder) built system dynamics model (GBSDM) through a component modeling approach based on widely applied tools such as MS Excel, Python and Visual Basic for Applications (VBA). The coupled model (P-GBSDM) was applied to test soil salinity management scenarios (proposed by stakeholders) for the Haveli region of the Rechna Doab Basin in Pakistan. Scenarios such as water banking, vertical drainage, canal lining, and irrigation water reallocation were simulated with the integrated model. Spatiotemporal maps and economic and environmental trade-off criteria were used to examine the effectiveness of the selected management scenarios. After 20 years of simulation, canal lining reduced soil salinity by 22% but caused an initial reduction of 18% in farm income, which requires an initial investment from the government. The government-sponsored Salinity Control and Reclamation Project (SCARP) is a short-term policy that resulted in a 37% increase in water availability with a 12% increase in farmer income. However, it showed detrimental effects on soil salinity in the long term, with a 21% increase in soil salinity due to secondary salinization. The new P-GBSDM was shown to be an effective platform for engaging stakeholders and simulating their proposed management policies while taking into account socioeconomic considerations. This was not possible using the physically based SAHYSMOD model alone.

Local infestation or long-distance migration? The seasonal recolonization of dairy farms by Stomoxys calcitrans (Diptera: Muscidae) in south central Ontario, Canada.

PubMed

Beresford, D V; Sutcliffe, J F

2009-04-01

Stable fly (Diptera: Muscidae) populations in south central Ontario, Canada, first occur on dairy farms in late spring, grow exponentially throughout the summer, and are frozen back each autumn. We examined the extent of overwinter persistence on 22 dairy farms in a 55- by 60-km region north of Lake Ontario that spans four climatic zones. Our overwintering sampling of larval habitat identified three farms located in the southern section of the study region as potential overwintering refugia. Using sticky trap catches to identify the timing of first spring appearance at each farm, we then tested two models of how local farm populations are reestablished annually: 1) stable flies disperse from local climatic refuges and colonize neighboring farms (the local source model); and 2) stable flies are carried into the study region by frontal weather systems (the distant source model). The timing of when stable flies first occurred at these farms supported a local source of dispersing colonists from a small proportion of local refuge farms. We discuss our results in terms of how yearly fluctuation in climate would affect refuge farm density in the region and how this, in turn, would shift the recolonization dynamic. Implications for controlling stable flies also are discussed.

Transition to farming more likely for small, conservative groups with property rights, but increased productivity is not essential

PubMed Central

Gallagher, Elizabeth M.; Shennan, Stephen J.; Thomas, Mark G.

2015-01-01

Theories for the origins of agriculture are still debated, with a range of different explanations offered. Computational models can be used to test these theories and explore new hypotheses; Bowles and Choi [Bowles S, Choi J-K (2013) Proc Natl Acad Sci USA 110(22):8830–8835] have developed one such model. Their model shows the coevolution of farming and farming-friendly property rights, and by including climate variability, replicates the timings for the emergence of these events seen in the archaeological record. Because the processes modeled occurred a long time ago, it can be difficult to justify exact parameter values; hence, we propose a fitting to idealized outcomes (FIO) method to explore the model’s parameter space in more detail. We have replicated the model of Bowles and Choi, and used the FIO method to identify complexities and interactions of the model previously unidentified. Our results indicate that the key parameters for the emergence of farming are group structuring, group size, conservatism, and farming-friendly property rights (lending further support to Bowles and Choi’s original proposal). We also find that although advantageous, it is not essential that farming productivity be greater than foraging productivity for farming to emerge. In addition, we highlight how model behaviors can be missed when gauging parameter sensitivity via a fix-all-but-one variation approach. PMID:26578766

Agent Based Model of Livestock Movements

NASA Astrophysics Data System (ADS)

Miron, D. J.; Emelyanova, I. V.; Donald, G. E.; Garner, G. M.

The modelling of livestock movements within Australia is of national importance for the purposes of the management and control of exotic disease spread, infrastructure development and the economic forecasting of livestock markets. In this paper an agent based model for the forecasting of livestock movements is presented. This models livestock movements from farm to farm through a saleyard. The decision of farmers to sell or buy cattle is often complex and involves many factors such as climate forecast, commodity prices, the type of farm enterprise, the number of animals available and associated off-shore effects. In this model the farm agent's intelligence is implemented using a fuzzy decision tree that utilises two of these factors. These two factors are the livestock price fetched at the last sale and the number of stock on the farm. On each iteration of the model farms choose either to buy, sell or abstain from the market thus creating an artificial supply and demand. The buyers and sellers then congregate at the saleyard where livestock are auctioned using a second price sealed bid. The price time series output by the model exhibits properties similar to those found in real livestock markets.

Estimating the sensitivity of passive surveillance for HPAI H5N1 in Bayelsa state, Nigeria.

PubMed

Ojimelukwe, Agatha E; Prakarnkamanant, Apisit; Rushton, Jonathan

2016-07-01

This study identified characteristics of poultry farming with a focus on practices that affect the detection of HPAI; and estimated the system sensitivity of passive surveillance for HPAI H5N1 in commercial and backyard chicken farms in Bayelsa-State, Nigeria. Field studies were carried out in Yenegoa and Ogbia local government areas in Bayelsa state. Willingness to report HPAI was highest in commercial poultry farms (13/13) than in Backyard farms (8/13). Poor means of dead bird disposal was common to both commercial and backyard farms. Administering some form of treatment to sick birds without prior consultation with a professional was higher in backyard farms (8/13) than in commercial farms (4/13). Consumption of sick birds was reported in 4/13 backyard farms and sale of dead birds was recorded in one commercial farm. The sensitivity of passive surveillance for HPAI was assessed using scenario tree modelling. A scenario tree model was developed and applied to estimate the sensitivity, i.e. the probability of detecting one or more infected chicken farms in Bayelsa state at different levels of disease prevalence. The model showed a median sensitivity of 100%, 67% and 23% for detecting HPAI by passive surveillance at a disease prevalence of 0.1%, a minimum of 10 and 3 infected poultry farms respectively. Passive surveillance system sensitivity at a design prevalence of 10 infected farms is increasable up to 86% when the disease detection in backyard chicken farms is enhanced. Copyright © 2016 Elsevier B.V. All rights reserved.

Numerical and Experimental Study of Wake Redirection Techniques in a Boundary Layer Wind Tunnel

NASA Astrophysics Data System (ADS)

Wang, J.; Foley, S.; Nanos, E. M.; Yu, T.; Campagnolo, F.; Bottasso, C. L.; Zanotti, A.; Croce, A.

2017-05-01

The aim of the present paper is to validate a wind farm LES framework in the context of two distinct wake redirection techniques: yaw misalignment and individual cyclic pitch control. A test campaign was conducted using scaled wind turbine models in a boundary layer wind tunnel, where both particle image velocimetry and hot-wire thermo anemometers were used to obtain high quality measurements of the downstream flow. A LiDAR system was also employed to determine the non-uniformity of the inflow velocity field. A high-fidelity large-eddy simulation lifting-line model was used to simulate the aerodynamic behavior of the system, including the geometry of the wind turbine nacelle and tower. A tuning-free Lagrangian scale-dependent dynamic approach was adopted to improve the sub-grid scale modeling. Comparisons with experimental measurements are used to systematically validate the simulations. The LES results are in good agreement with the PIV and hot-wire data in terms of time-averaged wake profiles, turbulence intensity and Reynolds shear stresses. Discrepancies are also highlighted, to guide future improvements.

[Parameter optimization of BEPS model based on the flux data of the temperate deciduous broad-leaved forest in Northeast China.

PubMed

Lu, Wei; Fan, Wen Yi; Tian, Tian

2016-05-01

Keeping other parameters as empirical constants, different numerical combinations of the main photosynthetic parameters V c max and J max were conducted to estimate daily GPP by using the iteration method in this paper. To optimize V c max and J max in BEPSHourly model at hourly time steps, simulated daily GPP using different numerical combinations of the parameters were compared with the flux tower data obtained from the temperate deciduous broad-leaved forest of the Maoershan Forest Farm in Northeast China. Comparing the simulated daily GPP with the observed flux data in 2011, the results showed that optimal V c max and J max for the deciduous broad-leaved forest in Northeast China were 41.1 μmol·m -2 ·s -1 and 82.8 μmol·m -2 ·s -1 respectively with the minimal RMSE and the maximum R 2 of 1.10 g C·m -2 ·d -1 and 0.95. After V c max and J max optimization, BEPSHourly model simulated the seasonal variation of GPP better.

Evaluation in Appalachian pasture systems of the 1996 (update 2000) National Research Council model for weaning cattle.

PubMed

Whetsell, M S; Rayburn, E B; Osborne, P I

2006-05-01

This study was conducted to evaluate the accuracy of the National Research Council's (2000) Nutrient Requirements of Beef Cattle computer model when used to predict calf performance during on-farm pasture or dry-lot weaning and backgrounding. Calf performance was measured on 22 farms in 2002 and 8 farms in 2003 that participated in West Virginia Beef Quality Assurance Sale marketing pools. Calves were weaned on pasture (25 farms) or dry-lot (5 farms) and fed supplemental hay, haylage, ground shell corn, soybean hulls, or a commercial concentrate. Concentrates were fed at a rate of 0.0 to 1.5% of BW. The National Research Council (2000) model was used to predict ADG of each group of calves observed on each farm. The model error was measured by calculating residuals (the difference between predicted ADG minus observed ADG). Predicted animal performance was determined using level 1 of the model. Results show that, when using normal on-farm pasture sampling and forage analysis methods, the model error for ADG is high and did not accurately predict the performance of steers or heifers fed high-forage pasture-based diets; the predicted ADG was lower (P < 0.05) than the observed ADG. The estimated intake of low-producing animals was similar to the expected DMI, but for the greater-producing animals it was not. The NRC (2000) beef model may more accurately predict on-farm animal performance in pastured situations if feed analysis values reflect the energy value of the feed, account for selective grazing, and relate empty BW and shrunk BW to NDF.

