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Sample records for agricultural sector model

  1. A process-based agricultural model for the irrigated agriculture sector in Alberta, Canada

    NASA Astrophysics Data System (ADS)

    Ammar, M. E.; Davies, E. G.

    2015-12-01

    Connections between land and water, irrigation, agricultural productivity and profitability, policy alternatives, and climate change and variability are complex, poorly understood, and unpredictable. Policy assessment for agriculture presents a large potential for development of broad-based simulation models that can aid assessment and quantification of policy alternatives over longer temporal scales. The Canadian irrigated agriculture sector is concentrated in Alberta, where it represents two thirds of the irrigated land-base in Canada and is the largest consumer of surface water. Despite interest in irrigation expansion, its potential in Alberta is uncertain given a constrained water supply, significant social and economic development and increasing demands for both land and water, and climate change. This paper therefore introduces a system dynamics model as a decision support tool to provide insights into irrigation expansion in Alberta, and into trade-offs and risks associated with that expansion. It is intended to be used by a wide variety of users including researchers, policy analysts and planners, and irrigation managers. A process-based cropping system approach is at the core of the model and uses a water-driven crop growth mechanism described by AquaCrop. The tool goes beyond a representation of crop phenology and cropping systems by permitting assessment and quantification of the broader, long-term consequences of agricultural policies for Alberta's irrigation sector. It also encourages collaboration and provides a degree of transparency that gives confidence in simulation results. The paper focuses on the agricultural component of the systems model, describing the process involved; soil water and nutrients balance, crop growth, and water, temperature, salinity, and nutrients stresses, and how other disciplines can be integrated to account for the effects of interactions and feedbacks in the whole system. In later stages, other components such as

  2. Flood damage modeling based on expert knowledge: Insights from French damage model for agricultural sector

    NASA Astrophysics Data System (ADS)

    Grelot, Frédéric; Agenais, Anne-Laurence; Brémond, Pauline

    2014-05-01

    In France, since 2011, it is mandatory for local communities to conduct cost-benefit analysis (CBA) of their flood management projects, to make them eligible for financial support from the State. Meanwhile, as a support, the French Ministry in charge of Environment proposed a methodology to fulfill CBA. Like for many other countries, this methodology is based on the estimation of flood damage. Howerver, existing models to estimate flood damage were judged not convenient for a national-wide use. As a consequence, the French Ministry in charge of Environment launched studies to develop damage models for different sectors, such as: residential sector, public infrastructures, agricultural sector, and commercial and industrial sector. In this presentation, we aim at presenting and discussing methodological choices of those damage models. They all share the same principle: no sufficient data from past events were available to build damage models on a statistical analysis, so modeling was based on expert knowledge. We will focus on the model built for agricultural activities and more precisely for agricultural lands. This model was based on feedback from 30 agricultural experts who experienced floods in their geographical areas. They were selected to have a representative experience of crops and flood conditions in France. The model is composed of: (i) damaging functions, which reveal physiological vulnerability of crops, (ii) action functions, which correspond to farmers' decision rules for carrying on crops after a flood, and (iii) economic agricultural data, which correspond to featured characteristics of crops in the geographical area where the flood management project studied takes place. The two first components are generic and the third one is specific to the area studied. It is, thus, possible to produce flood damage functions adapted to different agronomic and geographical contexts. In the end, the model was applied to obtain a pool of damage functions giving

  3. Flood damage modeling based on expert knowledge: Insights from French damage model for agricultural sector

    NASA Astrophysics Data System (ADS)

    Grelot, Frédéric; Agenais, Anne-Laurence; Brémond, Pauline

    2015-04-01

    In France, since 2011, it is mandatory for local communities to conduct cost-benefit analysis (CBA) of their flood management projects, to make them eligible for financial support from the State. Meanwhile, as a support, the French Ministry in charge of Environment proposed a methodology to fulfill CBA. Like for many other countries, this methodology is based on the estimation of flood damage. However, existing models to estimate flood damage were judged not convenient for a national-wide use. As a consequence, the French Ministry in charge of Environment launched studies to develop damage models for different sectors, such as: residential sector, public infrastructures, agricultural sector, and commercial and industrial sector. In this presentation, we aim at presenting and discussing methodological choices of those damage models. They all share the same principle: no sufficient data from past events were available to build damage models on a statistical analysis, so modeling was based on expert knowledge. We will focus on the model built for agricultural activities and more precisely for agricultural lands. This model was based on feedback from 30 agricultural experts who experienced floods in their geographical areas. They were selected to have a representative experience of crops and flood conditions in France. The model is composed of: (i) damaging functions, which reveal physiological vulnerability of crops, (ii) action functions, which correspond to farmers' decision rules for carrying on crops after a flood, and (iii) economic agricultural data, which correspond to featured characteristics of crops in the geographical area where the flood management project studied takes place. The two first components are generic and the third one is specific to the area studied. It is, thus, possible to produce flood damage functions adapted to different agronomic and geographical contexts. In the end, the model was applied to obtain a pool of damage functions giving

  4. Forest and Agricultural Sector Optimization Model Greenhouse Gas Version (FASOM-GHG)

    EPA Science Inventory

    FASOM-GHG is a dynamic, multi-period, intertemporal, price-endogenous, mathematical programming model depicting land transfers and other resource allocations between and within the agricultural and forest sectors in the US. The model solution portrays simultaneous market equilibr...

  5. Modelling the water-agricultural sector in Rosetta, Egypt: exploring the interaction between water and food

    NASA Astrophysics Data System (ADS)

    Sušnik, Janez; Vamvakeridou-Lyroudia, Lydia; Savic, Dragan; Kapelan, Zoran

    2014-05-01

    An integrated System Dynamics Model for the Rosetta region, Egypt, assessing local water balance and agricultural yield to 2050, is presented. Fifty-seven simulations are analysed to better understand potential impacts on water and food security resulting from climate and social change and local/regional policy decisions related to the agricultural sector. Water limitation is a national issue: Egypt relies on the Nile for >95% of supply, and the flow of which is regulated by the Aswan High Dam. Egypt's share water of Aswan water is limited to 55 x 19 m3 yr-1. Any reduction in supply to the reservoir or increase in demand (e.g. from an expanding agricultural sector), has the potential to lead to a serious food and water supply situation. Results show current water resource over-exploitation. The remaining suite of 56 simulations, divided into seven scenarios, also mostly show resource overexploitation. Only under significant increases to Nile flow volumes was the trend reversed. Despite this, by threading together multiple local policies to reduce demand and improve/maintain supply, water resource exploitation can be mitigated while allowing for agricultural development. By changing cropping patterns, it is possible to improve yield and revenue, while using up to 21% less water in 2050 when compared with today. The results are useful in highlighting pathways to improving future water resource availability. Many policies should be considered in parallel, introducing redundancy into the policy framework. We do not suggest actual policy measures; this was beyond the scope of the work. This work highlights the utility of systems modelling of complex systems such as the water-food nexus, with the potential to extend the methodology to other studies and scales. In particular, the benefit of being able to easily modify and extend existing models in light of results from initial modelling efforts is cited. Analysis of initial results led to the hypothesis that by producing

  6. Empirical support for global integrated assessment modeling: Productivity trends and technological change in developing countries' agriculture and electric power sectors

    SciTech Connect

    Sathaye, Jayant A.

    2000-04-01

    Integrated assessment (IA) modeling of climate policy is increasingly global in nature, with models incorporating regional disaggregation. The existing empirical basis for IA modeling, however, largely arises from research on industrialized economies. Given the growing importance of developing countries in determining long-term global energy and carbon emissions trends, filling this gap with improved statistical information on developing countries' energy and carbon-emissions characteristics is an important priority for enhancing IA modeling. Earlier research at LBNL on this topic has focused on assembling and analyzing statistical data on productivity trends and technological change in the energy-intensive manufacturing sectors of five developing countries, India, Brazil, Mexico, Indonesia, and South Korea. The proposed work will extend this analysis to the agriculture and electric power sectors in India, South Korea, and two other developing countries. They will also examine the impact of alternative model specifications on estimates of productivity growth and technological change for each of the three sectors, and estimate the contribution of various capital inputs--imported vs. indigenous, rigid vs. malleable-- in contributing to productivity growth and technological change. The project has already produced a data resource on the manufacturing sector which is being shared with IA modelers. This will be extended to the agriculture and electric power sectors, which would also be made accessible to IA modeling groups seeking to enhance the empirical descriptions of developing country characteristics. The project will entail basic statistical and econometric analysis of productivity and energy trends in these developing country sectors, with parameter estimates also made available to modeling groups. The parameter estimates will be developed using alternative model specifications that could be directly utilized by the existing IAMs for the manufacturing

  7. Optimization model for the allocation of water resources based on the maximization of employment in the agriculture and industry sectors

    NASA Astrophysics Data System (ADS)

    Habibi Davijani, M.; Banihabib, M. E.; Nadjafzadeh Anvar, A.; Hashemi, S. R.

    2016-02-01

    In many discussions, work force is mentioned as the most important factor of production. Principally, work force is a factor which can compensate for the physical and material limitations and shortcomings of other factors to a large extent which can help increase the production level. On the other hand, employment is considered as an effective factor in social issues. The goal of the present research is the allocation of water resources so as to maximize the number of jobs created in the industry and agriculture sectors. An objective that has attracted the attention of policy makers involved in water supply and distribution is the maximization of the interests of beneficiaries and consumers in case of certain policies adopted. The present model applies the particle swarm optimization (PSO) algorithm in order to determine the optimum amount of water allocated to each water-demanding sector, area under cultivation, agricultural production, employment in the agriculture sector, industrial production and employment in the industry sector. Based on the results obtained from this research, by optimally allocating water resources in the central desert region of Iran, 1096 jobs can be created in the industry and agriculture sectors, which constitutes an improvement of about 13% relative to the previous situation (non-optimal water utilization). It is also worth mentioning that by optimizing the employment factor as a social parameter, the other areas such as the economic sector are influenced as well. For example, in this investigation, the resulting economic benefits (incomes) have improved from 73 billion Rials at baseline employment figures to 112 billion Rials in the case of optimized employment condition. Therefore, it is necessary to change the inter-sector and intra-sector water allocation models in this region, because this change not only leads to more jobs in this area, but also causes an improvement in the region's economic conditions.

  8. Conceptual Model Linking Land Use to Human Consumption in the Agriculture Sector

    NASA Astrophysics Data System (ADS)

    Brown, M. E.; Bounoua, L.; Imhoff, M. L.; Karpman, K. J.

    2007-12-01

    Human activities are profoundly influenced by weather and climate. Agriculture is the most extensive and important uses of land, and is particularly sensitive to climate variability. In this talk we will present a conceptual model that seeks to integrate human appropriation of terrestrial net primary production (HANPP) with socio- economic models to explore the influence of commodities markets on land use decisions. Focusing on a single commodity as a building block, we explore the methodological and data requirements of the model, presenting the impact of precipitation, temperature, population and land use on food prices through a carbon-based calculation of supply and demand. We demonstrate the critical importance of accurate and temporally varying land use maps for models that integrate the social and biophysical spheres and show the mechanistic sensitivity of land use to change in the supply and demand ratio.

  9. Agricultural sector impacts of making ethanol from grain

    SciTech Connect

    Hertzmark, D.; Ray, D.; Parvin, G.

    1980-03-01

    This report presents the results of a model of the effects on the agricultural sector of producing ethanol from corn in the United States between 1979 and 1983. The model is aggregated at the national level, and results are given for all of the major food and feed crops, ethanol joint products, farm income, government payment, and agricultural exports. A stochastic simulation was performed to ascertain the impacts of yield and demand variations on aggregate performance figures. Results indicate minimal impacts on the agricultural sector for production levels of less than 1 billion gallons of ethanol per year. For higher production levels, corn prices will rise sharply, the agricultural sector will be more vulnerable to variations in yields and demands, and joint-product values will fall. Possibilities for ameliorating such effects are discussed, and such concepts as net energy and the biomass refinery are explored.

  10. Economic Drought Impact on Agriculture: analysis of all agricultural sectors affected

    NASA Astrophysics Data System (ADS)

    Gil, M.; Garrido, A.; Hernández-Mora, N.

    2012-04-01

    The analysis of drought impacts is essential to define efficient and sustainable management and mitigation. In this paper we present a detailed analysis of the impacts of the 2004-2008 drought in the agricultural sector in the Ebro river basin (Spain). An econometric model is applied in order to determine the magnitude of the economic loss attributable to water scarcity. Both the direct impacts of drought on agricultural productivity and the indirect impacts of drought on agricultural employment and agroindustry in the Ebro basin are evaluated. The econometric model measures losses in the economic value of irrigated and rainfed agricultural production, of agricultural employment and of Gross Value Added both from the agricultural sector and the agro-industrial sector. The explanatory variables include an index of water availability (reservoir storage levels for irrigated agriculture and accumulated rainfall for rainfed agriculture), a price index representative of the mix of crops grown in each region, and a time variable. The model allows for differentiating the impacts due to water scarcity from other sources of economic losses. Results show how the impacts diminish as we approach the macro-economic indicators from those directly dependent on water abstractions and precipitation. Sectors directly dependent on water are the most affected with identifiable economic losses resulting from the lack of water. From the management perspective implications of these findings are key to develop mitigation measures to reduce drought risk exposure. These results suggest that more open agricultural markets, and wider and more flexible procurement strategies of the agro-industry reduces the socio-economic exposure to drought cycles. This paper presents the results of research conducted under PREEMPT project (Policy relevant assessment of the socioeconomic effects of droughts and floods, ECHO - grant agreement # 070401/2010/579119/SUB/C4), which constitutes an effort to provide

  11. Agricultural and Industrial Process-Heat-Market Sector workbook

    SciTech Connect

    Shulman, M. J.; Kannan, N. P.; deJong, D. L.

    1980-01-01

    This workbook summarizes the preliminary data and assumptions of the Agricultural and Industrial Process Heat Market Sector prepared in conjunction with the development of inputs for a National Plan for the Accelerated Commercialization of Solar Energy.

  12. Competences in demand within the Spanish agricultural engineering sector

    NASA Astrophysics Data System (ADS)

    Perdigones, Alicia; Valera, Diego Luis; Moreda, Guillermo Pedro; García, Jose Luis

    2014-09-01

    The Rural Engineering Department (Technical University of Madrid) ran three competence surveys during the 2006-2007 and 2007-2008 academic years and evaluated: (1) the competences gained by agricultural engineer's degree and agricultural technical engineer's degree students (360 respondents); (2) the competences demanded by agricultural employers (50 farming sector employers); (3) competences required by farming sector professionals and former students (70 professionals). The surveys show significant differences between what competences agricultural employers require of graduates and the competences they acquire during their agricultural engineering degree courses. Recruiters are looking for generic competences such as the ability to coordinate groups and place less importance on knowledge of engineering, biology, applied economics and legislation. Of the computer-related competences, those most in demand by sector professionals were related to the use of Microsoft Office/Excel (used by 79% of professionals). Surveys were used to redesign some subjects of the degrees.

  13. Analysis of methods and models for assessing the direct and indirect economic impacts of CO/sub 2/-induced environmental changes in the agricultural sector of the US economy

    SciTech Connect

    Callaway, J.M.; Cronin, F.J.; Currie, J.W.; Tawil, J.

    1982-08-01

    The overall purpose of this research was to assist the US Department of Energy (DOE) in developing methods for assessing the direct and indirect economic impacts due to the effects of increases in the ambient concentration of CO/sub 2/ on agricultural production. First, a comprehensive literature search was undertaken to determine what types of models and methods have been developed, which could be effectively used to conduct assessments of the direct and indirect economic impacts of CO/sub 2/ buildup. Specific attention was focused upon models and methods for assessing the physical impacts of CO/sub 2/-induced environmental changes on crop yields; national and multi-regional agricultural sector models; and macroeconomic models of the US economy. The second task involved a thorough investigation of the research efforts being conducted by other public and private sector organizations in order to determine how more recent analytical methods being developed outside of DOE could be effectively integrated into a more comprehensive analysis of the direct economic impacts of CO/sub 2/ buildup. The third and final task involved synthesizing the information gathered in the first two tasks into a systematic framework for assessing the direct and indirect economic impacts of CO/sub 2/-induced environmental changes originating in the agricultural sector of the US economy. It is concluded that the direct economic impacts of CO/sub 2/ on the agricultural sector and the indirect economic impacts caused by spillover effects from agriculture to other sectors of the economy will be pervasive; however, the direction and magnitude of these impacts on producers and consumers cannot be determined a priori.

  14. Ecological Models: Agricultural Models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The agricultural research community is faced with a wide array of complex problems to solve. Continued population increases in developing countries require increased agricultural production, while agroecosystems are being stressed and negatively impacted by greater use of water and agrochemicals. F...

  15. AGRICULTURAL SIMULATION MODEL (AGSIM)

    EPA Science Inventory

    AGSIM is a large-scale econometric simulation model of regional crop and national livestock production in the United States. The model was initially developed to analyze the aggregate economic impacts of a wide variety issues facing agriculture, such as technological change, pest...

  16. Agricultural sectoral demand and crop productivity response across the world

    NASA Astrophysics Data System (ADS)

    Johnston, M.; Ray, D. K.; Cassidy, E. S.; Foley, J. A.

    2013-12-01

    With an increasing and increasingly affluent population, humans will need to roughly double agricultural production by 2050. Continued yield growth forms the foundation of all future strategies aiming to increase agricultural production while slowing or eliminating cropland expansion. However, a recent analysis by one of our co-authors has shown that yield trends in many important maize, wheat and rice growing regions have begun stagnating or declining from the highs seen during the green revolution (Ray et al. 2013). Additional research by our group has shown that nearly 50% of new agricultural production since the 1960s has gone not to direct human consumption, but instead to animal feed and other industrial uses. Our analysis for GLP looks at the convergence of these two trends by examining time series utilization data for 16 of the biggest crops to determine how demand from different sectors has shaped our land-use and intensification strategies around the world. Before rushing headlong into the next agricultural doubling, it would be prudent to first consult our recent agricultural history to better understand what was driving past changes in production. Using newly developed time series dataset - a fusion of cropland maps with historic agricultural census data gathered from around the world - we can examine yield and harvested area trends over the last half century for 16 top crops. We combine this data with utilization rates from the FAO Food Balance Sheet to see how demand from different sectors - food, feed, and other - has influenced long-term growth trends from the green revolution forward. We will show how intensification trends over time and across regions have grown or contracted depending on what is driving the change in production capacity. Ray DK, Mueller ND, West PC, Foley JA (2013) Yield Trends Are Insufficient to Double Global Crop Production by 2050. PLoS ONE 8(6): e66428. doi:10.1371/journal.pone.0066428

  17. 31 CFR 542.528 - Policy on activities related to the agricultural sector of Syria.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... agricultural sector of Syria. 542.528 Section 542.528 Money and Finance: Treasury Regulations Relating to Money... related to the agricultural sector of Syria. (a) Specific licenses may be issued on a case-by-case basis to authorize U.S. persons to engage in transactions involving Syria's agricultural sector that...

  18. Analysis of methods and models for assessing the direct and indirect economic impacts of CO/sub 2/-induced environmental changes in the agricultural sector of the US economy

    SciTech Connect

    Callaway, J.M.

    1982-08-01

    Alternative methods for quantifying the economic impacts associated with future increases in the ambient concentration of CO/sub 2/ were examined. A literature search was undertaken, both to gain a better understanding of the ways in which CO/sub 2/ buildup could affect crop growth and to identify the different methods available for assessing the impacts of CO/sub 2/-induced environmental changes on crop yields. The second task involved identifying the scope of both the direct and indirect economic impacts that could occur as a result of CO/sub 2/-induced changes in crop yields. The third task then consisted of a comprehensive literature search to identify what types of economic models could be used effectively to assess the kinds of direct and indirect economic impacts that could conceivably occur as a result of CO/sub 2/ buildup. Specific attention was focused upon national and multi-regional agricultural sector models, multi-country agricultural trade models, and macroeconomic models of the US economy. The fourth and final task of this research involved synthesizing the information gathered in the previous tasks into a systematic framework for assessing the direct and indirect economic impacts of CO/sub 2/-induced environmental changes related to agricultural production.

  19. Evaluation of the Food and Agriculture Sector Criticality Assessment Tool (FASCAT) and the Collected Data.

    PubMed

    Huff, Andrew G; Hodges, James S; Kennedy, Shaun P; Kircher, Amy

    2015-08-01

    To protect and secure food resources for the United States, it is crucial to have a method to compare food systems' criticality. In 2007, the U.S. government funded development of the Food and Agriculture Sector Criticality Assessment Tool (FASCAT) to determine which food and agriculture systems were most critical to the nation. FASCAT was developed in a collaborative process involving government officials and food industry subject matter experts (SMEs). After development, data were collected using FASCAT to quantify threats, vulnerabilities, consequences, and the impacts on the United States from failure of evaluated food and agriculture systems. To examine FASCAT's utility, linear regression models were used to determine: (1) which groups of questions posed in FASCAT were better predictors of cumulative criticality scores; (2) whether the items included in FASCAT's criticality method or the smaller subset of FASCAT items included in DHS's risk analysis method predicted similar criticality scores. Akaike's information criterion was used to determine which regression models best described criticality, and a mixed linear model was used to shrink estimates of criticality for individual food and agriculture systems. The results indicated that: (1) some of the questions used in FASCAT strongly predicted food or agriculture system criticality; (2) the FASCAT criticality formula was a stronger predictor of criticality compared to the DHS risk formula; (3) the cumulative criticality formula predicted criticality more strongly than weighted criticality formula; and (4) the mixed linear regression model did not change the rank-order of food and agriculture system criticality to a large degree. PMID:25857323

  20. Armenia: The challenge of reform in the agricultural sector. World Bank country study

    SciTech Connect

    1995-12-01

    This study provides a status report on the food and agriculture sector in the Republic Armenia and assesses the progress of ongoing sectoral reforms. In addition to giving an account of the reforms in private agriculture, it recommends a set of policies to complete the transition to a sector based on private ownership and market control. Chapters 1-6 of the report presents the major conclusions of the review. Chapters 7-11 provides background analysis of major subsectors in food and agriculture and contains the statistical annex.

  1. Competences in Demand within the Spanish Agricultural Engineering Sector

    ERIC Educational Resources Information Center

    Perdigones, Alicia; Valera, Diego Luis; Moreda, Guillermo Pedro; García, Jose Luis

    2014-01-01

    The Rural Engineering Department (Technical University of Madrid) ran three competence surveys during the 2006-2007 and 2007-2008 academic years and evaluated: (1) the competences gained by agricultural engineer's degree and agricultural technical engineer's degree students (360 respondents); (2) the competences demanded by agricultural…

  2. Entrepreneurship Education and Training Needs of Family Businesses Operating in the Agricultural Sector of India

    ERIC Educational Resources Information Center

    Sandhu, Navjot; Hussain, Javed; Matlay, Harry

    2012-01-01

    Purpose: The purpose of this paper is to investigate the entrepreneurship education and training (EET) needs of small family businesses operating in the agricultural sector of the Indian economy. Design/methodology/approach: Quantitative and qualitative data were collected through a survey of 122 agricultural family firms in the Indian state of…

  3. A Spatial Data Model Desing For The Management Of Agricultural Data (Farmer, Agricultural Land And Agricultural Production)

    NASA Astrophysics Data System (ADS)

    Taşkanat, Talha; İbrahim İnan, Halil

    2016-04-01

    Since the beginning of the 2000s, it has been conducted many projects such as Agricultural Sector Integrated Management Information System, Agriculture Information System, Agricultural Production Registry System and Farmer Registry System by the Turkish Ministry of Food, Agriculture and Livestock and the Turkish Statistical Institute in order to establish and manage better agricultural policy and produce better agricultural statistics in Turkey. Yet, it has not been carried out any study for the structuring of a system which can meet the requirements of different institutions and organizations that need similar agricultural data. It has been tried to meet required data only within the frame of the legal regulations from present systems. Whereas the developments in GIS (Geographical Information Systems) and standardization, and Turkey National GIS enterprise in this context necessitate to meet the demands of organizations that use the similar data commonly and to act in terms of a data model logic. In this study, 38 institutions or organization which produce and use agricultural data were detected, that and thanks to survey and interviews undertaken, their needs were tried to be determined. In this study which is financially supported by TUBITAK, it was worked out relationship between farmer, agricultural land and agricultural production data and all of the institutions and organizations in Turkey and in this context, it was worked upon the best detailed and effective possible data model. In the model design, UML which provides object-oriented design was used. In the data model, for the management of spatial data, sub-parcel data model was used. Thanks to this data model, declared and undeclared areas can be detected spatially, and thus declarations can be associated to sub-parcels. Within this framework, it will be able to developed agricultural policies as a result of acquiring more extensive, accurate, spatially manageable and easily updatable farmer and

  4. Ammonia Emissions from the Agriculture Sector of Argentina in a Context of Changing Technologies and Practices

    NASA Astrophysics Data System (ADS)

    Dawidowski, L. E.

    2015-12-01

    Agriculture is a key sector of the Argentinean economy, accounting for 6 to 8 5% of the GDP in the last ten years. Argentina switched in the 90´s from an articulated co-evolution between extensive livestock and crop farming, with annual rotation of crops and livestock, to intensive decoupled practices. Under these new production schemes, ecosystems were supplied with more nutrients, generating increasing levels of wastes. Other changes have also occurred, associated with the shift of the agricultural frontier and the consequent reduction in the cattle stock. In addition, changes related to climate through the strong increase in rainfall in the 80s and 90s in the west Pampas, helped to boost agricultural development. The agriculture sector accounts for practically all NH3 emissions in Argentina, however no inventory has been thus far available. To bridge this gap and particularly to have accurate input information to run coupled atmospheric chemistry models for secondary inorganic aerosols, we estimated 2000-2012 NH3 emissions, both at national and spatially disaggregated levels. Of particular interest for us was also temporal disaggregation as crops growing and temperature exhibit strong seasonal variability. As no NH3 inventory was available we also estimated related N2O emissions to verify our estimates with those of national GHG emission inventory (NEI). National NH3 emissions in 2012 amounted to 309.9 Gg, use of fertilizers accounted for 43.6%, manure management 18,9%, manure in pasture 36,0% and agricultural waste burning 1.5%. Our N2O estimates are in good agreement with the GHG-NEI. NH3 estimates in the EDGAR database for 2008 are 84.0% higher than ours for this year, and exhibit more significant differences per category, namely 113,6% higher for use of fertilizers and about 500% higher for agricultural waste burning. Urea dominates national NH3 emissions, accounting for 32,8% of the total and its use for wheat and corn crops dominates the trend.

  5. Environmental and socio-economic vulnerability of agricultural sector in Armenia.

    PubMed

    Melkonyan, Ani

    2014-08-01

    Being a mountainous country, Armenia has undergone different kinds of natural disasters, such as droughts, floods, and storms, which have a direct influence on economy and are expected to occur more frequently in terms of climate change, raising the need to estimate economic vulnerability especially in agricultural sector. Agriculture plays a great role in national economy of Armenia, with 21% share in Gross Domestic Production (GDP). For this reason, the estimation of agricultural resources of the country, their vulnerability towards current and future climate, and assessment of economical loss of the agricultural crop production due to climate change are the main goals of the given study. Crop productivity in dependence on climatic elements - temperature, radiation, precipitation, wind field, etc. has been estimated, further on interpolating these relations for future climate conditions using climate projections in the region for the time period of 2011-2040. Data on air temperature, precipitation, relative humidity, wind speed and direction for the period of 1966-2011 have been taken from 30 stations from the measuring network of Armenian State Hydrometeorological Service. Other climatic parameters like potential and actual evapotranspiration, soil temperature and humidity, field capacity, and wilting point have been calculated with the help of an AMBAV/AMBETTI (agroclimatic) model (German Weather Service). The results showed that temperature increase accompanied with evapotranspiration increase and water availability decrease especially in low and mid-low altitudes (where the main national crop production is centralized) caused a significant shift in the phenological phases of crops, which is very important information for effective farming dates, giving an opportunity to raise efficiency of agricultural production through minimizing the yield loss due to unfavorable climatic conditions. With the help of macroeconomical analysis of the crop market, it was

  6. Ergonomics and design in the Brazilian agricultural sector: a proposal to build matrix of contradictions.

    PubMed

    Tosetto, Thaís; Camarotto, João Alberto

    2012-01-01

    The paper presents a correlation between the parameters of classical TRIZ and variables of analysis of the EWA to construct a matrix of contradictions in ergonomics, with the objective of assisting the designing processes in the Brazilian agricultural sector. Given the representativeness of the sector in the economy, the boundary conditions in which the activities are developed and their impact on the health of workers, this proposal should contribute to the development of adaptable solutions and the promotion of Decent Work. PMID:22317547

  7. Spatially complex land change: The Indirect effect of Brazil's agricultural sector on land use in Amazonia.

    PubMed

    Richards, Peter D; Walker, Robert T; Arima, Eugenio Y

    2014-11-01

    Soybean farming has brought economic development to parts of South America, as well as environmental hopes and concerns. A substantial hope resides in the decoupling of Brazil's agricultural sector from deforestation in the Amazon region, in which case expansive agriculture need not imply forest degradation. However, concerns have also been voiced about the potential indirect effects of agriculture. This article addresses these indirect effects forthe case of the Brazilian Amazon since 2002. Our work finds that as much as thirty-two percent of deforestation, or the loss of more than 30,000 km(2) of Amazon forest, is attributable, indirectly, to Brazil's soybean sector. However, we also observe that the magnitude of the indirect impact of the agriculture sector on forest loss in the Amazon has declined markedly since 2006. We also find a shift in the underlying causes of indirect land use change in the Amazon, and suggest that land appreciation in agricultural regions has supplanted farm expansions as a source of indirect land use change. Our results are broadly congruent with recent work recognizing the success of policy changes in mitigating the impact of soybean expansion on forest loss in the Amazon. However, they also caution that the soybean sector may continue to incentivize land clearings through its impact on regional land markets. PMID:25492993

  8. Spatially complex land change: The Indirect effect of Brazil's agricultural sector on land use in Amazonia

    PubMed Central

    Richards, Peter D.; Walker, Robert T.; Arima, Eugenio Y.

    2014-01-01

    Soybean farming has brought economic development to parts of South America, as well as environmental hopes and concerns. A substantial hope resides in the decoupling of Brazil's agricultural sector from deforestation in the Amazon region, in which case expansive agriculture need not imply forest degradation. However, concerns have also been voiced about the potential indirect effects of agriculture. This article addresses these indirect effects forthe case of the Brazilian Amazon since 2002. Our work finds that as much as thirty-two percent of deforestation, or the loss of more than 30,000 km2 of Amazon forest, is attributable, indirectly, to Brazil's soybean sector. However, we also observe that the magnitude of the indirect impact of the agriculture sector on forest loss in the Amazon has declined markedly since 2006. We also find a shift in the underlying causes of indirect land use change in the Amazon, and suggest that land appreciation in agricultural regions has supplanted farm expansions as a source of indirect land use change. Our results are broadly congruent with recent work recognizing the success of policy changes in mitigating the impact of soybean expansion on forest loss in the Amazon. However, they also caution that the soybean sector may continue to incentivize land clearings through its impact on regional land markets. PMID:25492993

  9. ECONOMIC MODELING OF ELECTRIC POWER SECTOR

    EPA Science Inventory

    CAMD performs a variety of economic modeling analyses to evaluate the impact of air emissions control policies on the electric power sector. A range of tools are used for this purpose including linear programming models, general equilibrium models, and spreadsheet models. Examp...

  10. Vulnerability of U.S. Agriculture and Energy Sectors to Changes in Climate and Socioeconomics

    NASA Astrophysics Data System (ADS)

    Hejazi, M. I.; Voisin, N.; Liu, L.; Bramer, L.; Fortin, D.; Huang, M.; Hathaway, J.; Kyle, P.; Leung, L. R.; Li, H. Y.; Liu, Y.; Patel, P.; Pulsipher, T.; Rice, J.; Tesfa, T. K.; Vernon, C. R.; Zhou, Y.

    2014-12-01

    A prominent integrated assessment model (IAM), the Global Change Assessment Model (GCAM), has been coupled with the Community Land Model (CLM) of the Community Earth system model (CESM) to assess the vulnerability of the US agriculture and energy sectors to future water shortages under changing climate and socioeconomics. This study utilizes the regionalized version of GCAM for the U.S. with 50-state. GCAM-USA includes a detailed representation of water demands and tracks them at multiple spatial scales and annual scale. A spatial and temporal disaggregation approach is developed to project the annual regional water demand simulations into a daily time step and 1/8o spatial resolution for input to CLM, which has been coupled to a river routing model and generic water management model applicable globally at 1/2o resolution and regionally at 1/8o resolution. The coupled modeling framework demonstrated reasonable ability to simulate the historical flow regulation and water supply over the continental U.S. The coupled modeling framework has been used to investigate: 1) Which water use sector (agriculture or energy) and subbasins in the conterminous U.S. will experience water deficits in future decades; 2) What are the drivers for the deficit (i.e., water availability, water demands, or both); 3) Will climate mitigation policies alleviate or exacerbate the situation; and lastly 4) How will the frequency , severity, and spatial extent of water deficits (hot spots) evolve under a non-mitigation scenario (RCP8.5) in which conventional fossil-fueled technologies prevail versus a mitigation scenario (RCP4.5) in which the carbon price causes a shift toward renewables and expansion of bioenergy productions. Results show that irrigation will face greater water deficit overall except in the northeastern U.S. Water deficit is greatest in the western U.S. except the Pacific Northwest. Human footprints on the regulated flows are most pronounced over the Rio Grande, Colorado, Great

  11. Climate change and its effect on agriculture, water resources and human health sectors in Poland

    NASA Astrophysics Data System (ADS)

    Szwed, M.; Karg, G.; Pińskwar, I.; Radziejewski, M.; Graczyk, D.; Kedziora, A.; Kundzewicz, Z. W.

    2010-08-01

    Multi-model ensemble climate projections in the ENSEMBLES Project of the EU allowed the authors to quantify selected extreme-weather indices for Poland, of importance to climate impacts on systems and sectors. Among indices were: number of days in a year with high value of the heat index; with high maximum and minimum temperatures; length of vegetation period; and number of consecutive dry days. Agricultural, hydrological, and human health indices were applied to evaluate the changing risk of weather extremes in Poland in three sectors. To achieve this, model-based simulations were compared for two time horizons, a century apart, i.e., 1961-1990 and 2061-2090. Climate changes, and in particular increases in temperature and changes in rainfall, have strong impacts on agriculture via weather extremes - droughts and heat waves. The crop yield depends particularly on water availability in the plant development phase. To estimate the changes in present and future yield of two crops important for Polish agriculture i.e., potatoes and wheat, some simple empirical models were used. For these crops, decrease of yield is projected for most of the country, with national means of yield change being: -2.175 t/ha for potatoes and -0.539 t/ha for wheat. Already now, in most of Poland, evapotranspiration exceeds precipitation during summer, hence the water storage (in surface water bodies, soil and ground) decreases. Summer precipitation deficit is projected to increase considerably in the future. The additional water supplies (above precipitation) needed to use the agro-potential of the environment would increase by half. Analysis of water balance components (now and in the projected future) can corroborate such conclusions. As regards climate and health, a composite index, proposed in this paper, is a product of the number of senior discomfort days and the number of seniors (aged 65+). The value of this index is projected to increase over 8-fold during 100 years. This is an

  12. Environmental sub models for a macroeconomic model: agricultural contribution to climate change and acidification in Denmark.

    PubMed

    Jensen, Trine S; Jensen, Jørgen D; Hasler, Berit; Illerup, Jytte B; Andersen, Frits M

    2007-01-01

    Integrated modelling of the interaction between environmental pressure and economic development is a useful tool to evaluate environmental consequences of policy initiatives. However, the usefulness of such models is often restricted by the fact that these models only include a limited set of environmental impacts, which are often energy-related emissions. In order to evaluate the development in the overall environmental pressure correctly, these model systems must be extended. In this article an integrated macroeconomic model system of the Danish economy with environmental modules of energy related emissions is extended to include the agricultural contribution to climate change and acidification. Next to the energy sector, the agricultural sector is the most important contributor to these environmental themes and subsequently the extended model complex calculates more than 99% of the contribution to both climate change and acidification. Environmental sub-models are developed for agriculture-related emissions of CH(4), N(2)O and NH(3). Agricultural emission sources related to the production specific activity variables are mapped and emission dependent parameters are identified in order to calculate emission coefficients. The emission coefficients are linked to the economic activity variables of the Danish agricultural production. The model system is demonstrated by projections of agriculture-related emissions in Denmark under two alternative sets of assumptions: a baseline projection of the general economic development and a policy scenario for changes in the husbandry sector within the agricultural sector. PMID:16549237

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

    SciTech Connect

    Larson, J.A.; English, B.C.; De La Torre Ugarte, D. G.; Menard, R.J.; Hellwinckel, C.M.; West, Tristram O.

    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 higher 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.

  14. Which environmental problems get policy attention? Examining energy and agricultural sector policies in Sweden

    SciTech Connect

    Engstroem, Rebecka Nilsson, Mans Finnveden, Goeran

    2008-05-15

    Not all environmental problems get the same level of policy attention. An interesting question is thus why certain aspects receive attention and others do not. This paper studies the level of policy attention given to different environmental aspects in agriculture and energy policy in Sweden and explores empirically some factors that can explain the level of attention. The first step was to explore the link between environmental issue characteristics and the level of policy attention. The level of policy attention was measured through a content analysis of Swedish government bills. The results from the content analysis are clear and stable over the studied time period. In the agriculture sector biodiversity and toxicity are in focus whereas in the energy sector climate change and resources are given the attention. Besides these aspects, the attention is limited. These results were compared with the results from sector-wide environmental assessments of the same sectors. These assessments were based on hybrid input-output analysis and life cycle assessment methodologies. A main finding from the study is that issue importance is a necessary but not a sufficient condition for policy attention. Other explanations are needed to understand which environmental issues get attention in sectoral policy. Our assessment showed that while the level of knowledge does not provide an explanation, the presence of strong and well-organised stakeholders within the sector, with an interest in having a certain issue on the agenda, might be decisive for issue attention. Path dependency and limited attention capacity are other important factors.

  15. What Drives Indirect Land Use Change? How Brazil's Agriculture Sector Influences Frontier Deforestation

    PubMed Central

    Richards, Peter

    2015-01-01

    From 2000-2005 high returns to soybeans set off an unprecedented expansion of agricultural production across Brazil. The expansion occurred concurrently to a sharp rise in deforestation, leading academics and policy makers to question the extent and means by which the growing agricultural sector was driving regional forest loss. In this article we consider and question the underlying drivers of indirect land use change, namely the potential impact of soybean expansion on beef prices and of land use displacement, via migration. We then present field level results documenting the displacement process in northern Mato Grosso and western Pará States of the Amazon. Our results question the extent to which tropical Amazon deforestation is attributable to land use displacement; however, we argue that the agricultural sector may drive deforestation through other channels, namely through regional land markets. PMID:26985080

  16. Representing Extremes in Agricultural Models

    NASA Technical Reports Server (NTRS)

    Ruane, Alex

    2015-01-01

    AgMIP and related projects are conducting several activities to understand and improve crop model response to extreme events. This involves crop model studies as well as the generation of climate datasets and scenarios more capable of capturing extremes. Models are typically less responsive to extreme events than we observe, and miss several forms of extreme events. Models also can capture interactive effects between climate change and climate extremes. Additional work is needed to understand response of markets and economic systems to food shocks. AgMIP is planning a Coordinated Global and Regional Assessment of Climate Change Impacts on Agricultural Production and Food Security with an aim to inform the IPCC Sixth Assessment Report.

  17. Rabi multi-sector reservoir simulation model

    SciTech Connect

    Bruijnzeels, C.; O`Halloran, C.

    1995-12-31

    To ensure optimum ultimate recovery of the 46 meter thick oil rim of the Rabi Field in Gabon, a full field simulation model was required. Due to it`s size and complexity, with local cusping, coning and geological circumstances dominating individual well behavior, a single full field model would be too large for existing hardware. A method was developed to simulate the full field with 5 separate sector models, whilst allowing the development in one sector model to have an effect on the boundary conditions of another sector. In this manner, the 13 x 4.5 km field could be simulated with a horizontal well spacing down to 175 meter. This paper focuses on the method used to attach single 3-phase tank cells to a sector simulation grid in order to represent non-simulated parts of the field. It also describes the history matching methodology and how to run a multisector model in forecasting mode. This method can be used for any reservoir, where size and complexity require large reservoir simulation models that normally could not be modeled within the constraints of available computer facilities. Detailed studies can be conducted on specific parts of a field, whilst allowing for dynamic flow and pressure effects caused by the rest of the field.

  18. Modeling agriculture in the Community Land Model

    NASA Astrophysics Data System (ADS)

    Drewniak, B.; Song, J.; Prell, J.; Kotamarthi, V. R.; Jacob, R.

    2013-04-01

    The potential impact of climate change on agriculture is uncertain. In addition, agriculture could influence above- and below-ground carbon storage. Development of models that represent agriculture is necessary to address these impacts. We have developed an approach to integrate agriculture representations for three crop types - maize, soybean, and spring wheat - into the coupled carbon-nitrogen version of the Community Land Model (CLM), to help address these questions. Here we present the new model, CLM-Crop, validated against observations from two AmeriFlux sites in the United States, planted with maize and soybean. Seasonal carbon fluxes compared well with field measurements for soybean, but not as well for maize. CLM-Crop yields were comparable with observations in countries such as the United States, Argentina, and China, although the generality of the crop model and its lack of technology and irrigation made direct comparison difficult. CLM-Crop was compared against the standard CLM3.5, which simulates crops as grass. The comparison showed improvement in gross primary productivity in regions where crops are the dominant vegetation cover. Crop yields and productivity were negatively correlated with temperature and positively correlated with precipitation, in agreement with other modeling studies. In case studies with the new crop model looking at impacts of residue management and planting date on crop yield, we found that increased residue returned to the litter pool increased crop yield, while reduced residue returns resulted in yield decreases. Using climate controls to signal planting date caused different responses in different crops. Maize and soybean had opposite reactions: when low temperature threshold resulted in early planting, maize responded with a loss of yield, but soybean yields increased. Our improvements in CLM demonstrate a new capability in the model - simulating agriculture in a realistic way, complete with fertilizer and residue management

  19. Extending the Agricultural Extension Model. Preliminary Draft.

    ERIC Educational Resources Information Center

    Rogers, Everett M.; And Others

    The purposes of this report are: to describe the main elements of the U.S. agricultural extension model and its effects on the agricultural revolution; to analyze attempts to extend this model to non-agricultural technology and/or to less developed countries; and to draw general conclusions about the diffusion of technological innovations, with…

  20. Modeling agriculture in the Community Land Model

    NASA Astrophysics Data System (ADS)

    Drewniak, B.; Song, J.; Prell, J.; Kotamarthi, V. R.; Jacob, R.

    2012-12-01

    The potential impact of climate change on agriculture is uncertain. In addition, agriculture could influence above- and below-ground carbon storage. Development of models that represent agriculture is necessary to address these impacts. We have developed an approach to integrate agriculture representations for three crop types - maize, soybean, and spring wheat - into the coupled carbon-nitrogen version of the Community Land Model (CLM), to help address these questions. Here we present the new model, CLM-Crop, validated against observations from two AmeriFlux sites in the United States, planted with maize and soybean. Seasonal carbon fluxes compared well with field measurements. CLM-Crop yields were comparable with observations in some regions, although the generality of the crop model and its lack of technology and irrigation made direct comparison difficult. CLM-Crop was compared against the standard CLM3.5, which simulates crops as grass. The comparison showed improvement in gross primary productivity in regions where crops are the dominant vegetation cover. Crop yields and productivity were negatively correlated with temperature and positively correlated with precipitation. In case studies with the new crop model looking at impacts of residue management and planting date on crop yield, we found that increased residue returned to the litter pool increased crop yield, while reduced residue returns resulted in yield decreases. Using climate controls to signal planting date caused different responses in different crops. Maize and soybean had opposite reactions: when low temperature threshold resulted in early planting, maize responded with a loss of yield, but soybean yields increased. Our improvements in CLM demonstrate a new capability in the model - simulating agriculture in a realistic way, complete with fertilizer and residue management practices. Results are encouraging, with improved representation of human influences on the land surface and the potentially

  1. Estimating farmers' willingness to pay for climate change adaptation: the case of the Malaysian agricultural sector.

    PubMed

    Masud, Muhammad Mehedi; Junsheng, Ha; Akhtar, Rulia; Al-Amin, Abul Quasem; Kari, Fatimah Binti

    2015-02-01

    This paper estimates Malaysian farmers' willingness to pay (WTP) for a planned adaptation programme for addressing climate issues in the Malaysian agricultural sector. We used the contingent valuation method (CVM) for a monetary valuation of farmers' preferences for a planned adaptation programme by ascertaining the value attached to address climatic issues in the Malaysian agricultural sector. Structured questionnaires were distributed among the sampled farmers. The study found that 74 % of respondents were willing to pay for a planned adaptation programme and that several socioeconomic and motivation factors have greater influence on their WTP. This paper clearly specifies the steps needed for all institutional bodies to better address issues in climate change. The outcomes of this paper will support policy makers to better design an efficient adaptation framework for adapting to the adverse impacts of climate change. PMID:25632900

  2. A Decision Support System for Climate Change Adaptation in Rainfed Sectors of Agriculture for Central Europe

    NASA Astrophysics Data System (ADS)

    Mátyás, Csaba; Berki, Imre; Drüszler, Áron; Eredics, Attila; Gálos, Borbála; Illés, Gábor; Móricz, Norbert; Rasztovits, Ervin; Czimber, Kornél

    2013-04-01

    • Background and aims: Rainfed sectors of agriculture such as nature-close forestry, non-irrigated agriculture and animal husbandry on nature-close pastures are threatened by projected climate change especially in low-elevation regions in Southeast Europe, where precipitation is the limiting factor of production and ecosystem stability. Therefore the importance of complex, long term management planning and of land use optimization is increasing. The aim of the Decision Support System under development is to raise awareness and initiate preparation for frequency increase of extreme events, disasters and economic losses in the mentioned sectors. • Services provided: The Decision Support System provides GIS-supported information about the most important regional and local risks and mitigation options regarding climate change impacts, projected for reference periods until 2100 (e.g. land cover/use and expectable changes, potential production, water and carbon cycle, biodiversity and other ecosystem services, potential pests and diseases, tolerance limits etc.). The projections are referring first of all on biological production (natural produce), but the System includes also social and economic consequences. • Methods: In the raster based system, the latest image processing technology is used. We apply fuzzy membership functions, Support Vector Machine and Maximum Likelihood classifier. The System is developed in the first step for a reference area in SW Hungary (Zala county). • Novelty: The coherent, fine-scale regional system integrates the basic information about present and projected climates, extremes, hydrology and soil conditions and expected production potential for three sectors of agriculture as options for land use and conservation. • Funding: The development of the Decision Support System "Agrárklíma" is supported by TÁMOP-4.2.2.A-11/1/KONV and 4.2.2.B-10/1-2010-0018 "Talentum" joint EU-national research projects. Keywords: climate change

  3. Hidden sector DM models and Higgs physics

    SciTech Connect

    Ko, P.

    2014-06-24

    We present an extension of the standard model to dark sector with an unbroken local dark U(1){sub X} symmetry. Including various singlet portal interactions provided by the standard model Higgs, right-handed neutrinos and kinetic mixing, we show that the model can address most of phenomenological issues (inflation, neutrino mass and mixing, baryon number asymmetry, dark matter, direct/indirect dark matter searches, some scale scale puzzles of the standard collisionless cold dark matter, vacuum stability of the standard model Higgs potential, dark radiation) and be regarded as an alternative to the standard model. The Higgs signal strength is equal to one as in the standard model for unbroken U(1){sub X} case with a scalar dark matter, but it could be less than one independent of decay channels if the dark matter is a dark sector fermion or if U(1){sub X} is spontaneously broken, because of a mixing with a new neutral scalar boson in the models.

  4. Vulnerability of the Ecuador's Agricultural Sector as part of an Integrated Climate Change Vulnerability Study

    NASA Astrophysics Data System (ADS)

    Flores-Lopez, F.; Depsky, N. J.

    2014-12-01

    Earlier this year SEI, in conjunction with the Environmental Secretary of Quito, concluded a vulnerability analysis for the Metropolitan District of Quito (DMQ). The study analyzed future anthropogenic and natural hazards, and how these threats may be potentially exacerbated by a changing climate over the next 40 years. The focus of this abstract is specifically on the vulnerability of the agricultural sector.Overall, there is a lack of consensus amongst the results of long-term trends of precipitation in the Quito region. However, there is much more confidence in the trends of mean air temperature increase, and therefore this analysis focused specifically upon the effects of increasing temperatures upon Quito's agricultural sector. Effects of a roughly 2°C increase in mean air temperature by 2050 (corresponding to a relative CO2 concentration pathway within the GCMs of 8.5) was evaluated with respect to its potential effects upon the length of growing season for principal crops, and which of these crops are most vulnerable to the increased heat stress. Also studied was the potential expansion of agriculture into higher elevation areas, namely the sensitive 'paramo' alpine ecosystem, due to increasing arability of these areas as temperatures rise. The extent of cultivation of 'paramos' areas was estimated in order to assess the likely diminutive effects upon local hydrology and ecosystem well-being.Our results show that in fact it is expected that the increase in temperature would have a positive effect on the development of some crops, though the growing seasons would likely be shortened, which may be problematic given soil and rainfall constraints.Regarding expansion of agriculture into the 'paramo' highlands, results showed that each 200m zone above 3400masl would experience a marked increase in agricultural land conversion, ranging from 15 - 55km2, depending upon the zone. The lowest zones are expectedly the most vulnerable as they already exist at the

  5. Communicating Climate Change in the Agricultural Sector: Insights from Surveys and Interviews with Agricultural Advisors in the Midwestern United States

    NASA Astrophysics Data System (ADS)

    Prokopy, L. S.; Carlton, S.; Dunn, M.

    2014-12-01

    Understanding U.S. agricultural stakeholder views about the existence of climate change and what influences these views is central to developing communication in support of adaptation and mitigation. It has been postulated in the literature that extreme weather events can shape people's climate change beliefs and adaptation attitudes. In this presentation, we use data from pre- and post-extreme event surveys and interviews to examine the effects of the 2012 Midwestern US drought on agricultural advisors' climate change beliefs, adaptation attitudes, and risk perceptions. We found that neither climate change beliefs nor attitudes toward adaptation changed significantly as a result of the drought. Risk perceptions did change, however, with advisors becoming more concerned about risks from drought and pests and less concerned about risks related to flooding and ponding. Qualitative interviews revealed that while advisors readily accept the occurrence of extreme weather as a risk, the irregularity and unpredictability of extreme events for specific localities limits day-to-day consideration in respect to prescribed management advice. Instead, advisors' attention is directed towards planning for short-term changes encompassing weather, pests, and the market, as well as planning for long-term trends related to water availability. These findings provide important insights for communicating climate change in this critical sector while illustrating the importance of social science research in planning and executing communication campaigns.

  6. Model documention: Commercial Sector Energy Model. [CSEM

    SciTech Connect

    Not Available

    1984-08-10

    The CSEM forecasts floorspace area and demand for natural gas, electricity and fuel oil for six building categories in four Census regions. Real disposable personal income, population and real fuel prices are the major exogenous drivers of these forecasts. The commercial model uses the coefficients from the three econometric submodules to calculate building floorspace, end-use fuel choices, and utilization (enegy use per square foot) for the three major fuels. Separately from these structural components the model also calculates energy use for the minor fuels liquefied petroleum gas, kerosene, coal and motor gasoline. Through the use of accounting equations, the commercial model combines the structural components to get total commercial energy use over the major fuels. It then adds in the minor fuels, passes the information back to the other models and writes reports.

  7. Agricultural, domestic and handicraft folk uses of plants in the Tyrrhenian sector of Basilicata (Italy)

    PubMed Central

    Salerno, Giovanni; Guarrera, Paolo Maria; Caneva, Giulia

    2005-01-01

    Background Research was carried out into agricultural and domestic-handicraft uses in folk traditions in the Tyrrhenian sector of the Basilicata region (southern Italy), as it is typically representative of ethnobotanical applications in the Mediterranean area. From the point of view of furnishing a botanical support for the study of local "material culture" data was collected through field interviews of 49 informants, most of whom were farmers. Results The taxa cited are 60, belonging to 32 botanical families, of which 18 are employed for agricultural uses and 51 for domestic-handicraft folk uses. Data show a diffuse use of plants for many purposes, both in agricultural (present uses 14%; past uses 1%) and for domestic-handicraft use (present uses 40%; past uses 45%); most of the latter are now in decline. Conclusion 60 data look uncommon or typical of the places studied. Some domestic-handicraft folk uses are typical of southern Italy (e.g. the use of Ampelodesmos mauritanicus for making ties, ropes, torches, baskets or that of Acer neapolitanum for several uses). Other uses (e.g. that of Inula viscosa and Calamintha nepeta for peculiar brooms, and of Origanum heracleoticum for dyeing wool red) are previously unpublished. PMID:16270919

  8. Climate change mitigation in the agricultural sector- an analysis of marginal abatement costs of climate mitigation in global paddy rice agriculture based on DNDC simulations

    NASA Astrophysics Data System (ADS)

    Li, C.; Li, J.; Beach, R.; Salas, W.; Ingraham, P.; Ragnauth, S.

    2012-12-01

    Authors: Jia Li1, Robert H. Beach2, Changsheng Li3, William Salas4, Pete Ingraham5, Shaun Ragnauth1 INSTITUTIONS (ALL): 1. Climate Change Division, US Environmental Protection Agency, Washington, DC, United States. 2. RTI International, Durham, NC, United States. 3. ESRC, University of New Hampshire, Durham, NH, United States. 4. Applied Geosolutions, LLC, Newmarket, NH, United States. Global agriculture sector faces the dual challenge of climate change mitigation and providing food security for a growing population. In a new study, the U.S. EPA has developed an analysis of mitigation of non-CO2 greenhouse gases for the global agriculture sector. We estimate global greenhouse gas (GHG) emissions from paddy rice cultivation and rice yields under baseline management conditions as well as for alternative mitigation options. These biophysical effects are combined with data on input use and costs to estimate marginal abatement cost curves and evaluate the cost-effectiveness of mitigation options for global rice cropping systems. DNDC, a process-based crop model, is used to simulate crop yields, methane and nitrous oxide emissions, as well as soil carbon sequestration of the various rice cropping systems (irrigated and rainfed, and single, double, triple and mixed rotations) under local climatic and soil conditions at a 0.5 degree resolution at the global scale. We evaluate the impacts of various management alternatives (e.g., flooding methods, fertilizer applications, and crop residue management) on crop yields and GHG emissions and report the spatial and temporal distributions of the outcomes. The analysis provides important insights on the potential for closing the production efficiency gaps and the trade-offs and synergies between GHG mitigation and food security in different parts of the world.

  9. Pesticide Health and Safety Challenges Facing Informal Sector Workers: A Case of Small-scale Agricultural Workers in Tanzania.

    PubMed

    Ngowi, Aiwerasia; Mrema, Ezra; Kishinhi, Stephen

    2016-08-01

    The Tanzania informal sector is growing fast, with precarious working conditions and particular hazards for women and children in agriculture. Hazardous agricultural chemicals including pesticides are mostly imported and have been used for many years. Despite the role played by pesticides in food security and vector control, these chemicals are responsible for acute and chronic illnesses among communities. The availability of obsolete persistent organic pesticides on the open market indicates existence of an inadequate regulatory system. People who get injured or ill in the agriculture sector in Tanzania receive health services in primary health care facilities where professionals have little or no knowledge of pesticides. We are presenting the pesticide health and safety challenges faced by small-scale farmers who fall in the informal sector. Achievements that have been made by the government and other players to reduce and prevent pesticide exposures and poisoning are also outlined. PMID:27406110

  10. Process heat in California: Applications and potential for solar energy in the industrial, agricultural and commercial sectors

    NASA Technical Reports Server (NTRS)

    Barbieri, R. H.; Bartera, R. E.; Davis, E. S.; Hlavka, G. E.; Pivirotto, D. S.; Yanow, G.

    1978-01-01

    A summary of the results of a survey of potential applications of solar energy for supplying process heat requirements in the industrial, agricultural, and commercial sectors of California is presented. Technical, economic, and institutional characteristics of the three sectors are examined. Specific applications for solar energy are then discussed. Finally, implications for California energy policy are discussed along with recommendations for possible actions by the State of California.

  11. Agriculture sector resource and environmental policy analysis: an economic and biophysical approach.

    PubMed

    House, R; McDowell, H; Peters, M; Heimlich, R

    1999-01-01

    Agricultural pollution of the environment is jointly determined by economic decisions driving land use, production practices, and stochastic biophysical processes associated with agricultural production, land and climate characteristics. It follows that environmental and economic statistics, traditionally collected independently of each other, offer little insight into non-point pollutant loadings. We argue that effective policy development would be facilitated by integrating environmental and economic data gathering, combined with simulation modelling linking economic and biophysical components. Integrated data collection links economics, land use, production methods and environmental loadings. An integrated economic/biophysical modelling framework facilitates policy analysis because monetary incentives to reduce pollution can be evaluated in the context of market costs and returns that influence land use and production activity. This allows prediction of environmental and economic outcomes from alternative policies to solve environmental problems. We highlight steps taken to merge economic and biophysical modelling for policy analysis within the Economic Research Service of the United States Department of Agriculture. An example analysis of a policy to reduce agricultural nitrogen pollution is presented, with the economic and environmental results illustrating the value of linked economic and biophysical analysis. PMID:10231835

  12. Accounting for cross-sectoral linkages of climate change impacts based on multi-model projections

    NASA Astrophysics Data System (ADS)

    Frieler, Katja

    2013-04-01

    Understanding how natural and human systems will be affected by climate change is not possible without accounting for cascading effects across different sectors. However, cross-sectoral inter-linkages remain strongly underrepresented in model-based assessments of climate change impacts. Based on the currently unique cross-sectoral multi-model data set generated for ISI-MIP (the first Inter-Sectoral Impact Model Intercomparison Project), we investigate climate-induced adaptation pressures on the global food production system, taking into account cross-sectoral co-limitations and response options, and quantifying uncertainties due to different model categories involved (climate-, crop-, hydrology-, ecosystem-models). Results from 7 global crop models are synthesised to analyse changes in global wheat, maize, rice, and soy production as a function of global mean warming, on current agricultural land. To integrate constraints on the availability of water we propose a simple approach to estimate the maximum possible increase in global production based on limitations of renewable irrigation water as projected by 11 global hydrological models. The effect is compared to the production increase due to land-use changes as suggested by the demand fulfilling agro-economic model MAgPIE. While providing production increases the extension of farmland exerts a strong pressure on natural vegetation systems. This pressure is again compared to the pressure on natural vegetation that is induced by climate change itself. The analysis will provide a cross sectoral synthesis of the ISI-MIP results.

  13. The Agricultural Model Intercomparison and Improvement Project (AgMIP): Overview and Progress

    NASA Astrophysics Data System (ADS)

    Rosenzweig, C.; Hatfield, J.; Jones, J. W.; Ruane, A. C.

    2012-12-01

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) is an international effort to assess the state of global agricultural modeling and to understand climate impacts on the agricultural sector. AgMIP connects the climate science, crop modeling, and agricultural economic modeling communities to generate probabilistic projections of current and future climate impacts. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. This presentation will describe the general approach of AgMIP and highlight its findings and activities. AgMIP crop model intercomparisons have been established for wheat (27 models participating), maize (25 models), and rice (15+ models), and are being established for sugarcane, soybean, sorghum/millet, and peanut. In coordination with these pilots, methodologies to utilize weather generators and downscaled climate simulations for agricultural applications are under development. An AgMIP global agricultural economics model intercomparison with participation of 11 international groups is ongoing, and a number of global biophysical models are currently being evaluated for future climate impacts on agricultural lands both as part of the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) and for contribution to the IPCC Fifth Assessment Report (AR5). AgMIP is also organizing regional research efforts, and has already held workshops in South America, Sub-Saharan Africa, South Asia, Europe, and North America. Outcomes from these meetings have informed AgMIP activities, and 10 research teams from Sub-Saharan Africa and South Asia have been selected for project funding. Additional activities are planned for Australia and East Asia. As the AgMIP research community continues to work towards its goals, three key cross-cutting scientific challenges have emerged and are being

  14. China-Us Border Effect of Agricultural Trade Using Gravity Model

    NASA Astrophysics Data System (ADS)

    Zhu, Haixia; Gu, Haiying

    Two border effect models capturing the characteristics of agricultural trade based on the Gravity Model are put forward to make a study on China-US border effects in the sector of agricultural trade. Different methods are used to check the robustness of the models. Applying the panel data covering 1987-2005, the empirical results show that the border effects of China-US exist with a great magnitude and tend to drop over time. They differ greatly from the direction of the international trade. Linear model in log-form can well explain the border effects of China-US agricultural trade.

  15. Quantifying the Value of Satellite Imagery in Agriculture and other Sectors

    NASA Astrophysics Data System (ADS)

    Brown, M. E.; Abbott, P. C.; Escobar, V. M.