The performance of approximations of farm contiguity compared to contiguity defined using detailed geographical information in two sample areas in Scotland: implications for foot-and-mouth disease modelling.

PubMed

Flood, Jessica S; Porphyre, Thibaud; Tildesley, Michael J; Woolhouse, Mark E J

2013-10-08

When modelling infectious diseases, accurately capturing the pattern of dissemination through space is key to providing optimal recommendations for control. Mathematical models of disease spread in livestock, such as for foot-and-mouth disease (FMD), have done this by incorporating a transmission kernel which describes the decay in transmission rate with increasing Euclidean distance from an infected premises (IP). However, this assumes a homogenous landscape, and is based on the distance between point locations of farms. Indeed, underlying the spatial pattern of spread are the contact networks involved in transmission. Accordingly, area-weighted tessellation around farm point locations has been used to approximate field-contiguity and simulate the effect of contiguous premises (CP) culling for FMD. Here, geographic data were used to determine contiguity based on distance between premises' fields and presence of landscape features for two sample areas in Scotland. Sensitivity, positive predictive value, and the True Skill Statistic (TSS) were calculated to determine how point distance measures and area-weighted tessellation compared to the 'gold standard' of the map-based measures in identifying CPs. In addition, the mean degree and density of the different contact networks were calculated. Utilising point distances <1 km and <5 km as a measure for contiguity resulted in poor discrimination between map-based CPs/non-CPs (TSS 0.279-0.344 and 0.385-0.400, respectively). Point distance <1 km missed a high proportion of map-based CPs; <5 km point distance picked up a high proportion of map-based non-CPs as CPs. Area-weighted tessellation performed best, with reasonable discrimination between map-based CPs/non-CPs (TSS 0.617-0.737) and comparable mean degree and density. Landscape features altered network properties considerably when taken into account. The farming landscape is not homogeneous. Basing contiguity on geographic locations of field boundaries and including landscape features known to affect transmission into FMD models are likely to improve individual farm-level accuracy of spatial predictions in the event of future outbreaks. If a substantial proportion of FMD transmission events are by contiguous spread, and CPs should be assigned an elevated relative transmission rate, the shape of the kernel could be significantly altered since ability to discriminate between map-based CPs and non-CPs is different over different Euclidean distances.

Creating a model to detect dairy cattle farms with poor welfare using a national database.

PubMed

Krug, C; Haskell, M J; Nunes, T; Stilwell, G

2015-12-01

The objective of this study was to determine whether dairy farms with poor cow welfare could be identified using a national database for bovine identification and registration that monitors cattle deaths and movements. The welfare of dairy cattle was assessed using the Welfare Quality(®) protocol (WQ) on 24 Portuguese dairy farms and on 1930 animals. Five farms were classified as having poor welfare and the other 19 were classified as having good welfare. Fourteen million records from the national cattle database were analysed to identify potential welfare indicators for dairy farms. Fifteen potential national welfare indicators were calculated based on that database, and the link between the results on the WQ evaluation and the national cattle database was made using the identification code of each farm. Within the potential national welfare indicators, only two were significantly different between farms with good welfare and poor welfare, 'proportion of on-farm deaths' (p<0.01) and 'female/male birth ratio' (p<0.05). To determine whether the database welfare indicators could be used to distinguish farms with good welfare from farms with poor welfare, we created a model using the classifier J48 of Waikato Environment for Knowledge Analysis. The model was a decision tree based on two variables, 'proportion of on-farm deaths' and 'calving-to-calving interval', and it was able to correctly identify 70% and 79% of the farms classified as having poor and good welfare, respectively. The national cattle database analysis could be useful in helping official veterinary services in detecting farms that have poor welfare and also in determining which welfare indicators are poor on each particular farm. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluation of average daily gain predictions by the integrated farm system model for forage-finished beef steers

USDA-ARS?s Scientific Manuscript database

Representing the performance of cattle finished on an all forage diet in process-based whole farm system models has presented a challenge. To address this challenge, a study was done to evaluate average daily gain (ADG) predictions of the Integrated Farm System Model (IFSM) for steers consuming all-...

Investment appraisal of automatic milking and conventional milking technologies in a pasture-based dairy system.

PubMed

Shortall, J; Shalloo, L; Foley, C; Sleator, R D; O'Brien, B

2016-09-01

The successful integration of automatic milking (AM) systems and grazing has resulted in AM becoming a feasible alternative to conventional milking (CM) in pasture-based systems. The objective of this study was to identify the profitability of AM in a pasture-based system, relative to CM herringbone parlors with 2 different levels of automation, across 2 farm sizes, over a 10-yr period following initial investment. The scenarios which were evaluated were (1) a medium farm milking 70 cows twice daily, with 1 AM unit, a 12-unit CM medium-specification (MS) parlor and a 12-unit CM high-specification (HS) parlor, and (2) a large farm milking 140 cows twice daily with 2 AM units, a 20-unit CM MS parlor and a 20-unit CM HS parlor. A stochastic whole-farm budgetary simulation model combined capital investment costs and annual labor and maintenance costs for each investment scenario, with each scenario evaluated using multiple financial metrics, such as annual net profit, annual net cash flow, total discounted net profitability, total discounted net cash flow, and return on investment. The capital required for each investment was financed from borrowings at an interest rate of 5% and repaid over 10-yr, whereas milking equipment and building infrastructure were depreciated over 10 and 20 yr, respectively. A supporting labor audit (conducted on both AM and CM farms) showed a 36% reduction in labor demand associated with AM. However, despite this reduction in labor, MS CM technologies consistently achieved greater profitability, irrespective of farm size. The AM system achieved intermediate profitability at medium farm size; it was 0.5% less profitable than HS technology at the large farm size. The difference in profitability was greatest in the years after the initial investment. This study indicated that although milking with AM was less profitable than MS technologies, it was competitive when compared with a CM parlor of similar technology. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The Relationship of Dairy Farm Eco-Efficiency with Intensification and Self-Sufficiency. Evidence from the French Dairy Sector Using Life Cycle Analysis, Data Envelopment Analysis and Partial Least Squares Structural Equation Modelling.

PubMed

Soteriades, Andreas Diomedes; Stott, Alistair William; Moreau, Sindy; Charroin, Thierry; Blanchard, Melanie; Liu, Jiayi; Faverdin, Philippe

2016-01-01

We aimed at quantifying the extent to which agricultural management practices linked to animal production and land use affect environmental outcomes at a larger scale. Two practices closely linked to farm environmental performance at a larger scale are farming intensity, often resulting in greater off-farm environmental impacts (land, non-renewable energy use etc.) associated with the production of imported inputs (e.g. concentrates, fertilizer); and the degree of self-sufficiency, i.e. the farm's capacity to produce goods from its own resources, with higher control over nutrient recycling and thus minimization of losses to the environment, often resulting in greater on-farm impacts (eutrophication, acidification etc.). We explored the relationship of these practices with farm environmental performance for 185 French specialized dairy farms. We used Partial Least Squares Structural Equation Modelling to build, and relate, latent variables of environmental performance, intensification and self-sufficiency. Proxy indicators reflected the latent variables for intensification (milk yield/cow, use of maize silage etc.) and self-sufficiency (home-grown feed/total feed use, on-farm energy/total energy use etc.). Environmental performance was represented by an aggregate 'eco-efficiency' score per farm derived from a Data Envelopment Analysis model fed with LCA and farm output data. The dataset was split into two spatially heterogeneous (bio-physical conditions, production patterns) regions. For both regions, eco-efficiency was significantly negatively related with milk yield/cow and the use of maize silage and imported concentrates. However, these results might not necessarily hold for intensive yet more self-sufficient farms. This requires further investigation with latent variables for intensification and self-sufficiency that do not largely overlap- a modelling challenge that occurred here. We conclude that the environmental 'sustainability' of intensive dairy farming depends on particular farming systems and circumstances, although we note that more self-sufficient farms may be preferable when they may benefit from relatively low land prices and agri-environment schemes aimed at maintaining grasslands.

How important is getting the land surface energy exchange correct in WRF for wind energy forecasting?

NASA Astrophysics Data System (ADS)

Wharton, S.; Simpson, M.; Osuna, J. L.; Newman, J. F.; Biraud, S.