    2013-12-01

    This study focused on quantifying the commercial value of satellite remote sensing for agriculture. Commercial value from satellite imagery arises when improved information leads to better economic decisions. We identified five areas of application of remote sensing to agriculture where there is this potential: crop management (precision agriculture), insurance, real estate assessment, crop forecasting, and environmental monitoring. These applications can be divided between public information (crop forecasting) and those that may generate private commercial value (crop management), with both public and private information dimensions in some categories. Public information applications of remote sensing have been more successful in the past, and are likely to generate more economic value in the future. It was found that several issues have limited realization of the potential to generate private value from remote sensing in agriculture. The scale of use is small to the high cost of acquiring and interpreting large images has limited the cost effectiveness to individual farmers. Insurance, environmental monitoring, and crop management services by cooperatives or consultants may be cases overcoming this limitation. The greatest opportunities for potential commercial value from agriculture are probably in the crop forecasting area, especially where agricultural statistics services are not as well developed, since public market information benefits a broad range of economic actors, not limited to countries where forecasts are made. We estimate here the value from components of USDA's World Agricultural Supply and Demand Estimates (WASDE) forecasts for corn, indicating potential value increasing in the range of 60 to 240 million if improved satellite based information enhances those forecasts. The research was conducted by agricultural economists at Purdue University, and will be the basis for further evaluation of the use of satellite data within the NASA Carbon

  16. Agricultural climate impacts assessment for economic modeling and decision support

    NASA Astrophysics Data System (ADS)

    Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

    2013-12-01

    A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a

  17. Technology choice and development in Brazil: An assessment of Brazil's alternative fuel program and the agriculture, manufacturing, energy, and service sectors

    NASA Astrophysics Data System (ADS)

    Nolan, Lucy A.

    Technology choice profoundly affects a country's development process because capital-intensive and labor-intensive technologies have different socioeconomic linkages within the economy. This research examines the impacts of technology choice through the use of a social accounting matrix (SAM) framework. SAM-based modeling determines the direct and indirect effects of technology choice on development, particularly poverty alleviation in Brazil. Brazil's alternative fuel program was analyzed as a special example of technology choice. Two ethanol production technologies and the gasoline sector were compared; to make the study more robust, labor and capital intensive technologies were evaluated in the production of agriculture, manufacturing, energy, and services. Growth in these economic sectors was examined to assess the effects on employment, factor and household income, energy intensity, and carbon dioxide costs. Poverty alleviation was a focus, so income to unskilled agriculture labor, unskilled non-agriculture labor, and income to rural and urban households in poverty was also analyzed. The major research finding is that overall, labor-intensive technologies generate more employment, factor and household income, environmental and energy benefits to Brazil's economy than capital-intensive technologies. In addition, labor-intensive technologies make a particular contribution to poverty alleviation. The results suggest that policies to encourage the adoption of these technologies, especially in the agriculture and renewable energy sectors, are important because of their intersectoral linkages within the economy. Many studies have shown that Brazil's fuel ethanol program has helped to realize multiple macroeconomic objectives. However, this is the first empirical study to quantify its household income effects. The ethanol industry generated the most household income of the energy sectors. The research confirms a key finding of the appropriate technology literature

  18. Modeling of pesticide emissions from agricultural ecosystems

    NASA Astrophysics Data System (ADS)

    Li, Rong

    2012-04-01

    Pesticides are applied to crops and soils to improve agricultural yields, but the use of pesticides has become highly regulated because of concerns about their adverse effects on human health and environment. Estimating pesticide emission rates from soils and crops is a key component for risk assessment for pesticide registration, identification of pesticide sources to the contamination of sensitive ecosystems, and appreciation of transport and fate of pesticides in the environment. Pesticide emission rates involve processes occurring in the soil, in the atmosphere, and on vegetation surfaces and are highly dependent on soil texture, agricultural practices, and meteorology, which vary significantly with location and/or time. To take all these factors into account for simulating pesticide emissions from large agricultural ecosystems, this study coupled a comprehensive meteorological model with a dynamic pesticide emission model. The combined model calculates hourly emission rates from both emission sources: current applications and soil residues resulting from historical use. The coupled modeling system is used to compute a gridded (36 × 36 km) hourly toxaphene emission inventory for North America for the year 2000 using a published U.S. toxaphene residue inventory and a Mexican toxaphene residue inventory developed using its historical application rates and a cropland inventory. To my knowledge, this is the first such hourly toxaphene emission inventory for North America. Results show that modeled emission rates have strong diurnal and seasonal variations at a given location and over the entire domain. The simulated total toxaphene emission from contaminated agricultural soils in North America in 2000 was about 255 t, which compares reasonably well to a published annual estimate. Most emissions occur in spring and summer, with domain-wide emission rates in April, May and, June of 36, 51, and 35 t/month, respectively. The spatial distribution of emissions depends

  19. How to engage across sectors: lessons from agriculture and nutrition in the Brazilian School Feeding Program

    PubMed Central

    Hawkes, Corinna; Brazil, Bettina Gerken; de Castro, Inês Rugani Ribeiro; Jaime, Patricia Constante

    2016-01-01

    ABSTRACT OBJECTIVE To provide insights for nutrition and public health practitioners on how to engage with other sectors to achieve public health goals. Specifically, this study provides lessons from the example of integrating family farming and a nutrition into a legal framework in Brazil on how to successfully shift other sectors toward nutrition goals. METHODS The study analyzed policy processes that led to a Brazilian law linking family farming with the National School Feeding Program. Main actors involved with the development of the law were interviewed and their narratives were analyzed using a well-established theoretical framework. RESULTS The study provides five key lessons for promoting intersectorality. First, nutrition and health practitioners can afford to embrace bold ideas when working with other sectors. Second, they should engage with more powerful sectors (or subsectors) and position nutrition goals as providing solutions that meet the interests of these sector. Third is the need to focus on a common goal – which may not be explicitly nutrition-related – as the focus of the intersectoral action. Fourth, philosophical, political, and governance spaces are needed to bring together different sectors. Fifth, evidence on the success of the intersectoral approach increases the acceptance of the process. CONCLUSIONS This study on policy processes shows how a convergence of factors enabled a link between family farming and school feeding in Brazil. It highlights that there are strategies to engage other sectors toward nutrition goals which provides benefits for all sectors involved. PMID:27533363

  20. Methodology for Modeling Building Energy Performance across the Commercial Sector

    SciTech Connect

    Griffith, B.; Long, N.; Torcellini, P.; Judkoff, R.; Crawley, D.; Ryan, J.

    2008-03-01

    This report uses EnergyPlus simulations of each building in the 2003 Commercial Buildings Energy Consumption Survey (CBECS) to document and demonstrate bottom-up methods of modeling the entire U.S. commercial buildings sector (EIA 2006). The ability to use a whole-building simulation tool to model the entire sector is of interest because the energy models enable us to answer subsequent 'what-if' questions that involve technologies and practices related to energy. This report documents how the whole-building models were generated from the building characteristics in 2003 CBECS and compares the simulation results to the survey data for energy use.

  1. ISI-MIP: The Inter-Sectoral Impact Model Intercomparison Project

    NASA Astrophysics Data System (ADS)

    Huber, V.; Dahlemann, S.; Frieler, K.; Piontek, F.; Schewe, J.; Serdeczny, O.; Warszawski, L.

    2013-12-01

    The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) aims to synthesize the state-of-the-art knowledge of climate change impacts at different levels of global warming. The project's experimental design is formulated to distinguish the uncertainty introduced by the impact models themselves, from the inherent uncertainty in the climate projections and the variety of plausible socio-economic futures. The unique cross-sectoral scope of the project provides the opportunity to study cascading effects of impacts in interacting sectors and to identify regional 'hot spots' where multiple sectors experience extreme impacts. Another emphasis lies on the development of novel metrics to describe societal impacts of a warmer climate. We briefly outline the methodological framework, and then present selected results of the first, fast-tracked phase of ISI-MIP. The fast track brought together 35 global impact models internationally, spanning five sectors across human society and the natural world (agriculture, water, natural ecosystems, health and coastal infrastructure), and using the latest generation of global climate simulations (RCP projections from the CMIP5 archive) and socioeconomic drivers provided within the SSP process. We also introduce the second phase of the project, which will enlarge the scope of ISI-MIP by encompassing further impact sectors (e.g., forestry, fisheries, permafrost) and regional modeling approaches. The focus for the next round of simulations will be the validation and improvement of models based on historical observations and the analysis of variability and extreme events. Last but not least, we discuss the longer-term objective of ISI-MIP to initiate a coordinated, ongoing impact assessment process, driven by the entire impact community and in parallel with well-established climate model intercomparisons (CMIP).

  2. White dwarfs constraints on dark sector models with light particles

    SciTech Connect

    Ubaldi, Lorenzo

    2014-06-24

    The white dwarf luminosity function is well understood in terms of standard model physics and leaves little room for exotic cooling mechanisms related to the possible existence of new weakly interacting light particles. This puts significant constraints on the parameter space of models that contain a massive dark photon and light dark sector particles.

  3. Modeling the Heterogeneous Effects of GHG Mitigation Policies on Global Agriculture and Forestry

    NASA Astrophysics Data System (ADS)

    Golub, A.; Henderson, B.; Hertel, T. W.; Rose, S. K.; Sohngen, B.

    2010-12-01

    Agriculture and forestry are envisioned as potentially key sectors for climate change mitigation policy, yet the depth of analysis of mitigation options and their economic consequences remains remarkably shallow in comparison to that for industrial mitigation. Farming and land use change - much of it induced by agriculture -account for one-third of global greenhouse gas (GHG) emissions. Any serious attempt to curtail these emissions will involve changes in the way farming is conducted, as well as placing limits on agricultural expansion into areas currently under more carbon-intensive land cover. However, agriculture and forestry are extremely heterogeneous, both in the technology and intensity of production, as well as in the GHG emissions intensity of these activities. And these differences, in turn, give rise to significant changes in the distribution of agricultural production, trade and consumption in the wake of mitigation policies. This paper assesses such distributional impacts via a global economic analysis undertaken with a modified version of the GTAP model. The paper builds on a global general equilibrium GTAP-AEZ-GHG model (Golub et al., 2009). This is a unified modeling framework that links the agricultural, forestry, food processing and other sectors through land, and other factor markets and international trade, and incorporates different land-types, land uses and related CO2 and non-CO2 GHG emissions and sequestration. The economic data underlying this work is the global GTAP data base aggregated up to 19 regions and 29 sectors. The model incorporates mitigation cost curves for different regions and sectors based on information from the US-EPA. The forestry component of the model is calibrated to the results of the state of the art partial equilibrium global forestry model of Sohngen and Mendelson (2007). Forest carbon sequestration at both the extensive and intensive margins are modeled separately to better isolate land competition between

  4. Photovoltaic applications definition and photovoltaic system definition study in the agricultural sector. Volume 2: Technical results

    NASA Astrophysics Data System (ADS)

    Mengel, R. W.; Nadolski, T. P.; Sparks, D. C.; Young, S. K.; Yingst, A.

    1980-05-01

    This volume describes the technical results of the study of potential photovoltaic (P/V) applications in US agriculture. The results presented address all technical aspects of the program and include a summary of agricultural energy consumption. The objectives of the technical effort reported were to: (1) identify and characterize agricultural energy demands that can effectively use P/V power systems; (2) develop effective P/V system designs for the four most promising applications; (3) determine performance and cost estimates for the designs; and (4) recommend systems for early test and demonstration and critical issues requiring further systems studies. The farms chosen for conceptual design include; (1) poultry layer farm, (2) hog production farm, (3) beef feedlot, and (4) year round vegetable farm.

  5. A Model for Agricultural Education in Public Schools.

    ERIC Educational Resources Information Center

    Hughes, Matthew; Barrick, R. Kirby

    1993-01-01

    A model for public school agricultural education is based on changes in the agriculture industry, student population, society, education, and the workplace. Its three components are classroom/lab instruction, application (supervised agricultural experience and Future Farmers of America), and employment/additional education and career (including…

  6. A carbon footprint simulation model for the cork oak sector.

    PubMed

    Demertzi, Martha; Paulo, Joana Amaral; Arroja, Luís; Dias, Ana Cláudia

    2016-10-01

    In the present study, a simulation model for the calculation of the carbon footprint of the cork oak sector (CCFM) is developed for the first time. A life cycle approach is adopted including the forest management, manufacturing, use and end-of-life stages. CCFM allows the user to insert the cork type used as raw material and its respective quantity and the distances in-between the various stages. The user can choose among different end-of-life destination options for the used cork products. The option of inserting different inputs, allows the use of the present simulation model for different cork oak systems, in different countries and with different conditions. CCFM allows the identification of the stages and products with the greatest carbon footprint and thus, a better management of the sector from an environmental perspective. The Portuguese cork oak sector is used as an application example of the model. The results obtained showed that the agglomeration industry is the hotspot for the carbon footprint of the cork sector mainly due to the production of the resins that are mixed with the cork granules for the production of agglomerated cork products. The consideration of the biogenic carbon emissions and sequestration of carbon at the forest in the carbon footprint, resulted to a great decrease of the sector's carbon footprint. Future actions for improvement are suggested in order to decrease the carbon footprint of the entire cork sector. It was found that by decreasing by 10% the emission factor of the agglomeration and transformation industries, substituting the transport trucks by more recent ones and by decreasing by 10% the cork products reaching the landfilling end-of-life destinations (while increasing the quantities reaching incineration and recycling), a decrease of the total CF (excluding the biogenic emissions and sequestration) of the entire cork industry by 10% can be achieved. PMID:27235900

  7. Preliminary energy sector assessments of Jamaica. Volume III: renewable energy. Part II: solar energy - agricultural

    SciTech Connect

    Not Available

    1980-01-01

    The study is concerned with the use of solar heat for drying agricultural products (crops, timber, and fish). The study finds that Jamaica has an ideal climate for solar agricultural product drying with the following methods offering the greatest promise; sun drying using open barbeques; drying in transparent buildings (with or without attached collectors) for small operations; new drying systems using solar air heaters with forced air drying; preheating air for existing commercial fossil-fueled dryers; and fish drying via chemical dehydration with solar regeneration of the chemical. The primary needs are to develop and construct environmentally suitable solar dryers and to train engineers in solar system design and installation.

  8. General and Partial Equilibrium Modeling of Sectoral Policies to Address Climate Change in the United States

    SciTech Connect

    Pizer, William; Burtraw, Dallas; Harrington, Winston; Newell, Richard; Sanchirico, James; Toman, Michael

    2003-03-31

    This document provides technical documentation for work using detailed sectoral models to calibrate a general equilibrium analysis of market and non-market sectoral policies to address climate change. Results of this work can be found in the companion paper, "Modeling Costs of Economy-wide versus Sectoral Climate Policies Using Combined Aggregate-Sectoral Model".

  9. Community Change and the Farm Sector: Impacts of Rural Development on Agriculture.

    ERIC Educational Resources Information Center

    Beaulieu, Lionel J.; Molnar, Joseph J.

    Findings from current literature form the basis for this examination of five critical elements of change and development within the local community setting which impact on agriculture: population, employment, land, water, and environment. Renewed rural population growth during the 1970's has reversed small farm trends but placed strains on local…

  10. System Dynamics Modelling of the Power Sector in Mauritius

    NASA Astrophysics Data System (ADS)

    Deenapanray, Prakash N. K.; Bassi, Andrea M.

    2015-12-01

    A system dynamics model has been developed for the power sector of Mauritius, which captures a range of complex interactions between the economic, social and environmental aspects of the national economy, with deeper emphasis on the role of energy in these interactions. The model has been validated by replicating the historical trends of key development indicators, and its results were compared to the projections of the national utility company. The validation process shows that the model provides a faithful representation of the actual electricity sector of Mauritius, and can be easily adapted to the use of different assumptions. This paper describes the main characteristics of the model and its results as compared to electricity demand projections carried out by the Central Electricity Board to 2022. The results suggest that further analysis could be done to test alternative low carbon investment scenarios.

  11. Multi-basin, Multi-sector Drought Economic Impact Model in Python: Development and Applications

    NASA Astrophysics Data System (ADS)

    Gutenson, J. L.; Zhu, L.; Ernest, A. N. S.; Oubeidillah, A.; Bearden, B.; Johnson, T. G.

    2015-12-01

    Drought is one of the most economically disastrous natural hazards, one whose impacts are exacerbated by the lack of abrupt onset and offset that define tornados and hurricanes. In the United States, about 30 billion dollars losses is caused by drought in 2012, resulting in widespread economic impacts for societies, industries, agriculture, and recreation. And in California, the drought cost statewide economic losses about 2.2 billion, with a total loss of 17,100 seasonal and part-time jobs. Driven by a variety of factors including climate change, population growth, increased water demands, alteration to land cover, drought occurs widely all over the world. Drought economic consequence assessment tool are greatly needed to allow decision makers and stakeholders to anticipate and manage effectively. In this study, current drought economic impact modeling methods were reviewed. Most of these models only deal with the impact in the agricultural sector with a focus on a single basin; few of these models analyze long term impact. However, drought impacts are rarely restricted to basin boundaries, and cascading economic impacts are likely to be significant. A holistic approach to multi-basin, multi-sector drought economic impact assessment is needed.In this work, we developed a new model for drought economic impact assessment, Drought Economic Impact Model in Python (PyDEM). This model classified all business establishments into thirteen categories based on NAICS, and using a continuous dynamic social accounting matrix approach, coupled with calculation of the indirect consequences for the local and regional economies and the various resilience. In addition, Environmental Policy Integrated Climate model was combined for analyzing drought caused soil erosion together with agriculture production, and then the long term impacts of drought were achieved. A visible output of this model was presented in GIS. In this presentation, Choctawhatchee-Pea-Yellow River Basins, Alabama

  12. Spatial Modeling of Indian Agriculture, Economic Activity and Population under Climate Change

    NASA Astrophysics Data System (ADS)

    McCord, G. C.

    2010-12-01

    We present a spatial model of economic activity and human population built on physical geography that takes particular account of its effects through agricultural productivity and transport costs for trade. A major component of this work is an agricultural model, driven in part by high-resolution climate data and model output. We put forward India as the initial region for this modeling work; India is a relatively data-rich country, it exhibits significant within-country spatial and temporal variation in agricultural productivity, urbanization rates, and population growth rates, and the climate dynamics of the monsoon are well-studied and expected to change on decadal time scales. Agricultural productivity is modeled as a function of soil, climate, and technology variables. Farmers locate optimally given varying geography and transport costs; in turn, food availability defines urbanization rates and economic activity in non-agricultural sectors. This “social system” integrated assessment model is a step towards a valuable policy tool, but requires a significant mobilization of data and a grid-cell-level system of equations to describe the underlying dynamics of the model. We test against past trends of social-natural system progression in demography, human location, income, food production, etc., and argue that the model could be used to assess future trends under varying climate change scenarios, and eventually serve to model feedbacks through effects on migration, population growth rates, or economic activity.

  13. Updated scalar sector constraints in the Higgs triplet model

    NASA Astrophysics Data System (ADS)

    Das, Dipankar; Santamaria, Arcadi

    2016-07-01

    We show that in the Higgs triplet model, after the Higgs discovery, the mixing angle in the C P -even sector can be strongly constrained from unitarity. We also discuss how large quantum effects in h →γ γ may arise in a Standard-Model-like scenario and a certain part of the parameter space can be ruled out from the diphoton signal strength. Using T -parameter and diphoton signal strength measurements, we update the bounds on the nonstandard scalar masses.

  14. Yukawa sector in minimal D-brane models

    NASA Astrophysics Data System (ADS)

    Ennadifi, Salah Eddine

    2015-07-01

    We investigate the Yukawa couplings sector in the minimal gauge theory U(3) × U(2) × U(1) with the Standard Model chiral and Higgs spectrum based on three stacks of intersecting D-branes. In this model, stringy corrections are required to induce the missing Yukawa couplings and generate hierarchical pattern. Under the known data, we assign the realistic Yukawa texture and then bound their strengths.

  15. Strategic Environmental Assessment of Greenhouse Gas Mitigation Options in the Canadian Agricultural Sector

    NASA Astrophysics Data System (ADS)

    Noble, Bram F.; Christmas, Lisa M.

    2008-01-01

    This article presents a methodological framework for strategic environmental assessment (SEA) application. The overall objective is to demonstrate SEA as a systematic and structured policy, plan, and program (PPP) decision support tool. In order to accomplish this objective, a stakeholder-based SEA application to greenhouse gas (GHG) mitigation policy options in Canadian agriculture is presented. Using a mail-out impact assessment exercise, agricultural producers and nonproducers from across the Canadian prairie region were asked to evaluate five competing GHG mitigation options against 13 valued environmental components (VECs). Data were analyzed using multi-criteria and exploratory analytical techniques. The results suggest considerable variation in perceived impacts and GHG mitigation policy preferences, suggesting that a blanket policy approach to GHG mitigation will create gainers and losers based on soil type and associate cropping and on-farm management practices. It is possible to identify a series of regional greenhouse gas mitigation programs that are robust, socially meaningful, and operationally relevant to both agricultural producers and policy decision makers. The assessment demonstrates the ability of SEA to address, in an operational sense, environmental problems that are characterized by conflicting interests and competing objectives and alternatives. A structured and systematic SEA methodology provides the necessary decision support framework for the consideration of impacts, and allows for PPPs to be assessed based on a much broader set of properties, objectives, criteria, and constraints whereas maintaining rigor and accountability in the assessment process.

  16. Effects of dynamic agricultural decision making in an ecohydrological model

    NASA Astrophysics Data System (ADS)

    Reichenau, T. G.; Krimly, T.; Schneider, K.

    2012-04-01

    Due to various interdependencies between the cycles of water, carbon, nitrogen, and energy the impacts of climate change on ecohydrological systems can only be investigated in an integrative way. Furthermore, the human intervention in the environmental processes makes the system even more complex. On the one hand human impact affects natural systems. On the other hand the changing natural systems have a feedback on human decision making. One of the most important examples for this kind of interaction can be found in the agricultural sector. Management dates (planting, fertilization, harvesting) are chosen based on meteorological conditions and yield expectations. A faster development of crops under a warmer climate causes shorter cropping seasons. The choice of crops depends on their profitability, which is mainly determined by market prizes, the agro-political framework, and the (climate dependent) crop yield. This study investigates these relations for the district Günzburg located in the Upper Danube catchment in southern Germany. The modeling system DANUBIA was used to perform dynamically coupled simulations of plant growth, surface and soil hydrological processes, soil nitrogen transformations, and agricultural decision making. The agro-economic model simulates decisions on management dates (based on meteorological conditions and the crops' development state), on fertilization intensities (based on yield expectations), and on choice of crops (based on profitability). The environmental models included in DANUBIA are to a great extent process based to enable its use in a climate change scenario context. Scenario model runs until 2058 were performed using an IPCC A1B forcing. In consecutive runs, dynamic crop management, dynamic crop selection, and a changing agro-political framework were activated. Effects of these model features on hydrological and ecological variables were analyzed separately by comparing the results to a model run with constant crop

  17. Ergonomics Perspective in Agricultural Research: A User-Centred Approach Using CAD and Digital Human Modeling (DHM) Technologies

    NASA Astrophysics Data System (ADS)

    Patel, Thaneswer; Sanjog, J.; Karmakar, Sougata

    2016-06-01

    Computer-aided Design (CAD) and Digital Human Modeling (DHM) (specialized CAD software for virtual human representation) technologies endow unique opportunities to incorporate human factors pro-actively in design development. Challenges of enhancing agricultural productivity through improvement of agricultural tools/machineries and better human-machine compatibility can be ensured by adoption of these modern technologies. Objectives of present work are to provide the detailed scenario of CAD and DHM applications in agricultural sector; and finding out means for wide adoption of these technologies for design and development of cost-effective, user-friendly, efficient and safe agricultural tools/equipment and operator's workplace. Extensive literature review has been conducted for systematic segregation and representation of available information towards drawing inferences. Although applications of various CAD software have momentum in agricultural research particularly for design and manufacturing of agricultural equipment/machinery, use of DHM is still at its infancy in this sector. Current review discusses about reasons of less adoption of these technologies in agricultural sector and steps to be taken for their wide adoption. It also suggests possible future research directions to come up with better ergonomic design strategies for improvement of agricultural equipment/machines and workstations through application of CAD and DHM.

  18. Dynamic Global Forest and Agriculture Model (D-GFAM)

    EPA Science Inventory

    D-GFAM was created by introduction of aggregate crop and livestock sectors to the Global Timber Model. D-GFAM maximizes net present value of global welfare in the forestry, crop, and livestock sectors by choosing outputs, land areas and inputs. Global consumption for each product...

  19. Energy-economy interactions revisited within a comprehensive sectoral model

    SciTech Connect

    Hanson, D. A.; Laitner, J. A.

    2000-07-24

    This paper describes a computable general equilibrium (CGE) model with considerable sector and technology detail, the ``All Modular Industry Growth Assessment'' Model (AMIGA). It is argued that a detailed model is important to capture and understand the several rolls that energy plays within the economy. Fundamental consumer and industrial demands are for the services from energy; hence, energy demand is a derived demand based on the need for heating, cooling mechanical, electrical, and transportation services. Technologies that provide energy-services more efficiently (on a life cycle basis), when adopted, result in increased future output of the economy and higher paths of household consumption. The AMIGA model can examine the effects on energy use and economic output of increases in energy prices (e.g., a carbon charge) and other incentive-based policies or energy-efficiency programs. Energy sectors and sub-sector activities included in the model involve energy extraction conversion and transportation. There are business opportunities to produce energy-efficient goods (i.e., appliances, control systems, buildings, automobiles, clean electricity). These activities are represented in the model by characterizing their likely production processes (e.g., lighter weight motor vehicles). Also, multiple industrial processes can produce the same output but with different technologies and inputs. Secondary recovery, i.e., recycling processes, are examples of these multiple processes. Combined heat and power (CHP) is also represented for energy-intensive industries. Other modules represent residential and commercial building technologies to supply energy services. All sectors of the economy command real resources (capital services and labor).

  20. Sector-specific issues and reporting methodologies supporting the General Guidelines for the voluntary reporting of greenhouse gases under Section 1605(b) of the Energy Policy Act of 1992. Volume 2: Part 4, Transportation sector; Part 5, Forestry sector; Part 6, Agricultural sector

    SciTech Connect

    Not Available

    1994-10-01

    This volume, the second of two such volumes, contains sector-specific guidance in support of the General Guidelines for the voluntary reporting of greenhouse gas emissions and carbon sequestration. This voluntary reporting program was authorized by Congress in Section 1605(b) of the Energy Policy Act of 1992. The General Guidelines, bound separately from this volume, provide the overall rationale for the program, discuss in general how to analyze emissions and emission reduction/carbon sequestration projects, and address programmatic issues such as minimum reporting requirements, time parameters, international projects, confidentiality, and certification. Together, the General Guidelines and the guidance in these supporting documents will provide concepts and approaches needed to prepare the reporting forms. This second volume of sector-specific guidance covers the transportation sector, the forestry sector, and the agricultural sector.

  1. Quality assurance of weather data for agricultural system model input

    Technology Transfer Automated Retrieval System (TEKTRAN)

    It is well known that crop production and hydrologic variation on watersheds is weather related. Rarely, however, is meteorological data quality checks reported for agricultural systems model research. We present quality assurance procedures for agricultural system model weather data input. Problems...

  2. AGRICULTURAL RUNOFF MANAGEMENT (ARM) MODEL VERSION II: REFINEMENT AND TESTING

    EPA Science Inventory

    The Agricultural Runoff Management (ARM) Model has been refined and tested on small agricultural watersheds in Georgia and Michigan. The ARM Model simulates the hydrologic, sediment production, pesticide, and nutrient processes on the land surface and in the soil profile that det...

  3. Searching for solutions to mitigate greenhouse gas emissions by agricultural policy decisions--Application of system dynamics modeling for the case of Latvia.

    PubMed

    Dace, Elina; Muizniece, Indra; Blumberga, Andra; Kaczala, Fabio

    2015-09-15

    European Union (EU) Member States have agreed to limit their greenhouse gas (GHG) emissions from sectors not covered by the EU Emissions Trading Scheme (non-ETS). That includes also emissions from agricultural sector. Although the Intergovernmental Panel on Climate Change (IPCC) has established a methodology for assessment of GHG emissions from agriculture, the forecasting options are limited, especially when policies and their interaction with the agricultural system are tested. Therefore, an advanced tool, a system dynamics model, was developed that enables assessment of effects various decisions and measures have on agricultural GHG emissions. The model is based on the IPCC guidelines and includes the main elements of an agricultural system, i.e. land management, livestock farming, soil fertilization and crop production, as well as feedback mechanisms between the elements. The case of Latvia is selected for simulations, as agriculture generates 22% of the total anthropogenic GHG emissions in the country. The results demonstrate that there are very limited options for GHG mitigation in the agricultural sector. Thereby, reaching the non-ETS GHG emission targets will be very challenging for Latvia, as the level of agricultural GHG emissions will be exceeded considerably above the target levels. Thus, other non-ETS sectors will have to reduce their emissions drastically to "neutralize" the agricultural sector's emissions for reaching the EU's common ambition to move towards low-carbon economy. The developed model may serve as a decision support tool for impact assessment of various measures and decisions on the agricultural system's GHG emissions. Although the model is applied to the case of Latvia, the elements and structure of the model developed are similar to agricultural systems in many countries. By changing numeric values of certain parameters, the model can be applied to analyze decisions and measures in other countries. PMID:25958357

  4. Future Public Policy and Ethical Issues Facing the Agricultural and Microbial Genomics Sectors of the Biotechnology Industry: A Roundtable Discussion

    SciTech Connect

    Diane E. Hoffmann

    2003-09-12

    On September 12, 2003, the University of Maryland School of Law's Intellectual Property and Law & Health Care Programs jointly sponsored and convened a roundtable discussion on the future public policy and ethical issues that will likely face the agricultural and microbial genomics sectors of the biotechnology industry. As this industry has developed over the last two decades, societal concerns have moved from what were often local issues, e.g., the safety of laboratories where scientists conducted recombinant DNA research on transgenic microbes, animals and crops, to more global issues. These newer issues include intellectual property, international trade, risks of genetically engineered foods and microbes, bioterrorism, and marketing and labeling of new products sold worldwide. The fast paced nature of the biotechnology industry and its new developments often mean that legislators, regulators and society, in general, must play ''catch up'' in their efforts to understand the issues, the risks, and even the benefits, that may result from the industry's new ways of conducting research, new products, and novel methods of product marketing and distribution. The goal of the roundtable was to develop a short list of the most significant public policy and ethical issues that will emerge as a result of advances in these sectors of the biotechnology industry over the next five to six years. More concretely, by ''most significant'' the conveners meant the types of issues that would come to the attention of members of Congress or state legislators during this time frame and for which they would be better prepared if they had well researched and timely background information. A concomitant goal was to provide a set of focused issues for academic debate and scholarship so that policy makers, industry leaders and regulators would have the intellectual resources they need to better understand the issues and concerns at stake. The goal was not to provide answers to any of the

  5. The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies

    NASA Technical Reports Server (NTRS)

    Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P.; Antle, J. M.; Nelson, G. C.; Porter, C.; Janssen, S.; Asseng, S.; Basso, B.; Ewert, F.; Wallach, D.; Baigorria, G.; Winter, J. M.

    2012-01-01

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model outputs are aggregated as inputs to regional and global economic models to determine regional vulnerabilities, changes in comparative advantage, price effects, and potential adaptation strategies in the agricultural sector. Climate, Crop Modeling, Economics, and Information Technology Team Protocols are presented to guide coordinated climate, crop modeling, economics, and information technology research activities around the world, along with AgMIP Cross-Cutting Themes that address uncertainty, aggregation and scaling, and the development of Representative Agricultural Pathways (RAPs) to enable testing of climate change adaptations in the context of other regional and global trends. The organization of research activities by geographic region and specific crops is described, along with project milestones. Pilot results demonstrate AgMIP's role in assessing climate impacts with explicit representation of uncertainties in climate scenarios and simulations using crop and economic models. An intercomparison of wheat model simulations near Obregón, Mexico reveals inter-model differences in yield sensitivity to [CO2] with model uncertainty holding approximately steady as concentrations rise, while uncertainty related to choice of crop model increases with

  6. Environmental and economic development consequences of forest and agricultural sector policies in Latin America (a synthesis of case studies of Costa Rica, Ecuador, and Bolivia)

    SciTech Connect

    Stewart, R.; Gibson, D.

    1994-04-15

    This paper draws heavily on the results of case studies in Bolivia, Costa Rica, and Ecuador to explain how sectoral policies have tilted land use decisions against forestry and in favor of agriculture, and to present estimates of the economic development effects of those decisions. The paper summarizes information on forests and forest industries of the three countries, and it describes the framework within which policies are designed. It presents the effects of sectoral policies on land use and forest management, and then quantifies and discusses economic costs of relevant sectoral policies. Conclusions and recommendations for policy reform are offered.

  7. Agricultural Model Intercomparison and Improvement Project: Phase I Activities by a Global Community of Science (Invited)

    NASA Astrophysics Data System (ADS)

    Rosenzweig, C.; Jones, J.; Hatfield, J.; Antle, J. M.; Mutter, C.; Ruane, A. C.

    2013-12-01

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. Currently, AgMIP has over 575 participants from more than 45 countries contributing their expertise to over 30 projects and activities. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models with a strong grounding in observations of current agricultural systems around the world. The performance of agricultural models in current climate forms a key basis for our understanding of how crops will respond to future climate changes, and thus AgMIP has a particular focus on extreme heat and drought. Climate, crop model, economics, and information technology protocols are used to guide coordinated AgMIP research activities around the world, along with cross-cutting themes that address aggregation, uncertainty, and the development of Representative Agricultural Pathways (RAPs) to enable testing of climate change adaptations in the context of other global trends. Research activities include ongoing crop-specific assessments (e.g., maize, wheat, sugarcane, rice) and improvement activities, global gridded crop and economic model intercomparisons, and many other initiatives that allow for the better evaluation of the impacts of climate change on agricultural production and food security around the world. AgMIP activities are improving the representation of crop response to changing carbon dioxide, temperature extremes, and water

  8. Airborne reconnaissance in the civilian sector - Agricultural monitoring from high-altitude powered platforms

    NASA Technical Reports Server (NTRS)

    Youngblood, J. W.; Jackson, R. D.

    1983-01-01

    Design concepts and mission applications for unmanned high-altitude powered platforms (HAPPs) are discussed. A chemically powered HAPP (operating altitude 18-21 km, wingspan 26 m, payload 91 kg, endurance 2-3 days) would use current turboprop technology. A microwave-powered HAPP (operating altitude around 21 km, wingspan 57.9 m, payload 500 kg, endurance weeks or months) would circle within or perform boost-glide maneuvers around a microwave beam of density 1.1 kw/sq m. Of two solar-powered-HAPP designs presented, the more promising uses five vertical solar-panel-bearing fins, two of which can be made horizontal at night, (wingspan 57.8/98.3 m, payload 113 kg, endurance weeks or months). The operating altitude depends on the latitude and season: this HAPP design is shown to be capable of year-round 20-km-altitude flights over the San Joaquin Valley in California, where an agricultural-monitoring mission using Landsat-like remote sensors is proposed. Other applications may be better served by the characteristics of the other HAPPs. The primary advantage of HAPPs over satellites is found to be their ability to provide rapidly available high-resolution continuous or repetitive coverage of specific areas at relatively low cost.

  9. Agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Agriculture within the United States is varied and produces a large value ($200 billion in 2002) of production across a wide range of plant and animal production systems. Because of this diversity, changes in climate will likely impact agriculture throughout the United States. Climate affects crop, ...

  10. The Development Model Electronic Commerce of Regional Agriculture

    NASA Astrophysics Data System (ADS)

    Kang, Jun; Cai, Lecai; Li, Hongchan

    With the developing of the agricultural information, it is inevitable trend of the development of agricultural electronic commercial affairs. On the basis of existing study on the development application model of e-commerce, combined with the character of the agricultural information, compared with the developing model from the theory and reality, a new development model electronic commerce of regional agriculture base on the government is put up, and such key issues as problems of the security applications, payment mode, sharing mechanisms, and legal protection are analyzed, etc. The among coordination mechanism of the region is discussed on, it is significance for regulating the development of agricultural e-commerce and promoting the regional economical development.

  11. Phosphorus modeling in tile drained agricultural systems using APEX

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Phosphorus losses through tile drained systems in agricultural landscapes may be causing the persistent eutrophication problems observed in surface water. The purpose of this paper is to evaluate the state of the science in the Agricultural Policy/Environmental eXtender (APEX) model related to surf...

  12. Agriculture and Climate Change in Global Scenarios: Why Don't the Models Agree

    SciTech Connect

    Nelson, Gerald; van der Mensbrugghe, Dominique; Ahammad, Helal; Blanc, Elodie; Calvin, Katherine V.; Hasegawa, Tomoko; Havlik, Petr; Heyhoe, Edwina; Kyle, G. Page; Lotze-Campen, Hermann; von Lampe, Martin; Mason d'Croz, Daniel; van Meijl, Hans; Mueller, C.; Reilly, J. M.; Robertson, Richard; Sands, Ronald; Schmitz, Christoph; Tabeau, Andrzej; Takahashi, Kiyoshi; Valin, Hugo; Willenbockel, Dirk

    2014-01-01

    Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs makes direct use of weather inputs. Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes of key variables such as prices, production, and trade. These divergent outcomes arise from differences in model inputs and model specification. The goal of this paper is to review climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By providing common productivity drivers that include climate change effects, differences in model outcomes are reduced. All models show higher prices in 2050 because of negative productivity shocks from climate change. The magnitude of the price increases, and the adaptation responses, differ significantly across the various models. Substantial differences exist in the structural parameters affecting demand, area, and yield, and should be a topic for future research.

  13. Shaping Collective Functions in Privatized Agricultural Knowledge and Information Systems: The Positioning and Embedding of a Network Broker in the Dutch Dairy Sector

    ERIC Educational Resources Information Center

    Klerkx, Laurens; Leeuwis, Cees

    2009-01-01

    This paper examines new organizational arrangements that have emerged in the context of a privatized extension system. It investigates the positioning and embedding of a network broker aimed at enhancing interaction in the privatized agricultural knowledge and information system (AKIS), to assess whether tensions reported in other sectors also…

  14. Extension Strategies Used To Develop a Traditional Farming Sector in an Advanced Agricultural Surrounding. The Case of the Nazareth Region in Israel.

    ERIC Educational Resources Information Center

    Blum, Abraham

    A case study of the Nazareth Region in Israel analyzed the extension strategies used to develop the traditional Arab farming sector in an advanced agricultural surrounding. As part of the study, the history of the Arab farmer before and after the creation of the State of Israel was given. The methodology for the study involved interviews with…

  15. A theorem on the Higgs sector of the Standard Model

    NASA Astrophysics Data System (ADS)

    Frasca, Marco

    2016-06-01

    We provide the solution of the classical theory for the Higgs sector of the Standard Model obtaining the exact Green's function for the broken phase. Solving the Dyson-Schwinger equations for the Higgs field we show that the propagator coincides with that of the classical theory confirming the spectrum also at the quantum level. In this way we obtain a proof of triviality using the Källen-Lehman representation. This has as a consequence that higher excited states must exist for the Higgs particle, representing an internal spectrum for it. Higher excited states have exponentially smaller amplitudes and, so, their production rates are significantly depressed.

  16. Trends in multi-pollutant emissions from a technology-linked inventory for India: II. Residential, agricultural and informal industry sectors

    NASA Astrophysics Data System (ADS)

    Pandey, Apoorva; Sadavarte, Pankaj; Rao, Anand B.; Venkataraman, Chandra

    2014-12-01

    Dispersed traditional combustion technologies, characterized by inefficient combustion and significant emissions, are widely used in residential cooking and "informal industries" including brick production, food and agricultural product processing operations like drying and cooking operations related to sugarcane juice, milk, food-grain, jute, silk, tea and coffee. In addition, seasonal agricultural residue burning in field is a discontinuous source of significant emissions. Here we estimate fuel consumption in these sectors and agricultural residue burned using detailed technology divisions and survey-based primary data for 2010 and projected between 1996 and 2015. In the residential sector, a decline in the fraction of solid biomass users for cooking from 79% in 1996 to 65% in 2010 was offset by a growing population, leading to a nearly constant population of solid biomass users, with a corresponding increase in the population of LPG users. Emissions from agriculture followed the growth in agricultural production and diesel use by tractors and pumps. Trends in emissions from the informal industries sector followed those in coal combustion in brick kilns. Residential biomass cooking stoves were the largest contributors to emissions of PM2.5, OC, CO, NMVOC and CH4. Highest emitting technologies of BC were residential kerosene wick lamps. Emissions of SO2 were largely from coal combustion in Bull's trench kilns and other brick manufacturing technologies. Diesel use in tractors was the major source of NOx emissions. Uncertainties in emission estimates were principally from highly uncertain emission factors, particularly for technologies in the informal industries.

  17. Integration of agricultural and energy system models for biofuel assessment

    EPA Science Inventory

    This paper presents a coupled modeling framework to capture the dynamic linkages between agricultural and energy markets that have been enhanced through the expansion of biofuel production, as well as the environmental impacts resulting from this expansion. The framework incorpor...

  18. Developing a model policy on youth employment in agriculture.

    PubMed

    Miller, Mary E; Lee, Barbara C

    2014-01-01

    The goal of this project was to develop a model policy that agricultural employers could adopt specific to youth employment, including age-appropriate assignments, training needs for adolescent workers, ideal supervision, and mentoring by adult workers. Methods included discussions at a national conference of agricultural employers, a survey of employers' perspectives on young workers, forming a task force to draft a model policy, and finalizing the policy document. The process resulted in a template that can be used by agricultural employers for immediate adoption, or to be customized and adapted for their unique company. Given new trends in agriculture to use certification systems, safety audits, and voluntary safety standards in addition to the regulatory process, there is value in having a voluntary "best practice" model policy that can be adopted in settings where safeguarding young farm workers is a priority. PMID:24959757

  19. Comparative performance of desiccant wheel with effective and ordinary regeneration sector using mathematical model

    NASA Astrophysics Data System (ADS)

    Yadav, Avadhesh; Yadav, Laxmikant

    2014-10-01

    A mathematical model for predicting the performance of a desiccant wheel with effective regeneration sector has been used. This model has been used to conduct a comparative performance of desiccant wheel with effective and ordinary regeneration sector. It was found that for all the cases considered in this study like rotation of wheel, regeneration temperature, velocity and ambient moisture, the desiccant wheel with "effective regeneration sector" gives better result as compared to ordinary regeneration sector.

  20. Decadal Climate Information Needs of Stakeholders for Decision Support in Water and Agriculture Production Sectors: A Case Study in the Missouri River Basin

    NASA Astrophysics Data System (ADS)

    Mehta, V. M.; Knutson, C.; Rosenberg, N.

    2012-12-01

    Many decadal climate prediction efforts have been initiated under the World Climate Research Programme's Coupled Model Intercomparison Project 5. There is considerable ongoing discussion about model deficiencies, initialization techniques, and data requirements, but not much attention is being given to decadal climate information (DCI) needs of stakeholders for decision support. We report the results of exploratory activities undertaken to assess DCI needs in water resources and agriculture sectors, using the Missouri River Basin (the Basin) as a case study. This assessment was achieved through discussions with 120 representative stakeholders. Stakeholders' awareness of decadal dry and wet spells and their societal impacts in the Basin is established; and stakeholders' DCI needs and potential barriers to their use of DCI are enumerated. We find that impacts, including economic impacts, of DCV on water and agricultural production in the Basin are distinctly identifiable and characterizable. Stakeholders have clear notions about their needs for DCI and have offered specific suggestions as to how these might be met. But, while stakeholders are eager to have climate information, including decadal climate outlooks (DCOs), there are many barriers to the use of such information. The first and foremost is that the credibility of DCOs is yet to be established. Secondly, the nature of institutional rules and regulations, laws, and legal precedents that pose obstacles to the use of DCOs must be better understood and means to modify these, where possible, must be sought. For the benefit of climate scientists, these and other stakeholder needs will also be articulated in this talk. We are engaged in a project to assess simulation and hindcast skills of DCV phenomena and their associations with hydro-meteorological variability in the Basin in the HadCM3, GFDL-CM2.1, NCAR CCSM4, and MIROC5 global coupled models participating in the WCRP's CMIP5 project. Results from this project

  1. The scalar sector in the Myers-Pospelov model

    SciTech Connect

    Reyes, C. M.; Urrutia, L.; Vergara, J. D.

    2008-03-06

    We construct a perturbative expansion of the scalar sector in the Myers-Pospelov model, up to second order in the Lorentz violating parameter and taking into account its higher-order time derivative character. This expansion allows us to construct an hermitian positive-definite Hamiltonian which provides a correct basis for quantization. Demanding that the modified normal frequencies remain real requires the introduction of an upper bound in the magnitude |k| of the momentum, which is a manifestation of the effective character of the model. The free scalar propagator, including the corresponding modified dispersion relations, is also calculated to the given order, thus providing the starting point to consider radiative corrections when interactions are introduced.

  2. Major models and data sources for residential and commercial sector energy conservation analysis. Final report

    SciTech Connect

    Not Available

    1980-09-01

    Major models and data sources are reviewed that can be used for energy-conservation analysis in the residential and commercial sectors to provide an introduction to the information that can or is available to DOE in order to further its efforts in analyzing and quantifying their policy and program requirements. Models and data sources examined in the residential sector are: ORNL Residential Energy Model; BECOM; NEPOOL; MATH/CHRDS; NIECS; Energy Consumption Data Base: Household Sector; Patterns of Energy Use by Electrical Appliances Data Base; Annual Housing Survey; 1970 Census of Housing; AIA Research Corporation Data Base; RECS; Solar Market Development Model; and ORNL Buildings Energy Use Data Book. Models and data sources examined in the commercial sector are: ORNL Commercial Sector Model of Energy Demand; BECOM; NEPOOL; Energy Consumption Data Base: Commercial Sector; F.W. Dodge Data Base; NFIB Energy Report for Small Businesses; ADL Commercial Sector Energy Use Data Base; AIA Research Corporation Data Base; Nonresidential Buildings Surveys of Energy Consumption; General Electric Co: Commercial Sector Data Base; The BOMA Commercial Sector Data Base; The Tishman-Syska and Hennessy Data Base; The NEMA Commercial Sector Data Base; ORNL Buildings Energy Use Data Book; and Solar Market Development Model. Purpose; basis for model structure; policy variables and parameters; level of regional, sectoral, and fuels detail; outputs; input requirements; sources of data; computer accessibility and requirements; and a bibliography are provided for each model and data source.

  3. Transportation Sector Model of the National Energy Modeling System. Volume 2 -- Appendices: Part 1

    SciTech Connect

    1998-01-01

    This volume contains input data and parameters used in the model of the transportation sector of the National Energy Modeling System. The list of Transportation Sector Model variables includes parameters for the following: Light duty vehicle modules (fuel economy, regional sales, alternative fuel vehicles); Light duty vehicle stock modules; Light duty vehicle fleet module; Air travel module (demand model and fleet efficiency model); Freight transport module; Miscellaneous energy demand module; and Transportation emissions module. Also included in these appendices are: Light duty vehicle market classes; Maximum light duty vehicle market penetration parameters; Aircraft fleet efficiency model adjustment factors; and List of expected aircraft technology improvements.

  4. Impacts of global change on water-related sectors and society in a trans-boundary central European river basin - Part 1: project framework and impacts on agriculture

    NASA Astrophysics Data System (ADS)

    Hattermann, F. F.; Gömann, H.; Conradt, T.; Kaltofen, M.; Kreins, P.; Wechsung, F.

    2007-06-01

    Central Europe, the focus region of this study, is a region in transition, climatically from maritime to continental and politically from formerly more planning-oriented to more market-oriented management regimes, and in terms of climate change from regions of increasing precipitation in the west and north of Europe to regions of decreasing precipitation in central and southern Europe. The Elbe basin, a trans-boundary catchment flowing from the Czech Republic through Germany into the North Sea, was selected to investigate the possible impacts of global change on crop yields and water resources in this region. For technical reasons, the paper has been split into two parts, the first showing the overall model concept, the model set-up for the agricultural sector, and first results linking eco-hydrological and agro-economic tools for the German part of the basin. The second part describes the model set-up for simulating water supply and demand linking eco-hydrological and water management tools for the entire basin including the Czech part.

  5. Models for forecasting energy use in the US farm sector

    NASA Astrophysics Data System (ADS)

    Christensen, L. R.

    1981-07-01

    Econometric models were developed and estimated for the purpose of forecasting electricity and petroleum demand in US agriculture. A structural approach is pursued which takes account of the fact that the quantity demanded of any one input is a decision made in conjunction with other input decisions. Three different functional forms of varying degrees of complexity are specified for the structural cost function, which describes the cost of production as a function of the level of output and factor prices. Demand for materials (all purchased inputs) is derived from these models. A separate model which break this demand up into demand for the four components of materials is used to produce forecasts of electricity and petroleum is a stepwise manner.

  6. Probabilistic assessment of agricultural droughts using graphical models

    NASA Astrophysics Data System (ADS)

    Ramadas, Meenu; Govindaraju, Rao S.

    2015-07-01

    Agricultural droughts are often characterized by soil moisture in the root zone of the soil, but crop needs are rarely factored into the analysis. Since water needs vary with crops, agricultural drought incidences in a region can be characterized better if crop responses to soil water deficits are also accounted for in the drought index. This study investigates agricultural droughts driven by plant stress due to soil moisture deficits using crop stress functions available in the literature. Crop water stress is assumed to begin at the soil moisture level corresponding to incipient stomatal closure, and reaches its maximum at the crop's wilting point. Using available location-specific crop acreage data, a weighted crop water stress function is computed. A new probabilistic agricultural drought index is then developed within a hidden Markov model (HMM) framework that provides model uncertainty in drought classification and accounts for time dependence between drought states. The proposed index allows probabilistic classification of the drought states and takes due cognizance of the stress experienced by the crop due to soil moisture deficit. The capabilities of HMM model formulations for assessing agricultural droughts are compared to those of current drought indices such as standardized precipitation evapotranspiration index (SPEI) and self-calibrating Palmer drought severity index (SC-PDSI). The HMM model identified critical drought events and several drought occurrences that are not detected by either SPEI or SC-PDSI, and shows promise as a tool for agricultural drought studies.

  7. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison.

    PubMed

    Rosenzweig, Cynthia; Elliott, Joshua; Deryng, Delphine; Ruane, Alex C; Müller, Christoph; Arneth, Almut; Boote, Kenneth J; Folberth, Christian; Glotter, Michael; Khabarov, Nikolay; Neumann, Kathleen; Piontek, Franziska; Pugh, Thomas A M; Schmid, Erwin; Stehfest, Elke; Yang, Hong; Jones, James W

    2014-03-01

    Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies. PMID:24344314

  8. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison

    PubMed Central

    Rosenzweig, Cynthia; Elliott, Joshua; Deryng, Delphine; Ruane, Alex C.; Müller, Christoph; Arneth, Almut; Boote, Kenneth J.; Folberth, Christian; Glotter, Michael; Khabarov, Nikolay; Neumann, Kathleen; Piontek, Franziska; Pugh, Thomas A. M.; Schmid, Erwin; Stehfest, Elke; Yang, Hong; Jones, James W.

    2014-01-01

    Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies. PMID:24344314

  9. Assessing Agricultural Risks of Climate Change in the 21st Century in a Global Gridded Crop Model Intercomparison

    NASA Technical Reports Server (NTRS)

    Rosenzweig, Cynthia E.; Elliott, Joshua; Deryng, Delphine; Ruane, Alex C.; Mueller, Christoph; Arneth, Almut; Boote, Kenneth J.; Folberth, Christian; Glotter, Michael; Khabarov, Nikolay

    2014-01-01

    Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.

  10. Modelling pollination services across agricultural landscapes

    PubMed Central

    Lonsdorf, Eric; Kremen, Claire; Ricketts, Taylor; Winfree, Rachael; Williams, Neal; Greenleaf, Sarah

    2009-01-01

    Background and Aims Crop pollination by bees and other animals is an essential ecosystem service. Ensuring the maintenance of the service requires a full understanding of the contributions of landscape elements to pollinator populations and crop pollination. Here, the first quantitative model that predicts pollinator abundance on a landscape is described and tested. Methods Using information on pollinator nesting resources, floral resources and foraging distances, the model predicts the relative abundance of pollinators within nesting habitats. From these nesting areas, it then predicts relative abundances of pollinators on the farms requiring pollination services. Model outputs are compared with data from coffee in Costa Rica, watermelon and sunflower in California and watermelon in New Jersey–Pennsylvania (NJPA). Key Results Results from Costa Rica and California, comparing field estimates of pollinator abundance, richness or services with model estimates, are encouraging, explaining up to 80 % of variance among farms. However, the model did not predict observed pollinator abundances on NJPA, so continued model improvement and testing are necessary. The inability of the model to predict pollinator abundances in the NJPA landscape may be due to not accounting for fine-scale floral and nesting resources within the landscapes surrounding farms, rather than the logic of our model. Conclusions The importance of fine-scale resources for pollinator service delivery was supported by sensitivity analyses indicating that the model's predictions depend largely on estimates of nesting and floral resources within crops. Despite the need for more research at the finer-scale, the approach fills an important gap by providing quantitative and mechanistic model from which to evaluate policy decisions and develop land-use plans that promote pollination conservation and service delivery. PMID:19324897

  11. APPLICATIONS OF AGRICULTURAL SYSTEM MODELS IN ASSESSING AND MANAGING CONTAMINATION OF THE SOIL-WATER-ATMOSPHERE CONTINUUM IN AGRICULTURE

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In the last three decades, there has been a growing public concern about the adverse effects of modern agriculture on environmental quality and soil-water resources. In the mid-1980's, the USDA, Agricultural Research Service (ARS) identified the need for models of whole agricultural systems that wi...

  12. Application of Agricultural System Models in Assessing and Managing Contamination of Soil-Water-Atmosphere Continuum in Agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In the last three decades, there has been a growing public concern about the adverse effects of modern agriculture on environmental quality and soil-water resources. In the mid-1980s, the USDA, Agricultural Research Service (ARS) identified the need for models of whole agricultural systems th...

  13. Plumbum contamination detecting model for agricultural soil using hyperspectral data

    NASA Astrophysics Data System (ADS)

    Liu, Xiangnan; Huang, Fang; Wang, Ping

    2008-10-01

    The issue of environmental pollution due to toxic heavy metals in agricultural land has caused worldwide growing concern in recent years. Being one of toxic heavy metals, the accumulation of Plumbum (Pb) may have negative effects on natural and agricultural vegetation growth, yield and quality. It can also constitute short-term and long-term health risks by entering the food chain. In this study, we analyze the relationships between physical and chemical characteristics, biological parameters of soil-vegetation system and hyperspectral spectrum responses systematically. The relation between hyperspectral data and the biological parameters of Pb polluted wheat canopy such as leaf pigments, leaf moisture, cell structure and leaf area index (LAI) are discussed. We detect the changes in the wheat biological parameters and spectral response associated with Pb concentration in soil. To reveal the impact mechanisms of Pb concentration on agricultural soil, six models including chlorophyll-leaf moisture model, chlorophyll-cell structure model, chlorophyll-LAI model, leaf moisture-cell structure model, leaf moisture-LAI model, cell structure- LAI model are explored. We find that changes in Pb concentration present various features in different models. Pb contamination in agricultural soil can be identified and assessed effectively while integrating the characteristics of those developed models.

  14. Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System

    SciTech Connect

    1998-01-01

    This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. The NEMS Commercial Sector Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the nine Census Division level of detail for eleven distinct categories of commercial buildings. Commercial equipment selections are performed for the major fuels of electricity, natural gas, and distillate fuel, for the major services of space heating, space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The algorithm also models demand for the minor fuels of residual oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene, the renewable fuel sources of wood and municipal solid waste, and the minor services of office equipment. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.

  15. Modeling the infrastructure dynamics of China -- Water, agriculture, energy, and greenhouse gases

    SciTech Connect

    Conrad, S.H.; Drennen, T.E.; Engi, D.; Harris, D.L.; Jeppesen, D.M.; Thomas, R.P.

    1998-08-01

    A comprehensive critical infrastructure analysis of the People`s Republic of China was performed to address questions about China`s ability to meet its long-term grain requirements and energy needs and to estimate greenhouse gas emissions in China likely to result from increased agricultural production and energy use. Four dynamic computer simulation models of China`s infrastructures--water, agriculture, energy and greenhouse gas--were developed to simulate, respectively, the hydrologic budgetary processes, grain production and consumption, energy demand, and greenhouse gas emissions in China through 2025. The four models were integrated into a state-of-the-art comprehensive critical infrastructure model for all of China. This integrated model simulates diverse flows of commodities, such as water and greenhouse gas, between the separate models to capture the overall dynamics of the integrated system. The model was used to generate projections of China`s available water resources and expected water use for 10 river drainage regions representing 100% of China`s mean annual runoff and comprising 37 major river basins. These projections were used to develop estimates of the water surpluses and/or deficits in the three end-use sectors--urban, industrial, and agricultural--through the year 2025. Projections of the all-China demand for the three major grains (corn, wheat, and rice), meat, and other (other grains and fruits and vegetables) were also generated. Each geographic region`s share of the all-China grain demand (allocated on the basis of each region`s share of historic grain production) was calculated in order to assess the land and water resources in each region required to meet that demand. Growth in energy use in six historically significant sectors and growth in greenhouse gas loading were projected for all of China.

  16. Scale invariant extension of the standard model with a strongly interacting hidden sector.

    PubMed

    Hur, Taeil; Ko, P

    2011-04-01

    We present a scale invariant extension of the standard model with a new QCD-like strong interaction in the hidden sector. A scale Λ(H) is dynamically generated in the hidden sector by dimensional transmutation, and chiral symmetry breaking occurs in the hidden sector. This scale is transmitted to the SM sector by a real singlet scalar messenger S and can trigger electroweak symmetry breaking. Thus all the mass scales in this model arise from the hidden sector scale Λ(H), which has quantum mechanical origin. Furthermore, the lightest hadrons in the hidden sector are stable by the flavor conservation of the hidden sector strong interaction, and could be the cold dark matter (CDM). We study collider phenomenology, relic density, and direct detection rates of the CDM of this model. PMID:21561182

  17. Building a Comprehensive Mill-Level Database for the Industrial Sectors Integrated Solutions (ISIS) Model of the U.S. Pulp and Paper Sector

    EPA Science Inventory

    The Industrial Sectors Integrated Solutions (ISIS) model for the pulp and paper sector is currently under development at the U.S. Environmental Protection Agency (EPA), and can be utilized to facilitate multi-pollutant sector-based analyses that are performed in conjunction with ...

  18. Building a Comprehensive Mill-Level Database for the Industrial Sectors Integrated Solutions (ISIS) Model of the US Pulp and Paper Sector

    EPA Science Inventory

    The Industrial Sectors Integrated Solutions (ISIS) model for the pulp and paper sector is currently under development at the U.S. Environmental Protection Agency (EPA), and can be utilized to facilitate multi-pollutant sector-based analyses that are performed in conjunction with ...

  19. Co-benefits, trade-offs, barriers and policies for greenhouse gas mitigation in the agriculture, forestry and other land use (AFOLU) sector.

    PubMed

    Bustamante, Mercedes; Robledo-Abad, Carmenza; Harper, Richard; Mbow, Cheikh; Ravindranat, Nijavalli H; Sperling, Frank; Haberl, Helmut; Pinto, Alexandre de Siqueira; Smith, Pete

    2014-10-01

    The agriculture, forestry and other land use (AFOLU) sector is responsible for approximately 25% of anthropogenic GHG emissions mainly from deforestation and agricultural emissions from livestock, soil and nutrient management. Mitigation from the sector is thus extremely important in meeting emission reduction targets. The sector offers a variety of cost-competitive mitigation options with most analyses indicating a decline in emissions largely due to decreasing deforestation rates. Sustainability criteria are needed to guide development and implementation of AFOLU mitigation measures with particular focus on multifunctional systems that allow the delivery of multiple services from land. It is striking that almost all of the positive and negative impacts, opportunities and barriers are context specific, precluding generic statements about which AFOLU mitigation measures have the greatest promise at a global scale. This finding underlines the importance of considering each mitigation strategy on a case-by-case basis, systemic effects when implementing mitigation options on the national scale, and suggests that policies need to be flexible enough to allow such assessments. National and international agricultural and forest (climate) policies have the potential to alter the opportunity costs of specific land uses in ways that increase opportunities or barriers for attaining climate change mitigation goals. Policies governing practices in agriculture and in forest conservation and management need to account for both effective mitigation and adaptation and can help to orient practices in agriculture and in forestry towards global sharing of innovative technologies for the efficient use of land resources. Different policy instruments, especially economic incentives and regulatory approaches, are currently being applied however, for its successful implementation it is critical to understand how land-use decisions are made and how new social, political and economic forces

  20. The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP): project framework.

    PubMed

    Warszawski, Lila; Frieler, Katja; Huber, Veronika; Piontek, Franziska; Serdeczny, Olivia; Schewe, Jacob

    2014-03-01

    The Inter-Sectoral Impact Model Intercomparison Project offers a framework to compare climate impact projections in different sectors and at different scales. Consistent climate and socio-economic input data provide the basis for a cross-sectoral integration of impact projections. The project is designed to enable quantitative synthesis of climate change impacts at different levels of global warming. This report briefly outlines the objectives and framework of the first, fast-tracked phase of Inter-Sectoral Impact Model Intercomparison Project, based on global impact models, and provides an overview of the participating models, input data, and scenario set-up. PMID:24344316

  1. The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project framework

    PubMed Central

    Warszawski, Lila; Frieler, Katja; Huber, Veronika; Piontek, Franziska; Serdeczny, Olivia; Schewe, Jacob

    2014-01-01

    The Inter-Sectoral Impact Model Intercomparison Project offers a framework to compare climate impact projections in different sectors and at different scales. Consistent climate and socio-economic input data provide the basis for a cross-sectoral integration of impact projections. The project is designed to enable quantitative synthesis of climate change impacts at different levels of global warming. This report briefly outlines the objectives and framework of the first, fast-tracked phase of Inter-Sectoral Impact Model Intercomparison Project, based on global impact models, and provides an overview of the participating models, input data, and scenario set-up. PMID:24344316

  2. Ecohydrological modeling: the consideration of agricultural trees is essential in the Mediterranean area

    NASA Astrophysics Data System (ADS)

    Fader, Marianela; von Bloh, Werner; Shi, Sinan; Bondeau, Alberte; Cramer, Wolfgang

    2016-04-01

    In the Mediterranean region, climate and land use change are expected to impact on natural and agricultural ecosystems by warming, reduced rainfall and direct degradation of ecosystems. Human population growth and socioeconomic changes, notably on the Eastern and Southern shores, will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive ecohydrological model. Here we present here the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (LPJmL, "Lund-Potsdam-Jena managed Land"): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was then successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. A first application of the model indicates that, currently, agricultural trees consume in average more irrigation water per hectare than annual crops. Also, different crops show different magnitude of changes in net irrigation requirements due to climate change, being the increases most pronounced in agricultural trees. This is very relevant since the Mediterranean area as a whole might face an increase in gross irrigation requirements between 4% and 74% from climate change and population growth if irrigation systems and conveyance are not improved. Additionally, future water scarcity might pose further challenges to the agricultural sector: Algeria, Libya, Israel, Jordan, Lebanon, Syria, Serbia, Morocco, Tunisia and Spain have a high risk of not being able to sustainably meet future irrigation water requirements in some scenarios by the end of the century (1). The importance of including agricultural trees in the ecohydrological models is also shown in the results concerning soil organic carbon (SOC). Since in former model

  3. Water Constraints in an Electric Sector Capacity Expansion Model

    SciTech Connect

    Macknick, Jordan; Cohen, Stuart; Newmark, Robin; Martinez, Andrew; Sullivan, Patrick; Tidwell, Vince

    2015-07-17

    This analysis provides a description of the first U.S. national electricity capacity expansion model to incorporate water resource availability and costs as a constraint for the future development of the electricity sector. The Regional Energy Deployment System (ReEDS) model was modified to incorporate water resource availability constraints and costs in each of its 134 Balancing Area (BA) regions along with differences in costs and efficiencies of cooling systems. Water resource availability and cost data are from recently completed research at Sandia National Laboratories (Tidwell et al. 2013b). Scenarios analyzed include a business-as-usual 3 This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. scenario without water constraints as well as four scenarios that include water constraints and allow for different cooling systems and types of water resources to be utilized. This analysis provides insight into where water resource constraints could affect the choice, configuration, or location of new electricity technologies.

  4. Modeling diffusion of electrical appliances in the residential sector

    SciTech Connect

    McNeil, Michael A.; Letschert, Virginie E.

    2009-11-22

    This paper presents a methodology for modeling residential appliance uptake as a function of root macroeconomic drivers. The analysis concentrates on four major energy end uses in the residential sector: refrigerators, washing machines, televisions and air conditioners. The model employs linear regression analysis to parameterize appliance ownership in terms of household income, urbanization and electrification rates according to a standard binary choice (logistic) function. The underlying household appliance ownership data are gathered from a variety of sources including energy consumption and more general standard of living surveys. These data span a wide range of countries, including many developing countries for which appliance ownership is currently low, but likely to grow significantly over the next decades as a result of economic development. The result is a 'global' parameterization of appliance ownership rates as a function of widely available macroeconomic variables for the four appliances studied, which provides a reliable basis for interpolation where data are not available, and forecasting of ownership rates on a global scale. The main value of this method is to form the foundation of bottom-up energy demand forecasts, project energy-related greenhouse gas emissions, and allow for the construction of detailed emissions mitigation scenarios.

  5. Modeling global distribution of agricultural insecticides in surface waters.

    PubMed

    Ippolito, Alessio; Kattwinkel, Mira; Rasmussen, Jes J; Schäfer, Ralf B; Fornaroli, Riccardo; Liess, Matthias

    2015-03-01

    Agricultural insecticides constitute a major driver of animal biodiversity loss in freshwater ecosystems. However, the global extent of their effects and the spatial extent of exposure remain largely unknown. We applied a spatially explicit model to estimate the potential for agricultural insecticide runoff into streams. Water bodies within 40% of the global land surface were at risk of insecticide runoff. We separated the influence of natural factors and variables under human control determining insecticide runoff. In the northern hemisphere, insecticide runoff presented a latitudinal gradient mainly driven by insecticide application rate; in the southern hemisphere, a combination of daily rainfall intensity, terrain slope, agricultural intensity and insecticide application rate determined the process. The model predicted the upper limit of observed insecticide exposure measured in water bodies (n = 82) in five different countries reasonably well. The study provides a global map of hotspots for insecticide contamination guiding future freshwater management and conservation efforts. PMID:25555206

  6. Automated canopy estimator (ACE): Enhancing crop modelling and decision making in agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Caribbean agriculture sector is dominated by small holdings, which are overly reliant on rainfall and highly dependent on manual means of optimization. The sector is therefore very vulnerable to the vagaries of climate variability and change, with rainfall variations being of particular concern...

  7. Model documentation report: Residential sector demand module of the national energy modeling system

    SciTech Connect

    1998-01-01

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This reference document provides a detailed description for energy analysts, other users, and the public. The NEMS Residential Sector Demand Module is currently used for mid-term forecasting purposes and energy policy analysis over the forecast horizon of 1993 through 2020. The model generates forecasts of energy demand for the residential sector by service, fuel, and Census Division. Policy impacts resulting from new technologies, market incentives, and regulatory changes can be estimated using the module. 26 refs., 6 figs., 5 tabs.

  8. Wisconsin's Model Academic Standards for Agricultural Education. Bulletin No. 9003.

    ERIC Educational Resources Information Center

    Fortier, John D.; Albrecht, Bryan D.; Grady, Susan M.; Gagnon, Dean P.; Wendt, Sharon, W.

    These model academic standards for agricultural education in Wisconsin represent the work of a task force of educators, parents, and business people with input from the public. The introductory section of this bulletin defines the academic standards and discusses developing the standards, using the standards, relating the standards to all…

  9. Agricultural Model for the Nile Basin Decision Support System

    NASA Astrophysics Data System (ADS)

    van der Bolt, Frank; Seid, Abdulkarim

    2014-05-01

    To analyze options for increasing food supply in the Nile basin the Nile Agricultural Model (AM) was developed. The AM includes state-of-the-art descriptions of biophysical, hydrological and economic processes and realizes a coherent and consistent integration of hydrology, agronomy and economics. The AM covers both the agro-ecological domain (water, crop productivity) and the economic domain (food supply, demand, and trade) and allows to evaluate the macro-economic and hydrological impacts of scenarios for agricultural development. Starting with the hydrological information from the NileBasin-DSS the AM calculates the available water for agriculture, the crop production and irrigation requirements with the FAO-model AquaCrop. With the global commodity trade model MAGNET scenarios for land development and conversion are evaluated. The AM predicts consequences for trade, food security and development based on soil and water availability, crop allocation, food demand and food policy. The model will be used as a decision support tool to contribute to more productive and sustainable agriculture in individual Nile countries and the whole region.

  10. MODEL TESTING IN PRECISION AGRICULTURE – COMPARING MEASURES OF VARIATION

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Statistical tests that compare means are widely known and used; tests that compare variation are less so. However, evaluating performance of a simulation model over a range of results requires both. In precision agriculture, comparing simulated results to measured results is usually done using linea...

  11. Renormalization effects on the MSSM from a calculable model of a strongly coupled hidden sector

    SciTech Connect

    Arai, Masato; Okada, Nobuchika

    2011-10-01

    We investigate possible renormalization effects on the low-energy mass spectrum of the minimal supersymmetric standard model (MSSM), using a calculable model of strongly coupled hidden sector. We model the hidden sector by N=2 supersymmetric quantum chromodynamics with gauge group SU(2)xU(1) and N{sub f}=2 matter hypermultiplets, perturbed by a Fayet-Iliopoulos term which breaks the supersymmetry down to N=0 on a metastable vacuum. In the hidden sector the Kaehler potential is renormalized. Upon identifying a hidden sector modulus with the renormalization scale, and extrapolating to the strongly coupled regime using the Seiberg-Witten solution, the contribution from the hidden sector to the MSSM renormalization group flows is computed. For concreteness, we consider a model in which the renormalization effects are communicated to the MSSM sector via gauge mediation. In contrast to the perturbative toy examples of hidden sector renormalization studied in the literature, we find that our strongly coupled model exhibits rather intricate effects on the MSSM soft scalar mass spectrum, depending on how the hidden sector fields are coupled to the messenger fields. This model provides a concrete example in which the low-energy spectrum of MSSM particles that are expected to be accessible in collider experiments is obtained using strongly coupled hidden sector dynamics.

  12. Collaboration between nurses and agricultural teachers to prevent adolescent agricultural injuries: the Agricultural Disability Awareness and Risk Education Model.

    PubMed

    Reed, Deborah B; Kidd, Pamela S

    2004-01-01

    Nearly 2 million children live or work on America's farms and ranches. Despite the increasing mechanization of production agriculture in the United States, children still constitute a considerable portion of the work force on farms and ranches. When adjusted for actual work exposure time, adolescent injury rates on agricultural establishments surpass those of adults (Castillo, D. N., Landen, D. D., & Layne, L. A. (1994). American Journal of Public Health, 84, 646-649). This project, headed by two public health nurses, developed and tested an agricultural safety curriculum [Agricultural Disability Awareness and Risk Education (AgDARE)] for use in high school agriculture classes. Students who participated in AgDARE scored significantly higher in farm safety attitude and intent to change work behavior than the control group. School and public health nurses, working together with agriculture teachers, may make an effective team in reducing injuries among teen agricultural workers. PMID:15260837

  13. Nonperturbative quantization of the electroweak model's electrodynamic sector

    NASA Astrophysics Data System (ADS)

    Fry, M. P.

    2015-04-01

    Consider the Euclidean functional integral representation of any physical process in the electroweak model. Integrating out the fermion degrees of freedom introduces 24 fermion determinants. These multiply the Gaussian functional measures of the Maxwell, Z , W , and Higgs fields to give an effective functional measure. Suppose the functional integral over the Maxwell field is attempted first. This paper is concerned with the large amplitude behavior of the Maxwell effective measure. It is assumed that the large amplitude variation of this measure is insensitive to the presence of the Z , W , and H fields; they are assumed to be a subdominant perturbation of the large amplitude Maxwell sector. Accordingly, we need only examine the large amplitude variation of a single QED fermion determinant. To facilitate this the Schwinger proper time representation of this determinant is decomposed into a sum of three terms. The advantage of this is that the separate terms can be nonperturbatively estimated for a measurable class of large amplitude random fields in four dimensions. It is found that the QED fermion determinant grows faster than exp [c e2∫d4x Fμν 2] , c >0 , in the absence of zero mode supporting random background potentials. This raises doubt on whether the QED fermion determinant is integrable with any Gaussian measure whose support does not include zero mode supporting potentials. Including zero mode supporting background potentials can result in a decaying exponential growth of the fermion determinant. This is prima facie evidence that Maxwellian zero modes are necessary for the nonperturbative quantization of QED and, by implication, for the nonperturbative quantization of the electroweak model.

  14. Modeling Sustainable Agricultural Residue Removal at the Subfield Scale

    SciTech Connect

    Muth, D.J.; McCorkle, D.S.; Koch, J.B.; Bryden, K.M.

    2012-05-02

    This study developed a computational strategy that utilizes data inputs from multiple spatial scales to investigate how variability within individual fields can impact sustainable residue removal for bioenergy production. Sustainable use of agricultural residues for bioenergy production requires consideration of the important role that residues play in limiting soil erosion and maintaining soil C, health, and productivity. Increased availability of subfield-scale data sets such as grain yield data, high-fidelity digital elevation models, and soil characteristic data provides an opportunity to investigate the impacts of subfield-scale variability on sustainable agricultural residue removal. Using three representative fields in Iowa, this study contrasted the results of current NRCS conservation management planning analysis with subfield-scale analysis for rake-and-bale removal of agricultural residue. The results of the comparison show that the field-average assumptions used in NRCS conservation management planning may lead to unsustainable residue removal decisions for significant portions of some fields. This highlights the need for additional research on subfield-scale sustainable agricultural residue removal including the development of real-time variable removal technologies for agricultural residue.

  15. Agrochemical fate models applied in agricultural areas from Colombia

    NASA Astrophysics Data System (ADS)

    Garcia-Santos, Glenda; Yang, Jing; Andreoli, Romano; Binder, Claudia

    2010-05-01

    The misuse application of pesticides in mainly agricultural catchments can lead to severe problems for humans and environment. Especially in developing countries where there is often found overuse of agrochemicals and incipient or lack of water quality monitoring at local and regional levels, models are needed for decision making and hot spots identification. However, the complexity of the water cycle contrasts strongly with the scarce data availability, limiting the number of analysis, techniques, and models available to researchers. Therefore there is a strong need for model simplification able to appropriate model complexity and still represent the processes. We have developed a new model so-called Westpa-Pest to improve water quality management of an agricultural catchment located in the highlands of Colombia. Westpa-Pest is based on the fully distributed hydrologic model Wetspa and a fate pesticide module. We have applied a multi-criteria analysis for model selection under the conditions and data availability found in the region and compared with the new developed Westpa-Pest model. Furthermore, both models were empirically calibrated and validated. The following questions were addressed i) what are the strengths and weaknesses of the models?, ii) which are the most sensitive parameters of each model?, iii) what happens with uncertainties in soil parameters?, and iv) how sensitive are the transfer coefficients?

  16. Agricultural and Environmental Input Parameters for the Biosphere Model

    SciTech Connect

    K. Rasmuson; K. Rautenstrauch

    2004-09-14

    This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters.

  17. Estimation and characterization of gaseous pollutant emissions from agricultural crop residue combustion in industrial and household sectors of Pakistan

    NASA Astrophysics Data System (ADS)

    Irfan, Muhammad; Riaz, Muhammad; Arif, Muhammad Saleem; Shahzad, Sher Muhammad; Saleem, Farhan; -Rahman, Naveed-ur; van den Berg, Leon; Abbas, Farhat

    2014-02-01

    A long-term energy crisis has resulted in increased combustion of biomass fuel in industrial and household sectors in Pakistan. We report results of a study on the emission characteristics of rice husk, rice straw, corncobs and bagasse since they are frequently used as biomass fuel and differed remarkably in physico-chemical and combustion characteristics. Emission concentrations and emission factors were determined experimentally by burning the biomass fuel using a burning tower. Modified combustion efficiency (MCE) of rice husk, rice straw, corncobs and bagasse was >0.97 indicating that combustion was dominated by flaming mode. Emission factors of gaseous pollutants CO, CO2, NO2, NO, NOx and SO2 for rice straw were calculated to be 17.19 ± 0.28, 1090.07 ± 24.0, 0.89 ± 0.03, 1.48 ± 0.04, 3.16 ± 0.08 and 0.38 ± 0.03 g kg-1 respectively which were significantly (p < 0.05) higher compared to those from rice husk (14.05 ± 0.18, 880.48 ± 8.99, 0.19 ± 0.01, 1.38 ± 0.02, 2.31 ± 0.04 and 0.11 ± 0.03 g kg-1), corncobs (8.63 ± 0.12, 595.44 ± 10.38, 0.16 ± 0.01, 0.70 ± 0.01, 1.23 ± 0.02 and 0.02 ± 0.00 g kg-1) and bagasse (12.39 ± 0.08, 937.03 ± 9.07, 0.36 ± 0.03, 1.44 ± 0.02, 2.57 ± 0.04 and 0.18 ± 0.02 g kg-1). Total emissions of CO, CO2, NO2, NO, NOx and SO2 were estimated to be 3.68, 230.51, 0.05, 0.36, 0.60 and 0.03 Gg for rice husk, 33.75, 2140.35, 1.75, 2.91, 6.20 and 0.75 Gg for rice straw, 1.11, 76.28, 0.02, 0.02 and 0.03 Gg for corncobs and 42.12, 3185.53, 1.22, 4.90, 8.74 and 0.61 Gg for bagasse respectively. Rice straw, however, had significantly (p < 0.05) higher potential of gaseous pollutant emission factors. Bagasse had the highest values of total emissions followed by rice straw, rice husk and corncobs. Rice straw and bagasse, on cumulative basis, contributed more than 90% of total emissions of gaseous pollutants. Results reported in this study are important in formulating provincial and regional emission budgets of gaseous pollutants

  18. Modeling Halophytic Plants in APEX for Sustainable Water and Agriculture

    NASA Astrophysics Data System (ADS)

    DeRuyter, T.; Saito, L.; Nowak, B.; Rossi, C.; Toderich, K.

    2013-12-01

    A major problem for irrigated agricultural production is soil salinization, which can occur naturally or can be human-induced. Human-induced, or secondary salinization, is particularly a problem in arid and semi-arid regions, especially in irrigated areas. Irrigated land has more than twice the production of rainfed land, and accounts for about one third of the world's food, but nearly 20% of irrigated lands are salt-affected. Many farmers worldwide currently seasonally leach their land to reduce the soil salt content. These practices, however, create further problems such as a raised groundwater table, and salt, fertilizer, and pesticide pollution of nearby lakes and groundwater. In Uzbekistan, a combination of these management practices and a propensity to cultivate 'thirsty' crops such as cotton has also contributed to the Aral Sea shrinking nearly 90% by volume since the 1950s. Most common agricultural crops are glycophytes that have reduced yields when subjected to salt-stress. Some plants, however, are known as halophytic or 'salt-loving' plants and are capable of completing their life-cycle in higher saline soil or water environments. Halophytes may be useful for human consumption, livestock fodder, or biofuel, and may also be able to reduce or maintain salt levels in soil and water. To assess the potential for these halophytes to assist with salinity management, we are developing a model that is capable of tracking salinity under different management practices in agricultural environments. This model is interdisciplinary as it combines fields such as plant ecology, hydrology, and soil science. The US Department of Agriculture (USDA) model, Agricultural Policy/Environmental Extender (APEX), is being augmented with a salinity module that tracks salinity as separate ions across the soil-plant-water interface. The halophytes Atriplex nitens, Climacoptera lanata, and Salicornia europaea are being parameterized and added into the APEX model database. Field sites

  19. Urban Agriculture Programs on the Rise: Agriculture Education Model Can Reach Students Other Classes Leave Behind

    ERIC Educational Resources Information Center

    Fritsch, Julie M.

    2013-01-01

    Agricultural education begins with hands-on classroom and laboratory instruction. Because agriculture is such a broad topic, schools typically tailor agriculture class offerings to match the interests of the student population, needs of nearby businesses and industry, or topics relevant to their state's standard assessments. Within most…

  20. UNIVERSAL INDUSTRIAL SECTORS INTEGRATED SOLUTIONS MODEL FOR PULP AND PAPER MANUFACTURING INDUSTRY – UISIS-PNP

    EPA Science Inventory

    The U.S. Environmental Protection Agency (EPA) has developed a model for the pulp and paper sector that provides an integrated approach for investigating, developing, and evaluating strategies for reducing the emissions of interest. The Universal Industrial Sectors Integrated Sol...

  1. Scale Issues in Modeling the Water Resources Sector in National Economic Models: A Case study of China

    NASA Astrophysics Data System (ADS)

    Strzepek, K. M.; Kirshen, P.; Yohe, G.

    2001-05-01

    unable to find any global or regional datasets of groundwater.. Combining Surface and Groundwater Supply Functions Water Demand Curves. Water Use data is reported on political regions. Water Supply is reported and modeled on river basin regions. It is necessary to allocate water demands to river basins. To accomplish this China's 9 major river basins were divided into 36 hydroeconomic regions. The counties were then allocated to one of the 36-hydroeconomic zones. The county-level water use data was aggregated to 5 major water use sectors: 1)industry; 2)urban municipal and vegetable gardens: 3) major irrigation; 4) Energy and 5)Other agriculture (forestry, pasture; fishery). Sectoral Demand functions that include price and income elasticity were developed for the 5 sectors for each of the 9 major river basin. The supply and demand curves were aggregated at a variety of geographical scales as well as levels of economic sectoral aggregation. Implications for investment and sustainable development policies were examined for the various aggregation using partial and general equilibrium modeling of the Chinese economy. These results and policy implications for China as well as insights and recommendation for other developing countries will be presented.

  2. Assessing and modelling ecohydrologic processes at the agricultural field scale

    NASA Astrophysics Data System (ADS)

    Basso, Bruno

    2015-04-01

    One of the primary goals of agricultural management is to increase the amount of crop produced per unit of fertilizer and water used. World record corn yields demonstrated that water use efficiency can increase fourfold with improved agronomic management and cultivars able to tolerate high densities. Planting crops with higher plant density can lead to significant yield increases, and increase plant transpiration vs. soil water evaporation. Precision agriculture technologies have been adopted for the last twenty years but seldom have the data collected been converted to information that led farmers to different agronomic management. These methods are intuitively appealing, but yield maps and other spatial layers of data need to be properly analyzed and interpreted to truly become valuable. Current agro-mechanic and geospatial technologies allow us to implement a spatially variable plan for agronomic inputs including seeding rate, cultivars, pesticides, herbicides, fertilizers, and water. Crop models are valuable tools to evaluate the impact of management strategies (e.g., cover crops, tile drains, and genetically-improved cultivars) on yield, soil carbon sequestration, leaching and greenhouse gas emissions. They can help farmers identify adaptation strategies to current and future climate conditions. In this paper I illustrate the key role that precision agriculture technologies (yield mapping technologies, within season soil and crop sensing), crop modeling and weather can play in dealing with the impact of climate variability on soil ecohydrologic processes. Case studies are presented to illustrate this concept.

  3. General structure of democratic mass matrix of quark sector in E6 model

    NASA Astrophysics Data System (ADS)

    Ciftci, R.; ćiftci, A. K.

    2016-03-01

    An extension of the Standard Model (SM) fermion sector, which is inspired by the E6 Grand Unified Theory (GUT) model, might be a good candidate to explain a number of unanswered questions in SM. Existence of the isosinglet quarks might explain great mass difference of bottom and top quarks. Also, democracy on mass matrix elements is a natural approach in SM. In this study, we have given general structure of Democratic Mass Matrix (DMM) of quark sector in E6 model.

  4. Modelling the economic consequences of the EU Water Framework Directive for Dutch agriculture.

    PubMed

    Helming, John; Reinhard, Stijn

    2009-10-01

    The EU Water Framework Directive (WFD) requires member states to take measures to ensure that bodies of water will be in good chemical and ecological condition by 2015. Important measures to achieve this goal include reducing emissions of nitrogen (N) and phosphate (P(2)O(5)) from manure and mineral fertilizers into the environment. In regions with a high livestock density, this measure is expected to affect agricultural production and income. To quantify these effects, an environmental economic model is required that can assess alternatives capable of reducing N and P(2)O(5) potential emissions to water. In this paper, we develop a model that is capable of analysing changes in potential emissions to water of N and P(2)O(5) and apply it to the Netherlands, a country with large nutrient emissions. Compared to a 2015 reference scenario based on current efforts to reduce nutrient emissions, we found that the WFD measures will increase regional transport and export of manure and reduce the number of animals in the Netherlands. Fodder adjustments (defined as lower N and P(2)O(5) input in purchased fodder) to decrease nutrient excretion in manure were a less attractive option than amongst others export, transportation of manure to another region, land use changes or reduction of the number of livestock. Compared to the reference scenario in 2015, total agricultural income will decrease by about 81.5 million euros per year (about 49 euros /ha per year), although the effects will differ among parts of the Netherlands and agricultural sectors. The average predicted decrease in N emissions from agricultural sites, vulnerable to leaching into bodies of water will be almost 20% or approximately 14.7 kg N/ha per year. The reduction in N emissions to air from animal sheds, manure storage systems, application of animal manure and mineral fertilisers to the crops and grazing animals equals 6.5% or 5 kg ammonia (NH(3)) per hectare. PMID:19716645

  5. MODELING OF MACROSCALE AGRICULTURAL ELEMENTS IN PESTICIDE EXPOSURE

    EPA Science Inventory

    Yuma County, Arizona, is the site of year around agriculture. To understand the role of agricultural pesticide exposures experienced by children, urinary metabolite concentrations were compared with agricultural use of pesticides. The urinary metabolite and household data wer...

  6. Importance of incorporating agriculture in conceptual rainfall-runoff models

    NASA Astrophysics Data System (ADS)

    de Boer-Euser, Tanja; Hrachowitz, Markus; Winsemius, Hessel; Savenije, Hubert

    2016-04-01

    Incorporating spatially variable information is a frequently discussed option to increase the performance of (semi-)distributed conceptual rainfall-runoff models. One of the methods to do this is by using this spatially variable information to delineate Hydrological Response Units (HRUs) within a catchment. In large parts of Europe the original forested land cover is replaced by an agricultural land cover. This change in land cover probably affects the dominant runoff processes in the area, for example by increasing the Hortonian overland flow component, especially on the flatter and higher elevated parts of the catchment. A change in runoff processes implies a change in HRUs as well. A previous version of our model distinguished wetlands (areas close to the stream) from the remainder of the catchment. However, this configuration was not able to reproduce all fast runoff processes, both in summer as in winter. Therefore, this study tests whether the reproduction of fast runoff processes can be improved by incorporating a HRU which explicitly accounts for the effect of agriculture. A case study is carried out in the Ourthe catchment in Belgium. For this case study the relevance of different process conceptualisations is tested stepwise. Among the conceptualisations are Hortonian overland flow in summer and winter, reduced infiltration capacity due to a partly frozen soil and the relative effect of rainfall and snow smelt in case of this frozen soil. The results show that the named processes can make a large difference on event basis, especially the Hortonian overland flow in summer and the combination of rainfall and snow melt on (partly) frozen soil in winter. However, differences diminish when the modelled period of several years is evaluated based on standard metrics like Nash-Sutcliffe Efficiency. These results emphasise on one hand the importance of incorporating the effects of agricultural in conceptual models and on the other hand the importance of more event

  7. Modelling tools to support the harmonization of Water Framework Directive and Common Agricultural Policy

    NASA Astrophysics Data System (ADS)

    Tediosi, A.; Bulgheroni, C.; Sali, G.; Facchi, A.; Gandolfi, C.

    2009-04-01

    After a few years from the delivery of the EU Water Framework Directive (WFD) the need to link agriculture and WFD has emerged as one of the highest priorities; therefore, it is important to discuss on how the EU Common Agricultural Policy (CAP) can contribute to the achievements of the WFD objectives. The recent CAP reform - known as Mid Term Review (MTR) or Fischler Reform - has increased the opportunities, offering to farmers increased support to address some environmental issues. The central novelty coming from the MTR is the introduction of a farm single payment which aims to the Decoupling of EU Agricultural Support from production. Other MTR important topics deal with the Modulation of the payments, the Cross-Compliance and the strengthening of the Rural Development policy. All these new elements will affect the farmers' behaviour, steering their productive choices for the future, which, in turn, will have consequences on the water demand for irrigation. Indeed, from the water quantity viewpoint, agriculture is a large consumer and improving water use efficiency is one of the main issues at stake, following the increasing impacts of water scarcity and droughts across Europe in a context of climate change. According to a recent survey of the European Commission the saving potential in the agricultural sector is 43% of present abstraction and 95% of it is concentrated in southern europe. Many models have been developed to forecast the farmers' behaviour as a consequence of agricultural policies, both at sector and regional level; all of them are founded on Mathematical Programming techniques and many of them use the Positive approach, which better fits the territorial dimension. A large body of literature also exists focusing on the assessment of irrigation water requirements. The examples of conjunctive modelling of the two aspects are however much more limited. The work presented has got some innovative aspects: not only does it couple an economical model

  8. Greenhouse gas mitigation options in the forestry sector of The Gambia: Analysis based on COMAP model

    SciTech Connect

    Jallow, B.P.

    1996-12-31

    Results of the 1993 Greenhouse Gas Emissions Inventory of The Gambia showed net CO{sub 2} emissions of over (1.66 x 10{sup 6} tons) and 1% was due to uptake by plantations (0.01 x 10{sup 6} tons). This is a clear indication that there is need to identify changes in the land-use policy, law and tenure that discourages forest clearing at the same time significantly influencing the sustainable distribution of land among forestry, rangeland and livestock, and agriculture. About 11% of the total area of The Gambia is either fallow or barren flats that once supported vegetation and hence is still capable of supporting vegetation. The US Country Study Programme has provided the Government of The Gambia through the National Climate Committee funds to conduct Assessment of Mitigation Options to Reduce Greenhouse Gas Emissions. The Forestry Sector is one area for which assessment is being conducted. The assessment is expected to end in September 1996. The Comprehensive Mitigation Analysis Process (COMAP) is one of the Models supplied to the National Climate Committee by the Lawrence Berkeley Laboratory, on behalf of the US Country Study Programme, and is being used to conduct the analysis in The Gambia.

  9. Building a Comprehensive Mill-Level Database for the Industrial Sectors Integrated Solutions (ISIS) Model of the U.S. Pulp and Paper Sector

    PubMed Central

    Modak, Nabanita; Spence, Kelley; Sood, Saloni; Rosati, Jacky Ann

    2015-01-01

    Air emissions from the U.S. pulp and paper sector have been federally regulated since 1978; however, regulations are periodically reviewed and revised to improve efficiency and effectiveness of existing emission standards. The Industrial Sectors Integrated Solutions (ISIS) model for the pulp and paper sector is currently under development at the U.S. Environmental Protection Agency (EPA), and can be utilized to facilitate multi-pollutant, sector-based analyses that are performed in conjunction with regulatory development. The model utilizes a multi-sector, multi-product dynamic linear modeling framework that evaluates the economic impact of emission reduction strategies for multiple air pollutants. The ISIS model considers facility-level economic, environmental, and technical parameters, as well as sector-level market data, to estimate the impacts of environmental regulations on the pulp and paper industry. Specifically, the model can be used to estimate U.S. and global market impacts of new or more stringent air regulations, such as impacts on product price, exports and imports, market demands, capital investment, and mill closures. One major challenge to developing a representative model is the need for an extensive amount of data. This article discusses the collection and processing of data for use in the model, as well as the methods used for building the ISIS pulp and paper database that facilitates the required analyses to support the air quality management of the pulp and paper sector. PMID:25806516

  10. Building a comprehensive mill-level database for the Industrial Sectors Integrated Solutions (ISIS) model of the U.S. pulp and paper sector.

    PubMed

    Modak, Nabanita; Spence, Kelley; Sood, Saloni; Rosati, Jacky Ann

    2015-01-01

    Air emissions from the U.S. pulp and paper sector have been federally regulated since 1978; however, regulations are periodically reviewed and revised to improve efficiency and effectiveness of existing emission standards. The Industrial Sectors Integrated Solutions (ISIS) model for the pulp and paper sector is currently under development at the U.S. Environmental Protection Agency (EPA), and can be utilized to facilitate multi-pollutant, sector-based analyses that are performed in conjunction with regulatory development. The model utilizes a multi-sector, multi-product dynamic linear modeling framework that evaluates the economic impact of emission reduction strategies for multiple air pollutants. The ISIS model considers facility-level economic, environmental, and technical parameters, as well as sector-level market data, to estimate the impacts of environmental regulations on the pulp and paper industry. Specifically, the model can be used to estimate U.S. and global market impacts of new or more stringent air regulations, such as impacts on product price, exports and imports, market demands, capital investment, and mill closures. One major challenge to developing a representative model is the need for an extensive amount of data. This article discusses the collection and processing of data for use in the model, as well as the methods used for building the ISIS pulp and paper database that facilitates the required analyses to support the air quality management of the pulp and paper sector. PMID:25806516

  11. World agriculture and climate change: Current modeling issues

    SciTech Connect

    Darwin, R.

    1996-12-31

    Recent studies suggest that although global increases in temperature and changes in precipitation patterns during the next century will affect world agriculture, farmer adaptations are likely to prevent climate change from jeopardizing world food production. The costs and benefits of global climate change, however, are not equally distributed around the world. Agricultural production may increase in high latitude and alpine areas, but decrease in tropical and some other areas. Also, land use changes that accompany climate-induced shifts in cropland and permanent pasture are likely to raise additional social and environmental issues. Despite these advances, some important aspects of climate change have not been adequately simulated in global models. These include the effects that climate-induced changes in water resources are likely to have on agricultural production, the well-documented beneficial effects of higher concentrations of atmospheric carbon dioxide on plant growth and water use, and the cooling effects of tropospheric emissions of sulfur dioxide. In addition, past research generally relied on equilibrium climates based on a doubling of atmospheric carbon dioxide. Now, however, results from transient climate change experiments are available.

  12. AgBase: supporting functional modeling in agricultural organisms.

    PubMed

    McCarthy, Fiona M; Gresham, Cathy R; Buza, Teresia J; Chouvarine, Philippe; Pillai, Lakshmi R; Kumar, Ranjit; Ozkan, Seval; Wang, Hui; Manda, Prashanti; Arick, Tony; Bridges, Susan M; Burgess, Shane C

    2011-01-01

    AgBase (http://www.agbase.msstate.edu/) provides resources to facilitate modeling of functional genomics data and structural and functional annotation of agriculturally important animal, plant, microbe and parasite genomes. The website is redesigned to improve accessibility and ease of use, including improved search capabilities. Expanded capabilities include new dedicated pages for horse, cat, dog, cotton, rice and soybean. We currently provide 590 240 Gene Ontology (GO) annotations to 105 454 gene products in 64 different species, including GO annotations linked to transcripts represented on agricultural microarrays. For many of these arrays, this provides the only functional annotation available. GO annotations are available for download and we provide comprehensive, species-specific GO annotation files for 18 different organisms. The tools available at AgBase have been expanded and several existing tools improved based upon user feedback. One of seven new tools available at AgBase, GOModeler, supports hypothesis testing from functional genomics data. We host several associated databases and provide genome browsers for three agricultural pathogens. Moreover, we provide comprehensive training resources (including worked examples and tutorials) via links to Educational Resources at the AgBase website. PMID:21075795

  13. AgBase: supporting functional modeling in agricultural organisms

    PubMed Central

    McCarthy, Fiona M.; Gresham, Cathy R.; Buza, Teresia J.; Chouvarine, Philippe; Pillai, Lakshmi R.; Kumar, Ranjit; Ozkan, Seval; Wang, Hui; Manda, Prashanti; Arick, Tony; Bridges, Susan M.; Burgess, Shane C.

    2011-01-01

    AgBase (http://www.agbase.msstate.edu/) provides resources to facilitate modeling of functional genomics data and structural and functional annotation of agriculturally important animal, plant, microbe and parasite genomes. The website is redesigned to improve accessibility and ease of use, including improved search capabilities. Expanded capabilities include new dedicated pages for horse, cat, dog, cotton, rice and soybean. We currently provide 590 240 Gene Ontology (GO) annotations to 105 454 gene products in 64 different species, including GO annotations linked to transcripts represented on agricultural microarrays. For many of these arrays, this provides the only functional annotation available. GO annotations are available for download and we provide comprehensive, species-specific GO annotation files for 18 different organisms. The tools available at AgBase have been expanded and several existing tools improved based upon user feedback. One of seven new tools available at AgBase, GOModeler, supports hypothesis testing from functional genomics data. We host several associated databases and provide genome browsers for three agricultural pathogens. Moreover, we provide comprehensive training resources (including worked examples and tutorials) via links to Educational Resources at the AgBase website. PMID:21075795

  14. Agricultural and Environmental Input Parameters for the Biosphere Model

    SciTech Connect

    Kaylie Rasmuson; Kurt Rautenstrauch

    2003-06-20

    This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN.

  15. Liberalization of the Spanish electricity sector: An advanced model

    SciTech Connect

    Unda, J.I.

    1998-06-01

    Spain`s electricity industry is being restructured to provide a competitive generation market, a regulated, open access transmission and distribution system, and phased-in customer choice. But while the reform is radical in its objectives, it will be gradual in its implementation. This article briefly describes the current state of affairs within the Spanish electricity sector and details the reform plans set out in the act, focusing on the adopted institutional design and the established transition period. It also offers an overview of the role that the regulatory authority will play throughout the process.

  16. The Development of the Integrated Three-Component Model of Agricultural Education

    ERIC Educational Resources Information Center

    Croom, D. Barry

    2008-01-01

    This research project sought to determine the origin of the three-component model of agricultural education in the United States and provided a contextual base for future research into the three-component model for agricultural education. The study concluded that each of the three components of the agricultural education model originated at…

  17. Methane Emissions From Global Paddy Rice Agriculture - a New Estimate Based on DNDC Model Simulations

    NASA Astrophysics Data System (ADS)

    Hagen, S. C.; Li, C.; Salas, W.; Ingraham, P.; Li, J.; Beach, R.; Frolking, S.

    2012-12-01

    Roughly one-quarter of global methane emissions to the atmosphere come from the agricultural sector. Agricultural emissions are dominated by livestock (ruminants) and paddy-rice agriculture. We report on a new estimate of global methane emissions from paddy rice c.2010, based on DNDC model simulations of rice cropping around the world. We first generated a global map of rice cropping at 0.5°-resolution, based on existing global crop maps and various other published data. For each 0.5° grid cell that has rice agriculture, we simulated all rice cropping systems that our mapping indicated to be occurring there - irrigated and/or rainfed; single-rice, double-rice, triple-rice, and/or rice-rotated with other upland crops - under local climate and soil conditions, with assumptions about crop management (e.g., fertilizer type and amount, irrigation, flooding frequency and duration, manure application, tillage, crop residue management). We estimate global paddy rice emissions at 23 Tg CH4/yr from 120 Mha of rice paddies (land area) and 160 Mha of rice cropping (harvested area) for the baseline management scenario. We also report on the spatial distribution of these emissions, and the impacts of various management alternatives (flooding methods, fertilizer types, crop residue incorporation etc.) on yield, soil carbon sequestration and emissions of methane and nitrous oxide. For example, simulations with continuous flooding on all paddies increased simulated global paddy rice emissions to 33 Tg CH4/yr, while simulations where all fertilizer was applied as ammonium sulfate reduced simulated global paddy rice emissions to about 19 Tg CH4/yr. Simulated global paddy rice yield was about 320 Tg C in grain.

  18. Econometrics and data of the 9 sector Dynamic General Equilibrium Model. Volume III. Final report

    SciTech Connect

    Berndt, E.R.; Fraumeni, B.M.; Hudson, E.A.; Jorgenson, D.W.; Stoker, T.M.

    1981-03-01

    This report presents the econometrics and data of the 9 sector Dynamic General Equilibrium Model. There are two key components of 9DGEM - the model of household behavior and the model of produconcrneer behavior. The household model is concerned with decisions on consumption, saving, labor supply and the composition of consumption. The producer model is concerned with output price formation and determination of input patterns and purchases for each of the nine producing sectors. These components form the behavioral basis of DGEM. The remaining components are concerned with constraints, balance conditions, accounting, and government revenues and expenditures (these elements are developed in the report on the model specification).

  19. Modeling Climate Impacts on Agriculture in South East South America

    NASA Astrophysics Data System (ADS)

    Ines, A. M.; Baethgen, W.; Greene, A. M.; Goddard, L. M.

    2013-12-01

    In the past two decades, a rapid expansion of croplands in South East South America is observed. This drastic change in landuse is seen to be due to two major factors - climate and economics. Converting marginal lands into agricultural lands is possible due to the increase in annual precipitation in the region and the increasing prices of soybeans and higher demands for grain crops have played a key role to this expansion. But the question is, how sustainable is the current trend in the future? A modeling study is conducted to evaluate the impacts of climate on agriculture in the Southern Cone of South America. We examine the impacts of climate variability and current climate change to crop yields using crop simulation models. Using the results of our current climate analysis as a baseline, we evaluate the impacts of future climate change in the next 10-30 years. Climate projections include scenarios considering only global warming, ozone and both impacting the near-term climate of the future in the region and considering decadal variability. We aim to evaluate the vulnerability of the current system to climate change. This paper will present the results of our modeling study.

  20. A new baseline of organic carbon stock in European agricultural soils using a modelling approach.

    PubMed

    Lugato, Emanuele; Panagos, Panos; Bampa, Francesca; Jones, Arwyn; Montanarella, Luca

    2014-01-01

    Proposed European policy in the agricultural sector will place higher emphasis on soil organic carbon (SOC), both as an indicator of soil quality and as a means to offset CO2 emissions through soil carbon (C) sequestration. Despite detailed national SOC data sets in several European Union (EU) Member States, a consistent C stock estimation at EU scale remains problematic. Data are often not directly comparable, different methods have been used to obtain values (e.g. sampling, laboratory analysis) and access may be restricted. Therefore, any evolution of EU policies on C accounting and sequestration may be constrained by a lack of an accurate SOC estimation and the availability of tools to carry out scenario analysis, especially for agricultural soils. In this context, a comprehensive model platform was established at a pan-European scale (EU + Serbia, Bosnia and Herzegovina, Croatia, Montenegro, Albania, Former Yugoslav Republic of Macedonia and Norway) using the agro-ecosystem SOC model CENTURY. Almost 164 000 combinations of soil-climate-land use were computed, including the main arable crops, orchards and pasture. The model was implemented with the main management practices (e.g. irrigation, mineral and organic fertilization, tillage) derived from official statistics. The model results were tested against inventories from the European Environment and Observation Network (EIONET) and approximately 20 000 soil samples from the 2009 LUCAS survey, a monitoring project aiming at producing the first coherent, comprehensive and harmonized top-soil data set of the EU based on harmonized sampling and analytical methods. The CENTURY model estimation of the current 0-30 cm SOC stock of agricultural soils was 17.63 Gt; the model uncertainty estimation was below 36% in half of the NUTS2 regions considered. The model predicted an overall increase of this pool according to different climate-emission scenarios up to 2100, with C loss in the south and east of the area

  1. Linking knowledge and action through mental models of sustainable agriculture.

    PubMed

    Hoffman, Matthew; Lubell, Mark; Hillis, Vicken

    2014-09-01

    Linking knowledge to action requires understanding how decision-makers conceptualize sustainability. This paper empirically analyzes farmer "mental models" of sustainability from three winegrape-growing regions of California where local extension programs have focused on sustainable agriculture. The mental models are represented as networks where sustainability concepts are nodes, and links are established when a farmer mentions two concepts in their stated definition of sustainability. The results suggest that winegrape grower mental models of sustainability are hierarchically structured, relatively similar across regions, and strongly linked to participation in extension programs and adoption of sustainable farm practices. We discuss the implications of our findings for the debate over the meaning of sustainability, and the role of local extension programs in managing knowledge systems. PMID:25157158

  2. Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System

    SciTech Connect

    1995-02-01

    This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. This report serves three purposes. First, it is a reference document providing a detailed description for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports (Public Law 93-275, section 57(b)(1)). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

  3. Climate Risk Management and Decision Support Tools for the Agriculture Sector in Lao PDR, Bangladesh, and Indonesia

    NASA Astrophysics Data System (ADS)

    Allis, E. C.; Greene, A. M.; Cousin, R.

    2014-12-01

    We describe a comprehensive project for developing climate information and decision support / climate risk management tools in Lao PDR, Bangladesh and Indonesia. Mechanisms are developed for bringing the benefits of these tools to both policy makers and poor rural farmers, with the goal of enabling better management, at the farm level, of the risks associated with climate variability and change. The project comprises several interwoven threads, differentially applied in the different study regions. These include data management and quality control, development of seasonal forecast capabilities, use of dynamic cropping calendars and climate advisories, the development of longer-term climate information for both past and future and a weather index insurance component. Stakeholder engagement and capacity building served as reinforcing and complementary elements to all components. In this talk we will provide a project overview, show how the various components fit together and describe some lessons learned in this attempt to promote the uptake of actionable climate information from farmer to policy level. The applied research project was led by the International Research Institute for Climate and Society (IRI) at Columbia University with funding from the International Fund for Agriculture Development (IFAD) and in close collaboration with our regional partners at the Centre for Climate Risk and Opportunity Management in Southeast Asia Pacific (at Bogor Agricultural University in Indonesia), Indonesia's National Agency for Meteorology, Climatology and Geophysics (BMKG), Lao PDR's National Agriculture and Forestry Research Institute (NAFRI), Laotian Department of Meteorology and Hydrology (DMH), WorldFish Center, Bangladesh Meteorology Department (BMD), and CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).

  4. Modeling a phosphorus credit trading program in an agricultural watershed.

    PubMed

    Corrales, Juliana; Naja, G Melodie; Bhat, Mahadev G; Miralles-Wilhelm, Fernando

    2014-10-01

    Water quality and economic models were linked to assess the economic and environmental benefits of implementing a phosphorus credit trading program in an agricultural sub-basin of Lake Okeechobee watershed, Florida, United States. The water quality model determined the effects of rainfall, land use type, and agricultural management practices on the amount of total phosphorus (TP) discharged. TP loadings generated at the farm level, reaching the nearby streams, and attenuated to the sub-basin outlet from all sources within the sub-basin, were estimated at 106.4, 91, and 85 mtons yr(-)(1), respectively. Almost 95% of the TP loadings reaching the nearby streams were attributed to agriculture sources, and only 1.2% originated from urban areas, accounting for a combined TP load of 87.9 mtons yr(-)(1). In order to compare a Least-Cost Abatement approach to a Command-and-Control approach, the most cost effective cap of 30% TP reduction was selected, and the individual allocation was set at a TP load target of 1.6 kg ha(-1) yr(-1) (at the nearby stream level). The Least-Cost Abatement approach generated a potential cost savings of 27% ($1.3 million per year), based on an optimal credit price of $179. Dairies (major buyer), ornamentals, row crops, and sod farms were identified as potential credit buyers, whereas citrus, improved pastures (major seller), and urban areas were identified as potential credit sellers. Almost 81% of the TP credits available for trading were exchanged. The methodology presented here can be adapted to deal with different forms of trading sources, contaminants, or other technologies and management practices. PMID:24907668

  5. Model documentation report: Industrial sector demand module of the National Energy Modeling System

    SciTech Connect

    1997-01-01

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects. The NEMS Industrial Demand Model is a dynamic accounting model, bringing together the disparate industries and uses of energy in those industries, and putting them together in an understandable and cohesive framework. The Industrial Model generates mid-term (up to the year 2015) forecasts of industrial sector energy demand as a component of the NEMS integrated forecasting system. From the NEMS system, the Industrial Model receives fuel prices, employment data, and the value of industrial output. Based on the values of these variables, the Industrial Model passes back to the NEMS system estimates of consumption by fuel types.

  6. Watershed Modeling in areas with Intensive Agricultural Irrigation

    NASA Astrophysics Data System (ADS)

    Wyss, J. R.; Watson, B. J.

    2011-12-01

    Irrigation in agricultural intensive watersheds affects soil moisture content, plays a major role in the overall water balance and also influences the hydrologic regime. Historically, irrigation in watershed modeling has been very difficult to simulate and was simulated in one of three general ways. 1) irrigation water was withdrawan from the model and never applied to the land, 2) ignored and assumed insignificant and 3) input as a constant by modifying atmospheric forcing files. For the Loading Simulation Program C++ (LSPC) model developed for the Flint River Watershed in southwest Georgia, we received a summary report of a study conducted to determine irrigation application depth, as well as spatial mapping of irrigated fields in the state of Georgia. The summary report provided minimum, mean, and maximum irrigation depth for both surface water and groundwater sources and the spatial mapping provided over 10,300 irrigated fields located within the boundaries of the Flint River Watershed. With this information we were able to calculate irrigation volume applied to the land by source water type. We discuss how these data were incorporated into the LSPC watershed modeling effort and demonstrate the utility and function of the model for irrigation application. We also investigate impacts to water balance and the hydrologic regime through a series of scenarios in the agriculturally dominated landscape of Ichawaynochaway Creek (HUC 03130009). The scenarios compare and contrast our approach with 1) ignoring irrigation both application and water withdrawal, and 2) only withdrawing the water and not applying it back to the land. We demonstrate the importance of properly simulating irrigation application in heavily influenced areas. The approach we have taken is applicable in other areas in the southeastern United States or any area that is highly influenced by irrigation practices.

  7. Making Other Worlds: Modelling Past Interactions of Agriculture and Erosion

    NASA Astrophysics Data System (ADS)

    Wainwright, J.

    2012-04-01

    It is argued that the understanding of past agricultural erosion has been greatly simplified because conceptual or numerical models have been used that emphasize the technical aspects of the erosion process, fail to recognize the spatial and temporal scaling of the erosion, and especially ignore the idea that such erosion is the result of multiple, interacting decisions made by people. While there have been significant developments in the first two of these areas over the last decade, there has been little explicit recognition of the third of these limitations. This problem is a consequence of the very different disciplinary approaches that are needed. One method that can be used to address this limitation is that of agent-based modelling. Agent-based models permit an explicit representation of how individuals or groups of individuals interact with each other and their environment. Furthermore, environmental changes can be fed back into agent behaviour, and other potential controls such as climate variations can be assessed. The CYBEROSION modelling framework has been developed to take this approach and evaluate patterns of erosion due to past land-use decision-making. Examples will be drawn from case studies in the Neolithic and Bronze Age, largely from the Mediterranean region. The emphasis is on modelling as a heuristic approach to understanding, rather than necessarily as a predictive tool. In particular, it provides guidance in relation to which parts of existing discipline-bound knowledge are needed to produce an explicit, interdisciplinary understanding of patterns of landscape change as a result of changing agricultural practice. Results from the case studies demonstrate how complex spatio-temporal patterns of past erosion can arise from relatively simple, local interactions between people and their environment. To conclude, will also be an assessment of more modern examples, as well as of related literature in archaeology, and geoarchaeology, and a

  8. Application Of Colored Petri Net In Modeling Ofan Agricultural Enterprise Informationmanagement System

    NASA Astrophysics Data System (ADS)

    Zhang, Fangtian; Wang, Kaiyi; Sui, Jin; Liu, Chang; Liu, Zhongqiang

    Business system modeling of an agricultural enterprise is one of the difficulties in developing and researching an agricultural enterprise management information system. Given the inadequate description of concurrent and synchronal events in the traditional modeling methods, this paper presents a modeling method, which uses Colored Petri Net. The paper discusses the application of Colored Petri Net in system modeling with the example of an agricultural enterprise production management system model, and analyzes the feasibility and effectiveness of that model.

  9. Development of an improved commercial sector energy model for national policy analysis

    SciTech Connect

    Belzer, D.B.

    1992-12-01

    Pacific Northwest Laboratory provided support to the Office of Conservation and Renewable Energy (CE), under the Office of Planning and Assessment, to develop improved energy and environmental analysis tools. Commercial building sector energy models from the past decade were analyzed in order to provoke comment and stimulate discussion between potential model users and developers as to the appropriate structure and capability of a commercial sector energy model supported by CE. Three specific areas were examined during this review. These areas provide (1) a look at recent suggestions and guidance as to what constitutes a minimal set of requirements and capabilities for a commercial buildings energy model for CE, (2) a review of several existing models in terms of their general structure and how they match up with the requirements listed previously, and (3) an overview of a proposed improved commercial sector energy model.

  10. A two-sector model of land use and deforestation: Funding urban development with a tax on urban and rural employment

    SciTech Connect

    Jones, D.W.; O`Neill, R.V.

    1992-07-17

    We model a small country with an urban manufacturing sector and a rural agricultural sector. Government taxes rural and urban employment to finance urban infrastructure which contributes to urban production. The manufacturing wage is fixed, leading to urban unemployment. Expansion of cultivated area involves deforestation at frontiers. An increment to urban infrastructure may draw resources into the city but a large enough addition to infrastructure may cause the tax rate to rise by more than urban labor productivity, which would exacerbate frontier deforestation. Improvement of rural transportation raises rural wages, reduces the urban unemployment rate, and extends the area under cultivation, causing deforestation; it also reduces the employment tax rate, which permits expansion of fixed-wage urban manufacturing. Such a wide, sectoral distribution of benefits may help explain the popularity of such policies despite their damage to frontier forest resources.

  11. Promoting Evidence-Based Practice: Models and Mechanisms from Cross-Sector Review

    ERIC Educational Resources Information Center

    Nutley, Sandra; Walter, Isabel; Davies, Huw T. O.

    2009-01-01

    This article draws on both a cross-sector literature review of mechanisms to promote evidence-based practice and a specific review of ways of improving research use in social care. At the heart of the article is a discussion of three models of evidence-based practice: the research-based practitioner model, the embedded research model, and the…

  12. Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model

    NASA Astrophysics Data System (ADS)

    Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.

    2015-11-01

    In the Mediterranean region, climate and land use change are expected to impact on natural and agricultural ecosystems by warming, reduced rainfall, direct degradation of ecosystems and biodiversity loss. Human population growth and socioeconomic changes, notably on the eastern and southern shores, will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (Lund-Potsdam-Jena managed Land - LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development paves the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments of the consequences of land use transitions, the influence of management practices and climate change impacts.

  13. Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model

    NASA Astrophysics Data System (ADS)

    Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.

    2015-06-01

    Climate and land use change in the Mediterranean region is expected to affect natural and agricultural ecosystems by decreases in precipitation, increases in temperature as well as biodiversity loss and anthropogenic degradation of natural resources. Demographic growth in the Eastern and Southern shores will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development pave the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments on the consequences of land use transitions, the influence of management practices and climate change impacts.

  14. Model documentation report: Residential sector demand module of the National Energy Modeling System

    SciTech Connect

    1995-03-01

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This document serves three purposes. First, it is a reference document providing a detailed description for energy analysts, other users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

  15. Model documentation report: Residential sector demand module of the National Energy Modeling System

    SciTech Connect

    1997-01-01

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This document serves three purposes. First, it is a reference document that provides a detailed description for energy analysts, other users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

  16. Wind Direction Bias in Generating Wind Roses and Conducting Sector-Based Air-Dispersion Modeling

    SciTech Connect

    Droppo, James G.; Napier, Bruce A.

    2008-07-01

    Certain widely used wind rose programs and air dispersion models use an overly-simple data-transfer algorithm that induces a directional bias in their output products. The purpose of this paper is to provide a revised algorithm that corrects the aliasing bias that occurs when the internals in reported wind direction data are on the same order of magnitude, but not equal to the intervals used in the wind direction summaries. The directional bias issue arises when output products in 22.5-degree sectors are produced from 10-degree wind direction data, which affects the results of simulations of air and surface concentrations using widely applied air-dispersion models. Datasets or models with the bias discussed here give consistent positive biases (approximately 30%) for cardinal direction sectors (north, south, east, and west) and consistent negative biases for all the other sectors (approximately -10%). Data summary and air dispersion programs providing outputs in directions sectors that do not match the observational sectors need to be checked for this bias. A revised data-transfer algorithm is provided that corrects the aliasing bias that can occur in transferring wind direction data between different sectors widths.

  17. Spatial modeling of agricultural land use change at global scale

    NASA Astrophysics Data System (ADS)

    Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.

    2014-11-01

    Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling

  18. Modeling of Internal State and Performance of an Ironmaking Blast Furnace: Slot vs Sector Geometries

    NASA Astrophysics Data System (ADS)

    Shen, Yansong; Guo, Baoyu; Chew, Sheng; Austin, Peter; Yu, Aibing

    2016-04-01

    Mathematical modeling is a cost-effective method to understand internal state and predict performance of ironmaking blast furnace (BF) for improving productivity and maintaining stability. In the past studies, both slot and sector geometries were used for BF modeling. In this paper, a mathematical model is described for simulating the complex behaviors of solid, gas and liquid multiphase flow, heat and mass transfers, and chemical reactions in a BF. Then the model is used to compare different model configurations, viz. slot and sector geometries by investigating their effects on predicted behaviors, in terms of two aspects: (i) internal state including cohesive zone, velocity, temperature, components concentration, reduction degree, gas utilization, and (ii) performance indicators including liquid output at the bottom and gas utilization rate at the furnace top. The comparisons show that on one hand, predictions of internal state of the furnace such as fluid flow and thermo-chemical phenomena using the slot and sector geometries are qualitatively comparable but quantitatively different. Both sector and slot geometries give a similar cohesive zone shape but the sector geometry gives a higher cohesive zone near the wall and faster reduction. On the other hand, the two geometries can produce similar performance indicators including gas utilization at the furnace top and liquid output at the bottom. Such a study is useful in selecting geometry for numerically examining BF operation with respect to different needs.

  19. Development of an Integrated Agricultural Planning Model Considering Climate Change

    NASA Astrophysics Data System (ADS)

    Santikayasa, I. P.

    2016-01-01

    The goal of this study is to develop an agriculture planning model in order to sustain the future water use under the estimation of crop water requirement, water availability and future climate projection. For this purpose, the Citarum river basin which is located in West Java - Indonesia is selected as the study area. Two emission scenarios A2 and B2 were selected. For the crop water requirement estimation, the output of HadCM3 AOGCM is statistically downscale using SDSM and used as the input for WEAP model developed by SEI (Stockholm Environmental Institute). The reliability of water uses is assessed by comparing the irrigation water demand and the water allocation for the irrigation area. The water supply resources are assessed using the water planning tool. This study shows that temperature and precipitation over the study area are projected to increase in the future. The water availability was projected to increase under both A2 and B2 emission scenarios in the future. The irrigation water requirement is expected to decrease in the future under A2 and B2 scenarios. By comparing the irrigation water demand and water allocation for irrigation, the reliability of agriculture water use is expected to change in the period of 2050s and 2080s while the reliability will not change in 2020s. The reliability under A2 scenario is expected to be higher than B2 scenario. The combination of WEAP and SDSM is significance to use in assessing and allocating the water resources in the region.

  20. Business model innovation in the water sector in developing countries.

    PubMed

    Gebauer, Heiko; Saul, Caroline Jennings

    2014-08-01

    Various technologies have been deployed in household devices or micro-water treatment plants for mitigating fluoride and arsenic, and thereby provide safe and affordable drinking water in low-income countries. While the technologies have improved considerably, organizations still face challenges in making them financially sustainable. Financial sustainability questions the business models behind these water technologies. This article makes three contributions to business models in the context of fluoride and arsenic mitigation. Firstly, we describe four business models: A) low-value devices given away to people living in extreme poverty, B) high-value devices sold to low-income customers, C) communities as beneficiaries of micro-water treatment plants and D) entrepreneurs as franchisees for selling water services and highlight the emergence of hybrid business models. Secondly, we show current business model innovations such as cost transparency & cost reductions, secured & extended water payments, business diversification and distribution channels. Thirdly, we describe skills and competencies as part of capacity building for creating even more business model innovations. Together, these three contributions will create more awareness of the role of business models in scaling-up water treatment technologies. PMID:24612490

  1. A Regional Model for Seasonal Sea Ice Prediction in the Pacific Sector of the Arctic

    NASA Astrophysics Data System (ADS)

    Yuan, X.; Li, Y.; Chen, D.; Zhang, Q.; Li, C.; Niu, F.; Sun, Y.

    2015-12-01

    The recent results from a linear Markov model for seasonal prediction of pan-Arctic sea ice concentration (SIC) show that sea ice in the Pacific sector has the lowest predictability compared to other regions. One reason could be that the climate variability in the Atlantic sector is so dominant that other signals in the Arctic climate system do not appear in the leading modes used for model construction. This study develops a regional Markov model to improve seasonal forecasting of SIC in the Pacific sector. The model climate system consists of various combinations of the monthly mean series of SIC, sea surface temperature (SST), surface air temperature (SAT), pressure/geopotential height fields and winds at pressure levels. Multivariate empirical orthogonal functions (MEOF) and rotated MEOF are applied to each set of data to reduce the model dimensions. After a series of experiments, the final model configuration selects 23 rotated MEOF modes from a data matrix of three variables (SIC, SST and SAT). This regional model shows considerable improvement in the prediction skill in the Pacific sector in all seasons. The anomaly correlation skill increases by 0.2 at 1- to 4-month leads in the Bering Sea, and by 0.1 at 1- to 10-month leads in the Sea of Okhotsk. In general, the model performs better in summer and fall than in winter and spring. On average, the correlation skill can reach 0.6 at a 2-month (4-month) lead in the Bering Sea (the Sea of Okhotsk).

  2. Modeling energy-sector issues of developing and industrializing countries

    SciTech Connect

    Macal, C.M.; Cirillo, R.R.

    1983-01-01

    This paper identifies important energy-planning issues in industrializing and developing countries based on the Argonne experience in energy-planning studies for Egypt, Korea, Portugal, Argentina, and Jamaica. Modeling approaches are reviewed for applicability to these issues.

  3. Agricultural Education Early Field Experience through the Lens of the EFE Model

    ERIC Educational Resources Information Center

    Smalley, Scott W.; Retallick, Michael S.

    2012-01-01

    The purpose of this national study was to describe agricultural teacher education early field experience (EFE) practices using the EFE model. The population for this study was all agricultural education teacher preparation programs (N = 83) listed in the AAAE Directory of University Faculty in Agricultural Education. Data were collected via an…

  4. Analysis of the research and development effort in the private sector to reduce energy consumption in irrigated agriculture

    SciTech Connect

    Rogers, E.A.; Cone, B.W.

    1980-09-01

    Manufacturers of irrigation equipment perform research and development in an effort to improve or maintain their position in a very competitive market. The market forces and conditions that create the intense competition and provide incentive for invention are described. Particular emphasis is placed on the market force of increased energy costs, but the analysis is developed from the perspective that energy is but one of many inputs to agricultural production. The analysis is based upon published literature, patent activity profiles, microeconomic theory, and conversations with many representatives of the irrigation industry. The published literature provides an understanding of the historical development of irrigation technology, a description of the industry's structure, and various data, which were important for the quantitative analyses. The patent activity profiles, obtained from the US Patent Office, provided details of patent activity within the irrigation industry over the past decade. Microeconomic theory was used to estimate industry-wide research and development expenditures on energy-conserving products. The results of these analyses were then compared with the insights gained from conversations with the industry representatives.