2013-12-01

Wind power forecasting is plagued with difficulties in accurately predicting the occurrence and intensity of atmospheric conditions at the heights spanned by industrial-scale turbines (~ 40 to 200 m above ground level). Better simulation of the relevant physics would enable operational practices such as integration of large fractions of wind power into power grids, scheduling maintenance on wind energy facilities, and deciding design criteria based on complex loads for next-generation turbines and siting. Accurately simulating the surface energy processes in numerical models may be critically important for wind energy forecasting as energy exchange at the surface strongly drives atmospheric mixing (i.e., stability) in the lower layers of the planetary boundary layer (PBL), which in turn largely determines wind shear and turbulence at heights found in the turbine rotor-disk. We hypothesize that simulating accurate a surface-atmosphere energy coupling should lead to more accurate predictions of wind speed and turbulence at heights within the turbine rotor-disk. Here, we tested 10 different land surface model configurations in the Weather Research and Forecasting (WRF) model including Noah, Noah-MP, SSiB, Pleim-Xiu, RUC, and others to evaluate (1) the accuracy of simulated surface energy fluxes to flux tower measurements, (2) the accuracy of forecasted wind speeds to observations at rotor-disk heights, and (3) the sensitivity of forecasting hub-height rotor disk wind speed to the choice of land surface model. WRF was run for four, two-week periods covering both summer and winter periods over the Southern Great Plains ARM site in Oklahoma. Continuous measurements of surface energy fluxes and lidar-based wind speed, direction and turbulence were also available. The SGP ARM site provided an ideal location for this evaluation as it centrally located in the wind-rich Great Plains and multi-MW wind farms are rapidly expanding in the area. We found significant differences in simulated wind speeds at rotor-disk heights from WRF which indicated, in part, the sensitivity of lower PBL winds to surface energy exchange. We also found significant differences in energy partitioning between sensible heat and latent energy depending on choice of land surface model. Overall, the most consistent, accurate model results were produced using Noah-MP. Noah-MP was most accurate at simulating energy fluxes and wind shear. Hub-height wind speed, however, was predicted with most accuracy with Pleim-Xiu. This suggests that simulating wind shear in the surface layer is consistent with accurately simulating surface energy exchange while the exact magnitudes of wind speed may be more strongly influenced by the PBL dynamics. As the nation is working towards a 20% wind energy goal by 2030, increasing the accuracy of wind forecasting at rotor-disk heights becomes more important considering that utilities require wind farms to estimate their power generation 24 to 36 hours ahead and face penalties for inaccuracies in those forecasts.

A sample theory-based logic model to improve program development, implementation, and sustainability of Farm to School programs.

PubMed

Ratcliffe, Michelle M

2012-08-01

Farm to School programs hold promise to address childhood obesity. These programs may increase students’ access to healthier foods, increase students’ knowledge of and desire to eat these foods, and increase their consumption of them. Implementing Farm to School programs requires the involvement of multiple people, including nutrition services, educators, and food producers. Because these groups have not traditionally worked together and each has different goals, it is important to demonstrate how Farm to School programs that are designed to decrease childhood obesity may also address others’ objectives, such as academic achievement and economic development. A logic model is an effective tool to help articulate a shared vision for how Farm to School programs may work to accomplish multiple goals. Furthermore, there is evidence that programs based on theory are more likely to be effective at changing individuals’ behaviors. Logic models based on theory may help to explain how a program works, aid in efficient and sustained implementation, and support the development of a coherent evaluation plan. This article presents a sample theory-based logic model for Farm to School programs. The presented logic model is informed by the polytheoretical model for food and garden-based education in school settings (PMFGBE). The logic model has been applied to multiple settings, including Farm to School program development and evaluation in urban and rural school districts. This article also includes a brief discussion on the development of the PMFGBE, a detailed explanation of how Farm to School programs may enhance the curricular, physical, and social learning environments of schools, and suggestions for the applicability of the logic model for practitioners, researchers, and policy makers.

Modeling Parasite Dynamics on Farmed Salmon for Precautionary Conservation Management of Wild Salmon

PubMed Central

Rogers, Luke A.; Peacock, Stephanie J.; McKenzie, Peter; DeDominicis, Sharon; Jones, Simon R. M.; Chandler, Peter; Foreman, Michael G. G.; Revie, Crawford W.; Krkošek, Martin

2013-01-01

Conservation management of wild fish may include fish health management in sympatric populations of domesticated fish in aquaculture. We developed a mathematical model for the population dynamics of parasitic sea lice (Lepeophtheirus salmonis) on domesticated populations of Atlantic salmon (Salmo salar) in the Broughton Archipelago region of British Columbia. The model was fit to a seven-year dataset of monthly sea louse counts on farms in the area to estimate population growth rates in relation to abiotic factors (temperature and salinity), local host density (measured as cohort surface area), and the use of a parasiticide, emamectin benzoate, on farms. We then used the model to evaluate management scenarios in relation to policy guidelines that seek to keep motile louse abundance below an average three per farmed salmon during the March–June juvenile wild Pacific salmon (Oncorhynchus spp.) migration. Abiotic factors mediated the duration of effectiveness of parasiticide treatments, and results suggest treatment of farmed salmon conducted in January or early February minimized average louse abundance per farmed salmon during the juvenile wild salmon migration. Adapting the management of parasites on farmed salmon according to migrations of wild salmon may therefore provide a precautionary approach to conserving wild salmon populations in salmon farming regions. PMID:23577082

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jonkman, Jason; Annoni, Jennifer; Hayman, Greg

This paper presents the development of FAST.Farm, a new multiphysics tool applicable to engineering problems in research and industry involving wind farm performance and cost optimization that is needed to address the current underperformance, failures, and expenses plaguing the wind industry. Achieving wind cost-of-energy targets - which requires improvements in wind farm performance and reliability, together with reduced uncertainty and expenditures - has been eluded by the complicated nature of the wind farm design problem, especially the sophisticated interaction between atmospheric phenomena and wake dynamics and array effects. FAST.Farm aims to balance the need for accurate modeling of the relevantmore » physics for predicting power performance and loads while maintaining low computational cost to support a highly iterative and probabilistic design process and system-wide optimization. FAST.Farm makes use of FAST to model the aero-hydro-servo-elastics of distinct turbines in the wind farm, and it is based on some of the principles of the Dynamic Wake Meandering (DWM) model, but avoids many of the limitations of existing DWM implementations.« less

IONSIV(R) IE-911 Performance in Savannah River Site Radioactive Waste

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walker, D.D.

2001-06-04

This report describes cesium sorption from high-level radioactive waste solutions onto IONSIV(R) IE-911 at ambient temperature. Researchers characterized six radioactive waste samples from five high-level waste tanks in the Savannah River Site tank farm, diluted the wastes to 5.6 M Na+, and made equilibrium and kinetic measurements of cesium sorption. The equilibrium measurements were compared to ZAM (Zheng, Anthony, and Martin) model predictions. The kinetic measurements were compared to simulant solutions whose column performance has been measured.

An individual reproduction model sensitive to milk yield and body condition in Holstein dairy cows.

PubMed

Brun-Lafleur, L; Cutullic, E; Faverdin, P; Delaby, L; Disenhaus, C

2013-08-01

To simulate the consequences of management in dairy herds, the use of individual-based herd models is very useful and has become common. Reproduction is a key driver of milk production and herd dynamics, whose influence has been magnified by the decrease in reproductive performance over the last decades. Moreover, feeding management influences milk yield (MY) and body reserves, which in turn influence reproductive performance. Therefore, our objective was to build an up-to-date animal reproduction model sensitive to both MY and body condition score (BCS). A dynamic and stochastic individual reproduction model was built mainly from data of a single recent long-term experiment. This model covers the whole reproductive process and is composed of a succession of discrete stochastic events, mainly calving, ovulations, conception and embryonic loss. Each reproductive step is sensitive to MY or BCS levels or changes. The model takes into account recent evolutions of reproductive performance, particularly concerning calving-to-first ovulation interval, cyclicity (normal cycle length, prevalence of prolonged luteal phase), oestrus expression and pregnancy (conception, early and late embryonic loss). A sensitivity analysis of the model to MY and BCS at calving was performed. The simulated performance was compared with observed data from the database used to build the model and from the bibliography to validate the model. Despite comprising a whole series of reproductive steps, the model made it possible to simulate realistic global reproduction outputs. It was able to well simulate the overall reproductive performance observed in farms in terms of both success rate (recalving rate) and reproduction delays (calving interval). This model has the purpose to be integrated in herd simulation models to usefully test the impact of management strategies on herd reproductive performance, and thus on calving patterns and culling rates.

A Regional Assessment of the Effects of Conservation Practices on In-stream Water Quality

NASA Astrophysics Data System (ADS)

Garcia, A. M.; Alexander, R. B.; Arnold, J.; Norfleet, L.; Robertson, D. M.; White, M.

2011-12-01

The Conservation Effects Assessment Program (CEAP), initiated by USDA Natural Resources Conservation Service (NRCS), has the goal of quantifying the environmental benefits of agricultural conservation practices. As part of this effort, detailed farmer surveys were compiled to document the adoption of conservation practices. Survey data showed that up to 38 percent of cropland in the Upper Mississippi River basin is managed to reduce sediment, nutrient and pesticide loads from agricultural activities. The broader effects of these practices on downstream water quality are challenging to quantify. The USDA-NRCS recently reported results of a study that combined farmer surveys with process-based models to deduce the effect of conservation practices on sediment and chemical loads in farm runoff and downstream waters. As a follow-up collaboration, USGS and USDA scientists conducted a semi-empirical assessment of the same suite of practices using the USGS SPARROW (SPAtially Referenced Regression On Watershed attributes) modeling framework. SPARROW is a hybrid statistical and mechanistic stream water quality model of annual conditions that has been used extensively in studies of nutrient sources and delivery. In this assessment, the USDA simulations of the effects of conservation practices on loads in farm runoff were used as an explanatory variable (i.e., change in farm loads per unit area) in a component of an existing a SPARROW model of the Upper Midwest. The model was then re-calibrated and tested to determine whether the USDA estimate of conservation adoption intensity explained a statistically significant proportion of the spatial variability in stream nutrient loads in the Upper Mississippi River basin. The results showed that the suite of conservation practices that NRCS has catalogued as complete nutrient and sediment management are a statistically significant feature in the Midwestern landscape associated with phosphorous runoff and delivery to downstream waters. Effects on the delivery of nitrogen will be also be studied. Estimates of the magnitude of this effect using SPARROW indicated that phosphorus load reductions ranged from about 2 - 38% for various spatial scales. This is less than reported by the USDA CEAP simulations, which ranged from 15 - 49%. Nevertheless, the results indicated that conservation practices play a significant role in reducing phosphorus pollution from agricultural activities to downstream receiving water bodies.

Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies

PubMed Central

Liu, Xiaolei; Huang, Meng; Fan, Bin; Buckler, Edward S.; Zhang, Zhiwu

2016-01-01

False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population structure and kinship among individuals to adjust association tests on markers; however, the adjustment also compromises true positives. The modified MLM method, Multiple Loci Linear Mixed Model (MLMM), incorporates multiple markers simultaneously as covariates in a stepwise MLM to partially remove the confounding between testing markers and kinship. To completely eliminate the confounding, we divided MLMM into two parts: Fixed Effect Model (FEM) and a Random Effect Model (REM) and use them iteratively. FEM contains testing markers, one at a time, and multiple associated markers as covariates to control false positives. To avoid model over-fitting problem in FEM, the associated markers are estimated in REM by using them to define kinship. The P values of testing markers and the associated markers are unified at each iteration. We named the new method as Fixed and random model Circulating Probability Unification (FarmCPU). Both real and simulated data analyses demonstrated that FarmCPU improves statistical power compared to current methods. Additional benefits include an efficient computing time that is linear to both number of individuals and number of markers. Now, a dataset with half million individuals and half million markers can be analyzed within three days. PMID:26828793

Early animal farming and zoonotic disease dynamics: modelling brucellosis transmission in Neolithic goat populations.

PubMed

Fournié, Guillaume; Pfeiffer, Dirk U; Bendrey, Robin

2017-02-01

Zoonotic pathogens are frequently hypothesized as emerging with the origins of farming, but evidence of this is elusive in the archaeological records. To explore the potential impact of animal domestication on zoonotic disease dynamics and human infection risk, we developed a model simulating the transmission of Brucella melitensis within early domestic goat populations. The model was informed by archaeological data describing goat populations in Neolithic settlements in the Fertile Crescent, and used to assess the potential of these populations to sustain the circulation of Brucella . Results show that the pathogen could have been sustained even at low levels of transmission within these domestic goat populations. This resulted from the creation of dense populations and major changes in demographic characteristics. The selective harvesting of young male goats, likely aimed at improving the efficiency of food production, modified the age and sex structure of these populations, increasing the transmission potential of the pathogen within these populations. Probable interactions between Neolithic settlements would have further promoted pathogen maintenance. By fostering conditions suitable for allowing domestic goats to become reservoirs of Brucella melitensis , the early stages of agricultural development were likely to promote the exposure of humans to this pathogen.

Early animal farming and zoonotic disease dynamics: modelling brucellosis transmission in Neolithic goat populations

PubMed Central

Pfeiffer, Dirk U.; Bendrey, Robin

2017-01-01

Zoonotic pathogens are frequently hypothesized as emerging with the origins of farming, but evidence of this is elusive in the archaeological records. To explore the potential impact of animal domestication on zoonotic disease dynamics and human infection risk, we developed a model simulating the transmission of Brucella melitensis within early domestic goat populations. The model was informed by archaeological data describing goat populations in Neolithic settlements in the Fertile Crescent, and used to assess the potential of these populations to sustain the circulation of Brucella. Results show that the pathogen could have been sustained even at low levels of transmission within these domestic goat populations. This resulted from the creation of dense populations and major changes in demographic characteristics. The selective harvesting of young male goats, likely aimed at improving the efficiency of food production, modified the age and sex structure of these populations, increasing the transmission potential of the pathogen within these populations. Probable interactions between Neolithic settlements would have further promoted pathogen maintenance. By fostering conditions suitable for allowing domestic goats to become reservoirs of Brucella melitensis, the early stages of agricultural development were likely to promote the exposure of humans to this pathogen. PMID:28386446

Farmers' contribution to landscape services in the Netherlands under different rural development scenarios.

PubMed

Pfeifer, Catherine; Sonneveld, Marthijn P W; Stoorvogel, Jetse J

2012-11-30

Landscape services represent the benefits human populations derive, directly or indirectly, from (agro-)ecosystem functions at the landscape scale. Many of these services are the result of farmers' decision making to allocate resources to other activities than food production and therefore are the result of farm the adoption of on-farm rural activities. With changing agricultural and rural policies, the future provision of landscape services to fulfill societal demands is not guaranteed. This study aims at mapping the spatial distribution of the adoption of on-farm rural activities under different explorative scenarios. For a Dutch landscape, storylines at the landscape scale were developed by combining global storylines, resulting from the Global Environmental Outlook, with local storylines resulting from key informant interviews. Subsequently these storylines were translated into quantitative scenarios that were implemented into a simulation procedure based on spatially explicit econometric models of farmer's decision making. Results show that further market liberalization leads to a decrease of landscape services in the study area. In our study, only increased cooperation between government, farmers and citizens appears to result in a general increase of all landscape services across the entire landscape. Copyright © 2012 Elsevier Ltd. All rights reserved.

Towards a mature offshore wind energy technology - guidelines from the opti-OWECS project

NASA Astrophysics Data System (ADS)

Kühn, M.; Bierbooms, W. A. A. M.; van Bussel, G. J. W.; Cockerill, T. T.; Harrison, R.; Ferguson, M. C.; Göransson, B.; Harland, L. A.; Vugts, J. H.; Wiecherink, R.

1999-01-01

The article reviews the main results of the recent European research project Opti-OWECS (Structural and Economic Optimisation of Bottom-Mounted Offshore Wind Energy Converters'), which has significantly improved the understanding of the requirements for a large-scale utilization of offshore wind energy. An integrated design approach was demonstrated for a 300 MW offshore wind farm at a demanding North Sea site. Several viable solutions were obtained and one was elaborated to include the design of all major components. Simultaneous structural and economic optimization took place during the different design stages. An offshore wind energy converter founded on a soft-soft monopile was tailored with respect to the distinct characteristics of dynamic wind and wave loading. The operation and maintenance behaviour of the wind farm was analysed by Monte Carlo simulations. With an optimized maintenance strategy and suitable hardware a high availability was achieved. Based upon the experience from the structural design, cost models for offshore wind farms were developed and linked to a European database of the offshore wind energy potential. This enabled the first consistent estimate of cost of offshore wind energy for entire European regions.

Farm-Level Effects of Soil Conservation and Commodity Policy Alternatives: Model and Data Documentation.

ERIC Educational Resources Information Center

Sutton, John D.

This report documents a profit-maximizing linear programming (LP) model of a farm typical of a major corn-soybean producing area in the Southern Michigan-Northern Indiana Drift Plain. Following an introduction, a complete description of the farm is provided. The next section presents the LP model, which is structured to help analyze after-tax…

Assessing the impact of marine wind farms on birds through movement modelling

PubMed Central

Masden, Elizabeth A.; Reeve, Richard; Desholm, Mark; Fox, Anthony D.; Furness, Robert W.; Haydon, Daniel T.

2012-01-01

Advances in technology and engineering, along with European Union renewable energy targets, have stimulated a rapid growth of the wind power sector. Wind farms contribute to carbon emission reductions, but there is a need to ensure that these structures do not adversely impact the populations that interact with them, particularly birds. We developed movement models based on observed avoidance responses of common eider Somateria mollissima to wind farms to predict, and identify potential measures to reduce, impacts. Flight trajectory data that were  collected post-construction of the Danish Nysted offshore wind farm were used to parameterize competing models of bird movements around turbines. The model most closely fitting the observed data incorporated individual variation in the minimum distance at which birds responded to the turbines. We show how such models can contribute to the spatial planning of wind farms by assessing their extent, turbine spacing and configurations on the probability of birds passing between the turbines. Avian movement models can make new contributions to environmental assessments of wind farm developments, and provide insights into how to reduce impacts that can be identified at the planning stage. PMID:22552921

Risk factors associated with bulk tank standard plate count, bulk tank coliform count, and the presence of Staphylococcus aureus on organic and conventional dairy farms in the United States.

PubMed

Cicconi-Hogan, K M; Gamroth, M; Richert, R; Ruegg, P L; Stiglbauer, K E; Schukken, Y H

2013-01-01

The purpose of this study was to assess the association of bulk tank milk standard plate counts, bulk tank coliform counts (CC), and the presence of Staphylococcus aureus in bulk tank milk with various management and farm characteristics on organic and conventional dairy farms throughout New York, Wisconsin, and Oregon. Data from size-matched organic farms (n=192), conventional nongrazing farms (n=64), and conventional grazing farms (n=36) were collected at a single visit for each farm. Of the 292 farms visited, 290 bulk tank milk samples were collected. Statistical models were created using data from all herds in the study, as well as exclusively for the organic subset of herds. Because of incomplete data, 267 of 290 herds were analyzed for total herd modeling, and 173 of 190 organic herds were analyzed for the organic herd modeling. Overall, more bulk tanks from organic farms had Staph. aureus cultured from them (62% of organic herds, 42% conventional nongrazing herds, and 43% of conventional grazing herds), whereas fewer organic herds had a high CC, defined as ≥50 cfu/mL, than conventional farms in the study. A high standard plate count (×1,000 cfu/mL) was associated with decreased body condition score of adult cows and decreased milk production in both models. Several variables were significant only in the model created using all herds or only in organic herds. The presence of Staph. aureus in the bulk tank milk was associated with fewer people treating mastitis, increased age of housing, and a higher percentage of cows with 3 or fewer teats in both the organic and total herd models. The Staph. aureus total herd model also showed a relationship with fewer first-lactation animals, higher hock scores, and less use of automatic takeoffs at milking. High bulk tank CC was related to feeding a total mixed ration and using natural service in nonlactating heifers in both models. Overall, attentive management and use of outside resources were useful with regard to CC on organic farms. In all models except the organic CC model, we observed an association with the average reported somatic cell count from 3 mo before the herd visit, indicating that many of the regularly tested milk quality parameters are interconnected. In conclusion, we found that conventional and organic farms are similar in regard to overall herd management, but each grazing system faces unique challenges when managing milk quality. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Two sides of a coin: Effects of climate change on the native and non-native distribution of Colossoma macropomum in South America.

PubMed

Lopes, Taise M; Bailly, Dayani; Almeida, Bia A; Santos, Natália C L; Gimenez, Barbara C G; Landgraf, Guilherme O; Sales, Paulo C L; Lima-Ribeiro, Matheus S; Cassemiro, Fernanda A S; Rangel, Thiago F; Diniz-Filho, José A F; Agostinho, Angelo A; Gomes, Luiz C

2017-01-01

Climate change and species invasions interact in nature, disrupting biological communities. Based on this knowledge, we simultaneously assessed the effects of climate change on the native distribution of the Amazonian fish Colossoma macropomum as well as on its invasiveness across river basins of South America, using ecological niche modeling. We used six niche models within the ensemble forecast context to predict the geographical distribution of C. macropomum for the present time, 2050 and 2080. Given that this species has been continuously introduced into non-native South American basins by fish farming activities, we added the locations of C. macropomum farms into the modeling process to obtain a more realistic scenario of its invasive potential. Based on modelling outputs we mapped climate refuge areas at different times. Our results showed that a plenty of climatically suitable areas for the occurrence of C. macropomum occurrence are located outside the original basins at the present time and that its invasive potential is greatly amplified by fish farms. Simulations of future geographic ranges revealed drastic range contraction in the native region, implying concerns not only with respect to the species conservation but also from a socio-economic perspective since the species is a cornerstone of artisanal and commercial fisheries in the Amazon. Although the invasive potential is projected to decrease in the face of climate change, climate refugia will concentrate in Paraná River, Southeast Atlantic and East Atlantic basins, putting intense, negative pressures on the native fish fauna these regions. Our findings show that short and long-term management actions are required for: i) the conservation of natural stocks of C. macropomum in the Amazon, and ii) protecting native fish fauna in the climate refuges of the invaded regions.

Two sides of a coin: Effects of climate change on the native and non-native distribution of Colossoma macropomum in South America

PubMed Central

Lopes, Taise M.; Bailly, Dayani; Almeida, Bia A.; Santos, Natália C. L.; Gimenez, Barbara C. G.; Landgraf, Guilherme O.; Sales, Paulo C. L.; Lima-Ribeiro, Matheus S.; Cassemiro, Fernanda A. S.; Rangel, Thiago F.; Diniz-Filho, José A. F.; Agostinho, Angelo A.; Gomes, Luiz C.

2017-01-01

Climate change and species invasions interact in nature, disrupting biological communities. Based on this knowledge, we simultaneously assessed the effects of climate change on the native distribution of the Amazonian fish Colossoma macropomum as well as on its invasiveness across river basins of South America, using ecological niche modeling. We used six niche models within the ensemble forecast context to predict the geographical distribution of C. macropomum for the present time, 2050 and 2080. Given that this species has been continuously introduced into non-native South American basins by fish farming activities, we added the locations of C. macropomum farms into the modeling process to obtain a more realistic scenario of its invasive potential. Based on modelling outputs we mapped climate refuge areas at different times. Our results showed that a plenty of climatically suitable areas for the occurrence of C. macropomum occurrence are located outside the original basins at the present time and that its invasive potential is greatly amplified by fish farms. Simulations of future geographic ranges revealed drastic range contraction in the native region, implying concerns not only with respect to the species conservation but also from a socio-economic perspective since the species is a cornerstone of artisanal and commercial fisheries in the Amazon. Although the invasive potential is projected to decrease in the face of climate change, climate refugia will concentrate in Paraná River, Southeast Atlantic and East Atlantic basins, putting intense, negative pressures on the native fish fauna these regions. Our findings show that short and long-term management actions are required for: i) the conservation of natural stocks of C. macropomum in the Amazon, and ii) protecting native fish fauna in the climate refuges of the invaded regions. PMID:28654663

Sustainable, alternative farming practices as a means to simultaneously secure food production and reduce air pollution in East Asia

NASA Astrophysics Data System (ADS)

Tai, A. P. K.; Fung, K. M.; Yong, T.; Liu, X.

2015-12-01

Proper agricultural land management is essential for securing food supply and minimizing damage to the environment. Among available farming practices, relay strip intercropping and fertilizer application are commonly used, but to study their wider environmental implications and possible feedbacks we require an Earth system modeling framework. In this study, the effectiveness of a maize-soybean relay strip intercropping system and fertilizer reduction is investigated using a multi-model method. The DNDC (DeNitrification-DeComposition) model is used to simulate agricultural activities and their impacts on the environment through nitrogen emissions and changes in soil chemical composition. Crop yield, soil nutrient content and nitrogen emissions to the atmosphere in major agricultural regions of China are predicted under various cultivation scenarios. The GEOS-Chem global chemical transport model is then used to estimate the effects on downwind particle and ozone air pollution. We show that relay strip intercropping and optimal fertilization not only improve crop productivity, but also retain soil nutrients, reduce ammonia emission and mitigate downwind air pollution. By cutting 25% fertilization inputs but cultivating maize and soybean together in a relay strip intercropping system used with field studies, total crop production was improved slightly by 4.4% compared to monoculture with conventional amount of fertilizers. NH3 volatilization decreases by 29%, equivalent to saving the pollution-induced health damage costs by about US$2.5 billion per year. The possible feedback effects from atmospheric nitrogen deposition onto the croplands are also investigated. We show that careful management and better quantitative understanding of alternative farming practices hold huge potential in simultaneously addressing different global change issues including the food crisis, air pollution and climate change, and calls for greater collaboration between scientists, farmers and policy makers concerning these issues.

Future climate impacts on maize farming and food security in Malawi

NASA Astrophysics Data System (ADS)

Stevens, Tilele; Madani, Kaveh

2016-11-01

Agriculture is the mainstay of Malawi’s economy and maize is the most important crop for food security. As a Least Developed Country (LDC), adverse effects of climate change (CC) on agriculture in Malawi are expected to be significant. We examined the impacts of CC on maize production and food security in Malawi’s dominant cereal producing region, Lilongwe District. We used five Global Circulation Models (GCMs) to make future (2011 to 2100) rainfall and temperature projections and simulated maize yields under these projections. Our future rainfall projections did not reveal a strong increasing or decreasing trend, but temperatures are expected to increase. Our crop modelling results, for the short-term future, suggest that maize farming might benefit from CC. However, faster crop growth could worsen Malawi’s soil fertility problem. Increasing temperature could drive lower maize yields in the medium to long-term future. Consequently, up to 12% of the population in Lilongwe District might be vulnerable to food insecurity by the end of the century. Measures to increase soil fertility and moisture must be developed to build resilience into Malawi’s agriculture sector.

The control of sea lice in Atlantic salmon by selective breeding.

PubMed

Gharbi, Karim; Matthews, Louise; Bron, James; Roberts, Ron; Tinch, Alan; Stear, Michael

2015-09-06

Sea lice threaten the welfare of farmed Atlantic salmon and the sustainability of fish farming across the world. Chemical treatments are the major method of control but drug resistance means that alternatives are urgently needed. Selective breeding can be a cheap and effective alternative. Here, we combine experimental trials and diagnostics to provide a practical protocol for quantifying resistance to sea lice. We then combined quantitative genetics with epidemiological modelling to make the first prediction of the response to selection, quantified in terms of reduced need for chemical treatments. We infected over 1400 young fish with Lepeophtheirus salmonis, the most important species in the Northern Hemisphere. Mechanisms of resistance were expressed early in infection. Consequently, the number of lice per fish and the ranking of families were very similar at 7 and 17 days post infection, providing a stable window for assessing susceptibility to infection. The heritability of lice numbers within this time window was moderately high at 0.3, confirming that selective breeding is viable. We combined an epidemiological model of sea lice infection and control on a salmon farm with genetic variation in susceptibility among individuals. We simulated 10 generations of selective breeding and examined the frequency of treatments needed to control infection. Our model predicted that substantially fewer chemical treatments are needed to control lice outbreaks in selected populations and chemical treatment could be unnecessary after 10 generations of selection. Selective breeding for sea lice resistance should reduce the impact of sea lice on fish health and thus substantially improve the sustainability of Atlantic salmon production. © 2015 The Author(s).

Assessing the impacts of the changes in farming systems on food security and environmental sustainability of a Chinese rural region under different policy scenarios: an agent-based model.

PubMed

Yuan, Chengcheng; Liu, Liming; Qi, Xiaoxing; Fu, Yonghu; Ye, Jinwei

2017-07-01

Since China has undergone a series of economic reforms and implemented opening up policies, its farming systems have significantly changed and have dramatically influenced the society, economy, and environment of China. To assess the comprehensive impacts of these changes on food security and environmental sustainability, and establish effective and environment-friendly subsidy policies, this research constructed an agent-based model (ABM). Daligang Town, which is located in the two-season rice region of Southern China, was selected as the case study site. Four different policy scenarios, i.e., "sharply increasing" (SI), "no-increase" (NI), "adjusted-method" (AM), and "trend" (TD) scenarios were investigated from 2015 to 2029. The validation result shows that the relative prediction errors between the simulated and actual values annually ranged from -20 to 20%, indicating the reliability of the proposed model. The scenario analysis revealed that the four scenarios generated different variations in cropping systems, rice yield, and fertilizer and pesticide inputs when the purchase price of rice and the non-agricultural income were assumed to increase annually by 0.1 RMB per kg and 10% per person, respectively. Among the four different policy scenarios in Daligang, the TD scenario was considered the best, because it had a relatively high rice yield, fairly minimal use of fertilizers and pesticides, and a lower level of subsidy. Despite its limitations, ABM could be considered a useful tool in analyzing, exploring, and discussing the comprehensive effects of the changes in farming system on food security and environmental sustainability.