  5. Monitoring and modeling agricultural drought for famine early warning (Invited)

    NASA Astrophysics Data System (ADS)

    Verdin, J. P.; Funk, C.; Budde, M. E.; Lietzow, R.; Senay, G. B.; Smith, R.; Pedreros, D.; Rowland, J.; Artan, G. A.; Husak, G. J.; Michaelsen, J.; Adoum, A.; Galu, G.; Magadzire, T.; Rodriguez, M.

    2009-12-01

    The Famine Early Warning Systems Network (FEWS NET) makes quantitative estimates of food insecure populations, and identifies the places and periods during which action must be taken to assist them. Subsistence agriculture and pastoralism are the predominant livelihood systems being monitored, and they are especially drought-sensitive. At the same time, conventional climate observation networks in developing countries are often sparse and late in reporting. Consequently, remote sensing has played a significant role since FEWS NET began in 1985. Initially there was heavy reliance on vegetation index imagery from AVHRR to identify anomalies in landscape greenness indicative of drought. In the latter part of the 1990s, satellite rainfall estimates added a second, independent basis for identification of drought. They are used to force crop water balance models for the principal rainfed staple crops in twenty FEWS NET countries. Such models reveal seasonal moisture deficits associated with yield reduction on a spatially continuous basis. In 2002, irrigated crops in southwest Asia became a concern, and prompted the implementation of a gridded energy balance model to simulate the seasonal mountain snow pack, the main source of irrigation water. MODIS land surface temperature data are also applied in these areas to directly estimate actual seasonal evapotranspiration on the irrigated lands. The approach reveals situations of reduced irrigation water supply and crop production due to drought. The availability of MODIS data after 2000 also brought renewed interest in vegetation index imagery. MODIS NDVI data have proven to be of high quality, thanks to significant spectral and spatial resolution improvements over AVHRR. They are vital to producing rapid harvest assessments for drought-impacted countries in Africa and Asia. The global food crisis that emerged in 2008 has led to expansion of FEWS NET monitoring to over 50 additional countries. Unlike previous practice, these

  6. The Role of Agriculture in the Economic Development of West Virginia: An Input-Output Analysis. Miscellaneous Publication No. 20.

    ERIC Educational Resources Information Center

    D'Souza, Gerard E.; And Others

    This study deals with the structural interrelationships among agricultural sub-sectors, and between the agricultural and non-agricultural sectors of the West Virginia economy. The study is intended to offer information on which to base sound economic development decisions. An input-output economic model is used in order to focus on the interaction…

  7. A GIS-based hedonic price model for agricultural land

    NASA Astrophysics Data System (ADS)

    Demetriou, Demetris

    2015-06-01

    Land consolidation is a very effective land management planning approach that aims towards rural/agricultural sustainable development. Land reallocation which involves land tenure restructuring is the most important, complex and time consuming component of land consolidation. Land reallocation relies on land valuation since its fundamental principle provides that after consolidation, each landowner shall be granted a property of an aggregate value that is approximately the same as the value of the property owned prior to consolidation. Therefore, land value is the crucial factor for the land reallocation process and hence for the success and acceptance of the final land consolidation plan. Land valuation is a process of assigning values to all parcels (and its contents) and it is usually carried out by an ad-hoc committee. However, the process faces some problems such as it is time consuming hence costly, outcomes may present inconsistency since it is carried out manually and empirically without employing systematic analytical tools and in particular spatial analysis tools and techniques such as statistical/mathematical. A solution to these problems can be the employment of mass appraisal land valuation methods using automated valuation models (AVM) based on international standards. In this context, this paper presents a spatial based linear hedonic price model which has been developed and tested in a case study land consolidation area in Cyprus. Results showed that the AVM is capable to produce acceptable in terms of accuracy and reliability land values and to reduce time hence cost required by around 80%.

  8. Models for residential-and commercial-sector energy conservation analysis: Applications, limitations, and future potential

    NASA Astrophysics Data System (ADS)

    Cole, H. E.; Fuller, R. E.

    1980-09-01

    Four of the major models used by DOE for energy conservation analyses in the residential and commercial building sectors are reviewed and critically analyzed to determine how these models can serve as tools for DOE and its Conservation Policy Office in evaluating and quantifying their policy and program requirements. The most effective role for each model in addressing future issues of buildings energy conservation policy and analysis is assessed. The four models covered are: Oak Ridge Residential Energy Model; Micro Analysis of Transfers to Households/Comprehensive Human Resources Data System (MATH/CHRDS) Model; Oak Ridge Commercial Energy Model; and Brookhaven Buildings Energy Conservation Optimization Model (BECOM).

  9. Advancing a Conceptual Model of Evidence-Based Practice Implementation in Public Service Sectors

    PubMed Central

    Hurlburt, Michael; Horwitz, Sarah McCue

    2010-01-01

    Implementation science is a quickly growing discipline. Lessons learned from business and medical settings are being applied but it is unclear how well they translate to settings with different historical origins and customs (e.g., public mental health, social service, alcohol/drug sectors). The purpose of this paper is to propose a multi-level, four phase model of the implementation process (i.e., Exploration, Adoption/Preparation, Implementation, Sustainment), derived from extant literature, and apply it to public sector services. We highlight features of the model likely to be particularly important in each phase, while considering the outer and inner contexts (i.e., levels) of public sector service systems. PMID:21197565

  10. Evapotranspiration: Progress in measurement and modeling in agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    As the water resources available for agriculture become limiting due to population growth, competition from other water users, drought and water quality degradation, the importance of evapotranspiration (ET) as a major component of water use in agriculture grows. This paper provides a focused survey...

  11. Agriflection: A Learning Model for Agricultural Extension in South Africa

    ERIC Educational Resources Information Center

    Worth, S. H.

    2006-01-01

    Prosperity--continuous and sustainable wealth creation--is an elusive goal in South African smallholder agriculture. This paper suggests that agricultural extension can facilitate realising this objective if an appropriate approach to extension can be developed. To develop such an approach requires that the definition of extension and the…

  12. Zoning of agricultural field using a fuzzy indicators model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Zoning of agricultural fields is an important task for utilization of precision farming technology. One method for deciding how to subdivide a field into a few relatively homogenous zones is using applications of fuzzy sets theory. Data collected from a precision agriculture study in central Texas...

  13. Exact cosmological solutions of models with an interacting dark sector

    NASA Astrophysics Data System (ADS)

    Pavan, A. B.; Ferreira, Elisa G. M.; Micheletti, Sandro M. R.; de Souza, J. C. C.; Abdalla, E.

    2012-11-01

    In this work we extend the first order formalism for cosmological models that present an interaction between a fermionic and a scalar field. Cosmological exact solutions describing universes filled with interacting dark energy and dark matter have been obtained. Viable cosmological solutions with an early period of decelerated expansion followed by late acceleration have been found, notably one which presents a dark matter component dominating in the past and a dark energy component dominating in the future. In another one, the dark energy alone is the responsible for both periods, similar to a Chaplygin gas case. Exclusively accelerating solutions have also been obtained.

  14. Extension of Standard Model in multi-spinor field formalism — Visible and dark sectors

    NASA Astrophysics Data System (ADS)

    Sogami, Ikuo S.

    2016-06-01

    With multi-spinor fields which behave as triple-tensor products of the Dirac spinors, the Standard Model is extended so as to embrace three families of ordinary quarks and leptons in the visible sector and an additional family of exotic quarks and leptons in the dark sector of our Universe. Apart from the gauge and Higgs fields of the Standard Model symmetry G, new gauge and Higgs fields of a symmetry isomorphic to G are postulated to exist in the dark sector. It is the bi-quadratic interaction between visible and dark Higgs fields that opens a main portal to the dark sector. Breakdowns of the visible and dark electroweak symmetries result in the Higgs boson with mass 125 GeV and a new boson which can be related to the diphoton excess around 750 GeV. Subsequent to a common inflationary phase and a reheating period, the visible and dark sectors follow weakly-interacting paths of thermal histories. We propose scenarios for dark matter in which no dark nuclear reaction takes place. A candidate for the main component of the dark matter is a stable dark hadron with spin 3/2, and the upper limit of its mass is estimated to be 15.1 GeV/c2.

  15. Disentangling dark sector models using weak lensing statistics

    NASA Astrophysics Data System (ADS)

    Giocoli, Carlo; Metcalf, R. Benton; Baldi, Marco; Meneghetti, Massimo; Moscardini, Lauro; Petkova, Margarita

    2015-09-01

    We perform multiplane ray tracing using the GLAMER gravitational lensing code within high-resolution light-cones extracted from the CoDECS simulations: a suite of cosmological runs featuring a coupling between dark energy and cold dark matter (CDM). We show that the presence of the coupling is evident not only in the redshift evolution of the normalization of the convergence power spectrum, but also in differences in non-linear structure formation with respect to ΛCDM. Using a tomographic approach under the assumption of a ΛCDM cosmology, we demonstrate that weak lensing measurements would result in a σ8 value that changes with the source redshift if the true underlying cosmology is a coupled dark energy (cDE) one. This provides a generic null test for these types of models. We also find that different models of cDE can show either an enhanced or a suppressed correlation between convergence maps with differing source redshifts as compared to ΛCDM. This would provide a direct way to discriminate between different possible realizations of the cDE scenario. Finally, we discuss the impact of the coupling on several lensing observables for different source redshifts and angular scales with realistic source redshift distributions for current ground-based and future space-based lensing surveys.

  16. Sector-Wide Transformational Leadership--How Effectively Is the EFQM Excellence Model[R] Used in the UK FE Sector?

    ERIC Educational Resources Information Center

    Cartmell, Jonathan; Binsardi, Ben; McLean, Alexis

    2011-01-01

    This seminal study investigates the use of the EFQM Excellence Model[R] in the UK Further Education sector. Following initial interviews with Senior Managers and Quality Consultants, an online survey was sent to Principals and Senior Managers in all Colleges across the UK to critically investigate the relationship between the use of the Model and…

  17. Transportation Sector Model of the National Energy Modeling System. Volume 1

    SciTech Connect

    1998-01-01

    This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. The NEMS Transportation Model comprises a series of semi-independent models which address different aspects of the transportation sector. The primary purpose of this model is to provide mid-term forecasts of transportation energy demand by fuel type including, but not limited to, motor gasoline, distillate, jet fuel, and alternative fuels (such as CNG) not commonly associated with transportation. The current NEMS forecast horizon extends to the year 2010 and uses 1990 as the base year. Forecasts are generated through the separate consideration of energy consumption within the various modes of transport, including: private and fleet light-duty vehicles; aircraft; marine, rail, and truck freight; and various modes with minor overall impacts, such as mass transit and recreational boating. This approach is useful in assessing the impacts of policy initiatives, legislative mandates which affect individual modes of travel, and technological developments. The model also provides forecasts of selected intermediate values which are generated in order to determine energy consumption. These elements include estimates of passenger travel demand by automobile, air, or mass transit; estimates of the efficiency with which that demand is met; projections of vehicle stocks and the penetration of new technologies; and estimates of the demand for freight transport which are linked to forecasts of industrial output. Following the estimation of energy demand, TRAN produces forecasts of vehicular emissions of the following pollutants by source: oxides of sulfur, oxides of nitrogen, total carbon, carbon dioxide, carbon monoxide, and volatile organic compounds.

  18. Vector field models of modified gravity and the dark sector

    NASA Astrophysics Data System (ADS)

    Zuntz, J.; Zlosnik, T. G.; Bourliot, F.; Ferreira, P. G.; Starkman, G. D.

    2010-05-01

    We present a comprehensive investigation of cosmological constraints on the class of vector field formulations of modified gravity called generalized Einstein-aether models. Using linear perturbation theory we generate cosmic microwave background and large-scale structure spectra for general parameters of the theory, and then constrain them in various ways. We investigate two parameter regimes: a dark matter candidate where the vector field sources structure formation, and a dark energy candidate where it causes late-time acceleration. We find that the dark matter candidate does not fit the data, and identify five physical problems that can restrict this and other theories of dark matter. The dark energy candidate does fit the data, and we constrain its fundamental parameters; most notably we find that the theory’s kinetic index parameter nae can differ significantly from its ΛCDM value.

  19. Vector field models of modified gravity and the dark sector

    SciTech Connect

    Zuntz, J.; Ferreira, P. G.; Zlosnik, T. G; Bourliot, F.; Starkman, G. D.

    2010-05-15

    We present a comprehensive investigation of cosmological constraints on the class of vector field formulations of modified gravity called generalized Einstein-aether models. Using linear perturbation theory we generate cosmic microwave background and large-scale structure spectra for general parameters of the theory, and then constrain them in various ways. We investigate two parameter regimes: a dark matter candidate where the vector field sources structure formation, and a dark energy candidate where it causes late-time acceleration. We find that the dark matter candidate does not fit the data, and identify five physical problems that can restrict this and other theories of dark matter. The dark energy candidate does fit the data, and we constrain its fundamental parameters; most notably we find that the theory's kinetic index parameter n{sub ae} can differ significantly from its {Lambda}CDM value.

  20. Culturally relevant model program to prevent and reduce agricultural injuries.

    PubMed

    Helitzer, D L; Hathorn, G; Benally, J; Ortega, C

    2014-07-01

    Limited research has explored pesticide injury prevention among American Indian farmers. In a five-year agricultural intervention, a university-community partnership, including the University of New Mexico School of Medicine, New Mexico State University, Shiprock Area Cooperative Extension Service, and Navajo Nation communities, used a culturally relevant model to introduce and maintain safe use of integrated pest management techniques. We applied the Diffusion of Innovations theory and community-based approaches to tailor health promotion strategies for our intervention. In a longitudinal study with repeated measures, we trained six "model farmers" to be crop management experts in pesticide safety, application, and control. Subsequently, these model farmers worked with 120 farm families randomized into two groups: intervention (Group 1) and delayed intervention (Group 2). Measurements included a walk-through analysis, test of knowledge and attitudes, and yield analysis. Both groups demonstrated improvements in pesticide storage behaviors after training. Test scores regarding safety practices improved significantly: from 57.3 to 72.4 for Group 1 and from 52.6 to 76.3 for Group 2. Group 1 maintained their knowledge and safety practices after the intervention. Attitudes about pesticides and communication of viewpoints changed across the study years. With pesticides and fertilizer, the number of corn ears increased by 56.3% and yield (kg m(-2)) of alfalfa increased by 41.2%. The study combined traditional farming practices with culturally relevant approaches and behavior change theory to affect knowledge, safety practices, attitudes, communication channels, and crop yield. Storage behaviors, use of pesticides and safety and application equipment, and safety practice knowledge changed significantly, as did attitudes about social networking, social support, and the compatibility and relative advantage of pesticides for farms. PMID:25174150

  1. Extended Standard Model in multi-spinor field formalism: Visible and dark sectors

    NASA Astrophysics Data System (ADS)

    Sogami, Ikuo S.

    2013-12-01

    To generalize the Standard Model so as to include dark matter, we formulate a theory of multi-spinor fields on the basis of an algebra that consists of triple-tensor products of elements of the Dirac algebra. Chiral combinations of multi-spinor fields form reducible representations of the Lorentz group possessing component fields with spin 1/2, which we interpret as expressing three ordinary families and an additional fourth family of quarks and leptons. Apart from the gauge and Higgs fields of the Standard Model interacting with the fermions of the three ordinary families, we assume the existence of additional gauge and Higgs fields interacting exclusively with the fermions of the fourth family. While the fields of the Standard Model organize the "visible sector" of our universe, the fields related with the fourth family are presumed to generate a "dark sector" that can contain dark matter. The two sectors possess a channel of communication through the bi-quadratic interaction between visible and dark Higgs fields. After experiencing a common inflationary phase, the two sectors follow a reheating period and weak-coupling paths of thermal histories. We propose scenarios for dark matter that have a tendency to take relatively broad interstellar distributions and examine methods for the detection of the main candidate particles of dark matter. The exchange of superposed fields of the visible and dark Higgs bosons induces weak reaction processes between the fields of the visible and dark sectors, which enables us to have a glimpse of the dark sector.

  2. Estimating NH3 emissions from agricultural fertilizer application in China using the bi-directional CMAQ model coupled to an agro-ecosystem model

    NASA Astrophysics Data System (ADS)

    Fu, X.; Wang, S. X.; Ran, L. M.; Pleim, J. E.; Cooter, E.; Bash, J. O.; Benson, V.; Hao, J. M.

    2015-06-01

    Atmospheric ammonia (NH3) plays an important role in atmospheric aerosol chemistry. China is one of the largest NH3 emitting countries with the majority of NH3 emissions coming from agricultural practices, such as fertilizer application and livestock production. The current NH3 emission estimates in China are mainly based on pre-defined emission factors that lack temporal or spatial details, which are needed to accurately predict NH3 emissions. This study provides the first online estimate of NH3 emissions from agricultural fertilizer application in China, using an agricultural fertilizer modeling system which couples a regional air quality model (the Community Multi-scale Air Quality model, or CMAQ) and an agro-ecosystem model (the Environmental Policy Integrated Climate model, or EPIC). This method improves the spatial and temporal resolution of NH3 emissions from this sector. We combined the cropland area data of 14 crops from 2710 counties with the Moderate Resolution Imaging Spectroradiometer (MODIS) land use data to determine the crop distribution. The fertilizer application rates and methods for different crops were collected at provincial or agricultural region levels. The EPIC outputs of daily fertilizer application and soil characteristics were input into the CMAQ model and the hourly NH3 emissions were calculated online with CMAQ running. The estimated agricultural fertilizer NH3 emissions in this study were approximately 3 Tg in 2011. The regions with the highest modeled emission rates are located in the North China Plain. Seasonally, peak ammonia emissions occur from April to July. Compared with previous researches, this study considers an increased number of influencing factors, such as meteorological fields, soil and fertilizer application, and provides improved NH3 emissions with higher spatial and temporal resolution.

  3. Modeling Financial Innovation and Economic Growth: Why the Financial Sector Matters to the Real Economy

    ERIC Educational Resources Information Center

    Chou, Yuan K.

    2007-01-01

    The author devises a simple way of incorporating the financial sector into a growth model that is pedagogically useful. Financial innovation raises the efficiency of financial intermediation by increasing the variety of financial products and services, resulting in improved matching of the needs of individual savers with those of firms raising…

  4. Modelling Approach to Assess Future Agricultural Water Demand

    NASA Astrophysics Data System (ADS)

    Spano, D.; Mancosu, N.; Orang, M.; Sarreshteh, S.; Snyder, R. L.

    2013-12-01

    The combination of long-term climate changes (e.g., warmer average temperatures) and extremes events (e.g., droughts) can have decisive impacts on water demand, with further implications on the ecosystems. In countries already affected by water scarcity, water management problems are becoming increasingly serious. The sustainable management of available water resources at the global, regional, and site-specific level is necessary. In agriculture, the first step is to compute how much water is needed by crops in regards to climate conditions. Modelling approach can be a way to compute crop water requirement (CWR). In this study, the improved version of the SIMETAW model was used. The model is a user friendly soil water balance model, developed by the University of California, Davis, the California Department of Water Resource, and the University of Sassari. The SIMETAW# model assesses CWR and generates hypothetical irrigation scheduling for a wide range of irrigated crops experiencing full, deficit, or no irrigation. The model computes the evapotranspiration of the applied water (ETaw), which is the sum of the net amount of irrigation water needed to match losses due to the crop evapotranspiration (ETc). ETaw is determined by first computing reference evapotranspiration (ETo) using the daily standardized Reference Evapotranspiration equation. ETaw is computed as ETaw = CETc - CEr, where CETc and CE are the cumulative total crop ET and effective rainfall values, respectively. Crop evapotranspiration is estimated as ETc = ETo x Kc, where Kc is the corrected midseason tabular crop coefficient, adjusted for climate conditions. The net irrigation amounts are determined from a daily soil water balance, using an integrated approach that considers soil and crop management information, and the daily ETc estimates. Using input information on irrigation system distribution uniformity and runoff, when appropriate, the model estimates the applied water to the low quarter of the

  5. Inter-sectoral comparison of model uncertainty of climate change impacts in Africa

    NASA Astrophysics Data System (ADS)

    van Griensven, Ann; Vetter, Tobias; Piontek, Franzisca; Gosling, Simon N.; Kamali, Bahareh; Reinhardt, Julia; Dinkneh, Aklilu; Yang, Hong; Alemayehu, Tadesse

    2016-04-01

    We present the model results and their uncertainties of an inter-sectoral impact model inter-comparison initiative (ISI-MIP) for climate change impacts in Africa. The study includes results on hydrological, crop and health aspects. The impact models used ensemble inputs consisting of 20 time series of daily rainfall and temperature data obtained from 5 Global Circulation Models (GCMs) and 4 Representative concentration pathway (RCP). In this study, we analysed model uncertainty for the Regional Hydrological Models, Global Hydrological Models, Malaria models and Crop models. For the regional hydrological models, we used 2 African test cases: the Blue Nile in Eastern Africa and the Niger in Western Africa. For both basins, the main sources of uncertainty are originating from the GCM and RCPs, while the uncertainty of the regional hydrological models is relatively low. The hydrological model uncertainty becomes more important when predicting changes on low flows compared to mean or high flows. For the other sectors, the impact models have the largest share of uncertainty compared to GCM and RCP, especially for Malaria and crop modelling. The overall conclusion of the ISI-MIP is that it is strongly advised to use ensemble modeling approach for climate change impact studies throughout the whole modelling chain.

  6. An optimization model to agroindustrial sector in antioquia (Colombia, South America)

    NASA Astrophysics Data System (ADS)

    Fernandez, J.

    2015-06-01

    This paper develops a proposal of a general optimization model for the flower industry, which is defined by using discrete simulation and nonlinear optimization, whose mathematical models have been solved by using ProModel simulation tools and Gams optimization. It defines the operations that constitute the production and marketing of the sector, statistically validated data taken directly from each operation through field work, the discrete simulation model of the operations and the linear optimization model of the entire industry chain are raised. The model is solved with the tools described above and presents the results validated in a case study.

  7. Analysis of the industrial sector representation in the Fossil2 energy-economic model

    SciTech Connect

    Wise, M.A.; Woodruff, M.G.; Ashton, W.B.

    1992-08-01

    The Fossil2 energy-economic model is used by the US Department of Energy (DOE) for a variety of energy and environmental policy analyses. A number of improvements to the model are under way or are being considered. This report was prepared by the Pacific Northwest Laboratory (PNL) to provide a clearer understanding of the current industrial sector module of Fossil2 and to explore strategies for improving it. The report includes a detailed description of the structure and decision logic of the industrial sector module, along with results from several simulation exercises to demonstrate the behavior of the module in different policy scenarios and under different values of key model parameters. The cases were run with the Fossil2 model at PNL using the National Energy Strategy Actions Case of 1991 as the point of departure. The report also includes a discussion of suggested industrial sector module improvements. These improvements include changes in the way the current model is used; on- and off-line adjustments to some of the model`s parameters; and significant changes to include more detail on the industrial processes, technologies, and regions of the country being modeled. The potential benefits and costs of these changes are also discussed.

  8. Fast community detection based on sector edge aggregation metric model in hyperbolic space

    NASA Astrophysics Data System (ADS)

    Wang, Zuxi; Li, Qingguang; Xiong, Wei; Jin, Fengdong; Wu, Yao

    2016-06-01

    By studying the edge aggregation characteristic of nodes in hyperbolic space, Sector Edge Aggregation Metric (SEAM) model is proposed and theoretically proved in this paper. In hyperbolic disk SEAM model determines the minimum angular range of a sector which possesses the maximal edge aggregation of nodes. The set of nodes within such sector has dense internal links, which corresponds with the characteristic of community structure. Based on SEAM model, we propose a fast community detection algorithm called Greedy Optimization Modularity Algorithm (GOMA) which employs greedy optimization strategy and hyperbolic coordinates. GOMA firstly divides initial communities according to the quantitative results of sector edge aggregation given by SEAM and the nodes' hyperbolic coordinates, then based on greedy optimization strategy, only merges the two angular neighboring communities in hyperbolic disk to optimize the network modularity function, and consequently obtains high-quality community detection. The strategies of initial community partition and merger in hyperbolic space greatly improve the speed of searching the most optimal modularity. Experimental results indicate that GOMA is able to detect out high-quality community structure in synthetic and real networks, and performs better when applied to the large-scale and dense networks with strong clustering.

  9. Transport Sector Marginal Abatement Cost Curves in Computable General Equilibrium Model

    NASA Astrophysics Data System (ADS)

    Tippichai, Atit; Fukuda, Atsushi; Morisugi, Hisayoshi

    In the last decade, computable general equilibrium (CGE) models have emerged a standard tool for climate policy evaluation due to their abilities to prospectively elucidate the character and magnitude of the economic impacts of energy and environmental policies. Furthermore, marginal abatement cost (MAC) curves which represent GHG emissions reduction potentials and costs can be derived from these top-down economic models. However, most studies have never address MAC curves for a specific sector that have a large coverage of countries which are needed for allocation of optimal emission reductions. This paper aims to explicitly describe the meaning and character of MAC curves for transport sector in a CGE context through using the AIM/CGE Model developed by Toshihiko Masui. It found that the MAC curves derived in this study are the inverse of the general equilibrium reduction function for CO2 emissions. Moreover, the transport sector MAC curves for six regions including USA, EU-15, Japan, China, India, and Brazil, derived from this study are compared to the reduction potentials under 100 USD/tCO2 in 2020 from a bottom-up study. The results showed that the ranking of the regional reduction potentials in transport sector from this study are almost same with the bottom-up study except the ranks of the EU-15 and China. In addition, the range of the reduction potentials from this study is wider and only the USA has higher potentials than those derived from the bottom-up study.

  10. Model-independent indirect detection constraints on hidden sector dark matter

    NASA Astrophysics Data System (ADS)

    Elor, Gilly; Rodd, Nicholas L.; Slatyer, Tracy R.; Xue, Wei

    2016-06-01

    If dark matter inhabits an expanded ``hidden sector'', annihilations may proceed through sequential decays or multi-body final states. We map out the potential signals and current constraints on such a framework in indirect searches, using a model-independent setup based on multi-step hierarchical cascade decays. While remaining agnostic to the details of the hidden sector model, our framework captures the generic broadening of the spectrum of secondary particles (photons, neutrinos, e+e‑ and bar p p) relative to the case of direct annihilation to Standard Model particles. We explore how indirect constraints on dark matter annihilation limit the parameter space for such cascade/multi-particle decays. We investigate limits from the cosmic microwave background by Planck, the Fermi measurement of photons from the dwarf galaxies, and positron data from AMS-02. The presence of a hidden sector can change the constraints on the dark matter by up to an order of magnitude in either direction (although the effect can be much smaller). We find that generally the bound from the Fermi dwarfs is most constraining for annihilations to photon-rich final states, while AMS-02 is most constraining for electron and muon final states; however in certain instances the CMB bounds overtake both, due to their approximate independence on the details of the hidden sector cascade. We provide the full set of cascade spectra considered here as publicly available code with examples at http://web.mit.edu/lns/research/CascadeSpectra.html.

  11. Analysis of the industrial sector representation in the Fossil2 energy-economic model

    SciTech Connect

    Wise, M.A.; Woodruff, M.G.; Ashton, W.B.

    1992-08-01

    The Fossil2 energy-economic model is used by the US Department of Energy (DOE) for a variety of energy and environmental policy analyses. A number of improvements to the model are under way or are being considered. This report was prepared by the Pacific Northwest Laboratory (PNL) to provide a clearer understanding of the current industrial sector module of Fossil2 and to explore strategies for improving it. The report includes a detailed description of the structure and decision logic of the industrial sector module, along with results from several simulation exercises to demonstrate the behavior of the module in different policy scenarios and under different values of key model parameters. The cases were run with the Fossil2 model at PNL using the National Energy Strategy Actions Case of 1991 as the point of departure. The report also includes a discussion of suggested industrial sector module improvements. These improvements include changes in the way the current model is used; on- and off-line adjustments to some of the model's parameters; and significant changes to include more detail on the industrial processes, technologies, and regions of the country being modeled. The potential benefits and costs of these changes are also discussed.

  12. A Conceptual Model of Intrapreneurship in the Iranian Agricultural Extension Organization: Implications for HRD

    ERIC Educational Resources Information Center

    Karimi, Asef; Malekmohamadi, Iraj; Daryani, Mahmoud Ahmadpour; Rezvanfar, Ahmad

    2011-01-01

    Purpose: This study seeks to build a conceptual model of agricultural extension intrapreneurship that discusses the concept and phenomenon of intrapreneurship as well as its prerequisites and outcomes. The proposed model is intended to depict the main factors that affect the phenomena of intrapreneurship within the agricultural extension…

  13. Model Course of Study for Agricultural Programs in Iowa. Preparing for the Future.

    ERIC Educational Resources Information Center

    Martin, Robert A.; And Others

    Each section contained in this packet is necessary for designing an effective program of agriculture education. The curriculum guide that is developed from this model should include the same sections. The model includes: (1) community description; (2) school description; (3) goals and objectives of education in agriculture; (4) evaluation policy;…

  14. Modeling irrigation-based climate change adaptation in agriculture: Model development and evaluation in Northeast China

    NASA Astrophysics Data System (ADS)

    Okada, Masashi; Iizumi, Toshichika; Sakurai, Gen; Hanasaki, Naota; Sakai, Toru; Okamoto, Katsuo; Yokozawa, Masayuki

    2015-09-01

    Replacing a rainfed cropping system with an irrigated one is widely assumed to be an effective measure for climate change adaptation. However, many agricultural impact studies have not necessarily accounted for the space-time variations in the water availability under changing climate and land use. Moreover, many hydrologic and agricultural assessments of climate change impacts are not fully integrated. To overcome this shortcoming, a tool that can simultaneously simulate the dynamic interactions between crop production and water resources in a watershed is essential. Here we propose the regional production and circulation coupled model (CROVER) by embedding the PRYSBI-2 (Process-based Regional Yield Simulator with Bayesian Inference version 2) large-area crop model into the global water resources model (called H08), and apply this model to the Songhua River watershed in Northeast China. The evaluation reveals that the model's performance in capturing the major characteristics of historical change in surface soil moisture, river discharge, actual crop evapotranspiration, and soybean yield relative to the reference data during the interval 1979-2010 is satisfactory accurate. The simulation experiments using the model demonstrated that subregional irrigation management, such as designating the area to which irrigation is primarily applied, has measurable influences on the regional crop production in a drought year. This finding suggests that reassessing climate change risk in agriculture using this type of modeling is crucial not to overestimate potential of irrigation-based adaptation.

  15. Collaborative evaluation and market research converge: an innovative model agricultural development program evaluation in Southern Sudan.

    PubMed

    O'Sullivan, John M; O'Sullivan, Rita

    2012-11-01

    In June and July 2006 a team of outside experts arrived in Yei, Southern Sudan through an AID project to provide support to a local agricultural development project. The team brought evaluation, agricultural marketing and financial management expertise to the in-country partners looking at steps to rebuild the economy of the war ravaged region. A partnership of local officials, agricultural development staff, and students worked with the outside team to craft a survey of agricultural traders working between northern Uganda and Southern Sudan the steps approach of a collaborative model. The goal was to create a market directory of use to producers, government officials and others interested in stimulating agricultural trade. The directory of agricultural producers and distributors served as an agricultural development and promotion tool as did the collaborative process itself. PMID:22309968

  16. Land use efficiency: anticipating future demand for land-sector greenhouse gas emissions abatement and managing trade-offs with agriculture, water, and biodiversity.

    PubMed

    Bryan, Brett A; Crossman, Neville D; Nolan, Martin; Li, Jing; Navarro, Javier; Connor, Jeffery D

    2015-11-01

    Competition for land is increasing, and policy needs to ensure the efficient supply of multiple ecosystem services from land systems. We modelled the spatially explicit potential future supply of ecosystem services in Australia's intensive agricultural land in response to carbon markets under four global outlooks from 2013 to 2050. We assessed the productive efficiency of greenhouse gas emissions abatement, agricultural production, water resources, and biodiversity services and compared these to production possibility frontiers (PPFs). While interacting commodity markets and carbon markets produced efficient outcomes for agricultural production and emissions abatement, more efficient outcomes were possible for water resources and biodiversity services due to weak price signals. However, when only two objectives were considered as per typical efficiency assessments, efficiency improvements involved significant unintended trade-offs for the other objectives and incurred substantial opportunity costs. Considering multiple objectives simultaneously enabled the identification of land use arrangements that were efficient over multiple ecosystem services. Efficient land use arrangements could be selected that meet society's preferences for ecosystem service provision from land by adjusting the metric used to combine multiple services. To effectively manage competition for land via land use efficiency, market incentives are needed that effectively price multiple ecosystem services. PMID:26147156

  17. Long-term Industrial Energy Forecasting (LIEF) model (18-sector version)

    SciTech Connect

    Ross, M.H.; Thimmapuram, P.; Fisher, R.E.; Maciorowski, W.

    1993-05-01

    The new 18-sector Long-term Industrial Energy Forecasting (LIEF) model is designed for convenient study of future industrial energy consumption, taking into account the composition of production, energy prices, and certain kinds of policy initiatives. Electricity and aggregate fossil fuels are modeled. Changes in energy intensity in each sector are driven by autonomous technological improvement (price-independent trend), the opportunity for energy-price-sensitive improvements, energy price expectations, and investment behavior. Although this decision-making framework involves more variables than the simplest econometric models, it enables direct comparison of an econometric approach with conservation supply curves from detailed engineering analysis. It also permits explicit consideration of a variety of policy approaches other than price manipulation. The model is tested in terms of historical data for nine manufacturing sectors, and parameters are determined for forecasting purposes. Relatively uniform and satisfactory parameters are obtained from this analysis. In this report, LIEF is also applied to create base-case and demand-side management scenarios to briefly illustrate modeling procedures and outputs.

  18. Landuse and agricultural management practice web-service (LAMPS) for agroecosystem modeling and conservation planning

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Agroecosystem models and conservation planning tools require spatially and temporally explicit input data about agricultural management operations. The USDA Natural Resources Conservation Service is developing a Land Management and Operation Database (LMOD) which contains potential model input, howe...

  19. Using historical and projected future climate model simulations as drivers of agricultural and biological models (Invited)

    NASA Astrophysics Data System (ADS)

    Stefanova, L. B.

    2013-12-01

    Climate model evaluation is frequently performed as a first step in analyzing climate change simulations. Atmospheric scientists are accustomed to evaluating climate models through the assessment of model climatology and biases, the models' representation of large-scale modes of variability (such as ENSO, PDO, AMO, etc) and the relationship between these modes and local variability (e.g. the connection between ENSO and the wintertime precipitation in the Southeast US). While these provide valuable information about the fidelity of historical and projected climate model simulations from an atmospheric scientist's point of view, the application of climate model data to fields such as agriculture, ecology and biology may require additional analyses focused on the particular application's requirements and sensitivities. Typically, historical climate simulations are used to determine a mapping between the model and observed climate, either through a simple (additive for temperature or multiplicative for precipitation) or a more sophisticated (such as quantile matching) bias correction on a monthly or seasonal time scale. Plants, animals and humans however are not directly affected by monthly or seasonal means. To assess the impact of projected climate change on living organisms and related industries (e.g. agriculture, forestry, conservation, utilities, etc.), derivative measures such as the heating degree-days (HDD), cooling degree-days (CDD), growing degree-days (GDD), accumulated chill hours (ACH), wet season onset (WSO) and duration (WSD), among others, are frequently useful. We will present a comparison of the projected changes in such derivative measures calculated by applying: (a) the traditional temperature/precipitation bias correction described above versus (b) a bias correction based on the mapping between the historical model and observed derivative measures themselves. In addition, we will present and discuss examples of various application-based climate

  20. Water-Constrained Electric Sector Capacity Expansion Modeling Under Climate Change Scenarios

    NASA Astrophysics Data System (ADS)

    Cohen, S. M.; Macknick, J.; Miara, A.; Vorosmarty, C. J.; Averyt, K.; Meldrum, J.; Corsi, F.; Prousevitch, A.; Rangwala, I.

    2015-12-01

    Over 80% of U.S. electricity generation uses a thermoelectric process, which requires significant quantities of water for power plant cooling. This water requirement exposes the electric sector to vulnerabilities related to shifts in water availability driven by climate change as well as reductions in power plant efficiencies. Electricity demand is also sensitive to climate change, which in most of the United States leads to warming temperatures that increase total cooling-degree days. The resulting demand increase is typically greater for peak demand periods. This work examines the sensitivity of the development and operations of the U.S. electric sector to the impacts of climate change using an electric sector capacity expansion model that endogenously represents seasonal and local water resource availability as well as climate impacts on water availability, electricity demand, and electricity system performance. Capacity expansion portfolios and water resource implications from 2010 to 2050 are shown at high spatial resolution under a series of climate scenarios. Results demonstrate the importance of water availability for future electric sector capacity planning and operations, especially under more extreme hotter and drier climate scenarios. In addition, region-specific changes in electricity demand and water resources require region-specific responses that depend on local renewable resource availability and electricity market conditions. Climate change and the associated impacts on water availability and temperature can affect the types of power plants that are built, their location, and their impact on regional water resources.

  1. Model documentation report: Transportation sector model of the National Energy Modeling System

    SciTech Connect

    Not Available

    1994-03-01

    This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. This document serves three purposes. First, it is a reference document providing a detailed description of TRAN for model analysts, users, and the public. Second, this report meets the legal requirements of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports (Public Law 93-275, 57(b)(1)). Third, it permits continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

  2. Vezimfilho: a model for health sector response to gender violence in South Africa.

    PubMed

    Jacobs, Tanya; Jewkes, Rachel

    2002-09-01

    Vezimfilho, a model program for the training of health care workers was developed, implemented and evaluated in close collaboration with government and non-government partners in South Africa. It was implemented and evaluated in two districts in the Eastern Cape and Western Cape provinces, respectively. This initiative represents one of the first attempts to build capacity in the health sector to address gender-based violence and has been a leading example of how to address within the South African context. Outputs have been the development of a model for the health sector response to gender violence, a training package Vezimfilho! and a partnership with the Department of Health to address the sustained integration of capacity building in this area. PMID:12429439

  3. Optimal control problem for the three-sector economic model of a cluster

    NASA Astrophysics Data System (ADS)

    Murzabekov, Zainel; Aipanov, Shamshi; Usubalieva, Saltanat

    2016-08-01

    The problem of optimal control for the three-sector economic model of a cluster is considered. Task statement is to determine the optimal distribution of investment and manpower in moving the system from a given initial state to desired final state. To solve the optimal control problem with finite-horizon planning, in case of fixed ends of trajectories, with box constraints, the method of Lagrange multipliers of a special type is used. This approach allows to represent the desired control in the form of synthesis control, depending on state of the system and current time. The results of numerical calculations for an instance of three-sector model of the economy show the effectiveness of the proposed method.

  4. Groundwater Modeling for the Southern Sector of A/M Area

    SciTech Connect

    HARRIS, MARYK.

    2001-11-01

    A plume of TCE contamination in the Southern Sector of A/M Area appears to have resulted from a former release at the A-014 outfall. A numerical groundwater flow and transport modeling analysis is described that addresses this plume, the existing remedial actions, and potential future remedial actions. The numerical flow and transport model is based on an understanding of the site that is formed in part by a recent analysis of hydrostratigraphic, head, and chemical data and by a recent groundwater flow modeling analysis that covers a wider area. The numerical model is calibrated to match observed water level measurements within acceptable criteria. The model is also qualitatively calibrated against the observed/inferred shape of the Southern Sector TCE plume. Though the calibration to the observed TCE plume is not perfect, the model is acceptable for comparing various remedial alternatives. Model simulations indicate that the existing remedial wells, which have been in operation near the A-014 outfall for over ten years, have been effective at removing much of the TCE plume mass. These wells should continue to be effective if operated. The model that is developed and used here can be used in the future to compare remedial alternatives and can be used as a tool to help optimize the operation of various remedial systems. The model may be improved in the future by recalibration following a revised interpretation of the source and/or the TCE plume.

  5. ISTUM PC: industrial sector technology use model for the IBM-PC

    SciTech Connect

    Roop, J.M.; Kaplan, D.T.

    1984-09-01

    A project to improve and enhance the Industrial Sector Technology Use Model (ISTUM) was originated in the summer of 1983. The project had dix identifiable objectives: update the data base; improve run-time efficiency; revise the reference base case; conduct case studies; provide technical and promotional seminars; and organize a service bureau. This interim report describes which of these objectives have been met and which tasks remain to be completed. The most dramatic achievement has been in the area of run-time efficiency. From a model that required a large proportion of the total resources of a mainframe computer and a great deal of effort to operate, the current version of the model (ISTUM-PC) runs on an IBM Personal Computer. The reorganization required for the model to run on a PC has additional advantages: the modular programs are somewhat easier to understand and the data base is more accessible and easier to use. A simple description of the logic of the model is given in this report. To generate the necessary funds for completion of the model, a multiclient project is proposed. This project will extend the industry coverage to all the industrial sectors, including the construction of process flow models for chemicals and petroleum refining. The project will also calibrate this model to historical data and construct a base case and alternative scenarios. The model will be delivered to clients and training provided. 2 references, 4 figures, 3 tables.

  6. The Global 2000 Report to the President. Volume Three. Documentation on the Government's Global Sectoral Models: The Government's "Global Model."

    ERIC Educational Resources Information Center

    Barney, Gerald O., Ed.

    The third volume of the Global 2000 study presents basic information ("documentation") on the long-term sectoral models used by the U.S. government to project global trends in population, resources, and the environment. Its threefold purposes are: (1) to present all this basic information in a single volume, (2) to provide an explanation, in the…

  7. A New Extension Model: The Memorial Middle School Agricultural Extension and Education Center

    ERIC Educational Resources Information Center

    Skelton, Peter; Seevers, Brenda

    2010-01-01

    The Memorial Middle School Agricultural Extension and Education Center is a new model for Extension. The center applies the Cooperative Extension Service System philosophy and mission to developing public education-based programs. Programming primarily serves middle school students and teachers through agricultural and natural resource science…

  8. Exploring Agricultural Production Systems and Their Fundmental Components With Dynamic Modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Agriculture is changing due to transitions in consumer demands, input costs, and concerns for food safety and the environment. Agricultural systems are comprised of multidimensional components, are quantitative and qualitative, and interact in complex ways. We developed a dynamic modeling environmen...

  9. Curriculum Guidelines for a Distance Education Course in Urban Agriculture Based on an Eclectic Model.

    ERIC Educational Resources Information Center

    Gaum, Wilma G.; van Rooyen, Hugo G.

    1997-01-01

    Describes research to develop curriculum guidelines for a distance education course in urban agriculture. The course, designed to train the teacher, is based on an eclectic curriculum design model. The course is aimed at the socioeconomic empowerment of urban farmers and is based on sustainable ecological-agricultural principles, an…

  10. State of science of phosphorus modeling in tile drained agricultural systems using APEX

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Phosphorus losses through tile drained systems in agricultural landscapes may be causing the persistent eutrophication problems observed in surface water. The purpose of this paper is to evaluate the state of the science in the Agricultural Policy/Environmental eXtender (APEX) model related to surf...

  11. Model documentation report: Transportation sector model of the National Energy Modeling System

    SciTech Connect

    1997-02-01

    Over the past year, several modifications have been made to the NEMS Transportation Model, incorporating greater levels of detail and analysis in modules previously represented in the aggregate or under a profusion of simplifying assumptions. This document is intended to amend those sections of the Model Documentation Report (MDR) which describe these superseded modules. Significant changes have been implemented in the LDV Fuel Economy Model, the Alternative Fuel Vehicle Model, the LDV Fleet Module, and the Highway Freight Model. The relevant sections of the MDR have been extracted from the original document, amended, and are presented in the following pages. A brief summary of the modifications follows: In the Fuel Economy Model, modifications have been made which permit the user to employ more optimistic assumptions about the commercial viability and impact of selected technological improvements. This model also explicitly calculates the fuel economy of an array of alternative fuel vehicles (AFV`s) which are subsequently used in the estimation of vehicle sales. In the Alternative Fuel Vehicle Model, the results of the Fuel Economy Model have been incorporated, and the program flows have been modified to reflect that fact. In the Light Duty Vehicle Fleet Module, the sales of vehicles to fleets of various size are endogenously calculated in order to provide a more detailed estimate of the impacts of EPACT legislation on the sales of AFV`s to fleets. In the Highway Freight Model, the previous aggregate estimation has been replaced by a detailed Freight Truck Stock Model, where travel patterns, efficiencies, and energy intensities are estimated by industrial grouping. Several appendices are provided at the end of this document, containing data tables and supplementary descriptions of the model development process which are not integral to an understanding of the overall model structure.

  12. The relationship between carbon dioxide and agriculture in Ghana: a comparison of VECM and ARDL model.

    PubMed

    Asumadu-Sarkodie, Samuel; Owusu, Phebe Asantewaa

    2016-06-01

    In this paper, the relationship between carbon dioxide and agriculture in Ghana was investigated by comparing a Vector Error Correction Model (VECM) and Autoregressive Distributed Lag (ARDL) Model. Ten study variables spanning from 1961 to 2012 were employed from the Food Agricultural Organization. Results from the study show that carbon dioxide emissions affect the percentage annual change of agricultural area, coarse grain production, cocoa bean production, fruit production, vegetable production, and the total livestock per hectare of the agricultural area. The vector error correction model and the autoregressive distributed lag model show evidence of a causal relationship between carbon dioxide emissions and agriculture; however, the relationship decreases periodically which may die over-time. All the endogenous variables except total primary vegetable production lead to carbon dioxide emissions, which may be due to poor agricultural practices to meet the growing food demand in Ghana. The autoregressive distributed lag bounds test shows evidence of a long-run equilibrium relationship between the percentage annual change of agricultural area, cocoa bean production, total livestock per hectare of agricultural area, total pulses production, total primary vegetable production, and carbon dioxide emissions. It is important to end hunger and ensure people have access to safe and nutritious food, especially the poor, orphans, pregnant women, and children under-5 years in order to reduce maternal and infant mortalities. Nevertheless, it is also important that the Government of Ghana institutes agricultural policies that focus on promoting a sustainable agriculture using environmental friendly agricultural practices. The study recommends an integration of climate change measures into Ghana's national strategies, policies and planning in order to strengthen the country's effort to achieving a sustainable environment. PMID:26898935

  13. ELICITED EXPERT PERCEPTIONS FOR CLIMATE CHANGE RISKS AND ADAPTATION IN AGRICULTURE AND FOOD PRODUCTION THROUGH MENTAL MODELS APPROACH

    NASA Astrophysics Data System (ADS)

    Suda, Eiko; Kubota, Hiromi; Baba, Kenshi; Hijioka, Yasuaki; Takahashi, Kiyoshi; Hanasaki, Naota

    Impacts of climate change have become obvious in agriculture and food production in Japan these days, and researches to adapt to their risks have been conducted as a key effort to cope with the climate change. Numerous scientific findings on climate change impacts have been presented so far; however, prospective risks to be adapted to and their management in the context of individual on-site situations have not been investigated in detail. The structure of climate change risks and their management vary depending on geographical and social features in the regions where the adaptation options should be applied; therefore, a practical adaptation strategy should consider actual on-site situations. This study intended to clarify climate change risks to be adapted to in the Japanese agricultural sector, and factors to be considered in adaptation options, for encouragement of decision-making on adaptation implementation in the field. Semi-structured individual interviews have been conducted with 9 multidisciplinary experts engaging in climate change impacts research in agricultural production, economics, engineering, policy, and so on. Based on the results of the interviews, and the latest literatures available for risk assessment and adaptation, an expert mental model including their perceptions which cover the process from climate change impacts assessment to adaptation has been developed. The prospective risks, adaptation options, and issues to be examined to progress the development of practical and effective adaptation options and to support individual or social decision-making, have been shown on the developed expert mental model. It is the basic information for developing social communication and stakeholders cooperations in climate change adaptation strategies in agriculture and food production in Japan.

  14. Modelling and analysis of inventory replenishment for perishable agricultural products with buyer-seller collaboration

    NASA Astrophysics Data System (ADS)

    Shen, Dongjie; Lai, K. K.; Leung, Stephen C. H.; Liang, Liang

    2011-07-01

    In this article, we study the inventory replenishment model for perishable agricultural products in a simple two-level supply chain. Collaborative forecasting is introduced into the inventory replenishment decisions to avoid overstocking and understocking of agricultural products, and to maximise profits. We analyse the model with ordering cost, holding cost, shortage cost, deterioration cost and opportunity lost cost of perishable agricultural products. Extensive numerical analysis is carried out to study the performance of the inventory policy. The optimal replenishment policy that minimises the total cost can be obtained from the model. It has demonstrated that the supply chain cost decreases with supplier and retailer's collaborative forecasting.

  15. Variation of the NMVOC speciation in the solvent sector and the sensitivity of modelled tropospheric ozone

    NASA Astrophysics Data System (ADS)

    von Schneidemesser, E.; Coates, J.; Denier van der Gon, H. A. C.; Visschedijk, A. J. H.; Butler, T. M.

    2016-06-01

    Non-methane volatile organic compounds (NMVOCs) are detrimental to human health owing to the toxicity of many of the NMVOC species, as well as their role in the formation of secondary air pollutants such as tropospheric ozone (O3) and secondary organic aerosol. The speciation and amount of NMVOCs emitted into the troposphere are represented in emission inventories (EIs) for input to chemical transport models that predict air pollutant levels. Much of the information in EIs pertaining to speciation of NMVOCs is likely outdated, but before taking on the task of providing an up-to-date and highly speciated EI, a better understanding of the sensitivity of models to the change in NMVOC input would be highly beneficial. According to the EIs, the solvent sector is the most important sector for NMVOC emissions. Here, the sensitivity of modelled tropospheric O3 to NMVOC emission inventory speciation was investigated by comparing the maximum potential difference in O3 produced using a variety of reported solvent sector EI speciations in an idealized study using a box model. The sensitivity was tested using three chemical mechanisms that describe O3 production chemistry, typically employed for different types of modelling scales - point (MCM v3.2), regional (RADM2), and global (MOZART-4). In the box model simulations, a maximum difference of 15 ppbv (ca. 22% of the mean O3 mixing ratio of 69 ppbv) between the different EI speciations of the solvent sector was calculated. In comparison, for the same EI speciation, but comparing the three different mechanisms, a maximum difference of 6.7 ppbv was observed. Relationships were found between the relative contribution of NMVOC compound classes (alkanes and oxygenated species) in the speciations to the amount of Ox produced in the box model. These results indicate that modelled tropospheric O3 is sensitive to the speciation of NMVOCs as specified by emission inventories, suggesting that detailed updates to the EI speciation

  16. Colombia and Cuba, contrasting models in Latin America's health sector reform.

    PubMed

    De Vos, Pol; De Ceukelaire, Wim; Van der Stuyft, Patrick

    2006-10-01

    Latin American national health systems were drastically overhauled by the health sector reforms the 1990s. Governments were urged by donors and by the international financial institutions to make major institutional changes, including the separation of purchaser and provider functions and privatization. This article first analyses a striking paradox of the far-reaching reform measures: contrary to what is imposed on public health services, after privatization purchaser and provider functions are reunited. Then we compare two contrasting examples: Colombia, which is internationally promoted as a successful--and radical--example of 'market-oriented' health care reform, and Cuba, which followed a highly 'conservative' path to adapt its public system to the new conditions since the 1990s, going against the model of the international institutions. The Colombian reform has not been able to materialize its promises of universality, improved equity, efficiency and better quality, while Cuban health care remains free, accessible for everybody and of good quality. Finally, we argue that the basic premises of the ongoing health sector reforms in Latin America are not based on the people's needs, but are strongly influenced by the needs of foreign--especially North American--corporations. However, an alternative model of health sector reform, such as the Cuban one, can probably not be pursued without fundamental changes in the economic and political foundations of Latin American societies. PMID:17002735

  17. Modeling Electricity Sector Vulnerabilities and Costs Associated with Water Temperatures Under Scenarios of Climate Change

    NASA Astrophysics Data System (ADS)

    Macknick, J.; Miara, A.; Brinkman, G.; Ibanez, E.; Newmark, R. L.

    2014-12-01

    The reliability of the power sector is highly vulnerable to variability in the availability and temperature of water resources, including those that might result from potential climatic changes or from competition from other users. In the past decade, power plants throughout the United States have had to shut down or curtail generation due to a lack of available water or from elevated water temperatures. These disruptions in power plant performance can have negative impacts on energy security and can be costly to address. Analysis of water-related vulnerabilities requires modeling capabilities with high spatial and temporal resolution. This research provides an innovative approach to energy-water modeling by evaluating the costs and reliability of a power sector region under policy and climate change scenarios that affect water resource availability and temperatures. This work utilizes results from a spatially distributed river water temperature model coupled with a thermoelectric power plant model to provide inputs into an electricity production cost model that operates on a high spatial and temporal resolution. The regional transmission organization ISO-New England, which includes six New England states and over 32 Gigawatts of power capacity, is utilized as a case study. Hydrological data and power plant operations are analyzed over an eleven year period from 2000-2010 under four scenarios that include climate impacts on water resources and air temperatures as well as strict interpretations of regulations that can affect power plant operations due to elevated water temperatures. Results of these model linkages show how the power sector's reliability and economic performance can be affected by changes in water temperatures and water availability. The effective reliability and capacity value of thermal electric generators are quantified and discussed in the context of current as well as potential future water resource characteristics.

  18. Modelling carbon stocks and fluxes in the wood product sector: a comparative review.

    PubMed

    Brunet-Navarro, Pau; Jochheim, Hubert; Muys, Bart

    2016-07-01

    In addition to forest ecosystems, wood products are carbon pools that can be strategically managed to mitigate climate change. Wood product models (WPMs) simulating the carbon balance of wood production, use and end of life can complement forest growth models to evaluate the mitigation potential of the forest sector as a whole. WPMs can be used to compare scenarios of product use and explore mitigation strategies. A considerable number of WPMs have been developed in the last three decades, but there is no review available analysing their functionality and performance. This study analyses and compares 41 WPMs. One surprising initial result was that we discovered the erroneous implementation of a few concepts and assumptions in some of the models. We further described and compared the models using six model characteristics (bucking allocation, industrial processes, carbon pools, product removal, recycling and substitution effects) and three model-use characteristics (system boundaries, model initialization and evaluation of results). Using a set of indicators based on the model characteristics, we classified models using a hierarchical clustering technique and differentiated them according to their increasing degrees of complexity and varying levels of user support. For purposes of simulating carbon stock in wood products, models with a simple structure may be sufficient, but to compare climate change mitigation options, complex models are needed. The number of models has increased substantially over the last ten years, introducing more diversity and accuracy. Calculation of substitution effects and recycling has also become more prominent. However, the lack of data is still an important constraint for a more realistic estimation of carbon stocks and fluxes. Therefore, if the sector wants to demonstrate the environmental quality of its products, it should make it a priority to provide reliable life cycle inventory data, particularly regarding aspects of time and

  19. Optical modeling of agricultural fields and rough-textured rock and mineral surfaces

    NASA Technical Reports Server (NTRS)

    Suits, G. H.; Vincent, R. K.; Horwitz, H. M.; Erickson, J. D.

    1973-01-01

    Review was made of past models for describing the reflectance and/or emittance properties of agricultural/forestry and geological targets in an effort to select the best theoretical models. An extension of the six parameter Allen-Gayle-Richardson model was chosen as the agricultural plant canopy model. The model is used to predict the bidirectional reflectance of a field crop from known laboratory spectra of crop components and approximate plant geometry. The selected geological model is based on Mie theory and radiative transfer equations, and will assess the effect of textural variations of the spectral emittance of natural rock surfaces.

  20. Research on agricultural ecology and environment analysis and modeling based on RS and GIS

    NASA Astrophysics Data System (ADS)

    Zhang, Wensheng; Chen, Hongfu; Wang, Mingsheng

    2009-07-01

    Analysis of agricultural ecology and environment is based on the data of agricultural resources, which are obtained by RS monitoring. The over-exploitation of farmlands will cause structural changes of the soil composition, and damage the planting environment and the agro-ecosystem. Through the research on the dynamic monitoring methods of multitemporal RS images and GIS technology, the crop growth status, crop acreage and other relevant information in agricultural production are extracted based on the monitor and analysis of the conditions of the fields and crop growth. The agro-ecological GIS platform is developed with the establishment of the agricultural resources management database, which manages spatial data, RS data and attribute data of agricultural resources. Using the RS, GIS analysis results, the reasons of agro-ecological destruction are analyzed and the evaluation methods are established. This paper puts forward the concept of utilization capacity of farmland, which describes farmland space for development and utilization that is influenced by the conditions of the land, water resources, climate, pesticides and chemical fertilizers and many other agricultural production factors. Assessment model of agricultural land use capacity is constructed with the help of Fuzzy. Assessing the utilization capacity of farmland can be helpful to agricultural production and ecological protection of farmland. This paper describes the application of the capacity evaluation model with simulated data in two aspects, namely, in evaluating the status of farmland development and utilization and in optimal planting.

  1. The Parallel System for Integrating Impact Models and Sectors (pSIMS)

    NASA Technical Reports Server (NTRS)

    Elliott, Joshua; Kelly, David; Chryssanthacopoulos, James; Glotter, Michael; Jhunjhnuwala, Kanika; Best, Neil; Wilde, Michael; Foster, Ian

    2014-01-01

    We present a framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS accelerates computational research, encourages model intercomparison, and enhances reproducibility of simulation results. We present the pSIMS design and use example assessments to demonstrate its multi-model, multi-scale, and multi-sector versatility.

  2. Instability in interacting dark sector: an appropriate holographic Ricci dark energy model

    NASA Astrophysics Data System (ADS)

    Herrera, Ramón; Hipólito-Ricaldi, W. S.; Videla, Nelson

    2016-08-01

    In this paper we investigate the consequences of phantom crossing considering the perturbative dynamics in models with interaction in their dark sector. By mean of a general study of gauge-invariant variables in comoving gauge, we relate the sources of instabilities in the structure formation process with the phantom crossing. In order to illustrate these relations and its consequences in more detail, we consider a specific case of an holographic dark energy interacting with dark matter. We find that in spite of the model is in excellent agreement with observational data at background level, however it is plagued of instabilities in its perturbative dynamics. We reconstruct the model in order to avoid these undesirable instabilities, and we show that this implies a modification of the concordance model at background. Also we find drastic changes on the parameters space in our model when instabilities are avoided.

  3. Cosmic strings in hidden sectors: 1. Radiation of standard model particles

    SciTech Connect

    Long, Andrew J.; Hyde, Jeffrey M.; Vachaspati, Tanmay E-mail: jmhyde@asu.edu

    2014-09-01

    In hidden sector models with an extra U(1) gauge group, new fields can interact with the Standard Model only through gauge kinetic mixing and the Higgs portal. After the U(1) is spontaneously broken, these interactions couple the resultant cosmic strings to Standard Model particles. We calculate the spectrum of radiation emitted by these ''dark strings'' in the form of Higgs bosons, Z bosons, and Standard Model fermions assuming that string tension is above the TeV scale. We also calculate the scattering cross sections of Standard Model fermions on dark strings due to the Aharonov-Bohm interaction. These radiation and scattering calculations will be applied in a subsequent paper to study the cosmological evolution and observational signatures of dark strings.

  4. Measuring job satisfaction in the social services sector with the Rasch model.

    PubMed

    Brentari, Eugenio; Golia, Silvia

    2008-01-01

    In the present paper, the Rasch measurement model is used in the validation and analysis of data coming from the satisfaction section of the first national survey concerning the social services sector carried out in Italy. A comparison between two Rasch models for polytomous data, that is the Rating Scale Model and the Partial Credit Model, is discussed. Given that the two models provide similar estimates of the item difficulties and workers satisfaction, for almost all the items the response probabilities computed using the RSM and the PCM are very close and the analysis of the bootstrap confidence intervals shows that the estimates obtained applying the RSM are more stable than the ones obtained using the PCM, it can be conclude that, for the present data, the RSM is more appropriate than the PCM. PMID:18180549

  5. Droughts in the US: Modeling and Forecasting for Agriculture-Water Management and Adaptation

    NASA Astrophysics Data System (ADS)

    Perveen, S.; Devineni, N.; Lall, U.

    2012-12-01

    More than half of all US counties are currently mired in a drought that is considered the worst in decades. A persistent drought can not only lead to widespread impacts on water access with interstate implications (as has been shown in the Southeast US and Texas), chronic scarcity can emerge as a risk in regions where fossil aquifers have become the primary source of supply and are being depleted at rates much faster than recharge (e.g., Midwestern US). The standardized drought indices on which the drought declarations are made in the US so far consider only the static decision frameworks—where only the supply is the control variable and not the water consumption. If a location has low demands, drought as manifest in the usual indices does not really have "proportionate" social impact. Conversely, a modest drought as indicated by the traditional measures may have significant impacts where demand is close to the climatological mean value of precipitation. This may also lead to drought being declared too late or too soon. Against this fact, the importance of improved drought forecasting and preparedness for different sectors of the economy becomes increasingly important. The central issue we propose to address through this paper is the construction and testing of a drought index that considers regional water demands for specific purposes (e.g., crops, municipal use) and their temporal distribution over the year for continental US. Here, we have highlighted the use of the proposed index for three main sectors: (i) water management organizations, (ii) optimizing agricultural water use, and (iii) supply chain water risk. The drought index will consider day-to-day climate variability and sectoral demands to develop aggregate regional conditions or disaggregated indices for water users. For the daily temperature and precipitation data, we are using NLDAS dataset that is available from 1949 onwards. The national agricultural statistics services (NASS) online database has

  6. 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.

  7. The agroecological matrix as alternative to the land-sparing/agriculture intensification model

    PubMed Central

    Perfecto, Ivette; Vandermeer, John

    2010-01-01

    Among the myriad complications involved in the current food crisis, the relationship between agriculture and the rest of nature is one of the most important yet remains only incompletely analyzed. Particularly in tropical areas, agriculture is frequently seen as the antithesis of the natural world, where the problem is framed as one of minimizing land devoted to agriculture so as to devote more to conservation of biodiversity and other ecosystem services. In particular, the “forest transition model” projects an overly optimistic vision of a future where increased agricultural intensification (to produce more per hectare) and/or increased rural-to-urban migration (to reduce the rural population that cuts forest for agriculture) suggests a near future of much tropical aforestation and higher agricultural production. Reviewing recent developments in ecological theory (showing the importance of migration between fragments and local extinction rates) coupled with empirical evidence, we argue that there is little to suggest that the forest transition model is useful for tropical areas, at least under current sociopolitical structures. A model that incorporates the agricultural matrix as an integral component of conservation programs is proposed. Furthermore, we suggest that this model will be most successful within a framework of small-scale agroecological production. PMID:20339080

  8. Estimating agricultural N2O emissions in France: comparison of a spatialized agro-ecosytem model (CERES-EGC) and a terrestrial biosphere model (O-CN)

    NASA Astrophysics Data System (ADS)

    Massad, R. S.; Prieur, V.; Boukari, E.; Lehuger, S.; Chaumartin, F.; Schultz, M.; Gabrielle, B.

    2012-04-01

    Nitrous oxide (N2O) is a major greenhouse gas and air pollutant. Considered over a 100 year period, it has 298 times more impact 'per unit weight' (Global warming potential) than carbon dioxide. The parties to the United Nations Framework Convention on Climate Change (UNFCCC), including France, are committed to estimate their national nitrous oxide (N2O) budgets and to establish regional programmes of N2O emissions reductions. Agricultural activities are gradually coming into focus as a major GHG emission sector; precise regional estimates of current N2O emissions from arable land are being needed, along with possible means for mitigating emissions. The use of biogeochemical simulation models to estimate N2O fluxes from agricultural soils has obvious benefits. These models provide a unique potential to mechanistically predict N2O emissions from arable soils on both the plot-scale and the regional/national scale on daily time resolutions. In this study we apply two biogeochemical simulation models: CERES-EGC and O-CN all over France for the year 2007 in the perspective of producing an inventory of N2O emissions from croplands. Simulated total N2O emissions from agricultural soils sum up to 20.4 Gg N-N2O/yr with the CERES-EGC model and to 95.1 Gg N-N2O/yr with the O-CN model. Even though the total emissions are largely different between the two models, the temporal and spatial distributions are comparable. When compared to the EDGAR 4.2 emission database we note that O-CN overestimates the annual emissions by approximately a factor of two, whereas CERES-EGC underestimates those emissions. These differences can be explained to a certain extent by the difference in land-use types considered in each of the models and the inventories.

  9. Using Multispectral Analysis in GIS to Model the Potential for Urban Agriculture in Philadelphia

    NASA Astrophysics Data System (ADS)

    Dmochowski, J. E.; Cooper, W. P.

    2010-12-01

    In the context of growing concerns about the international food system’s dependence on fossil fuels, soil degradation, climate change, and other diverse issues, a number of initiatives have arisen to develop and implement sustainable agricultural practices. Many seeking to reform the food system look to urban agriculture as a means to create localized, sustainable agricultural production, while simultaneously providing a locus for community building, encouraging better nutrition, and promoting the rebirth of depressed urban areas. The actual impact of such system, however, is not well understood, and many critics of urban agriculture regard its implementation as impractical and unrealistic. This project uses multispectral imagery from United States Department of Agriculture’s National Agricultural Imagery Program with a one-meter resolution to quantify the potential for increasing urban agriculture in an effort to create a sustainable food system in Philadelphia. Color infrared images are classified with a minimum distance algorithm in ArcGIS to generate baseline data on vegetative cover in Philadelphia. These data, in addition to mapping on the ground, form the basis of a model of land suitable for conversion to agriculture in Philadelphia, which will help address questions related to potential yields, workforce, and energy requirements. This research will help city planners, entrepreneurs, community leaders, and citizens understand how urban agriculture can contribute to creating a sustainable food system in a major North American city.

  10. Modeling the impacts of climate change and agricultural management practices on surface erosion in a dryland agricultural basin

    NASA Astrophysics Data System (ADS)

    Ottenbreit, E.; Adam, J. C.; Barber, M. E.

    2010-12-01

    The objective of this study is to investigate the effects of climate change and agricultural management practices on suspended sediment concentrations in the Potlach River basin in northwestern Idaho. Suspended sediment is a pollutant in many water systems and contributes to the impairment of streams. Conventional tillage practices and rain-on-snow events in the Palouse region of northern Idaho and eastern Washington can produce some of the highest sediment losses per acre in the United States. Climate change may lead to further problems as more frequent and intense winter storm events are predicted to occur. Many hydrological models have been developed which examine suspended sediment in river systems. The Potlatch River basin near Julietta, ID was examined using the Distributed Hydrology Soil Vegetation Model (DHSVM), which has a sediment module that includes surface erosion and channel sediment transport. DHSVM was calibrated and evaluated over the historical period of streamflow observations and was used to predict soil erosion rates and suspended sediment concentrations using a range of downscaled Global Climate Models (GCMs) emissions scenarios for the year 2045. Furthermore, the sensitivity of suspended sediment concentrations to conventional versus convservative tillage practices was explored. The results show that as the projected climate-driven intensity of storms increase, more sediment is predicted in the Potlatch River. Suspended sediment and streamflow are predicted to increase during the late fall through the early spring. This increase occurs during times of heightened runoff when suspended sediment concentration in the river is highest. Three tillage scenarios were incorporated into DHSVM for winter wheat: conventional till, reduced till, and no till. Erosion and suspended sediment were higher during storm events under conventional agricultural tillage scenarios. In the long-term, this research can lead to examination of the effects of climate

  11. Classical Lagrangians and Finsler structures for the nonminimal fermion sector of the standard model extension

    NASA Astrophysics Data System (ADS)

    Schreck, M.

    2016-05-01

    This article is devoted to finding classical point-particle equivalents for the fermion sector of the nonminimal standard model extension (SME). For a series of nonminimal operators, such Lagrangians are derived at first order in Lorentz violation using the algebraic concept of Gröbner bases. Subsequently, the Lagrangians serve as a basis for reanalyzing the results of certain kinematic tests of special relativity that were carried out in the past century. Thereby, a number of new constraints on coefficients of the nonminimal SME is obtained. In the last part of the paper we point out connections to Finsler geometry.

  12. Infrared dynamics of a large N QCD model, the massless string sector and mesonic spectra

    NASA Astrophysics Data System (ADS)

    Dasgupta, Keshav; Gale, Charles; Mia, Mohammed; Richard, Michael; Trottier, Olivier

    2015-07-01

    A consistency check for any UV complete model for large N QCD should be, among other things, the existence of a well-defined vector and scalar mesonic spectra. In this paper, we use our UV complete model in type IIB string theory to study the IR dynamics and use this to predict the mesonic spectra in the dual type IIA side. The advantage of this approach is two-fold: not only will this justify the consistency of the supergravity approach, but it will also give us a way to compare the IR spectra and the model with the ones proposed earlier by Sakai and Sugimoto. Interestingly, the spectra coming from the massless stringy sector are independent of the UV physics, although the massive string sector may pose certain subtleties regarding the UV contributions as well as the mappings to actual QCD. Additionally, we find that a component of the string landscape enters the picture: there are points in the landscape where the spectra can be improved somewhat over the existing results in the literature. These points in the landscape in-turn also determine certain background supergravity components and fix various pathologies that eventually lead to a consistent low energy description of the theory.

  13. MODELING FOR PRECISION AGRICULTURE-HOW GOOD IS GOOD ENOUGH, AND HOW CAN WE TELL?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    During the development of precision agriculture technology, prior existence of crop simulation models prompted their application to modeling spatial variation in yield. On the face of it, extending a fairly mature 1-D model of crop growth and yield appeared to be a matter of developing spatial suite...

  14. SEPARATING SPATIAL AND TEMPORAL SOURCES OF VARIATION FOR MODEL TESTING IN PRECISION AGRICULTURE

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Applying crop simulation models to precision agriculture appears to be a matter of developing spatial suites of input parameters and running a model for each set. Extensive modeling literature has reported independent tests in multiple combinations of variety, soils, and climate, which has been gene...

  15. On the utility of land surface models for agricultural drought monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The lagged rank cross-correlation between model-derived root-zone soil moisture estimates and remotely-sensed vegetation indices (VI) is examined from January 2000 until December 2010 to quantify the skill of various soil moisture models for agricultural drought monitoring. Examined modeling strateg...

  16. Inducing the shift from flat-rate or free agricultural power to metered supply: Implications for groundwater depletion and power sector viability in India

    NASA Astrophysics Data System (ADS)

    Kumar, M. Dinesh; Scott, Christopher A.; Singh, O. P.

    2011-10-01

    SummaryIndia's farm sector sustains livelihoods for hundreds of millions of rural people, but faces serious management challenges for land, water, and energy resources. Growing dependence on groundwater threatens water resources sustainability and power sector viability. Sustaining India's rising prosperity rests on managing groundwater. This study shows that raising power tariffs in the farm sector to achieve efficiency and sustainability of groundwater use is both socially and economically viable. The question is about how to introduce this shift. This paper discusses five different options for power supply, metering and energy pricing in the farm sector and the expected outcomes of implementing each vis-a-vis efficiency of groundwater and energy use, equity in access and sustainability of groundwater. It concludes that establishing an energy quota for each farm-based on sustainability considerations, and metering and charging pro rata for power used are the best options to manage groundwater and the energy economy.

  17. Population health improvement: a community health business model that engages partners in all sectors.

    PubMed

    Kindig, David A; Isham, George

    2014-01-01

    Because population health improvement requires action on multiple determinants--including medical care, health behaviors, and the social and physical environments--no single entity can be held accountable for achieving improved outcomes. Medical organizations, government, schools, businesses, and community organizations all need to make substantial changes in how they approach health and how they allocate resources. To this end, we suggest the development of multisectoral community health business partnership models. Such collaborative efforts are needed by sectors and actors not accustomed to working together. Healthcare executives can play important leadership roles in fostering or supporting such partnerships in local and national arenas where they have influence. In this article, we develop the following components of this argument: defining a community health business model; defining population health and the Triple Aim concept; reaching beyond core mission to help create the model; discussing the shift for care delivery beyond healthcare organizations to other community sectors; examining who should lead in developing the community business model; discussing where the resources for a community business model might come from; identifying that better evidence is needed to inform where to make cost-effective investments; and proposing some next steps. The approach we have outlined is a departure from much current policy and management practice. But new models are needed as a road map to drive action--not just thinking--to address the enormous challenge of improving population health. While we applaud continuing calls to improve health and reduce disparities, progress will require more robust incentives, strategies, and action than have been in practice to date. Our hope is that ideas presented here will help to catalyze a collective, multisectoral response to this critical social and economic challenge. PMID:25671991

  18. Modeling water outflow from tile-drained agricultural fields.

    PubMed

    Kuzmanovski, Vladimir; Trajanov, Aneta; Leprince, Florence; Džeroski, Sašo; Debeljak, Marko

    2015-02-01

    The estimation of the pollution risk of surface and ground water with plant protection products applied on fields depends highly on the reliable prediction of the water outflows over (surface runoff) and through (discharge through sub-surface drainage systems) the soil. In previous studies, water movement through the soil has been simulated mainly using physically-based models. The most frequently used models for predicting soil water movement are MACRO, HYDRUS-1D/2D and Root Zone Water Quality Model. However, these models are difficult to apply to a small portion of land due to the information required about the soil and climate, which are difficult to obtain for each plot separately. In this paper, we focus on improving the performance and applicability of water outflow modeling by using a modeling approach based on machine learning techniques. It allows us to overcome the major drawbacks of physically-based models e.g., the complexity and difficulty of obtaining the information necessary for the calibration and the validation, by learning models from data collected from experimental fields that are representative for a wider area (region). We evaluate the proposed approach on data obtained from the La Jaillière experimental site, located in Western France. This experimental site represents one of the ten scenarios contained in the MACRO system. Our study focuses on two types of water outflows: discharge through sub-surface drainage systems and surface runoff. The results show that the proposed modeling approach successfully extracts knowledge from the collected data, avoiding the need to provide the information for calibration and validation of physically-based models. In addition, we compare the overall performance of the learned models with the performance of existing models MACRO and RZWQM. The comparison shows overall improvement in the prediction of discharge through sub-surface drainage systems, and partial improvement in the prediction of the surface

  19. Improved Decision Support in the Energy Sector Using NASA Spaceborne Observations and Models

    NASA Astrophysics Data System (ADS)

    Eckman, R. S.; Stackhouse, P. W.

    2006-12-01

    The NASA Applied Sciences Program Energy Management Program Element establishes partnerships with federal and private organizations to improve their decisions and assessments that impact the energy sector. These improvements are enabled by leveraging the knowledge generated from research resulting from spacecraft observations and model predictions conducted by NASA and providing these as inputs to the decision support and scenario assessment tools used by partner organizations. The Energy Management Program element focuses its efforts to provide for improved decisions and assessments for the following primary areas:, (1) Renewable energy & Energy efficiency, (2) Impacts of climate change on the energy sector, (3) Long-term energy modeling and forecasting, and (4) Supply and load forecasting/Distributed energy. The goals of the Program Element seek to maintain alignment and contribute to national and international priorities, specifically the Climate Change Science and Technology Programs, and the Group on Earth Observations (GEO). The approach of the Energy Management Program Element is to develop information pathways from NASA spacecraft observations and Earth system modeling to decision support tools (DST) supporting energy demand and availability in industry, government, and private entities. These entities require historical, near-real time, and forecasted environmental observations as inputs to the DST for management decisions and scenario assessments for policy. NASA works with its partners to identify the physical quantities provided by NASA observations and model predictions resulting from Earth science research, which are specifically selected, derived, and formatted to meet the needs of a specific DST. Specific case studies describing partnerships with the National Renewable Energy Laboratory and with the International Energy Agency resulting in the use of NASA measurements in renewable energy DSTs are presented. We also describe a partnership whereby

  20. Neutrino properties from maximally-predictive GUT models and the structure of the heavy Majorana sector

    NASA Astrophysics Data System (ADS)

    Papageorgiu, E.

    1995-03-01

    Starting from a complete set of possible parametrisations of the quark-mass matrices that have the maximum number of texture zeros at the grand unification scale, and the Georgi-Jarlskog mass relations, we classify the neutrino spectra with respect to the unknown structure of the heavy Majorana sector. The results can be casted into a small number of phenomenologically distinct classes of neutrino spectra, characterised by universal mass-hierarchy and oscillation patterns. One finds that the neutrino masses reflect the natural hierarchy among the three generations and obey the quadratic seesaw, for most GUT models that contain a rather “unsophisticated” Majorana sector. A scenario with v τ as the missing hot dark matter component and v e ↔ v µ oscillations accounting for the solar neutrino deficit comes naturally out of this type of models and is very close to the experimental limit of confirmation or exclusion. In contrast, in the presence of a strong hierarchy of heavy scales or/and some extra symmetries in the Majorana mass matrix, this natural hierarchy gets distorted or even reversed. This fact can become a link between searches for neutrino oscillations and searches for discrete symmetries close to the Planck scale.

  1. Modeling Climate-Water Impacts on Electricity Sector Capacity Expansion: Preprint

    SciTech Connect

    Cohen, S. M.; Macknick, J.; Averyt, K.; Meldrum, J.

    2014-05-01

    Climate change has the potential to exacerbate water availability concerns for thermal power plant cooling, which is responsible for 41% of U.S. water withdrawals. This analysis describes an initial link between climate, water, and electricity systems using the National Renewable Energy Laboratory (NREL) Regional Energy Deployment System (ReEDS) electricity system capacity expansion model. Average surface water projections from Coupled Model Intercomparison Project 3 (CMIP3) data are applied to surface water rights available to new generating capacity in ReEDS, and electric sector growth is compared with and without climate-influenced water rights. The mean climate projection has only a small impact on national or regional capacity growth and water use because most regions have sufficient unappropriated or previously retired water rights to offset climate impacts. Climate impacts are notable in southwestern states that purchase fewer water rights and obtain a greater share from wastewater and other higher-cost water resources. The electric sector climate impacts demonstrated herein establish a methodology to be later exercised with more extreme climate scenarios and a more rigorous representation of legal and physical water availability.

  2. Higgs sector of the left-right model with explicit CP violation

    NASA Astrophysics Data System (ADS)

    Kiers, Ken; Assis, Michael; Petrov, Alexey A.

    2005-06-01

    We explore the Higgs sector of the Minimal Left-Right (LR) Model based on the gauge group SU(2)L×SU(2)R×U(1)B-L with explicit CP violation in the Higgs potential. Since flavour-changing neutral current experiments and the small scale of neutrino masses both place stringent constraints on the Higgs potential, we seek to determine whether minima of the Higgs potential exist that are consistent with current experimental bounds. We focus on the case in which the right-handed symmetry-breaking scale is only moderately large, of order 15 50 TeV. Unlike the case in which the Higgs potential is CP-invariant, the CP noninvariant case does yield viable scenarios, although these require a small amount of fine-tuning. We consider a LR model supplemented by an additional U(1) horizontal symmetry, which results in a Higgs sector consistent with current experimental constraints and a realistic spectrum of neutrino masses.

  3. Reverse engineering of legacy agricultural phenology modeling system

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A program which implements predictive phenology modeling is a valuable tool for growers and scientists. Such a program was created in the late 1980's by the creators of general phenology modeling as proof of their techniques. However, this first program could not continue to meet the needs of the fi...

  4. Chapter 3: Cropland Agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In 2013, cropland agriculture resulted in total emissions of approximately 209 MMT CO2 eq. of greenhouse gases (GHG). Cropland agriculture is responsible for almost half (46%) of all emissions from the agricultural sector. Nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) emissions from c...

  5. Climate change induced transformations of agricultural systems: insights from a global model

    NASA Astrophysics Data System (ADS)

    Leclère, D.; Havlík, P.; Fuss, S.; Schmid, E.; Mosnier, A.; Walsh, B.; Valin, H.; Herrero, M.; Khabarov, N.; Obersteiner, M.

    2014-12-01

    Climate change might impact crop yields considerably and anticipated transformations of agricultural systems are needed in the coming decades to sustain affordable food provision. However, decision-making on transformational shifts in agricultural systems is plagued by uncertainties concerning the nature and geography of climate change, its impacts, and adequate responses. Locking agricultural systems into inadequate transformations costly to adjust is a significant risk and this acts as an incentive to delay action. It is crucial to gain insight into how much transformation is required from agricultural systems, how robust such strategies are, and how we can defuse the associated challenge for decision-making. While implementing a definition related to large changes in resource use into a global impact assessment modelling framework, we find transformational adaptations to be required of agricultural systems in most regions by 2050s in order to cope with climate change. However, these transformations widely differ across climate change scenarios: uncertainties in large-scale development of irrigation span in all continents from 2030s on, and affect two-thirds of regions by 2050s. Meanwhile, significant but uncertain reduction of major agricultural areas affects the Northern Hemisphere’s temperate latitudes, while increases to non-agricultural zones could be large but uncertain in one-third of regions. To help reducing the associated challenge for decision-making, we propose a methodology exploring which, when, where and why transformations could be required and uncertain, by means of scenario analysis.

  6. The Urban Food-Water Nexus: Modeling Water Footprints of Urban Agriculture using CityCrop

    NASA Astrophysics Data System (ADS)

    Tooke, T. R.; Lathuilliere, M. J.; Coops, N. C.; Johnson, M. S.

    2014-12-01

    Urban agriculture provides a potential contribution towards more sustainable food production and mitigating some of the human impacts that accompany volatility in regional and global food supply. When considering the capacity of urban landscapes to produce food products, the impact of urban water demand required for food production in cities is often neglected. Urban agricultural studies also tend to be undertaken at broad spatial scales, overlooking the heterogeneity of urban form that exerts an extreme influence on the urban energy balance. As a result, urban planning and management practitioners require, but often do not have, spatially explicit and detailed information to support informed urban agricultural policy, especially as it relates to potential conflicts with sustainability goals targeting water-use. In this research we introduce a new model, CityCrop, a hybrid evapotranspiration-plant growth model that incorporates detailed digital representations of the urban surface and biophysical impacts of the built environment and urban trees to account for the daily variations in net surface radiation. The model enables very fine-scale (sub-meter) estimates of water footprints of potential urban agricultural production. Results of the model are demonstrated for an area in the City of Vancouver, Canada and compared to aspatial model estimates, demonstrating the unique considerations and sensitivities for current and future water footprints of urban agriculture and the implications for urban water planning and policy.

  7. Using landscape typologies to model socioecological systems: Application to agriculture of the United States Gulf Coast

    DOE PAGESBeta

    Preston, Benjamin L.; King, Anthony Wayne; Mei, Rui; Nair, Sujithkumar Surendran

    2016-02-11

    Agricultural enterprises are vulnerable to the effects of climate variability and change. Improved understanding of the determinants of vulnerability and adaptive capacity in agricultural systems is important for projecting and managing future climate risk. At present, three analytical tools dominate methodological approaches to understanding agroecological vulnerability to climate: process-based crop models, empirical crop models, and integrated assessment models. A common weakness of these approaches is their limited treatment of socio-economic conditions and human agency in modeling agroecological processes and outcomes. This study proposes a framework that uses spatial cluster analysis to generate regional socioecological typologies that capture geographic variance inmore » regional agricultural production and enable attribution of that variance to climatic, topographic, edaphic, and socioeconomic components. This framework was applied to historical corn production (1986-2010) in the U.S. Gulf of Mexico region as a testbed. The results demonstrate that regional socioeconomic heterogeneity is an important driving force in human dominated ecosystems, which we hypothesize, is a function of the link between socioeconomic conditions and the adaptive capacity of agricultural systems. Meaningful representation of future agricultural responses to climate variability and change is contingent upon understanding interactions among biophysical conditions, socioeconomic conditions, and human agency their incorporation in predictive models.« less

  8. Turkey energy and environmental review - Task 7 energy sector modeling : executive summary.

    SciTech Connect

    Conzelmann, G.; Koritarov, V.; Decision and Information Sciences

    2008-02-28

    Turkey's demand for energy and electricity is increasing rapidly. Since 1990, energy consumption has increased at an annual average rate of 4.3%. As would be expected, the rapid expansion of energy production and consumption has brought with it a wide range of environmental issues at the local, regional and global levels. With respect to global environmental issues, Turkey's carbon dioxide (CO2) emissions have grown along with its energy consumption. Emissions in 2000 reached 211 million metric tons. With GDP projected to grow at over 6% per year over the next 25 years, both the energy sector and the pollution associated with it are expected to increase substantially. This is expected to occur even if assuming stricter controls on lignite and hard coal-fired power generation. All energy consuming sectors, that is, power, industrial, residential, and transportation, will contribute to this increased emissions burden. Turkish Government authorities charged with managing the fundamental problem of carrying on economic development while protecting the environment include the Ministry of Environment (MOE), the Ministry of Energy and Natural Resources (MENR), and the Ministry of Health, as well as the Turkish Electricity Generation & Transmission Company (TEAS). The World Bank, working with these agencies, is planning to assess the costs and benefits of various energy policy alternatives under an Energy and Environment Review (EER). Eight individual studies have been conducted under this activity to analyze certain key energy technology issues and use this analysis to fill in the gaps in data and technical information. This will allow the World Bank and Turkish authorities to better understand the trade-offs in costs and impacts associated with specific policy decisions. The purpose of Task 7-Energy Sector Modeling, is to integrate information obtained in other EER tasks and provide Turkey's policy makers with an integrated systems analysis of the various options for

  9. Modeling climate change impact in hospitality sector, using building resources consumption signature

    NASA Astrophysics Data System (ADS)

    Pinto, Armando; Bernardino, Mariana; Silva Santos, António; Pimpão Silva, Álvaro; Espírito Santo, Fátima

    2016-04-01

    Hotels are one of building types that consumes more energy and water per person and are vulnerable to climate change because in the occurrence of extreme events (heat waves, water stress) same failures could compromise the hotel services (comfort) and increase energy cost or compromise the landscape and amenities due to water use restrictions. Climate impact assessments and the development of adaptation strategies require the knowledge about critical climatic variables and also the behaviour of building. To study the risk and vulnerability of buildings and hotels to climate change regarding resources consumption (energy and water), previous studies used building energy modelling simulation (BEMS) tools to study the variation in energy and water consumption. In general, the climate change impact in building is evaluated studying the energy and water demand of the building for future climate scenarios. But, hotels are complex buildings, quite different from each other and assumption done in simplified BEMS aren't calibrated and usually neglect some important hotel features leading to projected estimates that do not usually match hotel sector understanding and practice. Taking account all uncertainties, the use of building signature (statistical method) could be helpful to assess, in a more clear way, the impact of Climate Change in the hospitality sector and using a broad sample. Statistical analysis of the global energy consumption obtained from bills shows that the energy consumption may be predicted within 90% confidence interval only with the outdoor temperature. In this article a simplified methodology is presented and applied to identify the climate change impact in hospitality sector using the building energy and water signature. This methodology is applied to sixteen hotels (nine in Lisbon and seven in Algarve) with four and five stars rating. The results show that is expect an increase in water and electricity consumption (manly due to the increase in

  10. What is the difference between a 2, 3, 4, or 5 °C world and how good are we at telling this difference? Results from ISI-MIP the first Inter-Sectoral Impact Model Intercomparison Project

    NASA Astrophysics Data System (ADS)

    Frieler, K.; Huber, V.; Piontek, F.; Schewe, J.; Serdeczny, O.; Warszawski, L.

    2012-12-01

    The Inter-sectoral Impact Model Intercomparison Project (ISI-MIP) aims to synthesize the state-of-the-art knowledge of climate change impacts at different levels of global warming. Over 25 climate impact modelling teams from around the world, working within the agriculture, water, biomes, infrastructure and health sectors, are collaborating to find answers to the question "What is the difference between a 2, 3, 4, or 5 °C world and how good are we at telling this difference?". The analysis is based on common, bias-corrected climate projections, and socio-economic pathways. The first, fast-tracked phase of the ISI-MIP has a focus on global impact models. The project's experimental design is formulated to distinguish the uncertainty introduced by the impact models themselves, from the inherent uncertainty in the climate projections and the variety of plausible socio-economic futures. Novel metrics, developed to emphasize societal impacts, will be used to identify regional 'hot-spots' of climate change impacts, as well as to quantify the cross-sectoral impact of the increasing frequency of extreme events in future climates. We present here first results from the Fast-Track phase of the project covering impact simulations in the biomes, agriculture and water sectors, in which the societal impacts of climate change are quantified for different levels of global warming. We also discuss the design of the scenario set-up and impact indicators chosen to suit the unique cross-sectoral, multi-model nature of the project.

  11. Global model simulations of the impact of the transport sectors on atmospheric aerosol and climate

    NASA Astrophysics Data System (ADS)

    Righi, Mattia; Hendricks, Johannes; Sausen, Robert

    2013-04-01

    The transport sector, including land transport, shipping and aviation, is one of the major sources of tropospheric aerosol. Land transport, in particular, is a relevant source of pollution in highly populated areas (e.g. megacities), with significant impacts on climate and health. Transport emissions are expected to grow in the near future, especially in the developing countries. In this work we use the EMAC-MADE global aerosol model to quantify the impact of transport emissions on global aerosol, for both present-day (2000) and future (2030) scenarios. Number emissions are also included in the model and derived from mass emissions under different assumptions on the size distribution of particles emitted by the three transport modes. Additional sensitivity experiments are performed to quantify the effects of the uncertainties behind such assumptions. The model simulations reveal that land transport is the most important source of black carbon pollution in the densely populated regions of Eastern U.S. and Europe. High particle concentrations are simulated for Southeast Asian areas, although pollution in this region is mostly due to non-transport sources. Shipping strongly contributes to aerosol sulphate concentrations along the most-traveled routes of the Northern Atlantic and Northern Pacific oceans, with significant impact along the coastlines and nearby major harbors and with large effects on cloud properties. The impacts on particle number concentrations are very sensitive to the assumptions on size distribution of emitted particles, with the largest uncertainties simulated for the land transport sector. The model results further reveal significant climate impacts of transport-induced particles.

  12. Modelling of a downdraft gasifier fed by agricultural residues

    SciTech Connect

    Antonopoulos, I.-S.; Karagiannidis, A.; Gkouletsos, A.; Perkoulidis, G.

    2012-04-15

    Highlights: Black-Right-Pointing-Pointer Development of software for downdraft gasification simulation. Black-Right-Pointing-Pointer Prediction of the syngas concentration. Black-Right-Pointing-Pointer Prediction of the syngas heating value. Black-Right-Pointing-Pointer Investigation of the temperature effect in reduction zone in syngas concentration. - Abstract: A non-stoichiometric model for a downdraft gasifier was developed in order to simulate the overall gasification process. Mass and energy balances of the gasifier were calculated and the composition of produced syngas was predicted. The capacity of the modeled gasifier was assumed to be 0.5 MW, with an Equivalence Ratio (EQ) of 0.45. The model incorporates the chemical reactions and species involved, while it starts by selecting all species containing C, H, and O, or any other dominant elements. Olive wood, miscanthus and cardoon were tested in the formulated model for a temperature range of 800-1200 Degree-Sign C, in order to examine the syngas composition and the moisture impact on the supplied fuel. Model results were then used in order to design an olive wood gasification reactor.

  13. Object-Oriented Agricultural System Modeling: Component-Driven Nutrient Dynamics and Crop Yield Simulations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Challenges in agro-ecosystem conservation management have created demand for state-of-the-art, integrated, and flexible modeling tools. For example, agricultural system modeling tools are needed which are robust and fast enough to be applied on large watershed scales, but which are also able to sim...

  14. Integrated agricultural system modeling using OMS3: component driven runoff and nutrient dynamics simulations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Challenges in agro-ecosystem conservation management have created demand for state-of-the-art, integrated, and flexible modeling tools. For example, agricultural system modeling tools are needed which are robust and fast enough to be applied on large watershed scales, but which are also able to simu...

  15. Simulating semiarid dryland cropping systems using the precision agricultural landscape modeling system

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Precision Agricultural Landscape Modeling System (PALMS) is a terrain and weather driven, and distributed parameter hydrological-biophysical model primarily used in the Midwestern United States. Recently, research was started to evaluate the effectiveness of PALMS on irrigated and on dryland cro...

  16. Application of the precision agricultural landscape modeling system in semiarid environments

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Precision Agricultural Landscape Modeling System (PALMS) is a terrain and weather driven, distributed parameter hydrological-biophysical model primarily used in the Midwestern United States. Recently, research was started to evaluate the effectiveness of PALMS on irrigated and on dryland croppin...

  17. MODELING LONG-TERM NITRATE BASE-FLOW LOADING FROM TWO AGRICULTURAL WATERSHEDS

    EPA Science Inventory

    Nitrate contamination of ground water from agricultural practices may be contributing to the eutrophication of the Chesapeake Bay, degrading water quality and aquatic habitats. Groundwater flow and nitrate transport and fate are modeled, using MODFLOW and MT3D computer models, in...

  18. Definition of zones with different levels of productivity within an agricultural field using fuzzy modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Zoning of agricultural fields is an important task for utilization of precision farming technology. One method for the definition of zones with different levels of productivity is based on fuzzy indicator model. Fuzzy indicator model for identification of zones with different levels of productivit...

  19. The Agriculture Model Intercomparison and Improvement Project (AgMIP) (Invited)

    NASA Astrophysics Data System (ADS)

    Rosenzweig, C.

    2010-12-01

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation exercise for historical model intercomparison and future climate change conditions with participation of multiple crop and world agricultural trade modeling groups around the world. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Historical period results will spur model improvement and interaction among major modeling groups, while future period results will lead directly to tests of adaptation and mitigation strategies across a range of scales. AgMIP will consist of a multi-scale impact assessment utilizing the latest methods for climate and agricultural scenario generation. Scenarios and modeling protocols will be distributed on the web, and multi-model results will be collated and analyzed to ensure the widest possible coverage of agricultural crops and regions. AgMIP will place regional changes in agricultural production in a global context that reflects new trading opportunities, imbalances, and shortages in world markets resulting from climate change and other driving forces for food supply. Such projections are essential inputs from the Vulnerability, Impacts, and Adaptation (VIA) research community to the Intergovernmental Panel on Climate Change Fifth Assessment (AR5), now underway, and the UN Framework Convention on Climate Change. They will set the context for local-scale vulnerability and adaptation studies, supply test scenarios for national-scale development of trade policy instruments, provide critical information on changing supply and demand for water resources, and elucidate interactive effects of climate change and land use change. AgMIP will not only provide crucially-needed new global estimates of how climate change will affect food supply and hunger in the

  20. Paying informally in the Albanian health care sector: a two-tiered stochastic frontier model.

    PubMed

    Tomini, Sonila; Groot, Wim; Pavlova, Milena

    2012-12-01

    Informal payments are deeply ingrained in the health care sector of most Central, Eastern and Southern European countries. Evidence suggests that the price paid informally to medical staff is negotiated either directly or indirectly between patients and medical staff. The aim of this paper is to measure the imperfect information that exists on the amount that has to be paid informally to medical staff. We measure the extent to which patients pay more than the amount medical staff expect informally and the extent to which medical staff request less than patients are willing to pay informally. A two-tiered stochastic frontier model is developed to estimate indicators of patients' and medical staff's imperfect information on informal payments and the effects on the amount the other party is minimally expecting or maximally willing to pay informally. The estimates are based on informal payments to medical staff in the inpatient health care sector in Albania. We use data from the Albania Living Standards Measurement Survey 2002 and 2005. The pooled samples include 707 individuals who have visited inpatient health care services in these 2 years. Our results show that medical staff has less information on the patients' maximum willingness to pay informally than patients have on medical staff's minimum expected amount. These estimates do not depend on categories of illnesses but on certain socio-demographic characteristics. PMID:21691842

  1. The hydrological model of the Mahanagdong sector, Greater Tongonan Geothermal Field, Philippines

    SciTech Connect

    Herras, E.B.; Licup, A.C. Jr.; Vicedo, R.O.

    1996-12-31

    The Mahanagdong sector of the Greater Tongonan Geothermal Field is committed to supply 180 MWe of steam by mid-1997. An updated hydrological model was constructed based on available geoscientific and reservoir engineering data from a total of 34 wells drilled in the area. The Mahanagdong; resource is derived from a fracture-controlled and volcano hosted geothermal system characterized by neutral to slightly alkali-chloride fluids with reservoir temperatures exceeding 295{degrees}C. A major upflow region was identified in the vicinity of MG-3D, MG-14D and MG-5D. Isochemical contours indicate outflowing fluids with temperatures of 270-275{degrees}C to the south and west. Its southwesterly flow is restricted by the intersection of the impermeable Mahanagdong Claystone near MG-10D, which delimits the southern part of the resource. Low temperature (<200{degrees}C), shallow inflows are evident at the west near MG-4D and MG-17D wells which act as a cold recharge in this sector.

  2. Use of the Edmonds-Reilly Model to model energy-sector impacts of greenhouse gas emissions control strategies

    SciTech Connect

    Barns, D.W.; Edmonds, J.A.; Reilly, J.M.

    1992-01-01

    The purpose of this paper is to document the results of our application of the Edmonds-Reilly Model (ERM) using several scenarios provided in connection with the 1991 Energy Modeling Forum (EMF). The purpose of this session of the forum is to compare the efforts of several modeling teams using common assumptions to examine the energy sector impacts of strategies to control greenhouse gas emissions. Because the output of this exercise is data-rich, most of this exposition is in graphical form with the narrative serving mainly as a roadmap for moving from one highlight to the next. The following sessions briefly describe the model and some of the special modifications made for this effort. The case-by-case discussion is contained in Section IV, followed by a summary of the potential pitfalls involved in attempting to assess the cost of emissions reduction from the model data.

  3. GREENHOUSE GAS MITIGATION POTENTIAL IN U.S. FORESTRY AND AGRICULTURE

    EPA Science Inventory

    This report describes the FASOM-GHG model (Forestry and Agriculture Sector Optimization Model with Greenhouse Gases), the GHG mitigation scenarios for U.S. forestry and agriculture run through the FASOM-GHG model, and the results and insights that are generated. GHG mitigation po...

  4. Modelling of agricultural combination driver behaviour from the aspect of safety of movement.

    PubMed

    Szczepaniak, Jan; Tanaś, Wojciech; Pawłowski, Tadeusz; Kromulski, Jacek

    2014-01-01

    Statistics show that the travel of agricultural machinery to a work area and their movement during labour is the source of many serious accidents. The most dangerous in consequences prove to be those that occur during transport and associated with maneuvering tractors and machinery (about 30% of all fatal accidents). It can be assumed that at least some of these accidents were caused indirectly by the specific design features of agricultural machines which adversely affect the driveability. The single- and multi-loop structures of the driver-vehicle system models are formulated to study the contributions of various preview and prediction strategies to the path tracking and dynamic performance of the articulated vehicle. In the presented study the compensatory model of driver utilizes the lateral acceleration of the tractor, roll angle of trailer sprung mass and the articulation rate as the internal motion feedback variables. The control model of steering of an agricultural set has been implemented in the Matlab/Simulink environment. The model has been constructed with the use of stochastic methods and operational transmittances describing the various components of the system. The model operational transmittances has been estimated using Box-Jenkins and continuous-time process models from input-output data. The model has been tested using experimental data from road investigation of the agricultural set. PMID:24959798

  5. The Agricultural Model Intercomparison and Improvement Project (AgMIP) Town Hall

    NASA Technical Reports Server (NTRS)

    Ruane, Alex; Rosenzweig, Cynthia; Kyle, Page; Basso, Bruno; Winter, Jonathan; Asseng, Senthold

    2015-01-01

    AgMIP (www.agmip.org) is an international community of climate, crop, livestock, economics, and IT experts working to further the development and application of multi-model, multi-scale, multi-disciplinary agricultural models that can inform policy and decision makers around the world. This meeting will engage the AGU community by providing a brief overview of AgMIP, in particular its new plans for a Coordinated Global and Regional Assessment of climate change impacts on agriculture and food security for AR6. This Town Hall will help identify opportunities for participants to become involved in AgMIP and its 30+ activities.

  6. Model documentation report: Industrial sector demand module of the national energy modeling system

    SciTech Connect

    1998-01-01

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirements of the Energy Information Administration (EIA) to provide adequate documentation in support of its model. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

  7. Survey review of models for use in market penetration analysis: utility sector focus

    SciTech Connect

    Groncki, P.J.; Kydes, A.S.; Lamontagne, J.; Marcuse, W.; Vinjamuri, G.

    1980-11-01

    The ultimate benefits of federal expenditures in research and development for new technologies are dependent upon the degree of acceptance of these technologies. Market penetration considerations are central to the problem of quantifying the potential benefits. These benefits are inputs to the selection process of projects competing for finite R and D funds. Market penetration is the gradual acceptance of a new commodity or technology. The Office of Coal utilization is concerned with the specialized area of market penetration of new electric power generation technologies for both replacement and new capacity. The common measure of market penetration is the fraction of the market serviced by the challenging technology for each time point considered. The methodologies for estimating market penetration are divided into three generic classes: integrated energy/economy modeling systems, utility capacity expansion models, and technology substitution models. In general, the integrated energy/economy modeling systems have three advantages: they provide internally consistent macro, energy-economy scenarios, they account for the effect of prices on demand by fuel form, and they explicitly capture the effects of population growth and the level and structure of economic activity on energy demand. A variety of deficiencies appear in most energy-economy systems models. All of the methodologies may be applied at some level to questions of market penetration of new technologies in the utility sector; choice of methods for a particular analysis must be conditioned by the scope of the analysis, data availability, and the relative cost of alternative analysis.

  8. Probing the Higgs sector of high-scale supersymmetry-breaking models at the Tevatron.

    SciTech Connect

    Carena, M.; Draper, P.; Heinemeyer, S.; Liu, T.; Wagner, C. E. M.; Weiglein, G.

    2011-03-07

    A canonical signature of the minimal supersymmetric standard model (MSSM) is the presence of a neutral Higgs boson with mass bounded from above by about 135 GeV and standard model (SM)-like couplings to the electroweak gauge bosons. In this paper we investigate the reach of the Tevatron collider for the MSSM Higgs sector parameter space associated with a variety of high-scale minimal models of supersymmetry (SUSY) breaking, including the constrained MSSM, minimal gauge-mediated SUSY breaking, and minimal anomaly-mediated SUSY breaking. We find that the Tevatron can provide strong constraints on these models via Higgs boson searches. Considering a simple projection for the efficiency improvements in the Tevatron analyses, we find that with an integrated luminosity of 16 fb{sup -1} per detector and an efficiency improvement of 20% compared to the present situation, these models could be probed essentially over their entire ranges of validity. With 40% analysis improvements and 16 fb{sup -1}, our projection shows that evidence at the 3{sigma} level for the light Higgs boson could be expected in extended regions of parameter space.

  9. Probing the Higgs sector of high-scale supersymmetry-breaking models at the Tevatron

    SciTech Connect

    Carena, Marcela; Draper, Patrick; Heinemeyer, Sven; Liu, Tao; Wagner, Carlos E. M.; Weiglein, Georg

    2011-03-01

    A canonical signature of the minimal supersymmetric standard model (MSSM) is the presence of a neutral Higgs boson with mass bounded from above by about 135 GeV and standard model (SM)-like couplings to the electroweak gauge bosons. In this paper we investigate the reach of the Tevatron collider for the MSSM Higgs sector parameter space associated with a variety of high-scale minimal models of supersymmetry (SUSY) breaking, including the constrained MSSM, minimal gauge-mediated SUSY breaking, and minimal anomaly-mediated SUSY breaking. We find that the Tevatron can provide strong constraints on these models via Higgs boson searches. Considering a simple projection for the efficiency improvements in the Tevatron analyses, we find that with an integrated luminosity of 16 fb{sup -1} per detector and an efficiency improvement of 20% compared to the present situation, these models could be probed essentially over their entire ranges of validity. With 40% analysis improvements and 16 fb{sup -1}, our projection shows that evidence at the 3{sigma} level for the light Higgs boson could be expected in extended regions of parameter space.

  10. US Clean Energy Sector and the Opportunity for Modeling and Simulation

    NASA Technical Reports Server (NTRS)

    Inge, Carole Cameron

    2011-01-01

    The following paper sets forth the current understanding of the US clean energy demand and opportunity. As clean energy systems come online and technology is developed, modeling and simulation of these complex energy programs provides an untapped business opportunity. The US Department of Defense provides a great venue for developing new technology in the energy sector because it is demanding lower fuel costs, more energy efficiencies in its buildings and bases, and overall improvements in its carbon footprint. These issues coupled with the security issues faced by foreign dependence on oil will soon bring more clean energy innovations to the forefront (lighter batteries for soldiers, alternative fuel for jets, energy storage systems for ships, etc).

  11. The photino sector and a confining potential in a supersymmetric Lorentz-symmetry-violating model

    NASA Astrophysics Data System (ADS)

    Belich, H.; Bernald, L. D.; Gaete, Patricio; Helayël-Neto, J. A.

    2013-11-01

    We study the spectrum of the minimal supersymmetric extension of the Carroll-Field-Jackiw model for Electrodynamics with a topological Chern-Simons-like Lorentz-symmetry violating term. We identify a number of independent background fermion condensates, work out the gaugino dispersion relation and propose a photonic effective action to consider aspects of confinement induced by the SUSY background fermion condensates, which also appear to signal Lorentz-symmetry violation in the photino sector of the action. Our calculations of the static potential are carried out within the framework of the gauge-invariant but path-dependent variables formalism which are alternative to the Wilson loop approach. Our results show that the interaction energy contains a linear term leading to the confinement of static probe charges.

  12. Modeling soil processes for adapting agricultural systems to climate variability and change

    NASA Astrophysics Data System (ADS)

    Basso, B.

    2014-12-01

    Climate change, drought, and agricultural intensification are increasing the demand for enhanced resource use efficiency (water, nitrogen and radiation). There is a global consensus between climate and agricultural scientists about the need to quantify the likely impacts of climate change on crop yields due to their significant consequences on food prices as well as the global economy. Crop models have been extensively tested for yields, but their validation for soil water balance, and carbon and nitrogen cycling in agricultural systems has been limited. The objective of this research is to illustrate the importance of modeling soil processes correctly to identify management strategy that allow cropping systems to adapt to climate variability and change. Results from the first phase of the AgMIP soil and crop rotation initiative will also be discussed.

  13. General relativistic, nonstandard model for the dark sector of the Universe

    NASA Astrophysics Data System (ADS)

    Stichel, P. C.; Zakrzewski, W. J.

    2015-01-01

    We present a general relativistic version of the self-gravitating fluid model for the dark sector of the Universe (darkon fluid) introduced in Stichel and Zakrzewski (Phys Rev D 80:083513, 2009) and extended and reviewed in Stichel and Zakrzewski (Entropy 15:559, 2013). This model contains no free parameters in its Lagrangian. The resulting energy-momentum tensor is dustlike with a nontrivial energy flow. In an approximation valid at sub-Hubble scales we find that the present-day cosmic acceleration is not attributed to any kind of negative pressure but it is due to a dynamically determined negative energy density. This property turns out to be equivalent to a time-dependent spatial curvature. The obtained cosmological equations, at sub-Hubble scales, agree with those of the nonrelativistic model but they are given a new physical interpretation. Furthermore, we have derived the self-consistent equation to be satisfied by the nonrelativistic gravitational potential produced by a galactic halo in our model from a weak-field limit of a generalized Tolman-Oppenheimer-Volkoff equation.

  14. Global emission projections for the transportation sector using dynamic technology modeling

    NASA Astrophysics Data System (ADS)

    Yan, F.; Winijkul, E.; Streets, D. G.; Lu, Z.; Bond, T. C.; Zhang, Y.

    2013-09-01

    In this study, global emissions of gases and particles from the transportation sector are projected from the year 2010 to 2050. The Speciated Pollutant Emission Wizard (SPEW)-Trend model, a dynamic model that links the emitter population to its emission characteristics, is used to project emissions from on-road vehicles and non-road engines. Unlike previous models of global emission estimates, SPEW-Trend incorporates considerable details on the technology stock and builds explicit relationships between socioeconomic drivers and technological changes, such that the vehicle fleet and the vehicle technology shares change dynamically in response to economic development. Emissions from shipping, aviation, and rail are estimated based on other studies so that the final results encompass the entire transportation sector. The emission projections are driven by four commonly-used IPCC scenarios (A1B, A2, B1, and B2). We project that global fossil-fuel use (oil and coal) in the transportation sector will be in the range of 3.0-4.0 Gt across the four scenarios in the year 2030. Corresponding global emissions are projected to be 101-138 Tg of carbon monoxide (CO), 44-54 Tg of nitrogen oxides (NOx), 14-18 Tg of total hydrocarbons (THC), and 3.6-4.4 Tg of particulate matter (PM). At the global level, a common feature of the emission scenarios is a projected decline in emissions during the first one or two decades (2010-2030), because the effects of stringent emission standards offset the growth in fuel use. Emissions increase slightly in some scenarios after 2030, because of the fast growth of on-road vehicles with lax or no emission standards in Africa and increasing emissions from non-road gasoline engines and shipping. On-road vehicles and non-road engines contribute the most to global CO and THC emissions, while on-road vehicles and shipping contribute the most to NOx and PM emissions. At the regional level, Latin America and East Asia are the two largest contributors to

  15. Global emission projections for the transportation sector using dynamic technology modeling

    NASA Astrophysics Data System (ADS)

    Yan, F.; Winijkul, E.; Streets, D. G.; Lu, Z.; Bond, T. C.; Zhang, Y.

    2013-12-01

    In this study, global emissions of gases and particles from the transportation sector are projected from the year 2010 to 2050. The Speciated Pollutant Emission Wizard (SPEW)-Trend model, a dynamic model that links the emitter population to its emission characteristics, is used to project emissions from on-road vehicles and non-road engines. Unlike previous models of global emission estimates, SPEW-Trend incorporates considerable details on the technology stock and builds explicit relationships between socioeconomic drivers and technological changes, such that the vehicle fleet and the vehicle technology shares change dynamically in response to economic development. Emissions from shipping, aviation, and rail are estimated based on other studies so that the final results encompass the entire transportation sector. The emission projections are driven by four commonly-used IPCC scenarios (A1B, A2, B1, and B2). We project that global fossil-fuel use (oil and coal) in the transportation sector will be in the range of 3.0-4.0 Gt across the four scenarios in the year 2030. Corresponding global emissions are projected to be 101-138 Tg of carbon monoxide (CO), 44-54 Tg of nitrogen oxides (NOx), 14-18 Tg of total hydrocarbons (THC), and 3.6-4.4 Tg of particulate matter (PM). At the global level, a common feature of the emission scenarios is a projected decline in emissions during the first one or two decades (2010-2030), because the effects of stringent emission standards offset the growth in fuel use. Emissions increase slightly in some scenarios after 2030, because of the fast growth of on-road vehicles with lax or no emission standards in Africa and increasing emissions from non-road gasoline engines and shipping. On-road vehicles and non-road engines contribute the most to global CO and THC emissions, while on-road vehicles and shipping contribute the most to NOx and PM emissions. At the regional level, Latin America and East Asia are the two largest contributors to

  16. Global emission projections for the transportation sector using dynamic technology modeling

    NASA Astrophysics Data System (ADS)

    Yan, F.; Winijkul, E.; Streets, D. G.; Lu, Z.; Bond, T. C.; Zhang, Y.

    2014-06-01

    In this study, global emissions of gases and particles from the transportation sector are projected from the year 2010 to 2050. The Speciated Pollutant Emission Wizard (SPEW)-Trend model, a dynamic model that links the emitter population to its emission characteristics, is used to project emissions from on-road vehicles and non-road engines. Unlike previous models of global emission estimates, SPEW-Trend incorporates considerable detail on the technology stock and builds explicit relationships between socioeconomic drivers and technological changes, such that the vehicle fleet and the vehicle technology shares change dynamically in response to economic development. Emissions from shipping, aviation, and rail are estimated based on other studies so that the final results encompass the entire transportation sector. The emission projections are driven by four commonly-used IPCC (Intergovernmental Panel on Climate Change) scenarios (A1B, A2, B1, and B2). With global fossil-fuel use (oil and coal) in the transportation sector in the range of 128-171 EJ across the four scenarios, global emissions are projected to be 101-138 Tg of carbon monoxide (CO), 44-54 Tg of nitrogen oxides (NOx), 14-18 Tg of non-methane total hydrocarbons (THC), and 3.6-4.4 Tg of particulate matter (PM) in the year 2030. At the global level, a common feature of the emission scenarios is a projected decline in emissions during the first one or two decades (2010-2030), because the effects of stringent emission standards offset the growth in fuel use. Emissions increase slightly in some scenarios after 2030, because of the fast growth of on-road vehicles with lax or no emission standards in Africa and increasing emissions from non-road gasoline engines and shipping. On-road vehicles and non-road engines contribute the most to global CO and THC emissions, while on-road vehicles and shipping contribute the most to NOx and PM emissions. At the regional level, Latin America and East Asia are the two

  17. A steady state model of agricultural waste pyrolysis: A mini review.

    PubMed

    Trninić, M; Jovović, A; Stojiljković, D

    2016-09-01

    Agricultural waste is one of the main renewable energy resources available, especially in an agricultural country such as Serbia. Pyrolysis has already been considered as an attractive alternative for disposal of agricultural waste, since the technique can convert this special biomass resource into granular charcoal, non-condensable gases and pyrolysis oils, which could furnish profitable energy and chemical products owing to their high calorific value. In this regard, the development of thermochemical processes requires a good understanding of pyrolysis mechanisms. Experimental and some literature data on the pyrolysis characteristics of corn cob and several other agricultural residues under inert atmosphere were structured and analysed in order to obtain conversion behaviour patterns of agricultural residues during pyrolysis within the temperature range from 300 °C to 1000 °C. Based on experimental and literature data analysis, empirical relationships were derived, including relations between the temperature of the process and yields of charcoal, tar and gas (CO2, CO, H2 and CH4). An analytical semi-empirical model was then used as a tool to analyse the general trends of biomass pyrolysis. Although this semi-empirical model needs further refinement before application to all types of biomass, its prediction capability was in good agreement with results obtained by the literature review. The compact representation could be used in other applications, to conveniently extrapolate and interpolate these results to other temperatures and biomass types. PMID:27281226

  18. Study of lepton flavor violation in flavor symmetric models for lepton sector

    NASA Astrophysics Data System (ADS)

    Kobayashi, Tatsuo; Omura, Yuji; Takayama, Fumihiro; Yasuhara, Daiki

    2015-10-01

    Flavor symmetric model is one of the attractive Beyond Standard Models (BSMs) to reveal the flavor structure of the Standard Model (SM). A lot of efforts have been put into the model building and we find many kinds of flavor symmetries and setups are able to explain the observed fermion mass matrices. In this paper, we look for common predictions of physical observables among the ones in flavor symmetric models, and try to understand how to test flavor symmetry in experiments. Especially, we focus on the BSMs for leptons with extra Higgs SU(2) L doublets charged under flavor symmetry. In many flavor models for leptons, remnant symmetry is partially respected after the flavor symmetry breaking, and it controls well the Flavor Changing Neutral Currents (FCNCs) and suggests some crucial predictions against the flavor changing process, although the remnant symmetry is not respected in the full lagrangian. In fact, we see that τ - → e + μ - μ - ( μ + e - e -) and e + e - → τ + τ - ( μ - μ +) processes are the most important in the flavor models that the extra Higgs doublets belong to triplet representation of flavor symmetry. For instance, the stringent constraint from the μ → eγ process could be evaded according to the partial remnant symmetry. We also investigate the breaking effect of the remnant symmetry mediated by the Higgs scalars, and investigate the constraints from the flavor physics: the flavor violating τ and μ decays, the electric dipole moments, and the muon anomalous magnetic moment. We also discuss the correlation between FCNCs and nonzero θ 13, and point out the physical observables in the charged lepton sector to test the BSMs for the neutrino mixing.

  19. Spatial Mapping of Agricultural Water Productivity Using the SWAT Model

    NASA Astrophysics Data System (ADS)

    Thokal, Rajesh Tulshiram; Gorantiwar, S. D.; Kothari, Mahesh; Bhakar, S. R.; Nandwana, B. P.

    2015-03-01

    The Sina river basin is facing both episodic and chronic water shortages due to intensive irrigation development. The main objective of this study was to characterize the hydrologic processes of the Sina river basin and assess crop water productivity using the distributed hydrologic model, SWAT. In the simulation year (1998-1999), the inflow to reservoir from upstream side was the major contributor to the reservoir accounting for 92 % of the total required water release for irrigation purpose (119.5 Mm3), while precipitation accounted for 4.1 Mm3. Annual release of water for irrigation was 119.5 Mm3 out of which 54 % water was diverted for irrigation purpose, 26 % was wasted as conveyance loss, average discharge at the command outlet was estimated as 4 % and annual average ground-water recharge coefficient was in the range of 13-17 %. Various scenarios involving water allocation rule were tested with the goal of increasing economic water productivity values in the Sina Irrigation Scheme. Out of those, only most benefited allocation rule is analyzed in this paper. Crop yield varied from 1.98 to 25.9 t/ha, with the majority of the area between 2.14 and 2.78 t/ha. Yield and WP declined significantly in loamy soils of the irrigation command. Crop productivity in the basin was found in the lower range when compared with potential and global values. The findings suggested that there was a potential to improve further. Spatial variations in yield and WP were found to be very high for the crops grown during rabi season, while those were low for the crops grown during kharif season. The crop yields and WP during kharif season were more in the lower reach of the irrigation commands, where loamy soil is more concentrated. Sorghum in both seasons was most profitable. Sorghum fetched net income fivefold that of sunflower, two and half fold of pearl millet and one and half fold of mung beans as far as crop during kharif season were concerned and it fetched fourfold that of

  20. Basing care reforms on evidence: The Kenya health sector costing model

    PubMed Central

    2011-01-01

    Background The Government of the Republic of Kenya is in the process of implementing health care reforms. However, poor knowledge about costs of health care services is perceived as a major obstacle towards evidence-based, effective and efficient health care reforms. Against this background, the Ministry of Health of Kenya in cooperation with its development partners conducted a comprehensive costing exercise and subsequently developed the Kenya Health Sector Costing Model in order to fill this data gap. Methods Based on standard methodology of costing of health care services in developing countries, standard questionnaires and analyses were employed in 207 health care facilities representing different trustees (e.g. Government, Faith Based/Nongovernmental, private-for-profit organisations), levels of care and regions (urban, rural). In addition, a total of 1369 patients were randomly selected and asked about their demand-sided costs. A standard step-down costing methodology was applied to calculate the costs per service unit and per diagnosis of the financial year 2006/2007. Results The total costs of essential health care services in Kenya were calculated as 690 million Euros or 18.65 Euro per capita. 54% were incurred by public sector facilities, 17% by Faith Based and other Nongovernmental facilities and 23% in the private sector. Some 6% of the total cost is due to the overall administration provided directly by the Ministry and its decentralised organs. Around 37% of this cost is absorbed by salaries and 22% by drugs and medical supplies. Generally, costs of lower levels of care are lower than of higher levels, but health centres are an exemption. They have higher costs per service unit than district hospitals. Conclusions The results of this study signify that the costs of health care services are quite high compared with the Kenyan domestic product, but a major share are fixed costs so that an increasing coverage does not necessarily increase the health

  1. An inexact risk management model for agricultural land-use planning under water shortage

    NASA Astrophysics Data System (ADS)

    Li, Wei; Feng, Changchun; Dai, Chao; Li, Yongping; Li, Chunhui; Liu, Ming

    2016-09-01

    Water resources availability has a significant impact on agricultural land-use planning, especially in a water shortage area such as North China. The random nature of available water resources and other uncertainties in an agricultural system present risk for land-use planning and may lead to undesirable decisions or potential economic loss. In this study, an inexact risk management model (IRM) was developed for supporting agricultural land-use planning and risk analysis under water shortage. The IRM model was formulated through incorporating a conditional value-at-risk (CVaR) constraint into an inexact two-stage stochastic programming (ITSP) framework, and could be used to control uncertainties expressed as not only probability distributions but also as discrete intervals. The measure of risk about the second-stage penalty cost was incorporated into the model so that the trade-off between system benefit and extreme expected loss could be analyzed. The developed model was applied to a case study in the Zhangweinan River Basin, a typical agricultural region facing serious water shortage in North China. Solutions of the IRM model showed that the obtained first-stage land-use target values could be used to reflect decision-makers' opinions on the long-term development plan. The confidence level α and maximum acceptable risk loss β could be used to reflect decisionmakers' preference towards system benefit and risk control. The results indicated that the IRM model was useful for reflecting the decision-makers' attitudes toward risk aversion and could help seek cost-effective agricultural land-use planning strategies under complex uncertainties.

  2. An inexact risk management model for agricultural land-use planning under water shortage

    NASA Astrophysics Data System (ADS)

    Li, Wei; Feng, Changchun; Dai, Chao; Li, Yongping; Li, Chunhui; Liu, Ming

    2015-10-01

    Water resources availability has a significant impact on agricultural land-use planning, especially in a water shortage area such as North China. The random nature of available water resources and other uncertainties in an agricultural system present risk for land-use planning and may lead to undesirable decisions or potential economic loss. In this study, an inexact risk management model (IRM) was developed for supporting agricultural land-use planning and risk analysis under water shortage. The IRM model was formulated through incorporating a conditional value-at-risk (CVaR) constraint into an inexact two-stage stochastic programming (ITSP) framework, and could be used to control uncertainties expressed as not only probability distributions but also as discrete intervals. The measure of risk about the second-stage penalty cost was incorporated into the model so that the trade-off between system benefit and extreme expected loss could be analyzed. The developed model was applied to a case study in the Zhangweinan River Basin, a typical agricultural region facing serious water shortage in North China. Solutions of the IRM model showed that the obtained first-stage land-use target values could be used to reflect decision-makers' opinions on the long-term development plan. The confidence level α and maximum acceptable risk loss β could be used to reflect decisionmakers' preference towards system benefit and risk control. The results indicated that the IRM model was useful for reflecting the decision-makers' attitudes toward risk aversion and could help seek cost-effective agricultural land-use planning strategies under complex uncertainties.

  3. Evaluation of the Precision Agricultural Landscape Modeling System (PALMS) in the Semiarid Texas Southern High Plains

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Accurate models to simulate the soil water balance in semiarid cropping systems are needed to evaluate management practices for soil and water conservation in both irrigated and dryland production systems. The objective of this study was to evaluate the application of the Precision Agricultural Land...

  4. MODELING AND REMOTE SENSING APPLIED TO AGRICULTURE (U.S. AND MEXICO)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The simulation of hydrologic and agricultural processes began over 30 years ago as independent endeavors. Early hydrologic process models focused on the distribution and movement of water across the earth's surface and through the soil mantel with little attention to plants, the primary user of wat...

  5. The Study on "Academic Game"-Oriented English Course Model for Postgraduates in Agricultural Universities

    ERIC Educational Resources Information Center

    Xia, Xinrong

    2010-01-01

    Based on the analysis of the questionnaire survey on learning motivation and learning needs of postgraduates and their demands and suggestions on English teaching, the paper makes a beneficial exploration on English course model for postgraduates in agricultural universities. Under the guidance of academic game theory, the "language skills+…

  6. Evaluation of the precision agricultural landscape modeling system (PALMS) in the semiarid Texas southern high plains

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Accurate models to simulate the soil water balance in semiarid cropping systems are needed to evaluate management practices for soil and water conservation in both irrigated and dryland production systems. The objective of this study was to evaluate the application of the Precision Agricultural Land...