Identification and testing of early indicators for N leaching from urine patches.

PubMed

Vogeler, Iris; Cichota, Rogerio; Snow, Val

2013-11-30

Nitrogen leaching from urine patches has been identified as a major source of nitrogen loss under intensive grazing dairy farming. Leaching is notoriously variable, influenced by management, soil type, year-to-year variation in climate and timing and rate of urine depositions. To identify early indicators for the risk of N leaching from urine patches for potential usage in a precision management system, we used the simulation model APSIM (Agricultural Production Systems SIMulator) to produce an extensive N leaching dataset for the Waikato region of New Zealand. In total, nearly forty thousand simulation runs with different combinations of soil type and urine deposition times, in 33 different years, were done. The risk forecasting indicators were chosen based on their practicality: being readily measured on farm (soil water content, temperature and pasture growth) or that could be centrally supplied to farms (such as actual and forecast weather data). The thresholds of the early indicators that are used to forecast a period for high risk of N leaching were determined via classification and regression tree analysis. The most informative factors were soil temperature, pasture dry matter production, and average soil water content in the top soil over the two weeks prior to the urine N application event. Rainfall and air temperature for the two weeks following urine deposition were also important to fine-tune the predictions. The identified early indicators were then tested for their potential to predict the risk of N leaching in two typical soils from the Waikato region in New Zealand. The accuracy of the predictions varied with the number of indicators, the soil type and the risk level, and the number of correct predictions ranged from about 45 to over 90%. Further expansion and fine-tuning of the indicators and the development of a practical N risk tool based on these indicators is needed. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Relationship of Dairy Farm Eco-Efficiency with Intensification and Self-Sufficiency. Evidence from the French Dairy Sector Using Life Cycle Analysis, Data Envelopment Analysis and Partial Least Squares Structural Equation Modelling

PubMed Central

Soteriades, Andreas Diomedes; Stott, Alistair William; Moreau, Sindy; Charroin, Thierry; Blanchard, Melanie; Liu, Jiayi; Faverdin, Philippe

2016-01-01

We aimed at quantifying the extent to which agricultural management practices linked to animal production and land use affect environmental outcomes at a larger scale. Two practices closely linked to farm environmental performance at a larger scale are farming intensity, often resulting in greater off-farm environmental impacts (land, non-renewable energy use etc.) associated with the production of imported inputs (e.g. concentrates, fertilizer); and the degree of self-sufficiency, i.e. the farm’s capacity to produce goods from its own resources, with higher control over nutrient recycling and thus minimization of losses to the environment, often resulting in greater on-farm impacts (eutrophication, acidification etc.). We explored the relationship of these practices with farm environmental performance for 185 French specialized dairy farms. We used Partial Least Squares Structural Equation Modelling to build, and relate, latent variables of environmental performance, intensification and self-sufficiency. Proxy indicators reflected the latent variables for intensification (milk yield/cow, use of maize silage etc.) and self-sufficiency (home-grown feed/total feed use, on-farm energy/total energy use etc.). Environmental performance was represented by an aggregate ‘eco-efficiency’ score per farm derived from a Data Envelopment Analysis model fed with LCA and farm output data. The dataset was split into two spatially heterogeneous (bio-physical conditions, production patterns) regions. For both regions, eco-efficiency was significantly negatively related with milk yield/cow and the use of maize silage and imported concentrates. However, these results might not necessarily hold for intensive yet more self-sufficient farms. This requires further investigation with latent variables for intensification and self-sufficiency that do not largely overlap- a modelling challenge that occurred here. We conclude that the environmental ‘sustainability’ of intensive dairy farming depends on particular farming systems and circumstances, although we note that more self-sufficient farms may be preferable when they may benefit from relatively low land prices and agri-environment schemes aimed at maintaining grasslands. PMID:27832199

LandCaRe DSS--an interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies.

PubMed

Wenkel, Karl-Otto; Berg, Michael; Mirschel, Wilfried; Wieland, Ralf; Nendel, Claas; Köstner, Barbara

2013-09-01

Decision support to develop viable climate change adaptation strategies for agriculture and regional land use management encompasses a wide range of options and issues. Up to now, only a few suitable tools and methods have existed for farmers and regional stakeholders that support the process of decision-making in this field. The interactive model-based spatial information and decision support system LandCaRe DSS attempts to close the existing methodical gap. This system supports interactive spatial scenario simulations, multi-ensemble and multi-model simulations at the regional scale, as well as the complex impact assessment of potential land use adaptation strategies at the local scale. The system is connected to a local geo-database and via the internet to a climate data server. LandCaRe DSS uses a multitude of scale-specific ecological impact models, which are linked in various ways. At the local scale (farm scale), biophysical models are directly coupled with a farm economy calculator. New or alternative simulation models can easily be added, thanks to the innovative architecture and design of the DSS. Scenario simulations can be conducted with a reasonable amount of effort. The interactive LandCaRe DSS prototype also offers a variety of data analysis and visualisation tools, a help system for users and a farmer information system for climate adaptation in agriculture. This paper presents the theoretical background, the conceptual framework, and the structure and methodology behind LandCaRe DSS. Scenario studies at the regional and local scale for the two Eastern German regions of Uckermark (dry lowlands, 2600 km(2)) and Weißeritz (humid mountain area, 400 km(2)) were conducted in close cooperation with stakeholders to test the functionality of the DSS prototype. The system is gradually being transformed into a web version (http://www.landcare-dss.de) to ensure the broadest possible distribution of LandCaRe DSS to the public. The system will be continuously developed, updated and used in different research projects and as a learning and knowledge-sharing tool for students. The main objective of LandCaRe DSS is to provide information on the complex long-term impacts of climate change and on potential management options for adaptation by answering "what-if" type questions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Enabling Philippine Farmers to Adapt to Climate Variability Using Seasonal Climate and Weather Forecast with a Crop Simulation Model in an SMS-based Farmer Decision Support System

NASA Astrophysics Data System (ADS)

Ebardaloza, J. B. R.; Trogo, R.; Sabido, D. J.; Tongson, E.; Bagtasa, G.; Balderama, O. F.

2015-12-01

Corn farms in the Philippines are rainfed farms, hence, it is of utmost importance to choose the start of planting date so that the critical growth stages that are in need of water will fall on dates when there is rain. Most farmers in the Philippines use superstitions and traditions as basis for farming decisions such as when to start planting [1]. Before climate change, superstitions like planting after a feast day of a saint has worked for them but with the recent progression of climate change, farmers now recognize that there is a need for technological intervention [1]. The application discussed in this paper presents a solution that makes use of meteorological station sensors, localized seasonal climate forecast, localized weather forecast and a crop simulation model to provide recommendations to farmers based on the crop cultivar, soil type and fertilizer type used by farmers. It is critical that the recommendations given to farmers are not generic as each farmer would have different needs based on their cultivar, soil, fertilizer, planting schedule and even location [2]. This application allows the farmer to inquire about whether it will rain in the next seven days, the best date to start planting based on the potential yield upon harvest, when to apply fertilizer and by how much, when to water and by how much. Short messaging service (SMS) is the medium chosen for this application because while mobile penetration in the Philippines is as high as 101%, the smart phone penetration is only at 15% [3]. SMS has been selected as it has been identified as the most effective way of reaching farmers with timely agricultural information and knowledge [4,5]. The recommendations while derived from making use of Automated Weather Station (AWS) sensor data, Weather Research Forecasting (WRF) models and DSSAT 4.5 [9], are translated into the local language of the farmers and in a format that is easily understood as recommended in [6,7,8]. A pilot study has been started in May 2015 and the harvest of this pilot season will be September 2015.

Comparison of Artificial Neural Networks and ARIMA statistical models in simulations of target wind time series

NASA Astrophysics Data System (ADS)

Kolokythas, Kostantinos; Vasileios, Salamalikis; Athanassios, Argiriou; Kazantzidis, Andreas

2015-04-01

The wind is a result of complex interactions of numerous mechanisms taking place in small or large scales, so, the better knowledge of its behavior is essential in a variety of applications, especially in the field of power production coming from wind turbines. In the literature there is a considerable number of models, either physical or statistical ones, dealing with the problem of simulation and prediction of wind speed. Among others, Artificial Neural Networks (ANNs) are widely used for the purpose of wind forecasting and, in the great majority of cases, outperform other conventional statistical models. In this study, a number of ANNs with different architectures, which have been created and applied in a dataset of wind time series, are compared to Auto Regressive Integrated Moving Average (ARIMA) statistical models. The data consist of mean hourly wind speeds coming from a wind farm on a hilly Greek region and cover a period of one year (2013). The main goal is to evaluate the models ability to simulate successfully the wind speed at a significant point (target). Goodness-of-fit statistics are performed for the comparison of the different methods. In general, the ANN showed the best performance in the estimation of wind speed prevailing over the ARIMA models.