  7. Current Water Deficit Stress Simulations in Selected Agricultural System Simulation Models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    System models, which adequately simulate plant water stress effects, are valuable tools for developing management practices with improved water use efficiency in agriculture. Plants experience water stress when its supply in the soil fails to meet the demand. Although it is easy to define the conc...

  8. PRACTICAL SENSITIVITY AND UNCERTAINTY ANALYSIS TECHNIQUES APPLIED TO AGRICULTURAL SYSTEMS MODELS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We present a practical evaluation framework for analysis of two complex, process-based agricultural system models, WEPP and RZWQM. The evaluation framework combines sensitivity analysis and the uncertainty analysis techniques of first order error analysis (FOA) and Monte Carlo simulation with Latin ...

  9. Teaching Diversified Organic Crop Production Using the Community Supported Agriculture Farming System Model

    ERIC Educational Resources Information Center

    Falk, Constance L.; Pao, Pauline; Cramer, Christopher S.

    2005-01-01

    An organic garden operated as a community supported agriculture (CSA) venture on the New Mexico State University (NMSU) main campus was begun in January 2002. Students enroll in an organic vegetable production class during spring and fall semesters to help manage and work on the project. The CSA model of farming involves the sale of shares to…

  10. A framework for the cross-sectoral integration of multi-model impact projections: land use decisions under climate impacts uncertainties

    NASA Astrophysics Data System (ADS)

    Frieler, K.; Levermann, A.; Elliott, J.; Heinke, J.; Arneth, A.; Bierkens, M. F. P.; Ciais, P.; Clark, D. B.; Deryng, D.; Döll, P.; Falloon, P.; Fekete, B.; Folberth, C.; Friend, A. D.; Gellhorn, C.; Gosling, S. N.; Haddeland, I.; Khabarov, N.; Lomas, M.; Masaki, Y.; Nishina, K.; Neumann, K.; Oki, T.; Pavlick, R.; Ruane, A. C.; Schmid, E.; Schmitz, C.; Stacke, T.; Stehfest, E.; Tang, Q.; Wisser, D.; Huber, V.; Piontek, F.; Warszawski, L.; Schewe, J.; Lotze-Campen, H.; Schellnhuber, H. J.

    2015-07-01

    Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation

  11. World Bank Development Sector Adjustment Operation Life Line to Nigerian Universities: Impact on Information Demand and Supply in the University of Agriculture, Makurdi Library.

    ERIC Educational Resources Information Center

    Ozowa, Vincent Nnamdi

    1995-01-01

    Provides an overview of the rationale behind the World Bank credit line to Nigerian universities and examines the impact of the credit facility on the information demand and supply in the University of Agriculture, Makurdi Library (Nigeria). Discusses problems, such as poor quantity and quality of books and journals, lack of equipment, and lack of…

  12. Transportation Sector Model of the National Energy Modeling System. Volume 2 -- Appendices: Part 2

    SciTech Connect

    1998-01-01

    The attachments contained within this appendix provide additional details about the model development and estimation process which do not easily lend themselves to incorporation in the main body of the model documentation report. The information provided in these attachments is not integral to the understanding of the model`s operation, but provides the reader with opportunity to gain a deeper understanding of some of the model`s underlying assumptions. There will be a slight degree of replication of materials found elsewhere in the documentation, made unavoidable by the dictates of internal consistency. Each attachment is associated with a specific component of the transportation model; the presentation follows the same sequence of modules employed in Volume 1. The following attachments are contained in Appendix F: Fuel Economy Model (FEM)--provides a discussion of the FEM vehicle demand and performance by size class models; Alternative Fuel Vehicle (AFV) Model--describes data input sources and extrapolation methodologies; Light-Duty Vehicle (LDV) Stock Model--discusses the fuel economy gap estimation methodology; Light Duty Vehicle Fleet Model--presents the data development for business, utility, and government fleet vehicles; Light Commercial Truck Model--describes the stratification methodology and data sources employed in estimating the stock and performance of LCT`s; Air Travel Demand Model--presents the derivation of the demographic index, used to modify estimates of personal travel demand; and Airborne Emissions Model--describes the derivation of emissions factors used to associate transportation measures to levels of airborne emissions of several pollutants.

  13. An integrated Modelling framework to monitor and predict trends of agricultural management (iMSoil)

    NASA Astrophysics Data System (ADS)

    Keller, Armin; Della Peruta, Raneiro; Schaepman, Michael; Gomez, Marta; Mann, Stefan; Schulin, Rainer

    2014-05-01

    Agricultural systems lay at the interface between natural ecosystems and the anthroposphere. Various drivers induce pressures on the agricultural systems, leading to changes in farming practice. The limitation of available land and the socio-economic drivers are likely to result in further intensification of agricultural land management, with implications on fertilization practices, soil and pest management, as well as crop and livestock production. In order to steer the development into desired directions, tools are required by which the effects of these pressures on agricultural management and resulting impacts on soil functioning can be detected as early as possible, future scenarios predicted and suitable management options and policies defined. In this context, the use of integrated models can play a major role in providing long-term predictions of soil quality and assessing the sustainability of agricultural soil management. Significant progress has been made in this field over the last decades. Some of these integrated modelling frameworks include biophysical parameters, but often the inherent characteristics and detailed processes of the soil system have been very simplified. The development of such tools has been hampered in the past by a lack of spatially explicit soil and land management information at regional scale. The iMSoil project, funded by the Swiss National Science Foundation in the national research programme NRP68 "soil as a resource" (www.nrp68.ch) aims at developing and implementing an integrated modeling framework (IMF) which can overcome the limitations mentioned above, by combining socio-economic, agricultural land management, and biophysical models, in order to predict the long-term impacts of different socio-economic scenarios on the soil quality. In our presentation we briefly outline the approach that is based on an interdisciplinary modular framework that builds on already existing monitoring tools and model components that are

  14. Agricultural livelihoods in coastal Bangladesh under climate and environmental change--a model framework.

    PubMed

    Lázár, Attila N; Clarke, Derek; Adams, Helen; Akanda, Abdur Razzaque; Szabo, Sylvia; Nicholls, Robert J; Matthews, Zoe; Begum, Dilruba; Saleh, Abul Fazal M; Abedin, Md Anwarul; Payo, Andres; Streatfield, Peter Kim; Hutton, Craig; Mondal, M Shahjahan; Moslehuddin, Abu Zofar Md

    2015-06-01

    Coastal Bangladesh experiences significant poverty and hazards today and is highly vulnerable to climate and environmental change over the coming decades. Coastal stakeholders are demanding information to assist in the decision making processes, including simulation models to explore how different interventions, under different plausible future socio-economic and environmental scenarios, could alleviate environmental risks and promote development. Many existing simulation models neglect the complex interdependencies between the socio-economic and environmental system of coastal Bangladesh. Here an integrated approach has been proposed to develop a simulation model to support agriculture and poverty-based analysis and decision-making in coastal Bangladesh. In particular, we show how a simulation model of farmer's livelihoods at the household level can be achieved. An extended version of the FAO's CROPWAT agriculture model has been integrated with a downscaled regional demography model to simulate net agriculture profit. This is used together with a household income-expenses balance and a loans logical tree to simulate the evolution of food security indicators and poverty levels. Modelling identifies salinity and temperature stress as limiting factors to crop productivity and fertilisation due to atmospheric carbon dioxide concentrations as a reinforcing factor. The crop simulation results compare well with expected outcomes but also reveal some unexpected behaviours. For example, under current model assumptions, temperature is more important than salinity for crop production. The agriculture-based livelihood and poverty simulations highlight the critical significance of debt through informal and formal loans set at such levels as to persistently undermine the well-being of agriculture-dependent households. Simulations also indicate that progressive approaches to agriculture (i.e. diversification) might not provide the clear economic benefit from the perspective of

  15. Assessment of suspended matter transport in a large agricultural catchment using the MOHID water modelling system

    NASA Astrophysics Data System (ADS)

    David, Bailly; David, Brito; Chantha, Oeurng; Ramiro, Neves; Sabine, Sauvage; Sánchez-Pérez, José-Miguel

    2010-05-01

    Suspended sediment transport from agricultural catchments to stream networks is responsible for impaired water quality, reservoir sedimentation and the transport of sediment-bound pollutants (pesticides, particulate nutrients, metals and other adsorbed toxic substances). The dynamic of pollutants adsorbed on sediment and associated with particulate organic carbon, from land areas into stream network arises mainly from erosion and sedimentation processes. It is known that up to 90% of suspended sediment is transported during flood event and therefore quick flood events have a major impact on pollutant transport. This study - part of the EU AguaFlash (http://www.aguaflash-sudoe.eu/) project - examined and quantified suspended sediment dynamics from catchment to river (erosion, transport, deposition on hillside and in the river). Semi-distributed, physics-based watershed or reservoir models are generally used to simulate sediment dynamics. One of the limitations of this kind of modelling is that transport along agricultural field and the possibility of deposition of suspended sediments in hillslopes are not considered. Consequently, all sediments eroded are assumed to be accumulated in the river and the sediment and associated pollutant dynamics are over- or under-estimated. In our approach, the mechanistic physics-based water modelling system MOHID (http://www.mohid.com) was used to quantify soil erosion and sediment transport processes at the local and macroscopic scale. This paper present the erosion and transport mathematical model and modelling strategy used and compares our initial results with filed data obtained on an 1100 km² intensive agricultural catchment (Save catchment, South-west France) during 2007-2009 and with simulation data produced using SWAT (Soil and Water Assessment Tool, 2005 version). The contribution of the MOHID model compared with that of the semi-distributed SWAT model is discussed. Keywords: Erosion, suspended sediment, transport

  16. A pesticide runoff model for simulating runoff losses of pesticides from agricultural lands.

    PubMed

    Li, Y R; Huang, G H; Li, Y F; Struger, J; Fischer, J D

    2003-01-01

    An integrated modeling system was developed to predict runoff losses of pesticides from agricultural lands. The system is an integration of a mathematical model, a database system, and a geographic information system. Information on soil type, land use, land slope, watershed boundaries, precipitation, pesticide usage, as well as physical and chemical properties of pesticides have been input to a GIS, managed through a database, and used for further modeling studies. The modeling outputs were in turn put into the database, such that runoff patterns along with pesticides losses could be further simulated by using a database management system. The final results could then be visualized through GIS. The developed modeling system was applied to the Kintore Creek Watershed, Ontario, Canada, for simulating losses of atrazine from agricultural lands. A water quality monitoring project was carried out from 1988 to 1992 in the watershed to detect conditions of surface water pollution due to the use of pesticides. The modeling outputs were verified through the monitoring data, demonstrating reasonable prediction accuracy. The result indicated that the model provides an effective means for forecasting pesticide runoff from agriculture lands. PMID:12578171

  17. Modelling mitigation options to reduce diffuse nitrogen water pollution from agriculture.

    PubMed

    Bouraoui, Fayçal; Grizzetti, Bruna

    2014-01-15

    Agriculture is responsible for large scale water quality degradation and is estimated to contribute around 55% of the nitrogen entering the European Seas. The key policy instrument for protecting inland, transitional and coastal water resources is the Water Framework Directive (WFD). Reducing nutrient losses from agriculture is crucial to the successful implementation of the WFD. There are several mitigation measures that can be implemented to reduce nitrogen losses from agricultural areas to surface and ground waters. For the selection of appropriate measures, models are useful for quantifying the expected impacts and the associated costs. In this article we review some of the models used in Europe to assess the effectiveness of nitrogen mitigation measures, ranging from fertilizer management to the construction of riparian areas and wetlands. We highlight how the complexity of models is correlated with the type of scenarios that can be tested, with conceptual models mostly used to evaluate the impact of reduced fertilizer application, and the physically-based models used to evaluate the timing and location of mitigation options and the response times. We underline the importance of considering the lag time between the implementation of measures and effects on water quality. Models can be effective tools for targeting mitigation measures (identifying critical areas and timing), for evaluating their cost effectiveness, for taking into consideration pollution swapping and considering potential trade-offs in contrasting environmental objectives. Models are also useful for involving stakeholders during the development of catchments mitigation plans, increasing their acceptability. PMID:23998504

  18. Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

    NASA Technical Reports Server (NTRS)

    Glotter, Michael J.; Ruane, Alex C.; Moyer, Elisabeth J.; Elliott, Joshua W.

    2015-01-01

    Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

  19. Identifying Hydrologic Processes in Agricultural Watersheds Using Precipitation-Runoff Models

    USGS Publications Warehouse

    Linard, Joshua I.; Wolock, David M.; Webb, Richard M.T.; Wieczorek, Michael E.

    2009-01-01

    Understanding the fate and transport of agricultural chemicals applied to agricultural fields will assist in designing the most effective strategies to prevent water-quality impairments. At a watershed scale, the processes controlling the fate and transport of agricultural chemicals are generally understood only conceptually. To examine the applicability of conceptual models to the processes actually occurring, two precipitation-runoff models - the Soil and Water Assessment Tool (SWAT) and the Water, Energy, and Biogeochemical Model (WEBMOD) - were applied in different agricultural settings of the contiguous United States. Each model, through different physical processes, simulated the transport of water to a stream from the surface, the unsaturated zone, and the saturated zone. Models were calibrated for watersheds in Maryland, Indiana, and Nebraska. The calibrated sets of input parameters for each model at each watershed are discussed, and the criteria used to validate the models are explained. The SWAT and WEBMOD model results at each watershed conformed to each other and to the processes identified in each watershed's conceptual hydrology. In Maryland the conceptual understanding of the hydrology indicated groundwater flow was the largest annual source of streamflow; the simulation results for the validation period confirm this. The dominant source of water to the Indiana watershed was thought to be tile drains. Although tile drains were not explicitly simulated in the SWAT model, a large component of streamflow was received from lateral flow, which could be attributed to tile drains. Being able to explicitly account for tile drains, WEBMOD indicated water from tile drains constituted most of the annual streamflow in the Indiana watershed. The Nebraska models indicated annual streamflow was composed primarily of perennial groundwater flow and infiltration-excess runoff, which conformed to the conceptual hydrology developed for that watershed. The hydrologic

  20. Evaluation of groundwater pollution risk (GPR) from agricultural activities using DRASTIC model and GIS

    NASA Astrophysics Data System (ADS)

    Mohd Ariffin, Sabrina; Zawawi, Mohamed Azwan Mohamed; Che Man, Hasfalina

    2016-06-01

    Groundwater Pollution risk (GPR) map which utilized groundwater quality is important in order to prevent the groundwater contaminant concentration due to the agricultural activities. DRASTIC model and GIS application are two important tools that had been used for accessing and predicting the quality of groundwater. These supplementary tools are calculating, visualizing, and presenting the GPR by using DRASTIC index for each hydrogeologic factor through ArcGIS software. This study was covered approximately Selangor basin area where the GPR has been defined. There are four categories of agricultural activities in the Selangor basin which are animal husbandary areas, horticultural lands, short term crops and tree, palm and other permanent crops. The map showed that the “low” zones of GPR occupied 56% of the east side of the Selangor basin, 34% of the west side of the Selangor basin exposed to “medium” zones of GPR and the “high” zones of GPR covered 10% at the north side and the south to the west side of the Selangor basin. As a particular, for agricultural activities which is 52% of Selangor basin area, the “low”, ‘’medium” and “high” zones of GPR was occupied as 42%, 43% and 15% respectively. Based on four categories of agricultural landuse, GPR map validated by nitrate distribution map, shows that the 99% of the variation in nitrate distribution zones are explained by GPR zones. In conclusion, groundwater pollution risk was affected by agricultural activities.

  1. Preparing Rehabilitation Counselors for Private Sector Practice within a CORE Accredited Generalist Educational Model

    ERIC Educational Resources Information Center

    Zanskas, Stephen; Leahy, Michael

    2007-01-01

    As private sector rehabilitation has matured as a field of practice, the issue of how rehabilitation counselor educators can effectively prepare rehabilitation counselors for practice in this setting remains. This article reviews the literature regarding the training needs of rehabilitation counselors entering private sector practice, and proposes…

  2. Modeling the impact of conservation agriculture on crop production and soil properties in Mediterranean climate

    NASA Astrophysics Data System (ADS)

    Moussadek, Rachid; Mrabet, Rachid; Dahan, Rachid; Laghrour, Malika; Lembiad, Ibtissam; ElMourid, Mohamed

    2015-04-01

    In Morocco, rainfed agriculture is practiced in the majority of agricultural land. However, the intensive land use coupled to the irregular rainfall constitutes a serious threat that affect country's food security. Conservation agriculture (CA) represents a promising alternative to produce more and sustainably. In fact, the direct seeding showed high yield in arid regions of Morocco but its extending to other more humid agro-ecological zones (rainfall > 350mm) remains scarce. In order to promote CA in Morocco, differents trials have been installed in central plateau of Morocco, to compare CA to conventional tillage (CT). The yields of the main practiced crops (wheat, lentil and checkpea) under CA and CT were analyzed and compared in the 3 soils types (Vertisol, Cambisol and Calcisol). Also, we studied the effect of CA on soil organic matter (SOM) and soil losses (SL) in the 3 different sites. The APSIM model was used to model the long term impact of CA compared to CT. The results obtained in this research have shown favorable effects of CA on crop production, SOM and soil erosion. Key words: Conservation agriculture, yield, soil properties, modeling, APSIM, Morocco.

  3. Modelling of the atmospheric dispersion of mercury emitted from the power sector in Poland

    NASA Astrophysics Data System (ADS)

    Zyśk, J.; Roustan, Y.; Wyrwa, A.

    2015-07-01

    Poland belongs to the group of EU countries with the highest levels of mercury emissions, with a large portion of these emissions being related to coal combustion. This paper presents a modelling analysis of the impact that the Polish power sector has on the atmospheric concentrations of mercury. A detailed mercury emission inventory is used to analyse the concentration and deposition of mercury. For this study, a chemical scheme devoted to mercury transformations in the atmosphere was implemented into the Polyphemus air quality system. The system was then used to perform simulations for 2008 in two domains i.e. over Europe and over Poland. The impact of various parameters on concentration and wet scavenging of mercury has been analysed. The results of the mercury ambient concentrations and depositions, are presented. Additionally, the contribution of natural and anthropogenic sources to mercury deposition in Poland is shown. The performed works showed that the national sources have low impact to overall deposition, however local contribution in wet deposition of big emitters may reach 50%. Sensitive analysis showed a significant impact of reaction with bromine compound and scavenging coefficient on modelled results of mercury concentration and deposition.

  4. Conjunctive-Use Modeling and Irrigated Agriculture, Yaqui Valley, Sonora, Mexico

    NASA Astrophysics Data System (ADS)

    Addams, L.; Gorelick, S. M.

    2001-12-01

    The Yaqui Valley, a productive irrigated agricultural region in northwestern Mexico and home to the "Green Revolution" for wheat, finds itself with crucial water management challenges. With only 24cm annual precipitation, this coastal plain region is highly dependent upon surface runoff from the 72,000 km2 Yaqui River basin, of which approximately 2800MCM is available annually for irrigation of 228,000 ha. The use of the marginally-saline coastal aquifers have been historically a small part of the water supply for the wheat/maize based agricultural region, averaging around 260MCM each year. However, with persistent drought and continued municipal/industrial growth in the Yaqui Valley, future optimal water resource policy will undoubtedly include the increased use of groundwater mixed with Yaqui River water while maintaining salinity levels for acceptable crop yields. Thus, the mixing aspects of conjunctive use must be considered, with maximum benefits occurring where groundwater extraction and quality are managed both spatially and temporally. We are developing an infiltration/groundwater flow model of sufficient detail to more fully describe the effects of policy change on groundwater utilization in the Yaqui, as well as explore possibilities for innovative management tools in the future. Some early results from a three-layer groundwater flow model are presented, representing connections between surficial agricultural infiltration, open irrigation drains, and deeper groundwater supplies. Aquifer inflow derives from canal leakance, the Yaqui River, and excess irrigation, with outflows from the aquifer system occurring via 2600 km of agricultural drains, evapotranspiration, agricultural pumping, and subsurface flows to estuarine environments. The model has been calibrated to pumping and infiltration flows, and to piezometric levels in approximately 900 deep wells measured at intervals during the model period from 1970 to 2000. This preliminary work will lay the

  5. GlobWat - a global water balance model to assess water use in irrigated agriculture

    NASA Astrophysics Data System (ADS)

    Hoogeveen, J.; Faurès, J.-M.; Peiser, L.; Burke, J.; van de Giesen, N.

    2015-09-01

    GlobWat is a freely distributed, global soil water balance model that is used by the Food and Agriculture Organization (FAO) to assess water use in irrigated agriculture, the main factor behind scarcity of freshwater in an increasing number of regions. The model is based on spatially distributed high-resolution data sets that are consistent at global level and calibrated against values for internal renewable water resources, as published in AQUASTAT, the FAO's global information system on water and agriculture. Validation of the model is done against mean annual river basin outflows. The water balance is calculated in two steps: first a "vertical" water balance is calculated that includes evaporation from in situ rainfall ("green" water) and incremental evaporation from irrigated crops. In a second stage, a "horizontal" water balance is calculated to determine discharges from river (sub-)basins, taking into account incremental evaporation from irrigation, open water and wetlands ("blue" water). The paper describes the methodology, input and output data, calibration and validation of the model. The model results are finally compared with other global water balance models to assess levels of accuracy and validity.

  6. Comparison of models used for national agricultural ammonia emission inventories in Europe: Liquid manure systems

    NASA Astrophysics Data System (ADS)

    Reidy, B.; Dämmgen, U.; Döhler, H.; Eurich-Menden, B.; van Evert, F. K.; Hutchings, N. J.; Luesink, H. H.; Menzi, H.; Misselbrook, T. H.; Monteny, G.-J.; Webb, J.

    Ammonia (NH 3) emissions from agriculture commonly account for >80% of the total NH 3 emissions. Accurate agricultural NH 3 emission inventories are therefore required for reporting within the framework of the Gothenburg Protocol of the UN Convention on Long-range Transboundary Air Pollution. To allow a co-ordinated implementation of the Protocol, different national inventories should be comparable. A core group of emission inventory experts therefore developed a network and joint programme to achieve a detailed overview of the best inventory techniques currently available and compiled and harmonized the available knowledge on emission factors (EFs) for nitrogen (N)-flow emission calculation models and initiated a new generation of emission inventories. As a first step in summarizing the available knowledge, six N-flow models, used to calculate national NH 3 emissions from agriculture in different European countries, were compared using standard datasets. Two scenarios for slurry-based systems were run separately for dairy cattle and for pigs, with three different levels of model standardisation: (a) standardised inputs to all models (FF scenario); (b) standard N excretion, but national values for EFs (FN scenario); (c) national values for N excretion and EFs (NN scenario). Results of the FF scenario showed very good agreement among models, indicating that the underlying N flows of the different models are highly similar. As a result of the different national EFs and N excretion rates, larger differences among the results were observed for the FN and the NN scenarios. Reasons for the differences were primarily attributed to differences in the agricultural practices and climatic factors reflected in the EFs and the N excretion rates. The scientific debate necessary to understand the variation in the results generated awareness and consensus concerning available scientific data and the importance of specific processes not yet included in some models.

  7. The Agricultural Model Intercomparison and Improvement Project (AgMIP): Progress and Preliminary Results

    NASA Astrophysics Data System (ADS)

    Rosenzweig, C.

    2011-12-01

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation exercise for historical model intercomparison and future climate change conditions with participation of multiple crop and agricultural trade modeling groups around the world. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Recent progress and the current status of AgMIP will be presented, highlighting three areas of activity: preliminary results from crop pilot studies, outcomes from regional workshops, and emerging scientific challenges. AgMIP crop modeling efforts are being led by pilot studies, which have been established for wheat, maize, rice, and sugarcane. These crop-specific initiatives have proven instrumental in testing and contributing to AgMIP protocols, as well as creating preliminary results for aggregation and input to agricultural trade models. Regional workshops are being held to encourage collaborations and set research activities in motion for key agricultural areas. The first of these workshops was hosted by Embrapa and UNICAMP and held in Campinas, Brazil. Outcomes from this meeting have informed crop modeling research activities within South America, AgMIP protocols, and future regional workshops. Several scientific challenges have emerged and are currently being addressed by AgMIP researchers. Areas of particular interest include geospatial weather generation, ensemble methods for climate scenarios and crop models, spatial aggregation of field-scale yields to regional and global production, and characterization of future changes in climate variability.

  8. ImSET 3.1: Impact of Sector Energy Technologies Model Description and User's Guide

    SciTech Connect

    Scott, Michael J.; Livingston, Olga V.; Balducci, Patrick J.; Roop, Joseph M.; Schultz, Robert W.

    2009-05-22

    This 3.1 version of the Impact of Sector Energy Technologies (ImSET) model represents the next generation of the previously-built ImSET model (ImSET 2.0) that was developed in 2005 to estimate the macroeconomic impacts of energy-efficient technology in buildings. In particular, a special-purpose version of the Benchmark National Input-Output (I-O) model was designed specifically to estimate the national employment and income effects of the deployment of Office of Energy Efficiency and Renewable Energy (EERE)–developed energy-saving technologies. In comparison with the previous versions of the model, this version features the use of the U.S. Bureau of Economic Analysis 2002 national input-output table and the central processing code has been moved from the FORTRAN legacy operating environment to a modern C++ code. ImSET is also easier to use than extant macroeconomic simulation models and incorporates information developed by each of the EERE offices as part of the requirements of the Government Performance and Results Act. While it does not include the ability to model certain dynamic features of markets for labor and other factors of production featured in the more complex models, for most purposes these excluded features are not critical. The analysis is credible as long as the assumption is made that relative prices in the economy would not be substantially affected by energy efficiency investments. In most cases, the expected scale of these investments is small enough that neither labor markets nor production cost relationships should seriously affect national prices as the investments are made. The exact timing of impacts on gross product, employment, and national wage income from energy efficiency investments is not well-enough understood that much special insight can be gained from the additional dynamic sophistication of a macroeconomic simulation model. Thus, we believe that this version of ImSET is a cost-effective solution to estimating the economic

  9. PATHWAY: a simulation model of radionuclide-transport through agricultural food chains

    SciTech Connect

    Kirchner, T.B.; Whicker, F.W.; Otis, M.D.

    1982-01-01

    PATHWAY simulates the transport of radionuclides from fallout through an agricultural ecosystem. The agro-ecosystem is subdivided into several land management units, each of which is used either for grazing animals, for growing hay, or for growing food crops. The model simulates the transport of radionuclides by both discrete events and continuous, time-dependent processes. The discrete events include tillage of soil, harvest and storage of crops,and deposition of fallout. The continuous processes include the transport of radionuclides due to resuspension, weathering, rain splash, percolation, leaching, adsorption and desorption of radionuclides in the soil, root uptake, foliar absorption, growth and senescence of vegetation, and the ingestion assimilation, and excretion of radionuclides by animals. Preliminary validation studies indicate that the model dynamics and simulated values of radionuclide concentrations in several agricultural products agree well with measured values when the model is driven with site specific data on deposition from world-wide fallout.

  10. A watershed modeling framework for phosphorus loading from residential and agricultural sources.

    PubMed

    Sinclair, Andrew; Jamieson, Rob; Madani, Ali; Gordon, Robert J; Hart, William; Hebb, Dale

    2014-07-01

    Phosphorus (P) loading from residential onsite wastewater systems (OWSs) into neighboring surface waters is a poorly understood process in rural watersheds; this can be further challenged when rural residential dwellings are intermixed with agricultural land use. The objectives of this research were (i) to design a P onsite wastewater simulator (POWSIM) to assess P loads from individual or clusters of residential OWSs typically used in Nova Scotia, Canada; and (ii) to simulate OWS P loads in a mixed agricultural watershed (Thomas Brook Watershed [TBW], NS) using the Soil and Water Assessment Tool (SWAT) model in conjunction with POWSIM, to predict and compare P loading from agricultural and residential sources. The POWSIM loading tool has three computational components: (i) disposal field selection and treatment media mass calculation, (ii) disposal field P treatment dynamics, and (iii) soil subsurface plume P treatment dynamics. The combination TBW POWSIM and SWAT modeling approach produced a better simulation of baseflow total P (TP) loads in both a predominantly residential subcatchment and one dominated by agriculture than the SWAT model without POWSIM. The residential subcatchment had 48% of its average annual land use TP load (simulated) contributed by OWSs, whereas the agricultural subcatchment had 39%. Watershed-scale sensitivity analyses of POWSIM input parameters for 18- and 50-yr OWS operation periods found the P loading rate into the disposal field, long-term P removal rates in the disposal field and soil systems, soil maximum P sorption capacity, and mass of native soil involved in P treatment to be most sensitive. PMID:25603083

  11. Representative Agricultural Pathways: A Trans-Disciplinary Approach to Agricultural Model Inter-comparison, Improvement, Climate Impact Assessment and Stakeholder Engagement

    NASA Astrophysics Data System (ADS)

    Antle, J. M.; Valdivia, R. O.; Claessens, L.; Nelson, G. C.; Rosenzweig, C.; Ruane, A. C.; Vervoort, J.

    2013-12-01

    The global change research community has recognized that new pathway and scenario concepts are needed to implement impact and vulnerability assessment that is logically consistent across local, regional and global scales. For impact and vulnerability assessment, new socio-economic pathway and scenario concepts are being developed. Representative Agricultural Pathways (RAPs) are designed to extend global pathways to provide the detail needed for global and regional assessment of agricultural systems. In addition, research by the Agricultural Model Inter-comparison and Improvement Project (AgMIP) shows that RAPs provide a powerful way to engage stakeholders in climate-related research throughout the research process and in communication of research results. RAPs are based on the integrated assessment framework developed by AgMIP. This framework shows that both bio-physical and socio-economic drivers are essential components of agricultural pathways and logically precede the definition of adaptation and mitigation scenarios that embody associated capabilities and challenges. This approach is based on a trans-disciplinary process for designing pathways and then translating them into parameter sets for bio-physical and economic models that are components of agricultural integrated assessments of climate impact, adaptation and mitigation. RAPs must be designed to be part of a logically consistent set of drivers and outcomes from global to regional and local. Global RAPs are designed to be consistent with higher-level global socio-economic pathways, but add key agricultural drivers such as agricultural growth trends that are not specified in more general pathways, as illustrated in a recent inter-comparison of global agricultural models. To create pathways at regional or local scales, further detail is needed. At this level, teams of scientists and other experts with knowledge of the agricultural systems and regions work together through a step-wise process. Experiences

  12. Enhancing research capacity across healthcare and higher education sectors: development and evaluation of an integrated model

    PubMed Central

    2012-01-01

    Background With current policy in healthcare research, in the United Kingdom and internationally, focused on development of research excellence in individuals and teams, building capacity for implementation and translation of research is paramount among the professionals who use that research in daily practice. The judicious use of research outcomes and evaluation of best evidence and practice in healthcare is integrally linked to the research capacity and capabilities of the workforce. In addition to promoting high quality research, mechanisms for actively enhancing research capacity more generally must be in place to address the complexities that both undermine and facilitate this activity. Methods A comprehensive collaborative model for building research capacity in one health professional group, speech and language therapy, was developed in a region within the UK and is presented here. The North East of England and the strong research ethos of this profession in addressing complex interventions offered a fertile context for developing and implementing a model which integrated the healthcare and university sectors. Two key frameworks underpin this model. The first addresses the individual participants’ potential trajectory from research consciousness to research participative to research active. The second embeds a model developed for general practitioners into a broader framework of practice-academic partnership and knowledge and skills exchange, and considers external drivers and impacts on practice and patient outcomes as key elements. Results and discussion The integration of practice and academia has been successful in building a culture of research activity within one healthcare profession in a region in the UK and has resulted, to date, in a series of research related outcomes. Understanding the key components of this partnership and the explicit strategies used has driven the implementation of the model and are discussed here. Conclusions A strong

  13. Transportation Sector Model of the National Energy Modeling System. Volume 2 -- Appendices: Part 3

    SciTech Connect

    1998-01-01

    This Appendix consists of two unpublished reports produced by Energy and Environmental Analysis, Inc., under contract to Oak Ridge National Laboratory. These two reports formed the basis for the subsequent development of the Fuel Economy Model described in Volume 1. They are included in order to document more completely the efforts undertaken to construct a comprehensive model of automobile fuel economy. The supplemental reports are as follows: Supplement 1--Documentation Attributes of Technologies to Improve Automotive Fuel Economy; Supplement 2--Analysis of the Fuel Economy Boundary for 2010 and Comparison to Prototypes.

  14. Comparing Supply-Side Specifications in Models of Global Agriculture and the Food System

    SciTech Connect

    Robinson, Sherman; van Meijl, Hans; Willenbockel, Dirk; Valin, Hugo; Fujimori, Shinichiro; Masui, Toshihiko; Sands, Ronald; Wise, Marshall A.; Calvin, Katherine V.; Havlik, Petr; Mason d'Croz, Daniel; Tabeau, Andrzej; Kavallari, Aikaterini; Schmitz, Christoph; Dietrich, Jan P.; von Lampe, Martin

    2014-01-01

    This paper compares the theoretical specification of production and technical change across the partial equilibrium (PE) and computable general equilibrium (CGE) models of the global agricultural and food system included in the AgMIP model comparison study. The two modeling approaches have different theoretical underpinnings concerning the scope of economic activity they capture and how they represent technology and the behavior of supply and demand in markets. This paper focuses on their different specifications of technology and supply behavior, comparing their theoretical and empirical treatments. While the models differ widely in their specifications of technology, both within and between the PE and CGE classes of models, we find that the theoretical responsiveness of supply to changes in prices can be similar, depending on parameter choices that define the behavior of supply functions over the domain of applicability defined by the common scenarios used in the AgMIP comparisons. In particular, we compare the theoretical specification of supply in CGE models with neoclassical production functions and PE models that focus on land and crop yields in agriculture. In practice, however, comparability of results given parameter choices is an empirical question, and the models differ in their sensitivity to variations in specification. To illustrate the issues, sensitivity analysis is done with one global CGE model, MAGNET, to indicate how the results vary with different specification of technical change, and how they compare with the results from PE models.

  15. Climate change impacts utilizing regional models for agriculture, hydrology and natural ecosystems

    NASA Astrophysics Data System (ADS)

    Kafatos, M.; Asrar, G. R.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Medvigy, D.; Prasad, A. K.; Smith, E.; Stack, D. H.; Tremback, C.; Walko, R. L.

    2012-12-01

    Climate change impacts the entire Earth but with crucial and often catastrophic impacts at local and regional levels. Extreme phenomena such as fires, dust storms, droughts and other natural hazards present immediate risks and challenges. Such phenomena will become more extreme as climate change and anthropogenic activities accelerate in the future. We describe a major project funded by NIFA (Grant # 2011-67004-30224), under the joint NSF-DOE-USDA Earth System Models (EaSM) program, to investigate the impacts of climate variability and change on the agricultural and natural (i.e. rangeland) ecosystems in the Southwest USA using a combination of historical and present observations together with climate, and ecosystem models, both in hind-cast and forecast modes. The applicability of the methodology to other regions is relevant (for similar geographic regions as well as other parts of the world with different agriculture and ecosystems) and should advance the state of knowledge for regional impacts of climate change. A combination of multi-model global climate projections from the decadal predictability simulations, to downscale dynamically these projections using three regional climate models, combined with remote sensing MODIS and other data, in order to obtain high-resolution climate data that can be used with hydrological and ecosystem models for impacts analysis, is described in this presentation. Such analysis is needed to assess the future risks and potential impacts of projected changes on these natural and managed ecosystems. The results from our analysis can be used by scientists to assist extended communities to determine agricultural coping strategies, and is, therefore, of interest to wide communities of stakeholders. In future work we will be including surface hydrologic modeling and water resources, extend modeling to higher resolutions and include significantly more crops and geographical regions with different weather and climate conditions

  16. Occurrence and Distribution of Agricultural Pesticides and Transport Modeling in Surface and Subsurface Environments

    NASA Astrophysics Data System (ADS)

    Chu, X.; Marino, M. A.

    2007-12-01

    The use of a variety of pesticides has increased dramatically during the past decades to improve agricultural efficiency and productivity. However, these agricultural chemicals are often washed to surface waters by runoff and leached through the vadose zone to ground water, thereby polluting waters and threatening human health as well as aquatic and terrestrial ecosystems. It is of particular importance to develop effective modeling tools to assess the induced nonpoint source pollution, to regulate the use of agricultural pesticides, and to circumvent further deterioration in water quality. Different physically-based pesticide transport models, ranging from simple analytical models to semidiscrete and more rigorous numerical models, are discussed. In particular, the effects of use of pesticides on their occurrence and distribution in surface and subsurface environments are examined in this study. A windows-based integrated pesticide transport model (IPTM) is used to simulate three-phase pesticide transport and transformation and quantify spatial and temporal distributions in a coupled canopy-soil system as well as pesticide loading potential to the adjacent surface water through surface runoff and erosion. Five different pesticides (diazinon, 2,4-D acid, DBCP, simazine, and lindane) are examined. It is found that occurrence and distribution of pesticides in the environment are closely related to their use and determined by a series of pesticide transport and transformation processes. The occurrence and use of pesticides follow extremely complex and dynamic patterns that are affected by numerous factors related to their use and properties, hydrology, and agricultural activities. It is also found that changes in pesticide use (application quantity, frequency, timing, and method) may result in distinct environmental fate of pesticides in terms of their occurrence extent as well as spatial and temporal distributions.

  17. Linking an economic model for European agriculture with a mechanistic model to estimate nitrogen losses from cropland soil in Europe

    NASA Astrophysics Data System (ADS)

    Leip, A.; Marchi, G.; Koeble, R.; Kempen, M.; Britz, W.; Li, C.

    2007-07-01

    For the comprehensive assessment of the policy impact on greenhouse gas emissions from agricultural soils both socio-economic aspects and the environmental heterogeneity of the landscape are important factors that must be considered. We developed a modelling framework that links the large-scale economic model for agriculture CAPRI with the bio-geochemistry model DNDC to simulate greenhouse gas fluxes, carbon stock changes and the nitrogen budget of agricultural soils in Europe. The framework allows the ex-ante simulation of agricultural or agri-environmental policy impacts on wide range of environmental problems such as climate change (greenhouse gas emissions), air pollution and groundwater pollution. Those environmental impacts can be analysed in the context of economic and social indicators as calculated by the economic model. The methodology consists in four steps (i) the definition of appropriate calculation units that can be considered as homogeneous in terms of economic behaviour and environmental response; (ii) downscaling of regional agricultural statistics and farm management information from a CAPRI simulation run into the spatial calculation units; (iii) setting up of environmental model scenarios and model runs; and finally (iv) aggregating results for interpretation. We show first results of the nitrogen budget in cropland for the area of fourteen countries of the European Union. These results, in terms of estimated nitrogen fluxes, must still be considered as illustrative as needs for improvements in input data (e.g. the soil map) and management data (yield estimates) have been identified and will be the focus of future work. Nevertheless, we highlight inter-dependencies between farmer's choices of land uses and the environmental impact of different cultivation systems.

  18. REDD+ and climate smart agriculture in landscapes: A case study in Vietnam using companion modelling.

    PubMed

    Salvini, G; Ligtenberg, A; van Paassen, A; Bregt, A K; Avitabile, V; Herold, M

    2016-05-01

    Finding land use strategies that merge land-based climate change mitigation measures and adaptation strategies is still an open issue in climate discourse. This article explores synergies and trade-offs between REDD+, a scheme that focuses mainly on mitigation through forest conservation, with "Climate Smart Agriculture", an approach that emphasizes adaptive agriculture. We introduce a framework for ex-ante assessment of the impact of land management policies and interventions and for quantifying their impacts on land-based mitigation and adaptation goals. The framework includes a companion modelling (ComMod) process informed by interviews with policymakers, local experts and local farmers. The ComMod process consists of a Role-Playing Game with local farmers and an Agent Based Model. The game provided a participatory means to develop policy and climate change scenarios. These scenarios were then used as inputs to the Agent Based Model, a spatially explicit model to simulate landscape dynamics and the associated carbon emissions over decades. We applied the framework using as case study a community in central Vietnam, characterized by deforestation for subsistence agriculture and cultivation of acacias as a cash crop. The main findings show that the framework is useful in guiding consideration of local stakeholders' goals, needs and constraints. Additionally the framework provided beneficial information to policymakers, pointing to ways that policies might be re-designed to make them better tailored to local circumstances and therefore more effective in addressing synergistically climate change mitigation and adaptation objectives. PMID:26921566

  19. Global Transformations and Agriculture.

    ERIC Educational Resources Information Center

    Campbell, Rex R.

    1990-01-01

    Examines worldwide political, economic, and social transformations and their impact on agriculture, focusing on biotechnology. Discusses rise of international corporations and accompanying constraints on government power. Sees trend toward increasing agribusiness role in world food and agricultural sectors. Calls for broader views and research in…

  20. Design and merit of a river-aquifer model for optimal use of agricultural water

    NASA Astrophysics Data System (ADS)

    Morel-seytoux, H. J.; Daly, C. J.; Illangasekare, T.; Bazaraa, A.

    1981-05-01

    A stream-aquifer model was needed to assess the impact of alternate strategies of management for maximum beneficial agricultural use of water. The design of the model is discussed in detail in this paper. The design of a model specific to a particular area of the South Platte river basin in eastern Colorado was complex. The complexity resulted from the size of the system, from the need to simulate the system both at an operational time scale (week) and at a long-term planning horizon (10 yr.) and from the administration of a complicated water rights structure.

  1. Introduction The Role of the Agricultural Model Intercomparison and Improvement Project

    NASA Technical Reports Server (NTRS)

    Rosenzweig, Cynthia; Hillel, Daniel

    2015-01-01

    Climate impacts on agriculture are of increasing concern in both the scientific and policy communities because of the need to ensure food security for a growing population. A special challenge is posed by the changes in the frequency and intensity of heat-waves, droughts, and episodic rainstorms already underway in many parts of the world. Changes in production are directly linked to such variations in temperature and precipitation during the growing season, and often to offseason changes in weather affecting soil-water storage and availability to crops. This is not an isolated problem but one of both global and regional importance, because of impacts on the livelihoods of smallholder farmers as well as consequences for the world food trade system. This two-part set the Agricultural Model Intercomparison and Improvement Project (AgMIP): Integrated Crop and Economic Assessments is the first to be entirely devoted to AgMIP (www.agmip.org). AgMIP is a major international research program focused on climate change and agriculture. The goal of the two parts is to advance the field by providing detailed information on new simulation techniques and assessments being conducted by this program. It presents information about new methods of global and regional integrated assessment, results from agricultural regions, and adaptation strategies for maintaining food security under changing climate conditions.

  2. Assessing the mitigation potential of agricultural systems by optimization of the agricultural management: A modeling study on 8 agricultural observation sites across Europe with the process based model LandscapeDNDC

    NASA Astrophysics Data System (ADS)

    Molina Herrera, Saul; Haas, Edwin; Klatt, Steffen; Kraus, David; Kiese, Ralf; Butterbach-Bahl, Klaus

    2014-05-01

    The use of mineral nitrogen (N) fertilizers increase crop yields but cause the biggest anthropogenic source of nitrous oxide (N2O) emissions and strongly contribute to surface water eutrophication (e.g. nitrate leaching). The necessity to identify affordable strategies that improve crop production while improving ecosystem services are in continuous debate between policy decision makers and farmers. In this line, a lack commitment from farmers to enforce laws might result in the reduction of benefits. For this reason, farmers should aim to increase crop production and to reduce environmental harm by the adoption of precision climate smart agriculture tools applied to management practices for instance. In this study we present optimized strategies for 8 sites (agricultural and grassland ecosystems) with long term field observation across Europe to show the mitigation potential to reduce reactive nitrogen losses under the constrain of keeping yields at observed levels. LandscapeDNDC simulations of crop yields and associated nitrogen losses (N2O emissions and NO3 leaching) were evaluated against long term field measurements. The sites presented different management regimes including the main commodity crops (maize, wheat, barley, rape seeds, etc) and fertilization amendments (synthetic and organic fertilizers) in Europe. The simulations reproduced the observed yields, captured N2O emissions and NO3 leaching losses with high statistical presicion (r2), acurrency (ME) and agreement (RMSPEn). The mitigation potentials to reduce N losses while keeping yields at observed levels for all 8 sites were assesed by Monte Carlo optimizations of the individual underlying multi year agricultural management options (timings of planting and harvest, fertilization & manure applications and rates, residues management). In this study we present for all 8 agricultural observations sites their individual mitigation potentials to reduce N losses for multi year rotations. The conclusions

  3. An Integrated Model for Assessment of Sustainable Agricultural Residue Removal Limits for Bioenergy Systems

    SciTech Connect

    D. Muth; K. M. Bryden

    2003-12-01

    Agricultural residues have been identified as a significant potential resource for bioenergy production, but serious questions remain about the sustainability of harvesting residues. Agricultural residues play an important role in limiting soil erosion from wind and water and in maintaining soil organic carbon. Because of this, multiple factors must be considered when assessing sustainable residue harvest limits. Validated and accepted modeling tools for assessing these impacts include the Revised Universal Soil Loss Equation Version 2 (RUSLE2), the Wind Erosion Prediction System (WEPS), and the Soil Conditioning Index. Currently, these models do not work together as a single integrated model. Rather, use of these models requires manual interaction and data transfer. As a result, it is currently not feasible to use these computational tools to perform detailed sustainable agricultural residue availability assessments across large spatial domains or to consider a broad range of land management practices. This paper presents an integrated modeling strategy that couples existing datasets with the RUSLE2 water erosion, WEPS wind erosion, and Soil Conditioning Index soil carbon modeling tools to create a single integrated residue removal modeling system. This enables the exploration of the detailed sustainable residue harvest scenarios needed to establish sustainable residue availability. Using this computational tool, an assessment study of residue availability for the state of Iowa was performed. This study included all soil types in the state of Iowa, four representative crop rotation schemes, variable crop yields, three tillage management methods, and five residue removal methods. The key conclusions of this study are that under current management practices and crop yields nearly 26.5 million Mg of agricultural residue are sustainably accessible in the state of Iowa, and that through the adoption of no till practices residue removal could sustainably approach 40

  4. Determining agricultural land use scenarios in a mesoscale Bavarian watershed for modelling future water quality

    NASA Astrophysics Data System (ADS)

    Mehdi, B. B.; Ludwig, R.; Lehner, B.

    2012-06-01

    Land use scenarios are of primordial importance when implementing a hydrological model for the purpose of determining the future quality of water in a watershed. This paper provides the background for researching potential agricultural land use changes that may take place in a mesoscale watershed, for water quality research, and describes why studying the farm scale is important. An on-going study in Bavaria examining the local drivers of change in land use is described.

  5. Nitrate-Nitrogen Leaching and Modeling in Intensive Agriculture Farmland in China

    PubMed Central

    Xu, Ligang; Xu, Jin

    2013-01-01

    Protecting water resources from nitrate-nitrogen (NO3-N) contamination is an important public health concern and a major national environmental issue in China. Loss of NO3-N in soils due to leaching is not only one of the most important problems in agriculture farming, but is also the main factor causing nitrogen pollution in aquatic environments. Three typical intensive agriculture farmlands in Jiangyin City in China are selected as a case study for NO3-N leaching and modeling in the soil profile. In this study, the transport and fate of NO3-N within the soil profile and nitrate leaching to drains were analyzed by comparing field data with the simulation results of the LEACHM model. Comparisons between measured and simulated data indicated that the NO3-N concentrations in the soil and nitrate leaching to drains are controlled by the fertilizer practice, the initial conditions and the rainfall depth and distribution. Moreover, the study reveals that the LEACHM model gives a fair description of the NO3-N dynamics in the soil and subsurface drainage at the field scale. It can also be concluded that the model after calibration is a useful tool to optimize as a function of the combination “climate-crop-soil-bottom boundary condition” the nitrogen application strategy resulting for the environment in an acceptable level of nitrate leaching. The findings in this paper help to demonstrate the distribution and migration of nitrogen in intensive agriculture farmlands, as well as to explore the mechanism of groundwater contamination resulting from agricultural activities. PMID:23983629

  6. Looking back to move forward on model validation: insights from a global model of agricultural land use

    NASA Astrophysics Data System (ADS)

    Baldos, Uris Lantz C.; Hertel, Thomas W.

    2013-09-01

    Global agricultural models are becoming indispensable in the debate over climate change impacts and mitigation policies. Therefore, it is becoming increasingly important to validate these models and identify critical areas for improvement. In this letter, we illustrate both the opportunities and the challenges in undertaking such model validation, using the SIMPLE model of global agriculture. We look back at the long run historical period 1961-2006 and, using a few key historical drivers—population, incomes and total factor productivity—we find that SIMPLE is able to accurately reproduce historical changes in cropland use, crop price, crop production and average crop yields at the global scale. Equally important is our investigation into how the specific assumptions embedded in many agricultural models will likely influence these results. We find that those global models which are largely biophysical—thereby ignoring the price responsiveness of demand and supply—are likely to understate changes in crop production, while failing to capture the changes in cropland use and crop price. Likewise, global models which incorporate economic responses, but do so based on limited time series estimates of these responses, are likely to understate land use change and overstate price changes.

  7. User's Guide for the Agricultural Non-Point Source (AGNPS) Pollution Model Data Generator

    USGS Publications Warehouse

    Finn, Michael P.; Scheidt, Douglas J.; Jaromack, Gregory M.

    2003-01-01

    BACKGROUND Throughout this user guide, we refer to datasets that we used in conjunction with developing of this software for supporting cartographic research and producing the datasets to conduct research. However, this software can be used with these datasets or with more 'generic' versions of data of the appropriate type. For example, throughout the guide, we refer to national land cover data (NLCD) and digital elevation model (DEM) data from the U.S. Geological Survey (USGS) at a 30-m resolution, but any digital terrain model or land cover data at any appropriate resolution will produce results. Another key point to keep in mind is to use a consistent data resolution for all the datasets per model run. The U.S. Department of Agriculture (USDA) developed the Agricultural Nonpoint Source (AGNPS) pollution model of watershed hydrology in response to the complex problem of managing nonpoint sources of pollution. AGNPS simulates the behavior of runoff, sediment, and nutrient transport from watersheds that have agriculture as their prime use. The model operates on a cell basis and is a distributed parameter, event-based model. The model requires 22 input parameters. Output parameters are grouped primarily by hydrology, sediment, and chemical output (Young and others, 1995.) Elevation, land cover, and soil are the base data from which to extract the 22 input parameters required by the AGNPS. For automatic parameter extraction, follow the general process described in this guide of extraction from the geospatial data through the AGNPS Data Generator to generate input parameters required by the pollution model (Finn and others, 2002.)

  8. Cost-effective means of reducing ammonia emissions from UK agriculture using the NARSES model

    NASA Astrophysics Data System (ADS)

    Webb, J.; Ryan, M.; Anthony, S. G.; Brewer, A.; Laws, J.; Aller, M. F.; Misselbrook, T. H.

    To comply with International agreements to improve air quality, signatory states need to reduce emissions of ammonia (NH 3). Since the majority of NH 3 emissions come from agriculture, measures may need to be implemented by the farming industry. Member states of the EU will, by 2010, require large pig and poultry production units to reduce NH 3 emissions to comply with the integrated pollution prevention and control directive (IPPC). The NARSES model uses a mass-flow method to estimate NH 3 emission from UK agriculture and to identify the most cost-effective means of reducing NH 3 emissions. Model runs were carried out to assess the likely impact of the IPPC Directive on UK NH 3 emissions and the sensitivity of model output to input data on the costs and abatement efficiencies of proposed abatement measures. The impact of the IPPC Directive is likely to be small, offering a reduction of c. 8700 t, 3.5% of total UK agricultural NH 3 emissions. Even large (30%) changes in our estimates of cost or changes of 10% in our estimates of abatement efficiency will make little difference to the ranking of abatement techniques according to cost-effectiveness. The most cost-effective reductions may be achieved by replacing urea fertilizer with ammonium nitrate, immediate incorporation of manures and slurries to tillage land by discs, storing all FYM and poultry manures before spreading to land and applying slurries to grassland by trailing shoe.

  9. Evaluating the Impacts of an Agricultural Water Market in the Guadalupe River Basin, Texas: An Agent-based Modeling Approach

    NASA Astrophysics Data System (ADS)

    Du, E.; Cai, X.; Minsker, B. S.

    2014-12-01

    Agriculture comprises about 80 percent of the total water consumption in the US. Under conditions of water shortage and fully committed water rights, market-based water allocations could be promising instruments for agricultural water redistribution from marginally profitable areas to more profitable ones. Previous studies on water market have mainly focused on theoretical or statistical analysis. However, how water users' heterogeneous physical attributes and decision rules about water use and water right trading will affect water market efficiency has been less addressed. In this study, we developed an agent-based model to evaluate the benefits of an agricultural water market in the Guadalupe River Basin during drought events. Agricultural agents with different attributes (i.e., soil type for crops, annual water diversion permit and precipitation) are defined to simulate the dynamic feedback between water availability, irrigation demand and water trading activity. Diversified crop irrigation rules and water bidding rules are tested in terms of crop yield, agricultural profit, and water-use efficiency. The model was coupled with a real-time hydrologic model and run under different water scarcity scenarios. Preliminary results indicate that an agricultural water market is capable of increasing crop yield, agricultural profit, and water-use efficiency. This capability is more significant under moderate drought scenarios than in mild and severe drought scenarios. The water market mechanism also increases agricultural resilience to climate uncertainty by reducing crop yield variance in drought events. The challenges of implementing an agricultural water market under climate uncertainty are also discussed.

  10. TRACKING THE EMISSION OF CARBON DIOXIDE BY NATION, SECTOR, AND FUEL TYPE: A TRACE GAS ACCOUNTING SYSTEM (TGAS)

    EPA Science Inventory

    The paper describes a new way to estimate an efficient econometric model of global emissions of carbon dioxide (CO2) by nation, sector, and fuel type. Equations for fuel intensity are estimated for coal, oil, natural gas, electricity, and heat for six sectors: agricultural, indus...

  11. Agricultural growth, the status of women, and fertility.

    PubMed

    Whittington, L A; Stapleton, D C

    1995-08-01

    This study tests the hypothesis that fertility is affected differently by economic growth depending upon the specific sector (agriculture, manufacturing, heavy industry, and services) where growth occurred. The hypothesis is that fertility responses are not identical across sectors. The sample includes 51 World Bank member countries in varying stages of development. The econometric model pertains to 1965-88 and the percentage change in the total fertility rate (TFR). During the study period the average TFR declined by over 22%, but the extent of change varied by country and included, for instance, countries such as Ethiopia that experienced fertility increases from 5.8 to 6.5. Hong Kong's TFR declined by 66% from 4.7 to 1.6. Analysis included measures of changes in gross domestic product (GDP) for each of the four sectors and change in real per capita exports in agricultural commodities, resources, and manufactured products. Changes in educational status and changes in infant mortality were also included in some models. There were mixed results for the impact of total GDP. Sectoral analysis shows a positive, small significant impact on TFR from changes in the GDP per capita in agriculture (domestic and export products), and a negative, small significant impact from manufacturing growth. Heavy industry and services produced insignificant impact. In the model with only domestic consumption, results show a stronger coefficient and continued significance for agricultural productivity, agricultural exports, and manufacturing changes per capita. Manufacturing exports produced a negative, insignificant impact. The null hypothesis is rejected only in models comparing aggregate GDP in agriculture and manufacturing industries plus control variables (excluding heavy industry and services). Only secondary education was a negative, significant determinant of fertility. Infant mortality was insignificant when sectoral growth and education were included in the model. The evidence

  12. Comparative study of model prediction of diffuse nutrient losses in response to changes in agricultural practices.

    PubMed

    Vagstad, N; French, H K; Andersen, H E; Behrendt, H; Grizzetti, B; Groenendijk, P; Lo Porto, A; Reisser, H; Siderius, C; Stromquist, J; Hejzlar, J; Deelstra, J

    2009-03-01

    This article presents a comparative study of modelled changes in nutrient losses from two European catchments caused by modifications in agricultural practices. The purpose was not to compare the actual models used, but rather to assess the uncertainties a manager may be faced with after receiving decision support from consultants using different models. Seven modelling teams were given the same data about two catchments and their management characteristics and were asked to model the same changes in management practices using the model of their own choice. This can potentially cause accumulated 'errors' due to differences in the modelling teams' interpretation of relevant processes and definitions of boundary conditions (inputs). The study was carried out within the framework of the EUROHARP project, which aimed at harmonising procedures for quantifying diffuse losses of nitrogen and phosphorus from agriculture. Models are important for assessing river basin management plans (RBMPs) as required e.g. under the EC Water Framework Directive and Action Plans under the EC Nitrates Directive. This article illustrates some challenges with respect to interpreting such modelling results. The selected management scenarios include changes in fertiliser application levels, changes in livestock numbers and changes in land-use and crop rotation systems. Seven models were applied for the same scenarios in the Enza catchment in Italy and the Zelivka catchment in the Czech Republic. All models had been calibrated and validated with respect to historical data of climatic conditions, water quality and discharge measurements. The modelling results reveal a variation in predicted effects of the management scenarios, causing different conclusions with respect to choice of best management practice for reducing nutrient losses. The study demonstrates that it is important that care is taken by modellers and involved decision makers throughout the entire modelling process, both with regard

  13. Is "the perfect model" really needed? - Analysis of the quality level of climate information necessary for supporting adaptation in agriculture and forestry

    NASA Astrophysics Data System (ADS)

    Gálos, Borbála; Ostler, Wolf-Uwe; Csáki, Péter; Bidló, András; Panferov, Oleg

    2016-04-01

    agriculture a questionnaire has been carried out among 180 farms of different sizes and specializations (mostly arable farming and viniculture) in Reinland-Palatine, Germany. The results show that almost all farmers use the weather information daily and are in need of weather forecast. More than a half requires also the forecast on extreme events. However the farmers require more qualitative (e.g. temperature coarser than 1°C) than high-precision quantitative information in short and medium-term forecasts. Forestry requires long-term (30-100 years) climate projections. For the assessment of climate change impacts on forest distribution, production and tree species selection, monthly temperature means and precipitation sums are sufficient. Based on the results of regional climate models it will be shown how the bias, the spread and spatial resolution of the simulation results are affecting the accuracy of impact assessments. Our analyses can help to fill the gap between climate services and the needs of impact researchers and end users in agriculture and forestry. User-relevant climate information can contribute to appropriate adaptation support services and management options in the two sectors. Keywords: regional climate projections, climate impact assessment, agriculture, forestry, adaptation support, accuracy of climate information Funding: The research is supported by the "Agroclimate-2" (VKSZ_12-1-2013-0034) joint EU-national research project.

  14. On the blocking flow patterns in the Euro-Atlantic sector: A simple model study

    NASA Astrophysics Data System (ADS)

    Luo, Dehai; Yao, Yao

    2014-09-01

    The flow patterns of Euro-Atlantic blocking events in winter are investigated by dividing the sector into three subregions: 60°-30°W (Greenland region); 20°W-30°E [eastern Atlantic-Europe (EAE) region]; and 50°-90°E (Ural region). It is shown that blocking events in winter are extremely frequent in the three sub-regions. Composite 500-mb geopotential height fields for intense and long-lived blocking events demonstrate that the blocking fields over Greenland and Ural regions exhibit southwest-northeast (SW-NE) and southeast-northwest (SE-NW) oriented dipole-type patterns, respectively, while the composite field over the EAE region exhibits an Ω-type pattern. The type of composite blocking pattern seems to be related to the position of the blocking region relative to the positive center of the climatological stationary wave (CSW) anomaly existing near 10°W. The physical cause of why there are different composite blocking types in the three sub-regions is identified using a nonlinear multiscale interaction model. It is found that when the blocking event is in almost the same position as the positive CSW anomaly, the planetary-scale field can exhibit an Ω-type pattern due to the enhanced positive CSW anomaly. Nevertheless, a SW-NE (SE-NW) oriented dipole-type block can occur due to the reduced positive CSW anomaly as it is farther in the west (east) of the positive CSW anomaly. The total fields of blocking in the three regions may exhibit a meandering flow comprised of several isolated anticyclonic and cyclonic vortices, which resembles the Berggren-Bolin-Rossby meandering jet type.

  15. Impacts of input parameter spatial aggregation on an agricultural nonpoint source pollution model

    NASA Astrophysics Data System (ADS)

    FitzHugh, T. W.; Mackay, D. S.

    2000-09-01

    The accuracy of agricultural nonpoint source pollution models depends in part on how well model input parameters describe the relevant characteristics of the watershed. The spatial extent of input parameter aggregation has previously been shown to have a substantial impact on model output. This study investigates this problem using the Soil and Water Assessment Tool (SWAT), a distributed-parameter agricultural nonpoint source pollution model. The primary question addressed here is: how does the size or number of subwatersheds used to partition the watershed affect model output, and what are the processes responsible for model behavior? SWAT was run on the Pheasant Branch watershed in Dane County, WI, using eight watershed delineations, each with a different number of subwatersheds. Model runs were conducted for the period 1990-1996. Streamflow and outlet sediment predictions were not seriously affected by changes in subwatershed size. The lack of change in outlet sediment is due to the transport-limited nature of the Pheasant Branch watershed and the stable transport capacity of the lower part of the channel network. This research identifies the importance of channel parameters in determining the behavior of SWAT's outlet sediment predictions. Sediment generation estimates do change substantially, dropping by 44% between the coarsest and the finest watershed delineations. This change is primarily due to the sensitivity of the runoff term in the Modified Universal Soil Loss Equation to the area of hydrologic response units (HRUs). This sensitivity likely occurs because SWAT was implemented in this study with a very detailed set of HRUs. In order to provide some insight on the scaling behavior of the model two indexes were derived using the mathematics of the model. The indexes predicted SWAT scaling behavior from the data inputs without a need for running the model. Such indexes could be useful for model users by providing a direct way to evaluate alternative models

  16. A hydro-economic modelling framework for optimal management of groundwater nitrate pollution from agriculture

    NASA Astrophysics Data System (ADS)

    Peña-Haro, Salvador; Pulido-Velazquez, Manuel; Sahuquillo, Andrés

    2009-06-01

    SummaryA hydro-economic modelling framework is developed for determining optimal management of groundwater nitrate pollution from agriculture. A holistic optimization model determines the spatial and temporal fertilizer application rate that maximizes the net benefits in agriculture constrained by the quality requirements in groundwater at various control sites. Since emissions (nitrogen loading rates) are what can be controlled, but the concentrations are the policy targets, we need to relate both. Agronomic simulations are used to obtain the nitrate leached, while numerical groundwater flow and solute transport simulation models were used to develop unit source solutions that were assembled into a pollutant concentration response matrix. The integration of the response matrix in the constraints of the management model allows simulating by superposition the evolution of groundwater nitrate concentration over time at different points of interest throughout the aquifer resulting from multiple pollutant sources distributed over time and space. In this way, the modelling framework relates the fertilizer loads with the nitrate concentration at the control sites. The benefits in agriculture were determined through crop prices and crop production functions. This research aims to contribute to the ongoing policy process in the Europe Union (the Water Framework Directive) providing a tool for analyzing the opportunity cost of measures for reducing nitrogen loadings and assessing their effectiveness for maintaining groundwater nitrate concentration within the target levels. The management model was applied to a hypothetical groundwater system. Optimal solutions of fertilizer use to problems with different initial conditions, planning horizons, and recovery times were determined. The illustrative example shows the importance of the location of the pollution sources in relation to the control sites, and how both the selected planning horizon and the target recovery time can

  17. An agricultural drought risk-assessment model for corn and soybeans

    NASA Astrophysics Data System (ADS)

    Wu, Hong; Hubbard, Kenneth G.; Wilhite, Donald A.

    2004-05-01

    An agricultural drought risk-assessment model was developed for Nebraska, USA, for corn and soybeans on the basis of variables derived from the standardized precipitation index and crop-specific drought index using multivariate techniques. This model can be used to assess real-time agricultural drought risk for specific crops at critical times before and during the growing season by retaining previous, and adding current, weather information as the crops pass through the various development stages. This model will be helpful to decision makers, ranging from agricultural producers to policy makers and from local to national levels.The results of the model validation using three different datasets show that the risk-assessment accuracy improves as the crop develops. At the end of April, before corn is planted, the average assessment accuracy rate of drought risks on final yield is 60%. At the beginning of July, when corn is at the vegetative stage, the average assessment accuracy rate reaches 76%. In late July, when corn is at the ovule stage, the rate increases to 85%. The rates are 89% in the second half of August and the end of September, when corn is at the reproduction and ripening stages respectively. The model assessment accuracy for soybeans is lower than that for corn at the same growth stages because weather has less impact on soybeans than on corn. A reliable assessment, with 80% assessment accuracy rate, begins at mid-August, when soybeans are at pod formation stage. In early September and October, when soybeans are at pod fill and ripening stages respectively, the model is able to assess risks on soybean yield with 83% and 81% accuracy rates respectively.

  18. The Agricultural Policy/Environmental Extender (Apex) Model: An Emerging Tool for Landscape and Watershed Environmental Analyses

    SciTech Connect

    Gassman, Philip W.; Williams, Jimmy R.; Wang, Xiuying; Saleh, Ali; Osei, Edward; Hauck, Larry; Izaurralde, Roberto C.; Flowers, Joan

    2010-06-01

    The Agricultural Policy Environmental eXtender (APEX) model was developed by the Blacklands Research and Extension Center in Temple, Texas. APEX is a flexible and dynamic tool that is capable of simulating a wide array of management practices, cropping systems, and other land uses across a broad range of agricultural landscapes, including whole farms and small watersheds.

  19. Monitoring and APEX modeling of no-till and reduced-till in tile drained agricultural landscapes for water quality

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The evaluation of agricultural practices through monitoring and modeling is necessary for the development of more effective conservation programs and policies. No-till and reduced-till are both agricultural conservation practices widely promoted for their proven ability to conserve water and reduce ...

  20. GlobWat - a global water balance model to assess water use in irrigated agriculture

    NASA Astrophysics Data System (ADS)

    Hoogeveen, J.; Faurès, J.-M.; Peiser, L.; Burke, J.; van de Giesen, N.

    2015-01-01

    GlobWat is a freely distributed, global soil water balance model that is used by FAO to assess water use in irrigated agriculture; the main factor behind scarcity of freshwater in an increasing number of regions. The model is based on spatially distributed high resolution datasets that are consistent at global level and calibrated against values for Internal Renewable Water Resources, as published in AQUASTAT, FAO's global information system on water and agriculture. Validation of the model is done against mean annual river basin outflows. The water balance is calculated in two steps: first a "vertical" water balance is calculated that includes evaporation from in situ rainfall ("green" water) and incremental evaporation from irrigated crops. In a second stage, a "horizontal" water balance is calculated to determine discharges from river (sub-)basins, taking into account incremental evaporation from irrigation, open water and wetlands ("blue" water). The paper describes methodology, input and output data, calibration and validation of the model. The model results are finally compared with other global water balance models.

  1. Groundwater vulnerability assessment in agricultural areas using a modified DRASTIC model.

    PubMed

    Sadat-Noori, Mahmood; Ebrahimi, Kumars

    2016-01-01

    Groundwater contamination is a major concern for groundwater resource managers worldwide. We evaluated groundwater pollution potential by producing a vulnerability map of an aquifer using a modified Depth to water, Net recharge, Aquifer media, Soil media, Topography, Impact of vadose zone, and Hydraulic conductivity (DRASTIC) model within a Geographic Information System (GIS) environment. The proposed modification which incorporated the use of statistical techniques optimizes the rating function of the DRASTIC model parameters, to obtain a more accurate vulnerability map. The new rates were computed using the relationships between the parameters and point data chloride concentrations in groundwater. The model was applied on Saveh-Nobaran plain in central Iran, and results showed that the coefficient of determination (R (2)) between the point data and the relevant vulnerability map increased significantly from 0.52 to 0.78 after modification. As compared to the original DRASTIC model, the modified version produced better vulnerability zonation. Additionally, single-parameter and parameter removal sensitivity analyses were performed to evaluate the relative importance of each DRASTIC parameter. The results from both analyses revealed that the vadose zone is the most sensitive parameter influencing the variability of the aquifers' vulnerability index. Based on the results, for non-point source pollution in agricultural areas, using the modified DRASTIC model is efficient compared to the original model. The proposed method can be effective for future groundwater assessment and plain-land management where agricultural activities are dominant. PMID:26650205

  2. Modeling Agricultural Crop Production in China using AVHRR-based Vegetation Health Indices

    NASA Astrophysics Data System (ADS)

    Yang, B.; Kogan, F.; Guo, W.; Zhiyuan, P.; Xianfeng, J.

    Weather related crop losses have always been a concern for farmers On a wider scale it has always influenced decision of Governments traders and other policy makers for the purpose of balanced food supplies trade and distribution of aid to the nations in need Therefore national policy and decision makers are giving increasing importance to early assessment of crop losses in response to weather fluctuations This presentation emphasizes utility of AVHRR-based Vegetation health index VHI for early warning of drought-related losses of agricultural production in China The VHI is a three-channel index characterizing greenness vigor and temperature of land surface which can be used as proxy for estimation of how healthy and potentially productive could be vegetation China is the largest in the world producer of grain including wheat and rice and cotton In the major agricultural areas China s crop production is very dependent on weather The VHI being a proxy indicator of weather impact on vegetation showed some correlation with productivity of agricultural crops during the critical period of their development The periods of the strongest correlation were investigated and used to build regression models where crop yield deviation from technological trend was accepted as a dependent and VHI as independent variables The models were developed for several major crops including wheat corn and soybeans

  3. Dynamics of Nitrogen loads in surface water of an agricultural watershed by modelling approach, the Save, Southwest France.

    NASA Astrophysics Data System (ADS)

    Ferrant, S.; Oeurng, C.; Sauvage, S.; Durand, P.; Probst, J. L.; Sanchez-Perez, J. M.

    2009-04-01

    Agriculture is known to have a great impact of nutrients enrichment on continental water resources. In south-West of France (Gascogne region), water resource are essentially surface water and shallow aquifer. Nitrogen dynamic in river is complex and highly variable throughout season and year, depending on hydrology, landuse, removal in stream. In this context, agricultural impacts on nitrogen concentration are a matter of concern for agricultural decision-maker. In order to introduce sustainable land use concepts in this hilly, clayey and agricultural shallow soil context, the hydrological simulation model SWAT2005 has been tested as a valuable tool to evaluate the consequences of such land use changes on water and nutrient balance components. This semi-distributed hydrological model coupled with agronomical model EPIC is able to simulate the impact of each agricultural landuse at the outlet of the Save catchment (1100 km2). Hydrological parameters model are calibrated based on 14-year historical record (1994-2008). Nitrogen losses have been measured during 2 years (2006-2008) at the outlet and are used to validate the model calibration. Agricultural data at communal scale coupled with Spot image analyses have been used to evaluate agricultural distribution and pressure in SWAT. The aim of this modelling exercise is to simulate nitrogen cycle in whole agricultural Hydrological Response Units (HRU), depending on plant growth and culture rotation, to simulate accurately nitrate load in river. The ability of SWAT to reproduce nitrogen transfert and transformation at this scale and in this agricultural context will be evaluated by a discussion of importance of each nitrogen cycle process in nitrogen losses. SWAT could be a useful tool to test agricultural scenario to improve the nitrogen management in river.

  4. A radiative transfer model for microwave emissions from bare agricultural soils

    NASA Technical Reports Server (NTRS)

    Burke, W. J.; Paris, J. F.

    1975-01-01

    A radiative transfer model for microwave emissions from bare, stratified agricultural soils was developed to assist in the analysis of data gathered in the joint soil moisture experiment. The predictions of the model were compared with preliminary X band (2.8 cm) microwave and ground based observations. Measured brightness temperatures at vertical and horizontal polarizations can be used to estimate the moisture content of the top centimeter of soil with + or - 1 percent accuracy. It is also shown that the Stokes parameters can be used to distinguish between moisture and surface roughness effects.

  5. Regional scale cropland carbon budgets: evaluating a geospatial agricultural modeling system using inventory data

    SciTech Connect

    Zhang, Xuesong; Izaurralde, Roberto C.; Manowitz, David H.; Sahajpal, Ritvik; West, Tristram O.; Thomson, Allison M.; Xu, Min; Zhao, Kaiguang; LeDuc, Stephen D.; Williams, Jimmy R.

    2015-01-01

    Accurate quantification and clear understanding of regional scale cropland carbon (C) cycling is critical for designing effective policies and management practices that can contribute toward stabilizing atmospheric CO2 concentrations. However, extrapolating site-scale observations to regional scales represents a major challenge confronting the agricultural modeling community. This study introduces a novel geospatial agricultural modeling system (GAMS) exploring the integration of the mechanistic Environmental Policy Integrated Climate model, spatially-resolved data, surveyed management data, and supercomputing functions for cropland C budgets estimates. This modeling system creates spatially-explicit modeling units at a spatial resolution consistent with remotely-sensed crop identification and assigns cropping systems to each of them by geo-referencing surveyed crop management information at the county or state level. A parallel computing algorithm was also developed to facilitate the computationally intensive model runs and output post-processing and visualization. We evaluated GAMS against National Agricultural Statistics Service (NASS) reported crop yields and inventory estimated county-scale cropland C budgets averaged over 2000–2008. We observed good overall agreement, with spatial correlation of 0.89, 0.90, 0.41, and 0.87, for crop yields, Net Primary Production (NPP), Soil Organic C (SOC) change, and Net Ecosystem Exchange (NEE), respectively. However, we also detected notable differences in the magnitude of NPP and NEE, as well as in the spatial pattern of SOC change. By performing crop-specific annual comparisons, we discuss possible explanations for the discrepancies between GAMS and the inventory method, such as data requirements, representation of agroecosystem processes, completeness and accuracy of crop management data, and accuracy of crop area representation. Based on these analyses, we further discuss strategies to improve GAMS by updating input

  6. Developing Curriculum Markers for Agricultural Extension Education in South Africa

    ERIC Educational Resources Information Center

    Worth, S. H.

    2008-01-01

    Sufficient changes have occurred in both the agricultural and educational sectors of South Africa to warrant a careful scrutiny of the agricultural education offerings in South Africa. Agricultural extension is identified as an important part of the intended transformation of the agricultural sector. Further, agricultural extension is essentially…

  7. Models for residential- and commercial-sector energy-conservation analysis: applications, limitations, and future potential. Final report

    SciTech Connect

    Cole, Henry E.; Fullen, Robert E.

    1980-09-01

    This report reviews four of the major models used by the Department of Energy (DOE) for energy conservation analyses in the residential- and commercial-building sectors. The objective is to provide a critical analysis of how these models can serve as tools for DOE and its Conservation Policy Office in evaluating and quantifying their policy and program requirements. For this, the study brings together information on the models' analytical structure and their strengths and limitations in policy applications these are then employed to assess the most-effective role for each model in addressing future issues of buildings energy-conservation policy and analysis. The four models covered are: Oak Ridge Residential Energy Model; Micro Analysis of Transfers to Households/Comprehensive Human Resources Data System (MATH/CHRDS) Model; Oak Ridge Commercial Energy Model; and Brookhaven Buildings Energy Conservation Optimization Model (BECOM).

  8. Evaluation of Three Models for Simulating Pesticide Runoff from Irrigated Agricultural Fields.

    PubMed

    Zhang, Xuyang; Goh, Kean S

    2015-11-01

    Three models were evaluated for their accuracy in simulating pesticide runoff at the edge of agricultural fields: Pesticide Root Zone Model (PRZM), Root Zone Water Quality Model (RZWQM), and OpusCZ. Modeling results on runoff volume, sediment erosion, and pesticide loss were compared with measurements taken from field studies. Models were also compared on their theoretical foundations and ease of use. For runoff events generated by sprinkler irrigation and rainfall, all models performed equally well with small errors in simulating water, sediment, and pesticide runoff. The mean absolute percentage errors (MAPEs) were between 3 and 161%. For flood irrigation, OpusCZ simulated runoff and pesticide mass with the highest accuracy, followed by RZWQM and PRZM, likely owning to its unique hydrological algorithm for runoff simulations during flood irrigation. Simulation results from cold model runs by OpusCZ and RZWQM using measured values for model inputs matched closely to the observed values. The MAPE ranged from 28 to 384 and 42 to 168% for OpusCZ and RZWQM, respectively. These satisfactory model outputs showed the models' abilities in mimicking reality. Theoretical evaluations indicated that OpusCZ and RZWQM use mechanistic approaches for hydrology simulation, output data on a subdaily time-step, and were able to simulate management practices and subsurface flow via tile drainage. In contrast, PRZM operates at daily time-step and simulates surface runoff using the USDA Soil Conservation Service's curve number method. Among the three models, OpusCZ and RZWQM were suitable for simulating pesticide runoff in semiarid areas where agriculture is heavily dependent on irrigation. PMID:26641333

  9. Improved temporal resolution in process-based modelling of agricultural soil ammonia emissions

    NASA Astrophysics Data System (ADS)

    Beuning, J. D.; Pattey, E.; Edwards, G.; Van Heyst, B. J.

    An emerging environmental issue in Canada is how to quantify the contribution of agricultural soil emissions of ammonia (NH 3) to environmental pollution. Emission inventories are essential to predict these emissions and their subsequent atmospheric transportation, transformation, and deposition. Due to the high spatial and temporal variability associated with NH 3 emissions, emission inventories based on measurements become expensive and emission factors lose accuracy. Process-based models are capable of accounting for the complex soil interactions, but current models lack temporal refinement and few models consider NH 3 emissions. This paper presents the development of a one-dimensional (vertical), time-dependent model capable of predicting NH 3 emissions from a slurry applied to a bare soil. The model is based on chemical, physical and biological relationships that govern soil heat, moisture, and nitrogen movement. Processes considered include convection, diffusion, decomposition, nitrification, denitrification, and surface to atmosphere transport. The model is tested with experimental data from Agriculture and Agri-Food Canada which conducted NH 3 measurements following application of dairy cattle slurry to a bare field. An investigation into the sensitivity of emissions to pH and slurry infiltration rate is conducted and model predictions are best fit to measurements based on this investigation. Testing demonstrated the model's ability to predict the large NH 3 emissions immediately following application and subsequent emission trends associated with diurnal patterns that emission factors cannot capture. Results showed that model performance could benefit from a more in depth measurement program and empirical or process models of surface pH. Potential exists for the model to become a useful tool in predicting emissions on local, regional, or national scales.

  10. Modeling Spatial and Temporal Variability in Ammonia Emissions from Agricultural Fertilization

    NASA Astrophysics Data System (ADS)

    Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

    2013-12-01

    Ammonia (NH3), is an important component of the reactive nitrogen cycle and a precursor to formation of atmospheric particulate matter (PM). Predicting regional PM concentrations and deposition of nitrogen species to ecosystems requires representative emission inventories. Emission inventories have traditionally been developed using top down approaches and more recently from data assimilation based on satellite and ground based ambient concentrations and wet deposition data. The National Emission Inventory (NEI) indicates agricultural fertilization as the predominant contributor (56%) to NH3 emissions in Midwest USA, in 2002. However, due to limited understanding of the complex interactions between fertilizer usage, farm practices, soil and meteorological conditions and absence of detailed statistical data, such emission estimates are currently based on generic emission factors, time-averaged temporal factors and coarse spatial resolution. Given the significance of this source, our study focuses on developing an improved NH3 emission inventory for agricultural fertilization at finer spatial and temporal scales for air quality modeling studies. Firstly, a high-spatial resolution 4 km x 4 km NH3 emission inventory for agricultural fertilization has been developed for Illinois by modifying spatial allocation of emissions based on combining crop-specific fertilization rates with cropland distribution in the Sparse Matrix Operator Kernel Emissions model. Net emission estimates of our method are within 2% of NEI, since both methods are constrained by fertilizer sales data. However, we identified localized crop-specific NH3 emission hotspots at sub-county resolutions absent in NEI. Secondly, we have adopted the use of the DeNitrification-DeComposition (DNDC) Biogeochemistry model to simulate the physical and chemical processes that control volatilization of nitrogen as NH3 to the atmosphere after fertilizer application and resolve the variability at the hourly scale

  11. A model for inventory of ammonia emissions from agriculture in the Netherlands

    NASA Astrophysics Data System (ADS)

    Velthof, G. L.; van Bruggen, C.; Groenestein, C. M.; de Haan, B. J.; Hoogeveen, M. W.; Huijsmans, J. F. M.

    2012-01-01

    Agriculture is the major source of ammonia (NH 3). Methodologies are needed to quantify national NH 3 emissions and to identify the most effective options to mitigate NH 3 emissions. Generally, NH 3 emissions from agriculture are quantified using a nitrogen (N) flow approach, in which the NH 3 emission is calculated from the N flows and NH 3 emission factors. Because of the direct dependency between NH 3 volatilization and Total Ammoniacal N (TAN; ammonium-N + N compounds readily broken down to ammonium) an approach based on TAN is preferred to calculate NH 3 emission instead of an approach based on total N. A TAN-based NH 3-inventory model was developed, called NEMA (National Emission Model for Ammonia). The total N excretion and the fraction of TAN in the excreted N are calculated from the feed composition and N digestibility of the components. TAN-based emission factors were derived or updated for housing systems, manure storage outside housing, manure application techniques, N fertilizer types, and grazing. The NEMA results show that the total NH 3 emission from agriculture in the Netherlands in 2009 was 88.8 Gg NH 3-N, of which 50% from housing, 37% from manure application, 9% from mineral N fertilizer, 3% from outside manure storage, and 1% from grazing. Cattle farming was the dominant source of NH 3 in the Netherlands (about 50% of the total NH 3 emission). The NH 3 emission expressed as percentage of the excreted N was 22% of the excreted N for poultry, 20% for pigs, 15% for cattle, and 12% for other livestock, which is mainly related to differences in emissions from housing systems. The calculated ammonia emission was most sensitive to changes in the fraction of TAN in the excreted manure and to the emission factor of manure application. From 2011, NEMA will be used as official methodology to calculate the national NH 3 emission from agriculture in the Netherlands.

  12. Model analysis of riparian buffer effectiveness for reducing nutrient inputs to streams in agricultural landscapes

    NASA Astrophysics Data System (ADS)

    McKane, R. B.; M, S.; F, P.; Kwiatkowski, B. L.; Rastetter, E. B.

    2006-12-01

    Federal and state agencies responsible for protecting water quality rely mainly on statistically-based methods to assess and manage risks to the nation's streams, lakes and estuaries. Although statistical approaches provide valuable information on current trends in water quality, process-based simulation models are essential for understanding and forecasting how changes in human activities across complex landscapes impact the transport of nutrients and contaminants to surface waters. To address this need, we developed a broadly applicable, process-based watershed simulator that links a spatially-explicit hydrologic model and a terrestrial biogeochemistry model (MEL). See Stieglitz et al. and Pan et al., this meeting, for details on the design and verification of this simulator. Here we apply the watershed simulator to a generalized agricultural setting to demonstrate its potential for informing policy and management decisions concerning water quality. This demonstration specifically explores the effectiveness of riparian buffers for reducing the transport of nitrogenous fertilizers from agricultural fields to streams. The interaction of hydrologic and biogeochemical processes represented in our simulator allows several important questions to be addressed. (1) For a range of upland fertilization rates, to what extent do riparian buffers reduce nitrogen inputs to streams? (2) How does buffer effectiveness change over time as the plant-soil system approaches N-saturation? (3) How can buffers be managed to increase their effectiveness, e.g., through periodic harvest and replanting? The model results illustrate that, while the answers to these questions depend to some extent on site factors (climatic regime, soil properties and vegetation type), in all cases riparian buffers have a limited capacity to reduce nitrogen inputs to streams where fertilization rates approach those typically used for intensive agriculture (e.g., 200 kg N per ha per year for corn in the U

  13. Slash and Burn Agriculture: A Dynamic Spatio-temporal Model of Shifting Cultivation Locations and Areas

    NASA Astrophysics Data System (ADS)

    Plagge, C. E.; Frolking, S.; Chini, L. P.; Hurtt, G.

    2008-12-01

    Shifting cultivation is a form of agriculture, also known as slash-and-burn or swidden agriculture, in which a plot of forest is cleared and then cultivated continuously for several years, after which it is abandoned to revert to natural vegetation, and then is subsequently re-cleared after a longer fallow period. Shifting cultivation is an important form of agriculture because it affects soil erosion rates, canopy cover in tropical forests, nutrient deficiency in soils, and also has an impact on the global carbon cycle. Because it is generally outside of the larger economy, shifting cultivation is not well-represented in large-scale earth system analyses. We investigated a new way to model shifting cultivation which will be included in a global land-use transitions model to better quantify this type of land use, both historically and into the future. Ultimately this study will improve simulations of changes in the Earth system and will aid in the study of the carbon cycle and thus climate change. Our model calculates the area of shifting cultivation in square kilometers per half-degree grid cell, using gridded population data, the fraction of that population that is rural, the fraction of global population that practices shifting cultivation, the crop area needed per person, and the length of cultivation plus the fallow. Locations of shifting cultivation were further constrained by variables such as potential vegetation biomass density, population density, fraction of land already in use, GDP per capita, and average winter temperatures. With this model, we generated global estimates for total cultivated area, total population involved in shifting cultivation, and total shifting cultivation area including fallow lands. From this model it was estimated that the total global area of shifting cultivation in 2000 was approximately 1.5 million km2 with 90,000 km2 of that actually in cultivation by 190 million people.

  14. On the contribution of modelling to multifunctional agriculture: learning from comparisons.

    PubMed

    Groot, Jeroen C J; Rossing, Walter A H; Tichit, Muriel; Turpin, Nadine; Jellema, André; Baudry, Jacques; Verburg, Peter H; Doyen, Luc; van de Ven, Gerrie W J

    2009-05-01

    In this paper a set of criteria is proposed for the evaluation of the potential contribution of modelling tools to strengthening the multifunctionality of agriculture. The four main areas of evaluation are (1) policy relevance, (2) the temporal resolution and scope, (3) the degree to which spatial and socio-institutional scales and heterogeneity are addressed and (4) the level of integration in the assessment of scientific dimensions and of the multiple functions of agriculture. The evaluative criteria are applied to the portfolio of modelling approaches developed and applied in a joint project of the French research institute INRA and the Dutch Wageningen University & Research Centre. The CLUE-S model focuses on prediction of changes in multifunctional land-use at regional scale, given a set of predetermined scenarios or policy variants, e.g. for ex-ante policy assessment and initiation of discussions on regional development. The two other modelling approaches are complementary and aim to address multifunctional farming activities. The Landscape IMAGES framework generates a range of static images of possible but sometimes distant futures for multifunctional farming activities in a small region or landscape. It supports the exploration of trade-offs between financial returns from agriculture, landscape quality, nature conservation and restoration, and environmental quality. Co-Viability Analysis generates trajectories of states and farming decisions fulfilling a given set of ecological and productive constraints representing a desired and sustainable future. The three modelling approaches differ in their policy relevance, in the ways that spatial and socio-institutional scales are addressed and in their degree of explicitation of interaction between the various functions of agriculture, but jointly cover most of the desired capabilities for assessment of multifunctionality. Caveats were particularly identified in the integration of the socio-institutional dimension

  15. Review: Computer-based models for managing the water-resource problems of irrigated agriculture

    NASA Astrophysics Data System (ADS)

    Singh, Ajay

    2015-09-01

    Irrigation is essential for achieving food security to the burgeoning global population but unplanned and injudicious expansion of irrigated areas causes waterlogging and salinization problems. Under this backdrop, groundwater resources management is a critical issue for fulfilling the increasing water demand for agricultural, industrial, and domestic uses. Various simulation and optimization approaches were used to solve the groundwater management problems. This paper presents a review of the individual and combined applications of simulation and optimization modeling for the management of groundwater-resource problems associated with irrigated agriculture. The study revealed that the combined use of simulation-optimization modeling is very suitable for achieving an optimal solution for groundwater-resource problems, even with a large number of variables. Independent model tools were used to solve the problems of uncertainty analysis and parameter estimation in groundwater modelling studies. Artificial neural networks were used to minimize the problem of computational complexity. The incorporation of socioeconomic aspects into the groundwater management modeling would be an important development in future studies.

  16. Integrated Modelling on Flow and Water Quality Under the Impacts of Climate Change and Agricultural Activities

    NASA Astrophysics Data System (ADS)

    SHI, J.

    2014-12-01

    Climate change is expected to have a significant impact on flooding in the UK, inducing more intense and prolonged storms. Frequent flooding due to climate change already exacerbates catchment water quality. Land use is another contributing factor to poor water quality. For example, the move to intensive farming could cause an increase in faecal coliforms entering the water courses. In an effort to understand better the effects on water quality from land use and climate change, the hydrological and estuarine processes are being modelled using SWAT (Soil and Water Assessment Tool), linked to a 2-D hydrodynamic model DIVAST(Depth Integrated Velocity and Solute Transport). The coupled model is able to quantify how much of each pollutant from the catchment reaches the harbour and the impact on water quality within the harbour. The work is focused on the transportation and decay of faecal coliforms from agricultural runoff into the rivers Frome and Piddle in the UK. The impact from the agricultural land use and activities on the catchment river hydrology and water quality are evaluated. The coupled model calibration and validation showed the good model performance on flow and faecal coliform in the watershed and estuary.

  17. Incorporating representation of agricultural ecosystems and management within a dynamic biosphere model: Approach, validation, and significance

    NASA Astrophysics Data System (ADS)

    Kucharik, C.

    2004-12-01

    At the scale of individual fields, crop models have long been used to examine the interactions between soils, vegetation, the atmosphere and human management, using varied levels of numerical sophistication. While previous efforts have contributed significantly towards the advancement of modeling tools, the models themselves are not typically applied across larger continental scales due to a lack of crucial data. Furthermore, many times crop models are used to study a single quantity, process, or cycle in isolation, limiting their value in considering the important tradeoffs between competing ecosystem services such as food production, water quality, and sequestered carbon. In response to the need for a more integrated agricultural modeling approach across the continental scale, an updated agricultural version of a dynamic biosphere model (IBIS) now integrates representations of land-surface physics and soil physics, canopy physiology, terrestrial carbon and nitrogen balance, crop phenology, solute transport, and farm management into a single framework. This version of the IBIS model (Agro-IBIS) uses a short 20 to 60-minute timestep to simulate the rapid exchange of energy, carbon, water, and momentum between soils, vegetative canopies, and the atmosphere. The model can be driven either by site-specific meteorological data or by gridded climate datasets. Mechanistic crop models for corn, soybean, and wheat use physiologically-based representations of leaf photosynthesis, stomatal conductance, and plant respiration. Model validation has been performed using a variety of temporal scale data collected at the following spatial scales: (1) the precision-agriculture scale (5 m), (2) the individual field experiment scale (AmeriFlux), and (3) regional and continental scales using annual USDA county-level yield data and monthly satellite (AVHRR) observations of vegetation characteristics at 0.5 degree resolution. To date, the model has been used with great success to

  18. How Do Private Sector Schools Serve the Public Good by Fostering Inclusive Service Delivery Models?

    ERIC Educational Resources Information Center

    Scanlan, Martin; Tichy, Karen

    2014-01-01

    Conversations about promoting educational reforms that redress educational inequities often ignore private schools as irrelevant. Yet pursuits of inclusivity in private sector schools serve the public interest. This article focuses on how the system of Catholic schools in the Archdiocese of St. Louis has been purposefully striving for 2 decades to…

  19. Modeling Soil Organic Carbon for Agricultural Land Use Under Various Management Practices

    NASA Astrophysics Data System (ADS)

    Kotamarthi, V. R.; Drewniak, B.; Song, J.; Prell, J.; Jacob, R. L.

    2009-12-01

    Bioenergy is generating tremendous interest as an alternative energy source that is both environmentally friendly and economically competitive. The amount of land designated for agriculture is expected to expand, including changes in the current distribution of crops, as demand for biofuels increases as a carbon neutral alternative fuel source. However, the influence of agriculture on the carbon cycle is complex, and varies depending on land use change and management practices. The purpose of this research is to integrate agriculture in the carbon-nitrogen based Community Land Model (CLM) to evaluate the above and below ground carbon storage for corn, soybean, and wheat crop lands. The new model, CLM-Crop simulates carbon allocation during four growth stages, a soybean nitrogen fixation scheme, fertilizer, and harvest practices. We present results from this model simulation, which includes the impact of a new dynamic roots module to simulate the changing root structure and depth with growing season based on the availability of water and nitrogen in the root zone and a retranslocation scheme to simulate redistribution of nitrogen from leaves, roots, and stems to grain during organ development for crop yields, leaf area index (LAI), carbon allocation, and changes in soil carbon budgets under various practices such as fertilizer and residue management. Simulated crop yields for corn, soybean and wheat are in general agreement with measurements. Initial model results indicate a loss of soil organic carbon over cultivated lands after removal of natural vegetation which continues in the following years. Soil carbon in crop lands is a strong function of the residue management and has the potential to impact crop yields significantly.

  20. Modeling Agricultural Nonpoint Source Pollution Using a Geographic Information System Approach

    NASA Astrophysics Data System (ADS)

    Emili, Lisa A.; Greene, Richard P.

    2013-01-01

    Agricultural non-point source (NPS) pollution, primarily sediment and nutrients, is the leading source of water-quality impacts to surface waters in North America. The overall goal of this study was to develop geographic information system (GIS) protocols to facilitate the spatial and temporal modeling of changes in soils, hydrology, and land-cover change at the watershed scale. In the first part of this article, we describe the use of GIS to spatially integrate watershed scale data on soil erodibility, land use, and runoff for the assessment of potential source areas within an intensively agricultural watershed. The agricultural non-point source pollution (AGNPS) model was used in the Muddy Creek, Ontario, watershed to evaluate the effectiveness of management strategies in decreasing sediment and nutrient [phosphorus (P)] pollution. This analysis was accompanied by the measurement of water-quality parameters (dissolved oxygen, pH, hardness, alkalinity, and turbidity) as well as sediment and P loadings to the creek. Practices aimed at increasing year-round soil cover would be most effective in decreasing sediment and P losses in this watershed. In the second part of this article, we describe a method for characterizing land-cover change in a dynamic urban fringe watershed. The GIS method we developed for the Blackberry Creek, Illinois, watershed will allow us to better account for temporal changes in land use, specifically corn and soybean cover, on an annual basis and to improve on the modeling of watershed processes shown for the Muddy Creek watershed. Our model can be used at different levels of planning with minimal data preprocessing, easily accessible data, and adjustable output scales.

  1. Accuracy of some simple models for predicting particulate interception and retention in agricultural systems

    SciTech Connect

    Pinder, J.E. III; McLeod, K.W.; Adriano, D.C.

    1989-04-01

    The accuracy of three radionuclide transfer models for predicting the interception and retention of airborne particles by agricultural crops was tested using Pu-bearing aerosols released to the atmosphere from nuclear fuel facilities on the U.S. Department of Energy's Savannah River Plant, near Aiken, SC. The models evaluated were: (1) NRC, the model defined in U.S. Nuclear Regulatory Guide 1.109; (2) FOOD, a model similar to the NRC model that also predicts concentrations in grains; and (3) AGNS, a model developed from the NRC model for the southeastern United States. Plutonium concentrations in vegetation and grain were predicted from measured deposition rates and compared to concentrations observed in the field. Crops included wheat, soybeans, corn and cabbage. Although predictions of the three models differed by less than a factor of 4, they showed different abilities to predict concentrations observed in the field. The NRC and FOOD models consistently underpredicted the observed Pu concentrations for vegetation. The AGNS model was a more accurate predictor of Pu concentrations for vegetation. Both the FOOD and AGNS models accurately predicted the Pu concentrations for grains.

  2. Modelling the impacts of agricultural management practices on river water quality in Eastern England.

    PubMed

    Taylor, Sam D; He, Yi; Hiscock, Kevin M

    2016-09-15

    Agricultural diffuse water pollution remains a notable global pressure on water quality, posing risks to aquatic ecosystems, human health and water resources and as a result legislation has been introduced in many parts of the world to protect water bodies. Due to their efficiency and cost-effectiveness, water quality models have been increasingly applied to catchments as Decision Support Tools (DSTs) to identify mitigation options that can be introduced to reduce agricultural diffuse water pollution and improve water quality. In this study, the Soil and Water Assessment Tool (SWAT) was applied to the River Wensum catchment in eastern England with the aim of quantifying the long-term impacts of potential changes to agricultural management practices on river water quality. Calibration and validation were successfully performed at a daily time-step against observations of discharge, nitrate and total phosphorus obtained from high-frequency water quality monitoring within the Blackwater sub-catchment, covering an area of 19.6 km(2). A variety of mitigation options were identified and modelled, both singly and in combination, and their long-term effects on nitrate and total phosphorus losses were quantified together with the 95% uncertainty range of model predictions. Results showed that introducing a red clover cover crop to the crop rotation scheme applied within the catchment reduced nitrate losses by 19.6%. Buffer strips of 2 m and 6 m width represented the most effective options to reduce total phosphorus losses, achieving reductions of 12.2% and 16.9%, respectively. This is one of the first studies to quantify the impacts of agricultural mitigation options on long-term water quality for nitrate and total phosphorus at a daily resolution, in addition to providing an estimate of the uncertainties of those impacts. The results highlighted the need to consider multiple pollutants, the degree of uncertainty associated with model predictions and the risk of

  3. A simple model of carbon in the soil profile for agricultural soils in Northwestern Europe

    NASA Astrophysics Data System (ADS)

    Taghizadeh-Toosi, Arezoo; Hutchings, Nicholas J.; Vejlin, Jonas; Christensen, Bent T.; Olesen, Jørgen E.

    2014-05-01

    World soil carbon (C) stocks are second to those in the ocean, and represent three times as much C as currently present in the atmosphere. The amount of C in soil may play a significant role in carbon exchanges between the atmosphere and the terrestrial environment. The C-TOOL model is a three-pool linked soil organic carbon (SOC) model in well-drained mineral soils under agricultural land management to allow generalized parameterization for estimating effects of management measures at medium to long time scales for the entire soil profile (0-100 cm). C-TOOL has been developed to enable simulations of SOC turnover in soil using temperature dependent first order kinetics for describing decomposition. Compared with many other SOC models, C-TOOL applies a less complicated structure, which facilitates easier calibration, and it requires only few inputs (i.e., average monthly air temperature, soil clay content,soil carbon-to-nitrogen ratio, and C inputs to the soil from plants and other sources). C-TOOL was parameterized using SOC and radiocarbon data from selected long-term field treatments in United Kingdom, Sweden and Denmark. However, less data were available for evaluation of subsoil C (25-100 cm) from the long-term experiments applied. In Denmark a national 7×7 km grid net was established in 1986 for soil C monitoring down to 100 cm depth. The results of SOC showed a significant decline from 1997 to 2009 in the 0-50 cm soil layer. This was mainly attributed to changes in the 25-50 cm layer, where a decline in SOC was found for all soil texture types. Across the period 1986 to 2009 there was clear tendency for increasing SOC on the sandy soils and reductions on the loamy soils. This effect is linked to land use, since grasslands and dairy farms are more abundant in the western parts of Denmark, where most of the sandy soils are located. The results and the data from soil monitoring have been used to validate the C-TOOL modelling approach used for accounting of

  4. Agricultural intensification escalates future conservation costs

    PubMed Central

    Phelps, Jacob; Carrasco, Luis Roman; Webb, Edward L.; Koh, Lian Pin; Pascual, Unai

    2013-01-01

    The supposition that agricultural intensification results in land sparing for conservation has become central to policy formulations across the tropics. However, underlying assumptions remain uncertain and have been little explored in the context of conservation incentive schemes such as policies for Reducing Emissions from Deforestation and forest Degradation, conservation, sustainable management, and enhancement of carbon stocks (REDD+). Incipient REDD+ forest carbon policies in a number of countries propose agricultural intensification measures to replace extensive “slash-and-burn” farming systems. These may result in conservation in some contexts, but will also increase future agricultural land rents as productivity increases, creating new incentives for agricultural expansion and deforestation. While robust governance can help to ensure land sparing, we propose that conservation incentives will also have to increase over time, tracking future agricultural land rents, which might lead to runaway conservation costs. We present a conceptual framework that depicts these relationships, supported by an illustrative model of the intensification of key crops in the Democratic Republic of Congo, a leading REDD+ country. A von Thünen land rent model is combined with geographic information systems mapping to demonstrate how agricultural intensification could influence future conservation costs. Once postintensification agricultural land rents are considered, the cost of reducing forest sector emissions could significantly exceed current and projected carbon credit prices. Our analysis highlights the importance of considering escalating conservation costs from agricultural intensification when designing conservation initiatives. PMID:23589860

  5. Agricultural intensification escalates future conservation costs.

    PubMed

    Phelps, Jacob; Carrasco, Luis Roman; Webb, Edward L; Koh, Lian Pin; Pascual, Unai

    2013-05-01

    The supposition that agricultural intensification results in land sparing for conservation has become central to policy formulations across the tropics. However, underlying assumptions remain uncertain and have been little explored in the context of conservation incentive schemes such as policies for Reducing Emissions from Deforestation and forest Degradation, conservation, sustainable management, and enhancement of carbon stocks (REDD+). Incipient REDD+ forest carbon policies in a number of countries propose agricultural intensification measures to replace extensive "slash-and-burn" farming systems. These may result in conservation in some contexts, but will also increase future agricultural land rents as productivity increases, creating new incentives for agricultural expansion and deforestation. While robust governance can help to ensure land sparing, we propose that conservation incentives will also have to increase over time, tracking future agricultural land rents, which might lead to runaway conservation costs. We present a conceptual framework that depicts these relationships, supported by an illustrative model of the intensification of key crops in the Democratic Republic of Congo, a leading REDD+ country. A von Thünen land rent model is combined with geographic information systems mapping to demonstrate how agricultural intensification could influence future conservation costs. Once postintensification agricultural land rents are considered, the cost of reducing forest sector emissions could significantly exceed current and projected carbon credit prices. Our analysis highlights the importance of considering escalating conservation costs from agricultural intensification when designing conservation initiatives. PMID:23589860

  6. Modeling the impacts of dryland agricultural reclamation on groundwater resources in Northern Egypt using sparse data

    NASA Astrophysics Data System (ADS)

    Switzman, Harris; Coulibaly, Paulin; Adeel, Zafar

    2015-01-01

    Demand for freshwater in many dryland environments is exerting negative impacts on the quality and availability of groundwater resources, particularly in areas where demand is high due to irrigation or industrial water requirements to support dryland agricultural reclamation. Often however, information available to diagnose the drivers of groundwater degradation and assess management options through modeling is sparse, particularly in low and middle-income countries. This study presents an approach for generating transient groundwater model inputs to assess the long-term impacts of dryland agricultural land reclamation on groundwater resources in a highly data-sparse context. The approach was applied to the area of Wadi El Natrun in Northern Egypt, where dryland reclamation and the associated water use has been aggressive since the 1960s. Statistical distributions of water use information were constructed from a variety of sparse field and literature estimates and then combined with remote sensing data in spatio-temporal infilling model to produce the groundwater model inputs of well-pumping and surface recharge. An ensemble of groundwater model inputs were generated and used in a 3D groundwater flow (MODFLOW) of Wadi El Natrun's multi-layer aquifer system to analyze trends in water levels and water budgets over time. Validation of results against monitoring records, and model performance statistics demonstrated that despite the extremely sparse data, the approach used in this study was capable of simulating the cumulative impacts of agricultural land reclamation reasonably well. The uncertainty associated with the groundwater model itself was greater than that associated with the ensemble of well-pumping and surface recharge estimates. Water budget analysis of the groundwater model output revealed that groundwater recharge has not changed significantly over time, while pumping has. As a result of these trends, groundwater was estimated to be in a deficit of

  7. Development of Groundwater Management Model for Sustainable Groundwater Use in the Agricultural Region

    NASA Astrophysics Data System (ADS)

    Park, D.; Bae, G.; Lee, K.

    2010-12-01

    In many agricultural regions, high dependence of irrigation on groundwater has brought about serious concerns about unplanned groundwater developments and over-pumping. Various agricultural activities including fertilization and livestock husbandry usually result in groundwater contamination in those regions. Field works in Icheon, Korea showed that in this region the rice farming still requires a significant amount of water and continuous construction of greenhouse can make the contamination from the fertilization more serious. In this study, a groundwater management model based on the simulation-optimization methodology is developed to achieve sufficient groundwater supply and groundwater quality conservation together on regional-scale. This model can obtain the on-ground contaminant loading mass by integrating an analytical model for 1-D solute transport in unsaturated zone with 3-D groundwater flow and solute transport model, HydroGeosphere. The outputs of the 1-D unsaturated transport model, concentrations of the contaminant leaching on water table, work as contaminant sources in the 3-D solute transport model in saturated zone. This integrated simulation model is linked to genetic algorithm that searches the global optimum for the sustainable groundwater use. And, in order for the design on the contaminant sources to be more effective, it also links the backward transport model useful for evaluating the contamination from contaminant sources to each pumping well. The first objective of the management in this study is to obtain the optimal pumping rates that not only can supply sufficient amount of the groundwater but protect the groundwater from the excessive drawdown and contamination. The second objective is to control the periodic loading of the contaminant by suggesting the allowable contaminant loading mass. For this multi-objective groundwater management, the objective function to maximize both pumping rates and allowable contaminant loading mass and at

  8. Reorienting Agricultural Education towards a Free Market Model Emphasizing Economic Understanding.

    ERIC Educational Resources Information Center

    Amberson, Max L.

    Agricultural education has grown and flourished in the past because it took students with farm backgrounds and helped them become better managers and producers, thus improving agriculture in general. Now that fewer students are coming from farms into agricultural education, agricultural education has lost its protected status and become just…

  9. Modeling future water demand in California from developed and agricultural land uses

    NASA Astrophysics Data System (ADS)

    Wilson, T. S.; Sleeter, B. M.; Cameron, D. R.

    2015-12-01

    Municipal and urban land-use intensification in coming decades will place increasing pressure on water resources in California. The state is currently experiencing one of the most extreme droughts on record. This coupled with earlier spring snowmelt and projected future climate warming will increasingly constrain already limited water supplies. The development of spatially explicit models of future land use driven by empirical, historical land use change data allow exploration of plausible LULC-related water demand futures and potential mitigation strategies. We utilized the Land Use and Carbon Scenario Simulator (LUCAS) state-and-transition simulation model to project spatially explicit (1 km) future developed and agricultural land use from 2012 to 2062 and estimated the associated water use for California's Mediterranean ecoregions. We modeled 100 Monte Carlo simulations to better characterize and project historical land-use change variability. Under current efficiency rates, total water demand was projected to increase 15.1% by 2062, driven primarily by increases in urbanization and shifts to more water intensive crops. Developed land use was projected to increase by 89.8%-97.2% and result in an average 85.9% increase in municipal water use, while agricultural water use was projected to decline by approximately 3.9%, driven by decreases in row crops and increases in woody cropland. In order for water demand in 2062 to balance to current demand levels, the currently mandated 25% reduction in urban water use must remain in place in conjunction with a near 7% reduction in agricultural water use. Scenarios of land-use related water demand are useful for visualizing alternative futures, examining potential management approaches, and enabling better informed resource management decisions.

  10. Modelling the effect of agricultural management practices on soil organic carbon stocks: does soil erosion matter?

    NASA Astrophysics Data System (ADS)

    Nadeu, Elisabet; Van Wesemael, Bas; Van Oost, Kristof

    2014-05-01

    Over the last decades, an increasing number of studies have been conducted to assess the effect of soil management practices on soil organic carbon (SOC) stocks. At regional scales, biogeochemical models such as CENTURY or Roth-C have been commonly applied. These models simulate SOC dynamics at the profile level (point basis) over long temporal scales but do not consider the continuous lateral transfer of sediment that takes place along geomorphic toposequences. As a consequence, the impact of soil redistribution on carbon fluxes is very seldom taken into account when evaluating changes in SOC stocks due to agricultural management practices on the short and long-term. To address this gap, we assessed the role of soil erosion by water and tillage on SOC stocks under different agricultural management practices in the Walloon region of Belgium. The SPEROS-C model was run for a 100-year period combining three typical crop rotations (using winter wheat, winter barley, sugar beet and maize) with three tillage scenarios (conventional tillage, reduced tillage and reduced tillage in combination with additional crop residues). The results showed that including soil erosion by water in the simulations led to a general decrease in SOC stocks relative to a baseline scenario (where no erosion took place). The SOC lost from these arable soils was mainly exported to adjacent sites and to the river system by lateral fluxes, with magnitudes differing between crop rotations and in all cases lower under conservation tillage practices than under conventional tillage. Although tillage erosion plays an important role in carbon redistribution within fields, lateral fluxes induced by water erosion led to a higher spatial and in-depth heterogeneity of SOC stocks with potential effects on the soil water holding capacity and crop yields. This indicates that studies assessing the effect of agricultural management practices on SOC stocks and other soil properties over the landscape should

  11. Stochastic and recursive calibration for operational, large-scale, agricultural land and water use management models

    NASA Astrophysics Data System (ADS)

    Maneta, M. P.; Kimball, J. S.; Jencso, K. G.

    2015-12-01

    Managing the impact of climatic cycles on agricultural production, on land allocation, and on the state of active and projected water sources is challenging. This is because in addition to the uncertainties associated with climate projections, it is difficult to anticipate how farmers will respond to climatic change or to economic and policy incentives. Some sophisticated decision support systems available to water managers consider farmers' adaptive behavior but they are data intensive and difficult to apply operationally over large regions. Satellite-based observational technologies, in conjunction with models and assimilation methods, create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents at seasonal scales.We present an integrated modeling framework that can be driven by satellite remote sensing to enable robust regional assessment and prediction of climatic and policy impacts on agricultural production, water resources, and management decisions. The core of this framework is a widely used model of agricultural production and resource allocation adapted to be used in conjunction with remote sensing inputs to quantify the amount of land and water farmers allocate for each crop they choose to grow on a seasonal basis in response to reduced or enhanced access to water due to climatic or policy restrictions. A recursive Bayesian update method is used to adjust the model parameters by assimilating information on crop acreage, production, and crop evapotranspiration as a proxy for water use that can be estimated from high spatial resolution satellite remote sensing. The data assimilation framework blends new and old information to avoid over-calibration to the specific conditions of a single year and permits the updating of parameters to track gradual changes in the agricultural system.This integrated framework provides an operational means of monitoring and forecasting what crops will be grown

  12. Building factorial regression models to explain and predict nitrate concentrations in groundwater under agricultural land

    NASA Astrophysics Data System (ADS)

    Stigter, T. Y.; Ribeiro, L.; Dill, A. M. M. Carvalho

    2008-07-01

    SummaryFactorial regression models, based on correspondence analysis, are built to explain the high nitrate concentrations in groundwater beneath an agricultural area in the south of Portugal, exceeding 300 mg/l, as a function of chemical variables, electrical conductivity (EC), land use and hydrogeological setting. Two important advantages of the proposed methodology are that qualitative parameters can be involved in the regression analysis and that multicollinearity is avoided. Regression is performed on eigenvectors extracted from the data similarity matrix, the first of which clearly reveals the impact of agricultural practices and hydrogeological setting on the groundwater chemistry of the study area. Significant correlation exists between response variable NO3- and explanatory variables Ca 2+, Cl -, SO42-, depth to water, aquifer media and land use. Substituting Cl - by the EC results in the most accurate regression model for nitrate, when disregarding the four largest outliers (model A). When built solely on land use and hydrogeological setting, the regression model (model B) is less accurate but more interesting from a practical viewpoint, as it is based on easily obtainable data and can be used to predict nitrate concentrations in groundwater in other areas with similar conditions. This is particularly useful for conservative contaminants, where risk and vulnerability assessment methods, based on assumed rather than established correlations, generally produce erroneous results. Another purpose of the models can be to predict the future evolution of nitrate concentrations under influence of changes in land use or fertilization practices, which occur in compliance with policies such as the Nitrates Directive. Model B predicts a 40% decrease in nitrate concentrations in groundwater of the study area, when horticulture is replaced by other land use with much lower fertilization and irrigation rates.

  13. Coupled planning of water resources and agricultural landuse based on an inexact-stochastic programming model

    NASA Astrophysics Data System (ADS)

    Dong, Cong; Huang, Guohe; Tan, Qian; Cai, Yanpeng

    2014-03-01

    Water resources are fundamental for support of regional development. Effective planning can facilitate sustainable management of water resources to balance socioeconomic development and water conservation. In this research, coupled planning of water resources and agricultural land use was undertaken through the development of an inexact-stochastic programming approach. Such an inexact modeling approach was the integration of interval linear programming and chance-constraint programming methods. It was employed to successfully tackle uncertainty in the form of interval numbers and probabilistic distributions existing in water resource systems. Then it was applied to a typical regional water resource system for demonstrating its applicability and validity through generating efficient system solutions. Based on the process of modeling formulation and result analysis, the developed model could be used for helping identify optimal water resource utilization patterns and the corresponding agricultural land-use schemes in three sub-regions. Furthermore, a number of decision alternatives were generated under multiple water-supply conditions, which could help decision makers identify desired management policies.

  14. Modeling effectiveness of agricultural BMPs to reduce sediment load and organophosphate pesticides in surface runoff.

    PubMed

    Zhang, Xuyang; Zhang, Minghua

    2011-04-15

    Quantifying effectiveness of agricultural BMPs at the watershed scale is a challenging issue, requiring robust algorithms to simulate not only the agricultural production system but also pollutant transport and fate. This research addresses the challenge to simulate performances of BMPs in reducing organophosphates (OPs) runoff at the watershed scale. The SWAT model is calibrated and validated following a sensitivity analysis combining Latin Hypercube sampling and One-factor-At-a-Time simulation. The calibrated model is then applied in the Orestimba Creek Watershed to simulate BMPs including buffer strips, sediment ponds, vegetated ditches, use reduction, and their combinations. BMP simulation suggested that sediment ponds trap 54-85% of sediment from field runoff, but less than 10% of dissolved diazinon and chlorpyrifos. Use reduction can reduce pesticide load in a close-to-linear fashion. Effectiveness of vegetated ditches and buffers depends on their physical dimension and vegetation cover. Combining individual BMPs provides enhanced mitigation effects. The combination of vegetated ditches, buffer strips and use reduction decreases diazinon and chlorpyrifos load by over 94%. This study has suggested that the SWAT model reasonably predicts BMP effectiveness at the watershed scale. Results will assist decision making in implementing BMPs to reduce pesticide loads in surface runoff. PMID:21377192

  15. Estimating nutrient releases from agriculture in China: an extended substance flow analysis framework and a modeling tool.

    PubMed

    Chen, M; Chen, J; Sun, F

    2010-10-01

    Agriculture related pollution has attracted the attention of policy makers as well as scientists in China as its contribution to water impairment has increased, and quantitative information at the national and regional levels is being sought to support decision making. However, traditional approaches are either time-consuming, expensive (e.g. national surveys) or oversimplified and crude (e.g. coefficient methods). Therefore, this study proposed an extended substance flow analysis (SFA) framework to estimate nutrient releases from agricultural and rural activities in China by depicting the nutrient flows in Chinese agro-ecosystems. The six-step process proposed herein includes: (a) system definition; (b) model development; (c) database development; (d) model validation; (e) results interpretation; and (f) uncertainty analysis. The developed Eubolism (Elementary Unit based nutrient Balance mOdeLIng in agro-ecoSysteM) model combined a nutrient balance module with an emission inventory module to quantify the nutrient flows in the agro-ecosystem. The model was validated and then applied to estimate the total agricultural nutrient loads, identify the contribution of different agricultural and rural activities and different land use types to the total loads, and analyze the spatial pattern of agricultural nutrient emissions in China. These results could provide an entire picture of agricultural pollution at the national level and be used to support policy making. Furthermore, uncertainties associated with the structure of the elementary units, spatial resolution, and inputs/parameters were also analyzed to evaluate the robustness of the model results. PMID:20691463

  16. Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments.

    PubMed

    Oliver, David M; Porter, Kenneth D H; Pachepsky, Yakov A; Muirhead, Richard W; Reaney, Sim M; Coffey, Rory; Kay, David; Milledge, David G; Hong, Eunmi; Anthony, Steven G; Page, Trevor; Bloodworth, Jack W; Mellander, Per-Erik; Carbonneau, Patrice E; McGrane, Scott J; Quilliam, Richard S

    2016-02-15

    The application of models to predict concentrations of faecal indicator organisms (FIOs) in environmental systems plays an important role for guiding decision-making associated with the management of microbial water quality. In recent years there has been an increasing demand by policy-makers for models to help inform FIO dynamics in order to prioritise efforts for environmental and human-health protection. However, given the limited evidence-base on which FIO models are built relative to other agricultural pollutants (e.g. nutrients) it is imperative that the end-user expectations of FIO models are appropriately managed. In response, this commentary highlights four over-arching questions associated with: (i) model purpose; (ii) modelling approach; (iii) data availability; and (iv) model application, that must be considered as part of good practice prior to the deployment of any modelling approach to predict FIO behaviour in catchment systems. A series of short and longer-term research priorities are proposed in response to these questions in order to promote better model deployment in the field of catchment microbial dynamics. PMID:26657248

  17. Modeling of Movement of Field Gudgeon, Gnathopogon elongatus elongatus, in Agricultural Canals in Yatsu Paddy Fields

    NASA Astrophysics Data System (ADS)

    Takemura, Takeshi; Koizumi, Noriyuki; Mizutani, Masakazu; Mori, Atsushi; Watabe, Keiji

    It is important as quantitative information for making a decision of project sites for networking of water area, to predict reproductive process of fish population when consolidating fish-ways on points dividing fish habitat. To that end, it is necessary to predict the number of individuals migrating to new habitats. Hence, modeling of movement of individuals is necessary as a first step in population modeling. We constructed a mathematical model of movement of field gudgeon in agricultural canals, comparing with observed data obtained by our surveys. A unit time span of this model is 50 days. This model is able to consider existence of 2 types of movement, namely, individuals of sedentary type and individuals of ambulant type. Parameters of the model were decided based on observed data which correspond to 1 unit span. Next, moving distances of 6 individuals for 4 unit span were calculated using those parameters. A histogram of calculated values was similar to that of observed data which correspond to 4 unit span. The model is expected to provide an important immigration component to a population dynamics model which is currently under development. The population model is needed to predict population recovery processes where areas of paddy fields are joined in larger networks through construction of fish-ways.

  18. A distribution model for the aerial application of granular agricultural particles

    NASA Technical Reports Server (NTRS)

    Fernandes, S. T.; Ormsbee, A. I.

    1978-01-01

    A model is developed to predict the shape of the distribution of granular agricultural particles applied by aircraft. The particle is assumed to have a random size and shape and the model includes the effect of air resistance, distributor geometry and aircraft wake. General requirements for the maintenance of similarity of the distribution for scale model tests are derived and are addressed to the problem of a nongeneral drag law. It is shown that if the mean and variance of the particle diameter and density are scaled according to the scaling laws governing the system, the shape of the distribution will be preserved. Distributions are calculated numerically and show the effect of a random initial lateral position, particle size and drag coefficient. A listing of the computer code is included.

  19. A Sectored-One-Dimensional Model for Simulating Combustion Instabilities in Premix Combustors

    NASA Technical Reports Server (NTRS)

    Paxson, Daniel E.

    1999-01-01

    A one-dimensional, CFD based combustor simulation has been developed that exhibits self-excited, thermoacoustic oscillations in premixed combustor geometries that typically have large, abrupt changes in cross sectional area. The combustor geometry is approximated by dividing it into a finite number of one-dimensional sectors. Within each sector, the equations of motion are integrated numerically, along with a species transport and a reaction equation. Across the sectors, mass and energy are conserved, and momentum loss is prescribed using appropriately compatible boundary conditions that account for the area change. The resulting simulation and associated boundary conditions essentially represent a one-dimensional, multi-block technique. Details of the simulation code are presented herein. Results are then shown comparing experimentally observed and simulated operation of a particular combustor rig that exhibited different instabilities at different operating points. It will be shown that the simulation closely matched the rig data in oscillation amplitudes, frequencies, and operating points at which the instabilities occurred. Finally, advantages and limitations of the simulation technique are discussed.

  20. Using Coupled Hydrologic and Agro-economic Models to Evaluate the Impact of Agricultural Activity on Streamflows

    NASA Astrophysics Data System (ADS)

    Brugger, D. R.; Maneta, M. P.

    2014-12-01

    Irrigation substantially alters the timing and magnitude of surface water flows, and continued agricultural intensification to keep up with demand means perpetual stress on surface water resources. A critical challenge is to manage irrigation in a way that balances ecosystem health with sustaining agricultural economies. Coupled hydrologic-agroeconomic models are promising tools for meeting this challenge: the models can quantify 1) how water withdrawal for irrigation impacts streamflows, 2) how these impacts propagate through a surface water system, 3) how the amount of water available for irrigation changes the allocation of resources (e.g. land, water) to available crops, and 4) the impact of water availability on agricultural economies. However, these models can be very data intensive, which limits their applicability. We present a parsimonious coupled hydrologic-agroeconomic model that uses the Positive Mathematical Programming (PMP) method, extensively used in agricultural resource economics, and calibrates to data on allotment of agricultural inputs, available from sources such as the USDA's National Agricultural Statistics Service. PMP assumes that farmers allocate resources to maximize net revenues, justifying the use of optimality conditions to constrain the parameters of the agroeconomic model. We improve the standard PMP model by 1) having the calibrated model reproduce not only the observed input allotment but also the observed yield, and 2) using the ensemble Kalman filter equations to solve the mathematical programming problem recursively, which permits refinement of the model calibration as new observations become available. We demonstrate the proposed agroeconomic model by coupling it to HEC-HMS, a hydrologic model capable of simulating regional natural and man-made water distribution networks, to investigate the sensitivity of streamflows to the allocation of agricultural inputs (land and water) in response to changes in climatic and economic

  1. Nutrient Models Developments Using Runoff-Nutrient Relationships in an Agricultural Prairie Basin, Manitoba.

    NASA Astrophysics Data System (ADS)

    Mahmood, T. H.; Pomeroy, J. W.; Wheater, H. S.; Elliott, J. A.; Baulch, H. M.; Lindenschmidt, K. E.

    2015-12-01

    Nutrient export to streams and lakes from agricultural activities can result in significant deterioration of water quality and aquatic ecosystem health. In Western Canada, particular concerns arise for prairie agricultural systems, which are dominated by the effects of a cold climate. Insufficient attention has been given to understand the links between cold region watershed responses and nutrient concentration and a robust watershed-scale modeling framework is needed to simulate nutrient concentration and loads. Long-term, field observations of nutrient concentration-runoff relationships were used to develop nutrient concentration models for the Tobacco Creek Model Watershed (TCMW) which drains into the Red River basin. Field observations include streamflow concentrations of N and P at multiple scales from two headwater basins. Distinct nutrient concentration-runoff models for snowmelt, rain on snow (ROS) and rainfall runoff processes were developed from observed runoff-nutrient concentration relationships. Snowmelt runoff had a moderately positive correlation with particulate nutrient concentrations but no correlation with that of dissolved nutrients. ROS runoff had a weak relationship with both particulate and dissolved nutrient concentrations. Rainfall runoff had the strongest positive correlation with particulate nutrient concentrations but no association with that of dissolved nutrients. The modeling approach also identified a clear hysteretic behavior in the relationship between runoff and particulate nutrient concentration during the 2013 snowmelt runoff event at the basin outlet gauge. The models provide insight into the hydrological controls on nutrient export from cold regions watersheds and the strong effects of inter-annual climatic variability. Snowmelt runoff is a reliable exporter of large nutrient loads while nutrient export by rainfall runoff exceeded snowmelt runoff during hydrologically wet summers such as 2002, 2005, 2011 and 2013.