Effects of Offshore Wind Turbines on Ocean Waves

NASA Astrophysics Data System (ADS)

Wimer, Nicholas; Churchfield, Matthew; Hamlington, Peter

2014-11-01

Wakes from horizontal axis wind turbines create large downstream velocity deficits, thus reducing the available energy for downstream turbines while simultaneously increasing turbulent loading. Along with this deficit, however, comes a local increase in the velocity around the turbine rotor, resulting in increased surface wind speeds. For offshore turbines, these increased speeds can result in changes to the properties of wind-induced waves at the ocean surface. In this study, the characteristics and implications of such waves are explored by coupling a wave simulation code to the Simulator for Offshore Wind Farm Applications (SOWFA) developed by the National Renewable Energy Laboratory. The wave simulator and SOWFA are bi-directionally coupled using the surface wind field produced by an offshore wind farm to drive an ocean wave field, which is used to calculate a wave-dependent surface roughness that is fed back into SOWFA. The details of this combined framework are outlined. The potential for using the wave field created at offshore wind farms as an additional energy resource through the installation of on-site wave converters is discussed. Potential negative impacts of the turbine-induced wave field are also discussed, including increased oscillation of floating turbines.

Wind Turbine Wakes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelley, Christopher Lee; Maniaci, David Charles; Resor, Brian R.

2015-10-01

The total energy produced by a wind farm depends on the complex interaction of many wind turbines operating in proximity with the turbulent atmosphere. Sometimes, the unsteady forces associated with wind negatively influence power production, causing damage and increasing the cost of producing energy associated with wind power. Wakes and the motion of air generated by rotating blades need to be better understood. Predicting wakes and other wind forces could lead to more effective wind turbine designs and farm layouts, thereby reducing the cost of energy, allowing the United States to increase the installed capacity of wind energy. The Windmore » Energy Technologies Department at Sandia has collaborated with the University of Minnesota to simulate the interaction of multiple wind turbines. By combining the validated, large-eddy simulation code with Sandia’s HPC capability, this consortium has improved its ability to predict unsteady forces and the electrical power generated by an array of wind turbines. The array of wind turbines simulated were specifically those at the Sandia Scaled Wind Farm Testbed (SWiFT) site which aided the design of new wind turbine blades being manufactured as part of the National Rotor Testbed project with the Department of Energy.« less

Improving Seasonal Crop Monitoring and Forecasting for Soybean and Corn in Iowa

NASA Astrophysics Data System (ADS)

Togliatti, K.; Archontoulis, S.; Dietzel, R.; VanLoocke, A.

2016-12-01

Accurately forecasting crop yield in advance of harvest could greatly benefit farmers, however few evaluations have been conducted to determine the effectiveness of forecasting methods. We tested one such method that used a combination of short-term weather forecasting from the Weather Research and Forecasting Model (WRF) to predict in season weather variables, such as, maximum and minimum temperature, precipitation and radiation at 4 different forecast lengths (2 weeks, 1 week, 3 days, and 0 days). This forecasted weather data along with the current and historic (previous 35 years) data from the Iowa Environmental Mesonet was combined to drive Agricultural Production Systems sIMulator (APSIM) simulations to forecast soybean and corn yields in 2015 and 2016. The goal of this study is to find the forecast length that reduces the variability of simulated yield predictions while also increasing the accuracy of those predictions. APSIM simulations of crop variables were evaluated against bi-weekly field measurements of phenology, biomass, and leaf area index from early and late planted soybean plots located at the Agricultural Engineering and Agronomy Research Farm in central Iowa as well as the Northwest Research Farm in northwestern Iowa. WRF model predictions were evaluated against observed weather data collected at the experimental fields. Maximum temperature was the most accurately predicted variable, followed by minimum temperature and radiation, and precipitation was least accurate according to RMSE values and the number of days that were forecasted within a 20% error of the observed weather. Our analysis indicated that for the majority of months in the growing season the 3 day forecast performed the best. The 1 week forecast came in second and the 2 week forecast was the least accurate for the majority of months. Preliminary results for yield indicate that the 2 week forecast is the least variable of the forecast lengths, however it also is the least accurate. The 3 day and 1 week forecast have a better accuracy, with an increase in variability.

Cost of post-weaning multi-systemic wasting syndrome and porcine circovirus type-2 subclinical infection in England - an economic disease model.

PubMed

Alarcon, Pablo; Rushton, Jonathan; Wieland, Barbara

2013-06-01

Post-weaning multi-systemic wasting syndrome (PMWS) is a multi-factorial disease with major economic implications for the pig industry worldwide. The present study aimed to assess the economic impact of PMWS and porcine circovirus type 2 (PCV2) subclinical infections (PCV2SI) for farrow-to-finish farms and to estimate the resulting cost to the English pig industry. A disease model was built to simulate the varying proportions of pigs in a batch that get infected with PCV2 and develop either PMWS, subclinical disease (reduce growth without evident clinical signs) or remain healthy (normal growth and no clinical signs), depending on the farm level PMWS severity. This PMWS severity measure accounted for the level of post-weaning mortality, PMWS morbidity and proportion of PCV2 infected pigs observed on farms. The model generated six outcomes: infected pigs with PMWS that die (PMWS-D); infected pigs with PMWS that recover (PMWS-R); subclinical pigs that die (Sub-D); subclinical pigs that reach slaughter age (Sub-S); healthy pigs sold (H-S); and pigs, infected or non-infected by PCV2, that die due to non-PCV2 related causes (nonPCV2-D). Enterprise and partial budget analyses were used to assess the deficit/profits and the extra costs/extra benefits of a change in disease status, respectively. Results from the economic analysis at pig level were combined with the disease model's estimates of the proportion of different pigs produced at different severity scores to assess the cost of PMWS and subclinical disease at farm level, and these were then extrapolated to estimate costs at national level. The net profit for a H-S pig was £19.2. The mean loss for a PMWS-D pig was £84.1 (90% CI: 79.6-89.1), £24.5 (90% CI: 15.1-35.4) for a PMWS-R pig, £82.3 (90% CI: 78.1-87.5) for a Sub-D pig, and £8.1 (90% CI: 2.18-15.1) for a Sub-S pig. At farm level, the greatest proportion of negative economic impact was attributed to PCV2 subclinical pigs. The economic impact for the English pig industry for the year 2008, prior to the introduction of PCV2 vaccines, was estimated at £52.6 million per year (90% CI: 34.7-72.0), and approximately £88 million per year during the epidemic period. This was the first study to use empirical data to model the cost of PMWS/PCV2SI at different farm severity levels. Results from this model will be used to assess the efficiency of different control measures and to provide a decision support tool to farmers and policy makers. Copyright © 2013 Elsevier B.V. All rights reserved.

Data-Driven Risk Assessment from Small Scale Epidemics: Estimation and Model Choice for Spatio-Temporal Data with Application to a Classical Swine Fever Outbreak

PubMed Central

Gamado, Kokouvi; Marion, Glenn; Porphyre, Thibaud

2017-01-01

Livestock epidemics have the potential to give rise to significant economic, welfare, and social costs. Incursions of emerging and re-emerging pathogens may lead to small and repeated outbreaks. Analysis of the resulting data is statistically challenging but can inform disease preparedness reducing potential future losses. We present a framework for spatial risk assessment of disease incursions based on data from small localized historic outbreaks. We focus on between-farm spread of livestock pathogens and illustrate our methods by application to data on the small outbreak of Classical Swine Fever (CSF) that occurred in 2000 in East Anglia, UK. We apply models based on continuous time semi-Markov processes, using data-augmentation Markov Chain Monte Carlo techniques within a Bayesian framework to infer disease dynamics and detection from incompletely observed outbreaks. The spatial transmission kernel describing pathogen spread between farms, and the distribution of times between infection and detection, is estimated alongside unobserved exposure times. Our results demonstrate inference is reliable even for relatively small outbreaks when the data-generating model is known. However, associated risk assessments depend strongly on the form of the fitted transmission kernel. Therefore, for real applications, methods are needed to select the most appropriate model in light of the data. We assess standard Deviance Information Criteria (DIC) model selection tools and recently introduced latent residual methods of model assessment, in selecting the functional form of the spatial transmission kernel. These methods are applied to the CSF data, and tested in simulated scenarios which represent field data, but assume the data generation mechanism is known. Analysis of simulated scenarios shows that latent residual methods enable reliable selection of the transmission kernel even for small outbreaks whereas the DIC is less reliable. Moreover, compared with DIC, model choice based on latent residual assessment correlated better with predicted risk. PMID:28293559

Simulation of Malaria Transmission among Households in a Thai Village using Remotely Sensed Parameters

NASA Technical Reports Server (NTRS)

Kiang, Richard K.; Adimi, Farida; Zollner, Gabriela E.; Coleman, Russell E.

2007-01-01

We have used discrete-event simulation to model the malaria transmission in a Thailand village with approximately 700 residents. Specifically, we model the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle under the explicit influences of selected extrinsic and intrinsic factors. Some of the meteorological and environmental parameters used in the simulation are derived from Tropical Rainfall Measuring Mission and the Ikonos satellite data. Parameters used in the simulations reflect the realistic condition of the village, including the locations and sizes of the households, ages and estimated immunity of the residents, presence of farm animals, and locations of larval habitats. Larval habitats include the actual locations where larvae were collected and the probable locations based on satellite data. The output of the simulation includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Simulated transmission under homogeneous environmental condition was compared with that predicted by a SEIR model. Sensitivity of the output with respect to some extrinsic and intrinsic factors was investigated. Results were compared with mosquito vector and human malaria data acquired over 4.5 years (June 1999 - January 2004) in Kong Mong Tha, a remote village in Kanchanaburi Province, western Thailand. The simulation method is useful for testing transmission hypotheses, estimating the efficacy of insecticide applications, assessing the impacts of nonimmune immigrants, and predicting the effects of socioeconomic, environmental and climatic changes.

Efficiency of dairy farms participating and not participating in veterinary herd health management programs.

PubMed

Derks, Marjolein; Hogeveen, Henk; Kooistra, Sake R; van Werven, Tine; Tauer, Loren W

2014-12-01

This paper compares farm efficiencies between dairies who were participating in a veterinary herd health management (VHHM) program with dairies not participating in such a program, to determine whether participation has an association with farm efficiency. In 2011, 572 dairy farmers received a questionnaire concerning the participation and execution of a VHHM program on their farms. Data from the questionnaire were combined with farm accountancy data from 2008 through 2012 from farms that used calendar year accounting periods, and were analyzed using Stochastic Frontier Analysis (SFA). Two separate models were specified: model 1 was the basic stochastic frontier model (output: total revenue; input: feed costs, land costs, cattle costs, non-operational costs), without explanatory variables embedded into the efficiency component of the error term. Model 2 was an expansion of model 1 which included explanatory variables (number of FTE; total kg milk delivered; price of concentrate; milk per hectare; cows per FTE; nutritional yield per hectare) inserted into the efficiency component of the joint error term. Both models were estimated with the financial parameters expressed per 100 kg fat and protein corrected milk and per cow. Land costs, cattle costs, feed costs and non-operational costs were statistically significant and positive in all models (P<0.01). Frequency distributions of the efficiency scores for the VHHM dairies and the non-VHHM dairies were plotted in a kernel density plot, and differences were tested using the Kolmogorov-Smirnov two-sample test. VHHM dairies had higher total revenue per cow, but not per 100 kg milk. For all SFA models, the difference in distribution was not statistically different between VHHM dairies and non-VHHM dairies (P values 0.94, 0.35, 0.95 and 0.89 for the basic and complete model per 100 kg fat and protein corrected milk and per cow respectively). Therefore we conclude that with our data farm participation in VHHM is not related to overall farm efficiency. Copyright © 2014 Elsevier B.V. All rights reserved.

Knowing requires data

USGS Publications Warehouse

Naranjo, Ramon C.

2017-01-01

Groundwater-flow models are often calibrated using a limited number of observations relative to the unknown inputs required for the model. This is especially true for models that simulate groundwater surface-water interactions. In this case, subsurface temperature sensors can be an efficient means for collecting long-term data that capture the transient nature of physical processes such as seepage losses. Continuous and spatially dense network of diverse observation data can be used to improve knowledge of important physical drivers, conceptualize and calibrate variably saturated groundwater flow models. An example is presented for which the results of such analysis were used to help guide irrigation districts and water management decisions on costly upgrades to conveyance systems to improve water usage, farm productivity and restoration efforts to improve downstream water quality and ecosystems.

Low- and High-Pathogenic Avian Influenza H5 and H7 Spread Risk Assessment Within and Between Australian Commercial Chicken Farms

PubMed Central

Scott, Angela Bullanday; Toribio, Jenny-Ann L. M. L.; Singh, Mini; Groves, Peter; Barnes, Belinda; Glass, Kathryn; Moloney, Barbara; Black, Amanda; Hernandez-Jover, Marta

2018-01-01

This study quantified and compared the probability of avian influenza (AI) spread within and between Australian commercial chicken farms via specified spread pathways using scenario tree mathematical modeling. Input values for the models were sourced from scientific literature, expert opinion, and a farm survey conducted during 2015 and 2016 on Australian commercial chicken farms located in New South Wales (NSW) and Queensland. Outputs from the models indicate that the probability of no establishment of infection in a shed is the most likely end-point after exposure and infection of low-pathogenic avian influenza (LPAI) in one chicken for all farm types (non-free range meat chicken, free range meat chicken, cage layer, barn layer, and free range layer farms). If LPAI infection is established in a shed, LPAI is more likely to spread to other sheds and beyond the index farm due to a relatively low probability of detection and reporting during LPAI infection compared to high-pathogenic avian influenza (HPAI) infection. Among farm types, the median probability for HPAI spread between sheds and between farms is higher for layer farms (0.0019, 0.0016, and 0.0031 for cage, barn, and free range layer, respectively) than meat chicken farms (0.00025 and 0.00043 for barn and free range meat chicken, respectively) due to a higher probability of mutation in layer birds, which relates to their longer production cycle. The pathway of LPAI spread between sheds with the highest average median probability was spread via equipment (0.015; 5–95%, 0.0058–0.036) and for HPAI spread between farms, the pathway with the highest average median probability was spread via egg trays (3.70 × 10−5; 5–95%, 1.47 × 10−6–0.00034). As the spread model did not explicitly consider volume and frequency of the spread pathways, these results provide a comparison of spread probabilities per pathway. These findings highlight the importance of performing biosecurity practices to limit spread of the AI virus. The models can be updated as new information on the mechanisms of the AI virus and on the volume and frequency of movements shed-to-shed and of movements between commercial chicken farms becomes available. PMID:29686993

Low- and High-Pathogenic Avian Influenza H5 and H7 Spread Risk Assessment Within and Between Australian Commercial Chicken Farms.

PubMed

Scott, Angela Bullanday; Toribio, Jenny-Ann L M L; Singh, Mini; Groves, Peter; Barnes, Belinda; Glass, Kathryn; Moloney, Barbara; Black, Amanda; Hernandez-Jover, Marta

2018-01-01

This study quantified and compared the probability of avian influenza (AI) spread within and between Australian commercial chicken farms via specified spread pathways using scenario tree mathematical modeling. Input values for the models were sourced from scientific literature, expert opinion, and a farm survey conducted during 2015 and 2016 on Australian commercial chicken farms located in New South Wales (NSW) and Queensland. Outputs from the models indicate that the probability of no establishment of infection in a shed is the most likely end-point after exposure and infection of low-pathogenic avian influenza (LPAI) in one chicken for all farm types (non-free range meat chicken, free range meat chicken, cage layer, barn layer, and free range layer farms). If LPAI infection is established in a shed, LPAI is more likely to spread to other sheds and beyond the index farm due to a relatively low probability of detection and reporting during LPAI infection compared to high-pathogenic avian influenza (HPAI) infection. Among farm types, the median probability for HPAI spread between sheds and between farms is higher for layer farms (0.0019, 0.0016, and 0.0031 for cage, barn, and free range layer, respectively) than meat chicken farms (0.00025 and 0.00043 for barn and free range meat chicken, respectively) due to a higher probability of mutation in layer birds, which relates to their longer production cycle. The pathway of LPAI spread between sheds with the highest average median probability was spread via equipment (0.015; 5-95%, 0.0058-0.036) and for HPAI spread between farms, the pathway with the highest average median probability was spread via egg trays (3.70 × 10 -5 ; 5-95%, 1.47 × 10 -6 -0.00034). As the spread model did not explicitly consider volume and frequency of the spread pathways, these results provide a comparison of spread probabilities per pathway. These findings highlight the importance of performing biosecurity practices to limit spread of the AI virus. The models can be updated as new information on the mechanisms of the AI virus and on the volume and frequency of movements shed-to-shed and of movements between commercial chicken farms becomes available.

Simulation of 1998-Big Flood in Changjiang River Catchment, China

NASA Astrophysics Data System (ADS)

Nakayama, T.; Watanabe, M.

2006-05-01

Almost every year, China is affected by severe flooding, which causes considerable economic loss and serious damage to towns and farms. Big floods are mainly concentrated in the middle and lower reaches of the "seven big rivers", which include the Changjiang (Yangtze) River, the Yellow (Huanghe) River, and the Huaihe River. The Changjiang River is the fourth largest water resource to the oceans after the Amazon, Zaire, and Orinoco Rivers. In addition to abnormal weather, artificial effects were considered as main causes of the big flood disaster in the Changjiang River catchment by the previous researches; (i) extreme deforestation and soil erosion in the upper reaches, (ii) shrinking of lake water volumes and their reduced connection with the Changjiang River due to reclamation of lakes that retarded water in the middle reaches, and (iii) restriction of channel capacity following levee construction. Because there is an urgent need to quantify these relations on the spatial scale of the whole catchment in order to prevent flood damage as small as possible, it is very important to evaluate the complicated phenomena of water/heat dynamics in the Changjiang River catchment by using process-based models. The present research focuses on simulating the water/heat dynamics for 1998 big-flood with 60-year recurrent period in the Changjiang River catchment. We compared the flood period of 1998 with the normal period of 1987-1988. We expanded the NIES Integrated Catchment-based Eco-hydrology (NICE) model (Nakayama and Watanabe, 2004; Nakayama et al., 2006) for the application to broader catchments in order to evaluate large- scale flooding in the Changjiang River (NICE-FLD). We simulated the water/heat dynamics in the entire catchment (3,000 km wide by 1,000 km long) with a resolution of 10 km mesh by using the NICE-FLD. The model reproduced excellently the river discharge, soil moisture, evapotranspiration, groundwater level, et al. Furthermore, we evaluated the role of flood storage capacity in the lakes and farms in relation to the water/heat budgets, and simulated the change of water/heat dynamics by human activity in order to help decision-making on sustainable development in the catchment.

From Wake Steering to Flow Control

DOE PAGES

Fleming, Paul A.; Annoni, Jennifer; Churchfield, Matthew J.; ...

2017-11-22

In this article, we investigate the role of flow structures generated in wind farm control through yaw misalignment. A pair of counter-rotating vortices are shown to be important in deforming the shape of the wake and in explaining the asymmetry of wake steering in oppositely signed yaw angles. We motivate the development of new physics for control-oriented engineering models of wind farm control, which include the effects of these large-scale flow structures. Such a new model would improve the predictability of control-oriented models. Results presented in this paper indicate that wind farm control strategies, based on new control-oriented models withmore » new physics, that target total flow control over wake redirection may be different, and perhaps more effective, than current approaches. We propose that wind farm control and wake steering should be thought of as the generation of large-scale flow structures, which will aid in the improved performance of wind farms.« less