  2. Changes in Discharge in an Agricultural Watershed in Iowa: Modeling and Projections

    NASA Astrophysics Data System (ADS)

    Villarini, G.

    2014-12-01

    Our improved capability to adapt to future changes in discharge is unavoidably linked to our capability to predict the magnitude or at least the direction of these changes. The importance of improving discharge projections is particularly relevant in an agricultural state like Iowa. Iowa has been affected by a sequence of extreme events over the most recent years, with the flood events of 1993, 2008, 2010, 2013 and 2014 interrupted by the droughts of 2012 and summer 2013. It is clear that too much or too little water will have severe economic and societal impacts for this state, and the agricultural U.S. Midwest more generally. Therefore, being able to increase our confidence in the direction and magnitude of the projected changes in discharge (from low to high flow) will be of key importance for improving our mitigation and management strategies during both flooding and droughts. Here we focus on the Raccoon River at Van Meter, Iowa, and use a statistical approach to examine projected changes in discharge. We build on statistical models using rainfall and harvested corn and soybean acreage to explain the observed stream flow variability. We then use projections of these two predictors to examine the projected discharge response. Results are based on seven state-of-the-art global climate models (GCMs) produced under the Fifth Coupled Model Intercomparison Project (CMIP5), and two representative concentration pathways (RCPs 4.5 and 8.5). We find that there is not a strong signal of change in the discharge projections under the RCP 4.5. On the other hand, the results for the RCP 8.5 point to a stronger changing signal, in particular increasing trends in the upper part of the discharge distribution. Examination of two hypothetical agricultural scenarios indicates that these increasing trends could be potentially offset by decreasing the extent of the agricultural production. Finally, we discuss how to move forward with the concept of return period for engineering

  3. Simulating The Change In Agricultural Fruit Patterns In The Context of River Basin Modelling

    NASA Astrophysics Data System (ADS)

    Kloecking, B.; Laue, K.; Stroebl, B.

    A new concept has been developed for the integrated analysis of impacts of Global Change and direct human activities on the environment and the society in mesoscale river basins. The main steps of this approach are: (1) Developing a set of regional scenarios of change considering expected changes in climate, economic, demographic and social development, (2) Identification of indicators of sustainability for the impact assessment, (3) Impact analysis of the defined scenarios of development, (4) Evalu- ation of the different scenarios on the basis of the impact analysis to elaborate new stategies in regional development. All steps include consultations with actors and stakeholders. The concept is applied in the western part of Thuringia (7.500 km2), covering the basin of the Unstrut river. This part of the German Elbe river basin is highly suited for food production under the present conditions. Therefore it is a good site for vulnerability studies focused on agriculture. The development of agricultural land-use scenarios for the Unstrut region will be done in form of a bottom-up approach based on adaptation reactions of example farms within the expected boundary condi- tions such as the global food markets and other global economic trends as well as in- ternational agreements. Representing the present conditions in Thuringia, a referential land-use scenario was developed, assuming a complete realisation of the AGENDA 2000 resolutions. Impacts of changed land use in combination with climate change scenarios on plant production and on availability and quality of water are been inves- tigated with the help of a spatial distributed river basin model. A GIS-based approach was developed to locate the spatially not explicit land use scenarios. This approach allows to reproduce the agricultural fruit patterns of a region in a river basin model without taking into account the real field boundaries. First simulation results for the referential climate and land-use scenario

  4. Modeling temperature-dependent survival with small datasets: insights from tropical mountain agricultural pests.

    PubMed

    Crespo-Pérez, Verónica; Dangles, Olivier; Régnière, Jacques; Chuine, Isabelle

    2013-06-01

    Many regions are increasingly threatened by agricultural pests but suffer from a lack of data that hampers the development of adequate population dynamics models that could contribute to pest management strategies. Here, we present a new model relating pest survival to temperature and compare its performance with two published models. We were particularly interested in their ability to simulate the deleterious effect of extreme temperatures even when adjusted to datasets that did not include extreme temperature conditions. We adjusted the models to survival data of three species of potato tuber moth (PTM), some major pests in the Tropical Andes. To evaluate model performance, we considered both goodness-of-fit and robustness. The latter consisted in evaluating their ability to predict the actual altitudinal limits of the species in the Ecuadorian Andes. We found that even though our model did not always provide the best fit to data, it predicted extreme temperature mortality and altitudinal limits accurately and better than the other two models. Our study shows that the ability to accurately represent the physiological limits of species is important to provide robust predictions of invasive pests' potential distribution, particularly in places where temperatures approach lethal extremes. The value of our model lies in its ability to simulate accurate thermal tolerance curves even with small datasets, which is useful in places where adequate pest management is urgent but data are scarce. PMID:23448173

  5. Who Talks to Whom in Malawi's Agricultural Research Information Network?

    ERIC Educational Resources Information Center

    Mapila, Mariam A. T. J.; Yauney, Jason; Thangata, Paul; Droppelmann, Klaus; Mazunda, John

    2016-01-01

    Purpose: The sector-wide approach currently dominates as the strategy for developing the agricultural sector of many African countries. Although recognised that collaborative agricultural research is vital in ensuring success of sector-wide agricultural development strategies; there have been few efforts to understand the dynamics of national…

  6. Modelling the effects of recent agricultural land use change on catchment flow and sediment generation

    NASA Astrophysics Data System (ADS)

    Escobar Ruiz, Veronica; Smith, Hugh; Blake, William

    2016-04-01

    Intensive agricultural practices can exacerbate runoff and soil erosion leading to detrimental impacts downstream. Physically-based models have previously been used to assess the impacts on flow and sediment transport in response to land use change, but there has been little investigation of the effect shorter-term changes linked to variations in the extent of cultivated land. The aim of this project is to quantify the impacts on flow generation and sediment transport of different catchment conditions related to both actual recent changes in agricultural land use as well as future change scenarios. To this end, a physically-based distributed hydrological model, SHETRAN was applied in the Blackwater catchment (12 km2) located in south-west England. Land cover was simulated on the basis of satellite-derived land cover maps (1990, 2000 and 2007) as well as a catchment-scale field survey (2011). Soils were represented in the model using five layers for five different soil types in which parameter values were varied in accordance with land use and literature values. Rainfall data (15 min) combined with monthly calculations of evapotranspiration using a simple temperature-based PE model were used to represent contemporary climatic conditions spanning 2010-2014. Calibration was undertaken for selected events during 2011 when land use information was concurrent with available flow and suspended sediment yield data. All land use simulations were then completed for the period 2010-2014 to enable the comparison of model outputs. This contribution will present preliminary results from these land use simulations alongside the effect of several future changes scenarios on catchment flow and sediment generation.

  7. Linking agricultural crop management and air quality models for regional to national-scale nitrogen assessments

    NASA Astrophysics Data System (ADS)

    Cooter, E. J.; Bash, J. O.; Benson, V.; Ran, L.

    2012-10-01

    While nitrogen (N) is an essential element for life, human population growth and demands for energy, transportation and food can lead to excess nitrogen in the environment. A modeling framework is described and implemented to promote a more integrated, process-based and system-level approach to the estimation of ammonia (NH3) emissions which result from the application of inorganic nitrogen fertilizers to agricultural soils in the United States. The United States Department of Agriculture (USDA) Environmental Policy Integrated Climate (EPIC) model is used to simulate plant demand-driven fertilizer applications to commercial cropland throughout the continental US. This information is coupled with a process-based air quality model to produce continental-scale NH3 emission estimates. Regional cropland NH3 emissions are driven by the timing and amount of inorganic NH3 fertilizer applied, soil processes, local meteorology, and ambient air concentrations. Initial fertilizer application often occurs when crops are planted. A state-level evaluation of EPIC-simulated, cumulative planted area compares well with similar USDA reported estimates. EPIC-annual, inorganic fertilizer application amounts also agree well with reported spatial patterns produced by others, but domain-wide the EPIC values are biased about 6% low. Preliminary application of the integrated fertilizer application and air quality modeling system produces a modified geospatial pattern of seasonal NH3 emissions that improves current simulations of observed atmospheric particle nitrate concentrations. This modeling framework provides a more dynamic, flexible, and spatially and temporally resolved estimate of NH3 emissions than previous factor-based NH3 inventories, and will facilitate evaluation of alternative nitrogen and air quality policy and adaptation strategies associated with future climate and land use changes.

  8. Linking agricultural crop management and air quality models for regional to national-scale nitrogen assessments

    NASA Astrophysics Data System (ADS)

    Cooter, E. J.; Bash, J. O.; Benson, V.; Ran, L.

    2012-05-01

    While nitrogen (N) is an essential element for life, human population growth and demands for energy, transportation and food can lead to excess nitrogen in the environment. A modeling framework is described and implemented, to promote a more integrated, process-based and system-level approach to the estimation of ammonia (NH3) emissions resulting from the application of inorganic nitrogen fertilizers to agricultural soils in the United States. The United States Department of Agriculture (USDA) Environmental Policy Integrated Climate (EPIC) model is used to simulate plant demand-driven fertilizer applications to commercial cropland throughout the continental US. This information is coupled with a process-based air quality model to produce continental-scale NH3 emission estimates. Regional cropland NH3 emissions are driven by the timing and amount of fertilizer applied, local meteorology, and ambient air concentrations. An evaluation of EPIC-simulated crop management activities associated with fertilizer application at planting compared with similar USDA state-level event estimates shows temporally progressive spatial patterns that agree well with one another. EPIC annual inorganic fertilizer application amounts also agree well with reported spatial patterns produced by others, but domain-wide the EPIC values are biased about 6 % low. Preliminary application of the integrated fertilizer application and air quality modeling system produces a modified geospatial pattern of seasonal NH3 emissions that improves current simulations of observed atmospheric nitrate concentrations. This modeling framework provides a more dynamic, flexible, and spatially and temporally resolved estimate of NH3 emissions than previous factor-based NH3 inventories, and will facilitate evaluation of alternative nitrogen and air quality policy and adaptation strategies associated with future climate and land use changes.

  9. Accessible integration of agriculture, groundwater, and economic models using the Open Modeling Interface (OpenMI): methodology and initial results

    NASA Astrophysics Data System (ADS)

    Bulatewicz, T.; Yang, X.; Peterson, J. M.; Staggenborg, S.; Welch, S. M.; Steward, D. R.

    2010-03-01

    Policy for water resources impacts not only hydrological processes, but the closely intertwined economic and social processes dependent on them. Understanding these process interactions across domains is an important step in establishing effective and sustainable policy. Multidisciplinary integrated models can provide insight to inform this understanding, though the extent of software development necessary is often prohibitive, particularly for small teams of researchers. Thus there is a need for practical methods for building interdisciplinary integrated models that do not incur a substantial development effort. In this work we adopt the strategy of linking individual domain models together to build a multidisciplinary integrated model. The software development effort is minimized through the reuse of existing models and existing model-linking tools without requiring any changes to the model source codes, and linking these components through the use of the Open Modeling Interface (OpenMI). This was found to be an effective approach to building an agricultural-groundwater-economic integrated model for studying the effects of water policy in irrigated agricultural systems. The construction of the integrated model provided a means to evaluate the impacts of two alternative water-use policies aimed at reducing irrigated water use to sustainable levels in the semi-arid grasslands overlying the Ogallala Aquifer of the Central US. The results show how both the economic impact in terms of yield and revenue and the environmental impact in terms of groundwater level vary spatially throughout the study region for each policy. Accessible integration strategies are necessary if the practice of interdisciplinary integrated simulation is to become widely adopted.

  10. Accessible integration of agriculture, groundwater, and economic models using the Open Modeling Interface (OpenMI): methodology and initial results

    NASA Astrophysics Data System (ADS)

    Bulatewicz, T.; Yang, X.; Peterson, J. M.; Staggenborg, S.; Welch, S. M.; Steward, D. R.

    2009-11-01

    Policy for water resources impacts not only hydrological processes, but the closely intertwined economic and social processes dependent on them. Understanding these process interactions across domains is an important step in establishing effective and sustainable policy. Multidisciplinary integrated models can provide insight to inform this understanding, though the extent of software development necessary is often prohibitive, particularly for small teams of researchers. Thus there is a need for practical methods for building interdisciplinary integrated models that do not incur a substantial development effort. In this work we adopt the strategy of linking individual domain models together to build a multidisciplinary integrated model. The software development effort is minimized through the reuse of existing models and existing model-linking tools without requiring any changes to the model source codes, and linking these components through the use of the Open Modeling Interface (OpenMI). This was found to be an effective approach to building an agricultural-groundwater-economic integrated model for studying the effects of water policy in irrigated agricultural systems. The construction of the integrated model provided a means to evaluate the impacts of two alternative water-use policies aimed at reducing irrigated water use to sustainable levels in the semi-arid grasslands overlying the Ogallala Aquifer of the Central US. The results show how both the economic impact in terms of yield and revenue and the environmental impact in terms of groundwater level vary spatially throughout the study region for each policy. Accessible integration strategies are necessary if the practice of interdisciplinary integrated simulation is to become widely adopted.

  11. A Satellite Based Modeling Framework for Estimating Seasonal Carbon Fluxes Over Agricultural Lands

    NASA Astrophysics Data System (ADS)

    Bandaru, V.; Houborg, R.; Izaurralde, R. C.

    2014-12-01

    Croplands are typically characterized by fine-scale heterogeneity, which makes it difficult to accurately estimate cropland carbon fluxes over large regions given the fairly coarse spatial resolution of high-frequency satellite observations. It is, however, important that we improve our ability to estimate spatially and temporally resolved carbon fluxes because croplands constitute a large land area and have a large impact on global carbon cycle. A Satellite based Dynamic Cropland Carbon (SDCC) modeling framework was developed to estimate spatially resolved crop specific daily carbon fluxes over large regions. This modeling framework uses the REGularized canopy reFLECtance (REGFLEC) model to estimate crop specific leaf area index (LAI) using downscaled MODIS reflectance data, and subsequently LAI estimates are integrated into the Environmental Policy Integrated Model (EPIC) model to determine daily net primary productivity (NPP) and net ecosystem productivity (NEP). Firstly, we evaluate the performance of this modeling framework over three eddy covariance flux tower sites (Bondville, IL; Fermi Agricultural Site, IL; and Rosemount site, MN). Daily NPP and NEP of corn and soybean crops are estimated (based on REGFLEC LAI) for year 2007 and 2008 over the flux tower sites and compared against flux tower observations and model estimates based on in-situ LAI. Secondly, we apply the SDCC framework for estimating regional NPP and NEP for corn, soybean and sorghum crops in Nebraska during year 2007 and 2008. The methods and results will be presented.

  12. A Satellite Based Modeling Framework for Estimating Seasonal Carbon Fluxes Over Agricultural Lands

    NASA Astrophysics Data System (ADS)

    Bandaru, V.; Izaurralde, R. C.; Sahajpal, R.; Houborg, R.; Milla, Z.

    2013-12-01

    Croplands are typically characterized by fine-scale heterogeneity, which makes it difficult to accurately estimate cropland carbon fluxes over large regions given the fairly coarse spatial resolution of high-frequency satellite observations. It is, however, important that we improve our ability to estimate spatially and temporally resolved carbon fluxes because croplands constitute a large land area and have a large impact on global carbon cycle. A Satellite based Dynamic Cropland Carbon (SDCC) modeling framework was developed to estimate spatially resolved crop specific daily carbon fluxes over large regions. This modeling framework uses the REGularized canopy reFLECtance (REGFLEC) model to estimate crop specific leaf area index (LAI) using downscaled MODIS reflectance data, and subsequently LAI estimates are integrated into the Environmental Policy Integrated Model (EPIC) model to determine daily net primary productivity (NPP) and net ecosystem productivity (NEP). Firstly, we evaluate the performance of this modeling framework over three eddy covariance flux tower sites (Bondville, IL; Fermi Agricultural Site, IL; and Rosemount site, MN). Daily NPP and NEP of corn and soybean crops are estimated (based on REGFLEC LAI) for year 2007 and 2008 over the flux tower sites and compared against flux tower observations and model estimates based on in-situ LAI. Secondly, we apply the SDCC framework for estimating regional NPP and NEP for corn, soybean and sorghum crops in Nebraska during year 2007 and 2008. The methods and results will be presented.

  13. Agricultural Water Use under Global Change

    NASA Astrophysics Data System (ADS)

    Zhu, T.; Ringler, C.; Rosegrant, M. W.

    2008-12-01

    Irrigation is by far the single largest user of water in the world and is projected to remain so in the foreseeable future. Globally, irrigated agricultural land comprises less than twenty percent of total cropland but produces about forty percent of the world's food. Increasing world population will require more food and this will lead to more irrigation in many areas. As demands increase and water becomes an increasingly scarce resource, agriculture's competition for water with other economic sectors will be intensified. This water picture is expected to become even more complex as climate change will impose substantial impacts on water availability and demand, in particular for agriculture. To better understand future water demand and supply under global change, including changes in demographic, economic and technological dimensions, the water simulation module of IMPACT, a global water and food projection model developed at the International Food Policy Research Institute, is used to analyze future water demand and supply in agricultural and several non-agricultural sectors using downscaled GCM scenarios, based on water availability simulation done with a recently developed semi-distributed global hydrological model. Risk analysis is conducted to identify countries and regions where future water supply reliability for irrigation is low, and food security may be threatened in the presence of climate change. Gridded shadow values of irrigation water are derived for global cropland based on an optimization framework, and they are used to illustrate potential irrigation development by incorporating gridded water availability and existing global map of irrigation areas.

  14. European scale climate information services for water use sectors

    NASA Astrophysics Data System (ADS)

    van Vliet, Michelle T. H.; Donnelly, Chantal; Strömbäck, Lena; Capell, René; Ludwig, Fulco

    2015-09-01

    This study demonstrates a climate information service for pan-European water use sectors that are vulnerable to climate change induced hydrological changes, including risk and safety (disaster preparedness), agriculture, energy (hydropower and cooling water use for thermoelectric power) and environment (water quality). To study the climate change impacts we used two different hydrological models forced with an ensemble of bias-corrected general circulation model (GCM) output for both the lowest (2.6) and highest (8.5) representative concentration pathways (RCP). Selected indicators of water related vulnerability for each sector were then calculated from the hydrological model results. Our results show a distinct north-south divide in terms of climate change impacts; in the south the water availability will reduce while in the north water availability will increase. Across different climate models precipitation and streamflow increase in northern Europe and decrease in southern Europe, but the latitude at which this change occurs varies depending on the GCM. Hydrological extremes are increasing over large parts of Europe. The agricultural sector will be affected by reduced water availability (in the south) and increased drought. Both streamflow and soil moistures droughts are projected to increase in most parts of Europe except in northern Scandinavia and the Alps. The energy sector will be affected by lower hydropower potential in most European countries and reduced cooling water availability due to higher water temperatures and reduced summer river flows. Our results show that in particular in the Mediterranean the pressures are high because of increasing drought which will have large impacts on both the agriculture and energy sectors. In France and Italy this is combined with increased flood hazards. Our results show important impacts of climate change on European water use sectors indicating a clear need for adaptation.

  15. LandSoil model application for erosion management in sustainable agricultural landscapes

    NASA Astrophysics Data System (ADS)

    Smetanova, Anna; Follain, Stéphane; Raclot, Damien; Le Bissonnais, Yves

    2016-04-01

    Soil erosion and land degradation can lead to irreversible changes and landscape degradation. In order to achieve the sustainability of agricultural landscapes, the land use scenarios might be developed and tested for their erosion mitigation effects. Despite the importance of the long-term scenarios (which are complicated by predictability of climate change in a small scale, its effect on change in soil properties and crops, and the societal behaviour of individual players), the management decision have to be applied already now. Therefore the short-term and medium term scenarios to achieve the most effective soil management and the least soil erosion footprint are necessary to develop. With increasing importance of individual large erosion events, the event-based models, considering soil properties and landscape structures appears to be suitable. The LandSoil model (Ciampalini et al., 2012) - a landscape evolution model operating at the field/small catchment scale, have been applied in order to analyse the effect of different soil erosion mitigation and connectivity management practices in two different Mediterranean catchments. In the soil erosion scenarios the proposed measures targeted soil erosion on field or on catchment scale, and the effect of different extreme events on soil redistribution was evaluated under different spatial designs. Anna Smetanová has received the support of the AgreenSkills fellowship (under grant agreement n°267196). R. Ciampalini, S. Follain, Y. Le Bissonnais, LandSoil: A model for analysing the impact of erosion on agricultural landscape evolution, Geomorphology, 175-176, 2012, 25-37.

  16. Testing parametric BRDF models with CHRIS/PROBA acquisitions over agricultural crops

    NASA Astrophysics Data System (ADS)

    Verger, Aleixandre; Camacho-de Coca, Fernando; Meli, Joaquin

    2004-10-01

    A proper determination of the BRDF is of interest for land surface studies in different topics such as albedo estimation, correction of anisotropy effects, and retrieval of vegetation parameters by defining optimal geometries. In this paper, we evaluate a set of parametric models widely-used for BRDF characterisation (Roujean model, Ambrals combinations, non-linear RPV and the empirical Walthall's model). These models are inverted and tested against atmospherically-corrected BRF measurements acquired with the CHRIS (Compact High Resolution Imaging Spectrometer) instrument on board the PROBA (Project for On-Board Autonomy) satellite over an agricultural test site located in Barrax, Spain) during the SPARC (SPectra bARrax Campaign) 2003 campaign. The study area presents different land crops with high variability in LAI values from 0 to 6. The objectives of the present study are to determine how well the different parametric BRDF models are able to fit CHRIS/PROBA's observed multiangular reflectances in order to determine the nadir-zenith reflectance, which is the optimal geometry to retrieve the fractional vegetation coverage (FVC), and to describe the anisotropy of vegetation canopies, which can be useful to estimate accurately the leaf area index (LAI). To do so, performance indicators are obtained for the different models. The results of this study show that all the tested models are fairly accurate in the entire spectral range (RMS<0.016 at 674 nm and RMS<0.025 at 803 nm) and thus are suitable for normalisation purposes. However, most of them are not able to describe BRDF features such as the hot spot, which hampers the use of these models for exploiting the directional information. There are no significant differences, for the experimental conditions, among those evaluated although the best models appear to be the linear Ross-Li model (low RMS) and the non-linear RPV model (more realistic BRDF).

  17. Uncertainties in data and models to describe event dynamics of agricultural sediment and phosphorus transfer.

    PubMed

    Krueger, Tobias; Quinton, John N; Freer, Jim; Macleod, Christopher J A; Bilotta, Gary S; Brazier, Richard E; Butler, Patricia; Haygarth, Philip M

    2009-01-01

    Mathematical models help to quantify agricultural sediment and phosphorus transfers and to simulate mitigation of pollution. This paper develops empirical models of the dominant sediment and phosphorus event dynamics observed at high resolution in a drained and undrained, intensive grassland field-scale lysimeter (1 ha) experiment. The uncertainties in model development and simulation are addressed using Generalized Likelihood Uncertainty Estimation. A comparison of suspended solids (SS) and total phosphorus (TP) samples with a limited number of manual repeats indicates larger data variability at low flows. Quantitative uncertainty estimates for discharge (Q) are available from another study. Suspended solids-discharge (SS-Q) hysteresis is analyzed for four events and two drained and two undrained fields. Hysteresis loops differ spatially and temporally, and exhaustion is apparent between sequential hydrograph peaks. A coherent empirical model framework for hysteresis, where SS is a function of Q and rate of change of Q, is proposed. This is evaluated taking the Q uncertainty into account, which can contribute substantially to the overall uncertainty of model simulations. The model simulates small hysteresis loops well but fails to simulate exhaustion of SS sources and flushing at the onset of events. Analysis of the TP-SS relationship reveals that most of the variability occurs at low flows, and a power-law relationship can explain the dominant behavior at higher flows, which is consistent across events, fields, and pathways. The need for further field experiments to test hypotheses of sediment mobilization and to quantify data uncertainties is identified. PMID:19398511

  18. Impact of energy prices on agricultural and energy markets: an integrated modeling approach

    EPA Science Inventory

    The accelerated growth in biofuels markets has both created and reinforced linkages between agricultural and energy markets. This study investigates the dynamics in biofuel and agricultural markets under alternative price scenarios for both crude oil and natural gas. Two energy ...

  19. Nonlinear stochastic model for the analysis of energy investment in the manufacturing sector of the United States

    SciTech Connect

    Pena-Taveras, M.S.

    1986-01-01

    The fast depletion of the non-renewable energy resources and the need to introduce new technologies into the manufacturing sector of the US economy require a better understanding of investment patterns for equipment and operational energy. In view of the above, and to provide a useful tool to the decision maker, a nonlinear, stochastic model is developed using the concepts of the Schumpeter Clock Model. The proposed model is validated using economic data for the period 1961-1980. It appears that the proposed model is a useful tool in the decision making process, where the manager, to maximize profit, must make choices between investing in equipment and the purchase of fuels and electricity.

  20. Climate Change for Agriculture, Forest Cover and 3d Urban Models

    NASA Astrophysics Data System (ADS)

    Kapoor, M.; Bassir, D.

    2014-11-01

    This research demonstrates the important role of the remote sensing in finding out the different parameters behind the agricultural crop change, forest cover and urban 3D models. Standalone software is developed to view and analysis the different factors effecting the change in crop productions. Open-source libraries from the Open Source Geospatial Foundation have been used for the development of the shape-file viewer. Software can be used to get the attribute information, scale, zoom in/out and pan the shapefiles. Environmental changes due to pollution and population that are increasing the urbanisation and decreasing the forest cover on the earth. Satellite imagery such as Landsat 5(1984) to Landsat TRIS/8 (2014), Landsat Data Continuity Mission (LDCM) and NDVI are used to analyse the different parameters that are effecting the agricultural crop production change and forest change. It is advisable for the development of good quality of NDVI and forest cover maps to use data collected from the same processing methods for the complete region. Management practices have been developed from the analysed data for the betterment of the crop and saving the forest cover

  1. Mathematical modelling of antimicrobial resistance in agricultural waste highlights importance of gene transfer rate.

    PubMed

    Baker, Michelle; Hobman, Jon L; Dodd, Christine E R; Ramsden, Stephen J; Stekel, Dov J

    2016-04-01

    Antimicrobial resistance is of global concern. Most antimicrobial use is in agriculture; manures and slurry are especially important because they contain a mix of bacteria, including potential pathogens, antimicrobial resistance genes and antimicrobials. In many countries, manures and slurry are stored, especially over winter, before spreading onto fields as organic fertilizer. Thus, these are a potential location for gene exchange and selection for resistance. We develop and analyse a mathematical model to quantify the spread of antimicrobial resistance in stored agricultural waste. We use parameters from a slurry tank on a UK dairy farm as an exemplar. We show that the spread of resistance depends in a subtle way on the rates of gene transfer and antibiotic inflow. If the gene transfer rate is high, then its reduction controls resistance, while cutting antibiotic inflow has little impact. If the gene transfer rate is low, then reducing antibiotic inflow controls resistance. Reducing length of storage can also control spread of resistance. Bacterial growth rate, fitness costs of carrying antimicrobial resistance and proportion of resistant bacteria in animal faeces have little impact on spread of resistance. Therefore, effective treatment strategies depend critically on knowledge of gene transfer rates. PMID:26906100

  2. Modeling the impacts of regulatory frameworks on self-organization in dryland agricultural systems

    NASA Astrophysics Data System (ADS)

    Gower, D.; Caylor, K. K.; McCord, P. F.; Evans, T. P.

    2015-12-01

    The climatological conditions that characterize dryland environments - high potential evapotranspiration combined with low and variable total rainfall - pose challenges for farmers deciding when and how much to irrigate. These challenges are greater in developing countries where the absence of sufficient storage infrastructure means that irrigation water is sometimes applied to agricultural fields directly from rivers. Because soil moisture and river flow both depend on recent rainfall, high irrigation demand often coincides with low river flow, limiting access to water when it is most needed. These feedbacks can constrain the yield increases expected from irrigation in such settings. Scaled up to the catchment level, irrigation water availability varies spatially as well as temporally. Irrigators in upstream areas of the catchment have first access to river water but rely on a smaller drainage network while those in downstream areas are affected by the opposite conditions. During periods of high rainfall, downstream users have the greatest access to water while upstream users are then favored during drought intervals. In the absence of rules governing water access, these flow dynamics will constrain the distribution of potential agricultural yields within the catchment. A simple numerical model simulating catchment and irrigation processes was constructed in order to better understand how climate and geomorphologic characteristics affect crop yield, economic returns and the spatial distribution of irrigated areas. By assuming a statistically representative river network structure, the model was first used to explore the effect of unregulated irrigation withdrawals on these variables. Multiple water management programs, including withdrawal limits, rotational systems and flow minima, were then simulated and the results compared to the unregulated case. This analysis shows the potential for simple models to provide insight into complex irrigation systems and to make

  3. Agriculture Education. Agriculture Structures.

    ERIC Educational Resources Information Center

    Stuttgart Public Schools, AR.

    This curriculum guide is designed for group instruction of secondary agricultural education students enrolled in one or two semester-long courses in agriculture structures. The guide presents units of study in the following areas: (1) shop safety, (2) identification and general use of hand tools, (3) power tools, (4) carpentry, (5) blueprint…

  4. Assessing the impacts of sustainable agricultural practices for water quality improvements in the Vouga catchment (Portugal) using the SWAT model.

    PubMed

    Rocha, João; Roebeling, Peter; Rial-Rivas, María Ermitas

    2015-12-01

    The extensive use of fertilizers has become one of the most challenging environmental issues in agricultural catchment areas. In order to reduce the negative impacts from agricultural activities and to accomplish the objectives of the European Water Framework Directive we must consider the implementation of sustainable agricultural practices. In this study, we assess sustainable agricultural practices based on reductions in N-fertilizer application rates (from 100% to 0%) and N-application methods (single, split and slow-release) across key agricultural land use classes in the Vouga catchment, Portugal. The SWAT model was used to relate sustainable agricultural practices, agricultural yields and N-NO3 water pollution deliveries. Results show that crop yields as well as N-NO3 exportation rates decrease with reductions in N-application rates and single N-application methods lead to lower crop yields and higher N-NO3 exportation rates as compared to split and slow-release N-application methods. PMID:26196068

  5. A conjunctive use hydrologic model for a semi-arid region with irrigated agriculture

    NASA Astrophysics Data System (ADS)

    Ruud, N. C.; Harter, T.

    2003-04-01

    A GIS-based sub-basin scale conjunctive use (CU) model is developed for a semi-arid agricultural area in the southern San Joaquin Valley, California. The study area is 2230 square kilometers, and consists of 9114 individual landuse units and 26 water service districts. The CU model consists of three sub-models: 1) a surface water supply (SWS) model, 2) an unsaturated zone water budget (UZWB) model, and 3) a groundwater flow model. The study period is 1970-99. For each modeled surface water channel, the SWS model computes monthly surface water deliveries to each district and conveyance losses due to evaporation and seepage. The UZWB model then calculates the monthly water storage changes in the soil root zone and deep vadose zone of each landuse unit. The UZWB model is driven by surface water applications, precipitation, and crop consumptive use (evapotranspiration) demands. Its outputs are the recharge to the unconfined aquifer and the groundwater pumping demand from the unconfined and confined aquifers. The transient recharge and pumping rates become input for the groundwater flow model which calculates changes in unconfined aquifer water levels and inter-district groundwater fluxes. The groundwater flow model was calibrated against data from 1970-85 and validated with data from 1986-99. From 1970-99, a total of 18500 million cubic meters (MCM) of surface water was applied to land units in the study area. Precipitation added from 219 MCM (1990) to 1200 MCM (1998) annually. The combined total annual agricultural and urban consumptive use ranged from 1070 MCM in 1970 to 1540 MCM in 1999. Total annual channel seepage varied over almost two orders of magnitude from a low of 10 MCM in 1977 to 576 MCM in 1983. Diffuse recharge from surface applied water ranged from 79.9 MCM in 1992 to 432 MCM in 1983. The estimated total pumping ranged from 183 MCM in 1978 to 703 MCM in 1990. As expected, pumping was heaviest during the droughts of 1975-77 and 1987-92, and lightest

  6. Agent-Based Modelling of Agricultural Water Abstraction in Response to Climate, Policy, and Demand Changes: Results from East Anglia, UK

    NASA Astrophysics Data System (ADS)

    Swinscoe, T. H. A.; Knoeri, C.; Fleskens, L.; Barrett, J.

    2014-12-01

    Freshwater is a vital natural resource for multiple needs, such as drinking water for the public, industrial processes, hydropower for energy companies, and irrigation for agriculture. In the UK, crop production is the largest in East Anglia, while at the same time the region is also the driest, with average annual rainfall between 560 and 720 mm (1971 to 2000). Many water catchments of East Anglia are reported as over licensed or over abstracted. Therefore, freshwater available for agricultural irrigation abstraction in this region is becoming both increasingly scarce due to competing demands, and increasingly variable and uncertain due to climate and policy changes. It is vital for water users and policy makers to understand how these factors will affect individual abstractors and water resource management at the system level. We present first results of an Agent-based Model that captures the complexity of this system as individual abstractors interact, learn and adapt to these internal and external changes. The purpose of this model is to simulate what patterns of water resource management emerge on the system level based on local interactions, adaptations and behaviours, and what policies lead to a sustainable water resource management system. The model is based on an irrigation abstractor typology derived from a survey in the study area, to capture individual behavioural intentions under a range of water availability scenarios, in addition to farm attributes, and demographics. Regional climate change scenarios, current and new abstraction licence reforms by the UK regulator, such as water trading and water shares, and estimated demand increases from other sectors were used as additional input data. Findings from the integrated model provide new understanding of the patterns of water resource management likely to emerge at the system level.

  7. Dynamic visual image modeling for 3D synthetic scenes in agricultural engineering

    NASA Astrophysics Data System (ADS)

    Gao, Li; Yan, Juntao; Li, Xiaobo; Ji, Yatai; Li, Xin

    The dynamic visual image modeling for 3D synthetic scenes by using dynamic multichannel binocular visual image based on the mobile self-organizing network. Technologies of 3D modeling synthetic scenes have been widely used in kinds of industries. The main purpose of this paper is to use multiple networks of dynamic visual monitors and sensors to observe an unattended area, to use the advantages of mobile network in rural areas for improving existing mobile network information service further and providing personalized information services. The goal of displaying is to provide perfect representation of synthetic scenes. Using low-power dynamic visual monitors and temperature/humidity sensor or GPS installed in the node equipment, monitoring data will be sent at scheduled time. Then through the mobile self-organizing network, 3D model is rebuilt by synthesizing the returned images. On this basis, we formalize a novel algorithm for multichannel binocular visual 3D images based on fast 3D modeling. Taking advantage of these low prices mobile, mobile self-organizing networks can get a large number of video from where is not suitable for human observation or unable to reach, and accurately synthetic 3D scene. This application will play a great role in promoting its application in agriculture.

  8. Quantitative Assessment of Agricultural Runoff and Soil Erosion Using Mathematical Modeling: Applications in the Mediterranean Region

    NASA Astrophysics Data System (ADS)

    Arhonditsis, G.; Giourga, C.; Loumou, A.; Koulouri, M.

    2002-09-01

    Three mathematical models, the runoff curve number equation, the universal soil loss equation, and the mass response functions, were evaluated for predicting nonpoint source nutrient loading from agricultural watersheds of the Mediterranean region. These methodologies were applied to a catchment, the gulf of Gera Basin, that is a typical terrestrial ecosystem of the islands of the Aegean archipelago. The calibration of the model parameters was based on data from experimental plots from which edge-of-field losses of sediment, water runoff, and nutrients were measured. Special emphasis was given to the transport of dissolved and solid-phase nutrients from their sources in the farmers' fields to the outlet of the watershed in order to estimate respective attenuation rates. It was found that nonpoint nutrient loading due to surface losses was high during winter, the contribution being between 50% and 80% of the total annual nutrient losses from the terrestrial ecosystem. The good fit between simulated and experimental data supports the view that these modeling procedures should be considered as reliable and effective methodological tools in Mediterranean areas for evaluating potential control measures, such as management practices for soil and water conservation and changes in land uses, aimed at diminishing soil loss and nutrient delivery to surface waters. Furthermore, the modifications of the general mathematical formulations and the experimental values of the model parameters provided by the study can be used in further application of these methodologies in watersheds with similar characteristics.

  9. Geospatial Modeling and Disease Insect Vector Management at the USDA-ARS Center for Medical, Agricultural, and Veterinary Entomology

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Geospatial modeling at the Center for Medical, Agricultural and Veterinary Entomology (CMAVE) is used assist in the surveillance of insect vectors and in the management of insect transmitted diseases. The most recent Geospatial Modeling/Technology Transfer success involves the prediction of Rift Val...

  10. Modeling human impact in the past: a dynamic soil model as a step towards quantifying agricultural carrying capacity

    NASA Astrophysics Data System (ADS)

    Van Loo, Maarten; Verstraeten, Gert

    2015-04-01

    Humans have impacted their environment throughout history, especially since the introduction of widespread agriculture and the associated forest logging activities. For the Mediterranean region the idea existed that the soil erosion following the cultivation of land degraded the landscape to such an extent it caused crisis in ancient societies. In order to quantify the impact of ancient societies on the landscape a simple water balance driven crop yield model is coupled to a soil erosion model. The soil erosion model was validated based on a detailed 4000 year long chronology of sediment deposition in a small mountainous catchment (1250 m a.s.l.) in the territory of the ancient city of Sagalassos (SW Turkey). The historic sediment dynamics are modeled reasonably well, with a model efficiency of 0.75 and a relative root mean squared error of 0.23, based on 250 yr averages. The model is capable of simulating the soil erosion phase after major deforestation from the Iron Age onwards, as well as the depletion of soil reservoirs on limestone lithologies on the hillslopes and the resulting decrease in sediment delivery towards the central valley around the Roman period. Although the spatial pattern of crop yield changes drastically throughout time, following the changes in soil thickness, the simulations show that the average yields in the catchment stay relatively constant, and certainly not collapse completely. Average barley yield at 4000 BP is estimated around 400 kg/ha, whereas during Roman times this even increases to around 500 kg/ha. These estimates however assume optimal conditions with no limitations from soil nutrients and land availability in the central valley bottoms. The latter could have been an issue, since results show that during winter water losses under a highly degraded landscape could have increased significantly, potentially resulting in an expansion of the lake occupying the lowest parts of the catchment. These stresses would have forced farmers

  11. Germany wide seasonal flood risk analysis for agricultural crops

    NASA Astrophysics Data System (ADS)

    Klaus, Stefan; Kreibich, Heidi; Kuhlmann, Bernd; Merz, Bruno; Schröter, Kai

    2016-04-01

    In recent years, large-scale flood risk analysis and mapping has gained attention. Regional to national risk assessments are needed, for example, for national risk policy developments, for large-scale disaster management planning and in the (re-)insurance industry. Despite increasing requests for comprehensive risk assessments some sectors have not received much scientific attention, one of these is the agricultural sector. In contrast to other sectors, agricultural crop losses depend strongly on the season. Also flood probability shows seasonal variation. Thus, the temporal superposition of high flood susceptibility of crops and high flood probability plays an important role for agricultural flood risk. To investigate this interrelation and provide a large-scale overview of agricultural flood risk in Germany, an agricultural crop loss model is used for crop susceptibility analyses and Germany wide seasonal flood-frequency analyses are undertaken to derive seasonal flood patterns. As a result, a Germany wide map of agricultural flood risk is shown as well as the crop type most at risk in a specific region. The risk maps may provide guidance for federal state-wide coordinated designation of retention areas.

  12. Integrating agricultural and forestry GHG mitigation responses into general economy frameworks: Developing a family of response functions

    SciTech Connect

    Gillig, Dhazn; McCarl, Bruce A.; Sands, Ronald D.

    2004-07-01

    An econometrically estimated family of response functions is developed for characterizing potential responses to greenhouse gas mitigation policies by the agriculture and forestry sectors. The response functions are estimated based on results of an agricultural/forestry sector model. They provide estimates of sequestration and emission reductions in forestry and agriculture along with levels of sectoral production, prices, welfare, and environmental attributes given a carbon price, levels of demand for agricultural goods, and the energy price. Six alternative mitigation policies representing types of greenhouse gas offsets allowed are considered. Results indicate that the largest quantity of greenhouse gas offset consistently appears with the mitigation policy that pays for all opportunities. Restricting carbon payments (emission tax or sequestration subsidy) only to aff/deforestation or only to agricultural sequestration substantially reduces potential mitigation. Higher carbon prices lead to more sequestration, less emissions, reduced consumer and total welfare, improved environmental indicators and increased producer welfare.

  13. Modeling the effect of terraces on land degradation in tropical upland agricultural area

    NASA Astrophysics Data System (ADS)

    Christanto, N.; Shrestha, D. P.; Jetten, V. G.; Setiawan, A.

    2012-04-01

    Java, the most populated Island in Indonesia, in the pas view decades suffer land degradation do to extreme weather, population pressure and landuse/cover change. The study area, Serayu sub-catchment, as part of Serayu catchment is one of the representative example of Indonesia region facing land use change and land degradation problem. The study attempted to simulate the effect of terraces on land degradation (Soil erosion and landslide hazard) in Serayu sub-catchment using deterministic modeling by means of PCRaster® simulation. The effect of the terraces on tropical upland agricultural area is less studied. This paper will discuss about the effect of terraces on land degradation assessment. Detail Dem is extremely difficult to obtain in developing country like Indonesia. Therefore, an artificial DEM which give an impression of the terraces was built. Topographical maps, Ikonos Image and average of height distribution based on field measurement were used to build the artificial DEM. The result is used in STARWARS model as an input. In combine with Erosion model and PROBSTAB, soil erosion and landslide hazard were quantified. The models were run in two different environment based on the: 1) normal DEM 2.) Artificial DEM (with terraces impression). The result is compared. The result shows that the models run in an artificial DEM give a significant increase on the probability of failure by 20.5%. In the other hand, the erosion rate has fall by 11.32% as compared to the normal DEM. The result of hydrological sensitivity analysis shows that soil depth was the most sensitive parameter. For the slope stability modeling, the most sensitive parameter was slope followed by friction angle and cohesion. The erosion modeling, the model was sensitive to the vegetation cover, soil erodibility followed by BD and KSat. Model validations were applied to assess the accuracy of the models. However, the results of dynamic modeling are ideal for land degradation assessment. Dynamic

  14. The Agricultural Model Intercomparison and Improvement Project: Phase I Activities by a Global Community of Science. Chapter 1

    NASA Technical Reports Server (NTRS)

    Rosenzweig, Cynthia E.; Jones, James W.; Hatfield, Jerry L.; Antle, John M.; Ruane, Alexander C.; Mutter, Carolyn Z.

    2015-01-01

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) was founded in 2010. Its mission is to improve substantially the characterization of world food security as affected by climate variability and change, and to enhance adaptation capacity in both developing and developed countries. The objectives of AgMIP are to: Incorporate state-of-the-art climate, crop/livestock, and agricultural economic model improvements into coordinated multi-model regional and global assessments of future climate impacts and adaptation and other key aspects of the food system. Utilize multiple models, scenarios, locations, crops/livestock, and participants to explore uncertainty and the impact of data and methodological choices. Collaborate with regional experts in agronomy, animal sciences, economics, and climate to build a strong basis for model applications, addressing key climate related questions and sustainable intensification farming systems. Improve scientific and adaptive capacity in modeling for major agricultural regions in the developing and developed world, with a focus on vulnerable regions. Improve agricultural data and enhance data-sharing based on their intercomparison and evaluation using best scientific practices. Develop modeling frameworks to identify and evaluate promising adaptation technologies and policies and to prioritize strategies.

  15. Modelling soil erosion in a clayey, subsurface-drained agricultural field with a three-dimensional FLUSH model

    NASA Astrophysics Data System (ADS)

    Warsta, Lassi; Taskinen, Antti; Koivusalo, Harri; Paasonen-Kivekäs, Maija; Karvonen, Tuomo

    2013-08-01

    Soil erosion is an important environmental issue in agricultural areas of northern Europe where clayey soils are prevalent. Clayey soils are routinely subsurface drained to accelerate drainage which creates an additional discharge route for suspended sediment. Previously, assessment of the sediment load from clayey fields has been difficult, because process-based models were only able to simulate sediment loads via surface runoff. A new distributed, process-based erosion model was developed and incorporated into the FLUSH modelling system to fulfil this void. The model facilitates simulation of spatially distributed soil erosion on the field surface and sediment loads via surface runoff and subsurface drainflow. Soil erosion on the field surface is simulated with the two-dimensional sediment continuity equation coupled with hydraulic and rain drop splash erosion, sediment settling, and transport capacity processes. Subsurface sediment transport in macropores is described with the three-dimensional advection-dispersion equation. The model was applied to a clayey, subdrained field section (∼3.6 ha) in southern Finland. The results demonstrated the capability of the model to simulate soil erosion and sediment transport in terms of the match between the measured (2669 kg ha-1) and modelled (2196 kg ha-1) sediment loads via surface runoff and the measured (2937 kg ha-1) and modelled (2245 kg ha-1) loads via drainflow during the validation period of 7 months. The model sensitivity analysis pointed out the importance of the flow model parameters in simulation of soil erosion through their control on the division of total runoff into surface runoff and drainflow components. The key parameters in the erosion model were those that affected hydraulic and splash erosion rates. The model application in the experimental field suggested that both hydraulic and splash erosion were the factors behind the sediment losses during the growing season and early autumn, whereas high

  16. Evaluating the Quality of the Learning Outcome in Healthcare Sector: The Expero4care Model

    ERIC Educational Resources Information Center

    Cervai, Sara; Polo, Federica

    2015-01-01

    Purpose: This paper aims to present the Expero4care model. Considering the growing need for a training evaluation model that does not simply fix processes, the Expero4care model represents the first attempt of a "quality model" dedicated to the learning outcomes of healthcare trainings. Design/Methodology/Approach: Created as development…

  17. Applying an agent-based model of agricultural terraces coupled with a landscape evolution model to explore the impact of human decision-making on terraced terrain

    NASA Astrophysics Data System (ADS)

    Glaubius, Jennifer

    2016-04-01

    Agricultural terraces impact landscape evolution as a result of long-term human-landscape interactions, including decisions regarding terrace maintenance and abandonment. Modeling simulations are often employed to examine the sensitivity of landscapes to various factors, such as rainfall and land cover. Landscape evolution models, erosion models, and hydrological models have all previously been used to simulate the impact of agricultural terrace construction on terrain evolution, soil erosion, and hydrological connectivity. Human choices regarding individual terraces have not been included in these models to this point, despite recent recognition that maintenance and abandonment decisions alter transport and storage patterns of soil and water in terraced terrain. An agent-based model of human decisions related to agricultural terraces is implemented based on a conceptual model of agricultural terrace life cycle stages created from a literature review of terracing impacts. The agricultural terracing agent-based model is then coupled with a landscape evolution model to explore the role of human decisions in the evolution of terraced landscapes. To fully explore this type of co-evolved landscape, human decision-making and its feedbacks must be included in landscape evolution models. Project results may also have implications for management of terraced terrain based on how human choices in these environments affect soil loss and land degradation.

  18. 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. PMID:21113782

  19. Agricultural terraces montoring and modeling: a field survey in Chianti region, Firenze, Italy – Second part

    NASA Astrophysics Data System (ADS)

    Preti, Federico; Caruso, Marco; Dani, Andrea; Cassiani, Giorgio; Romano, Nunzio; Tarolli, Paolo

    2015-04-01

    The two abstracts present the design and set-up of an experimental campaign which aims at sup-porting the modeling (conceptual and numerical) of water circulation in a terraced slope, and its in-fluence on stability of retaining dry stone walls. The case study is located at "Fattoria di Lamole" (Greve in Chianti, Firenze, Italy). At Lamole site both ancient and recently restored or rebuilt (with different techniques) dry stone walls are present. Furthermore the intense vineyards cultivation makes it very representative in terms of range of external stresses that affect both hillslopes and wall. The survey is developed within the bigger framework of landscape preservation as a way to prevent hydrogeological instabilities and landslide risks. Second Part A second effort is devoted to couple hydrological, hydraulic and geotechnical modeling: - Flow directions and the drainage area have been derived from DTM (high-resolution digital terrain model obtained by a terrestrial laser scanner.), and served for the RPII index calcula-tion (Tarolli et al., 2013), that is coherent with the critical spots observed in situ and marked with GPS. - Direct shear test on undisturbed and reconstituted soil samples will offer an estimation of the Mohr-Coulomb failure envelope parameters (friction angle and cohesion). - Retention curves related with different depths have been derived. - Geoelectric analysis in order to locate the bedrock and to determine the subterranean water flows originated from controlled infitration tests (1 l/s discharge). - A simple dry-wall stability model has been carried out; this model analyses the wall stability with finite elements method, evaluating pressures derived from uphill water infiltration, stone friction and buoyancy in retaining wall layers: simulated deformation are suitable with the observed ones. Acknowledgements Italian Research Project of Relevant Interest (PRIN2010-2011), prot. 20104ALME4, National network for monitoring, modeling, and

  20. 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

  1. Water and Nutrient Balances in a Large Tile-Drained Agricultural Catchment: A Distributed Modeling Study

    SciTech Connect

    Li, Hongyi; Sivapalan, Murugesu; Tian, Fuqiang; Liu, Dengfeng

    2010-11-16

    This paper presents the development and implementation of a distributed model of coupled water nutrient processes, based on the representative elementary watershed (REW) approach, to the Upper Sangamon River Basin, a large, tile-drained agricultural basin located in central Illinois, mid-west of USA. Comparison of model predictions with the observed hydrological and biogeochemical data, as well as regional estimates from literature studies, shows that the model is capable of capturing the dynamics of water, sediment and nutrient cycles reasonably well. The model is then used as a tool to gain insights into the physical and chemical processes underlying the inter- and intra-annual variability of water and nutrient balances. Model predictions show that about 80% of annual runoff is contributed by tile drainage, while the remainder comes from surface runoff (mainly saturation excess flow) and subsurface runoff. It is also found that, at the annual scale nitrogen storage in the soil is depleted during wet years, and is supplemented during dry years. This carryover of nitrogen storage from dry year to wet year is mainly caused by the lateral loading of nitrate. Phosphorus storage, on the other hand, is not affected much by wet/dry conditions simply because the leaching of it is very minor compared to the other mechanisms taking phosphorous out of the basin, such as crop harvest. The analysis then turned to the movement of nitrate with runoff. Model results suggested that nitrate loading from hillslope into the channel is preferentially carried by tile drainage. Once in the stream it is then subject to in-stream denitrification, the significant spatio-temporal variability of which can be related to the variation of the hydrologic and hydraulic conditions across the river network.

  2. Has the Swap Influenced Aid Flows in the Health Sector?

    PubMed

    Sweeney, Rohan; Mortimer, Duncan

    2016-05-01

    The sector wide approach (SWAp) emerged during the 1990s as a mechanism for managing aid from the multiplicity of development partners that operate in the recipient country's health, education or agricultural sectors. Health SWAps aim to give increased control to recipient governments, allowing greater domestic influence over how health aid is allocated and facilitating allocative efficiency gains. This paper assesses whether health SWAps have increased recipient control of health aid via increased general sector-support and have facilitated (re)allocations of health aid across disease areas. Using a uniquely compiled panel data set of countries receiving development assistance for health over the period 1990-2010, we employ fixed effects and dynamic panel models to assess the impact of introducing a health SWAp on levels of general sector-support for health and allocations of health-sector aid across key funding silos (including HIV, 'maternal and child health' and 'sector-support'). Our results suggest that health SWAps have influenced health-sector aid flows in a manner consistent with increased recipient control and improvements in allocative efficiency. Copyright © 2015 John Wiley & Sons, Ltd. PMID:25762110

  3. Risk assessment of consuming agricultural products irrigated with reclaimed wastewater: An exposure model

    NASA Astrophysics Data System (ADS)

    van Ginneken, Meike; Oron, Gideon

    2000-09-01

    This study assesses health risks to consumers due to the use of agricultural products irrigated with reclaimed wastewater. The analysis is based on a definition of an exposure model which takes into account several parameters: (1) the quality of the applied wastewater, (2) the irrigation method, (3) the elapsed times between irrigation, harvest, and product consumption, and (4) the consumers' habits. The exposure model is used for numerical simulation of human consumers' risks using the Monte Carlo simulation method. The results of the numerical simulation show large deviations, probably caused by uncertainty (impreciseness in quality of input data) and variability due to diversity among populations. There is a 10-orders of magnitude difference in the risk of infection between the different exposure scenarios with the same water quality. This variation indicates the need for setting risk-based criteria for wastewater reclamation rather than single water quality guidelines. Extra data are required to decrease uncertainty in the risk assessment. Future research needs to include definition of acceptable risk criteria, more accurate dose-response modeling, information regarding pathogen survival in treated wastewater, additional data related to the passage of pathogens into and in the plants during irrigation, and information regarding the behavior patterns of the community of human consumers.

  4. Effects of farm heterogeneity and methods for upscaling on modelled nitrogen losses in agricultural landscapes.

    PubMed

    Dalgaard, T; Hutchings, N; Dragosits, U; Olesen, J E; Kjeldsen, C; Drouet, J L; Cellier, P

    2011-11-01

    The aim of this study is to illustrate the importance of farm scale heterogeneity on nitrogen (N) losses in agricultural landscapes. Results are exemplified with a chain of N models calculating farm-N balances and distributing the N-surplus to N-losses (volatilisation, denitrification, leaching) and soil-N accumulation/release in a Danish landscape. Possible non-linearities in upscaling are assessed by comparing average model results based on (i) individual farm level calculations and (ii) averaged inputs at landscape level. Effects of the non-linearities that appear when scaling up from farm to landscape are demonstrated. Especially in relation to ammonia losses the non-linearity between livestock density and N-loss is significant (p > 0.999), with around 20-30% difference compared to a scaling procedure not taking this non-linearity into account. A significant effect of farm type on soil N accumulation (p > 0.95) was also identified and needs to be included when modelling landscape level N-fluxes and greenhouse gas emissions. PMID:21458123

  5. Modeling Spatial and Temporal Variability in Ammonia Emissions from Agricultural Fertilization in China

    NASA Astrophysics Data System (ADS)

    Chen, C.; Zhang, Q.

    2014-12-01

    Ammonia (NH3) is a key precursor to atmospheric fine particulate matter (PM2.5) and an important component of the reactive nitrogen cycle, with strong implications for both regional air quality and ecosystems. Due to limited parameterization of the complex interactions between fertilizer usage, farm practices, soil and meteorological conditions, ammonia emission estimates for agricultural fertilization over China, one of the most important ammonia emission sources, are usually based on time-averaged emission factors and temporal profiles. Here we develop a process-based ammonia emission model for fertilize use at fine spatial and temporal scales in support of air quality models. The model estimates NH3 emissions based on the parameterization of crop acreages, fertilizer application rates, plant growth period, fertilizer use patterns, soil processes, and meteorological conditions. Preliminary results show that the total ammonia fertilizer emission in China was approximately 3.8 Tg in 2006 with peak emissions during April to June. The regions with the highest emission rates are located in Central China. We also examine the sensitivities of different parameters on NH3 emission estimates. We found that the magnitude of NH3 emissions is most sensitive to fertilizer application rates while the seasonality of emissions is more sensitive to fertilization time.

  6. Linking an economic model for European agriculture with a mechanistic model to estimate nitrogen and carbon losses from arable soils in Europe

    NASA Astrophysics Data System (ADS)

    Leip, A.; Marchi, G.; Koeble, R.; Kempen, M.; Britz, W.; Li, C.

    2008-01-01

    A comprehensive assessment of policy impact on greenhouse gas (GHG) emissions from agricultural soils requires careful consideration of both socio-economic aspects and the environmental heterogeneity of the landscape. We developed a modelling framework that links the large-scale economic model for agriculture CAPRI (Common Agricultural Policy Regional Impact assessment) with the biogeochemistry model DNDC (DeNitrification DeComposition) to simulate GHG fluxes, carbon stock changes and the nitrogen budget of agricultural soils in Europe. The framework allows the ex-ante simulation of agricultural or agri-environmental policy impacts on a wide range of environmental problems such as climate change (GHG emissions), air pollution and groundwater pollution. Those environmental impacts can be analyzed in the context of economic and social indicators as calculated by the economic model. The methodology consists of four steps: (i) definition of appropriate calculation units that can be considered as homogeneous in terms of economic behaviour and environmental response; (ii) downscaling of regional agricultural statistics and farm management information from a CAPRI simulation run into the spatial calculation units; (iii) designing environmental model scenarios and model runs; and finally (iv) aggregating results for interpretation. We show the first results of the nitrogen budget in croplands in fourteen countries of the European Union and discuss possibilities to improve the detailed assessment of nitrogen and carbon fluxes from European arable soils.

  7. Plant physiological models of heat, water and photoinhibition stress for climate change modelling and agricultural prediction

    NASA Astrophysics Data System (ADS)

    Nicolas, B.; Gilbert, M. E.; Paw U, K. T.

    2015-12-01

    Soil-Vegetation-Atmosphere Transfer (SVAT) models are based upon well understood steady state photosynthetic physiology - the Farquhar-von Caemmerer-Berry model (FvCB). However, representations of physiological stress and damage have not been successfully integrated into SVAT models. Generally, it has been assumed that plants will strive to conserve water at higher temperatures by reducing stomatal conductance or adjusting osmotic balance, until potentially damaging temperatures and the need for evaporative cooling become more important than water conservation. A key point is that damage is the result of combined stresses: drought leads to stomatal closure, less evaporative cooling, high leaf temperature, less photosynthetic dissipation of absorbed energy, all coupled with high light (photosynthetic photon flux density; PPFD). This leads to excess absorbed energy by Photosystem II (PSII) and results in photoinhibition and damage, neither are included in SVAT models. Current representations of photoinhibition are treated as a function of PPFD, not as a function of constrained photosynthesis under heat or water. Thus, it seems unlikely that current models can predict responses of vegetation to climate variability and change. We propose a dynamic model of damage to Rubisco and RuBP-regeneration that accounts, mechanistically, for the interactions between high temperature, light, and constrained photosynthesis under drought. Further, these predictions are illustrated by key experiments allowing model validation. We also integrated this new framework within the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA). Preliminary results show that our approach can be used to predict reasonable photosynthetic dynamics. For instances, a leaf undergoing one day of drought stress will quickly decrease its maximum quantum yield of PSII (Fv/Fm), but it won't recover to unstressed levels for several days. Consequently, cumulative effect of photoinhibition on photosynthesis can cause

  8. Climate model emulation in an integrated assessment framework: a case study for mitigation policies in the electricity sector

    NASA Astrophysics Data System (ADS)

    Foley, A. M.; Holden, P. B.; Edwards, N. R.; Mercure, J.-F.; Salas, P.; Pollitt, H.; Chewpreecha, U.

    2016-02-01

    We present a carbon-cycle-climate modelling framework using model emulation, designed for integrated assessment modelling, which introduces a new emulator of the carbon cycle (GENIEem). We demonstrate that GENIEem successfully reproduces the CO2 concentrations of the Representative Concentration Pathways when forced with the corresponding CO2 emissions and non-CO2 forcing. To demonstrate its application as part of the integrated assessment framework, we use GENIEem along with an emulator of the climate (PLASIM-ENTSem) to evaluate global CO2 concentration levels and spatial temperature and precipitation response patterns resulting from CO2 emission scenarios. These scenarios are modelled using a macroeconometric model (E3MG) coupled to a model of technology substitution dynamics (FTT), and represent different emissions reduction policies applied solely in the electricity sector, without mitigation in the rest of the economy. The effect of cascading uncertainty is apparent, but despite uncertainties, it is clear that in all scenarios, global mean temperatures in excess of 2 °C above pre-industrial levels are projected by the end of the century. Our approach also highlights the regional temperature and precipitation patterns associated with the global mean temperature change occurring in these scenarios, enabling more robust impacts modelling and emphasizing the necessity of focusing on spatial patterns in addition to global mean temperature change.

  9. Developing an Integrated Model Framework for the Assessment of Sustainable Agricultural Residue Removal Limits for Bioenergy Systems

    SciTech Connect

    David Muth, Jr.; Jared Abodeely; Richard Nelson; Douglas McCorkle; Joshua Koch; Kenneth Bryden

    2011-08-01

    Agricultural residues have significant potential as a feedstock for bioenergy production, but removing these residues can have negative impacts on soil health. Models and datasets that can support decisions about sustainable agricultural residue removal are available; however, no tools currently exist capable of simultaneously addressing all environmental factors that can limit availability of residue. The VE-Suite model integration framework has been used to couple a set of environmental process models to support agricultural residue removal decisions. The RUSLE2, WEPS, and Soil Conditioning Index models have been integrated. A disparate set of databases providing the soils, climate, and management practice data required to run these models have also been integrated. The integrated system has been demonstrated for two example cases. First, an assessment using high spatial fidelity crop yield data has been run for a single farm. This analysis shows the significant variance in sustainably accessible residue across a single farm and crop year. A second example is an aggregate assessment of agricultural residues available in the state of Iowa. This implementation of the integrated systems model demonstrates the capability to run a vast range of scenarios required to represent a large geographic region.

  10. Linking Remote Sensing Data and Energy Balance Models for a Scalable Agriculture Insurance System for sub-Saharan Africa

    NASA Astrophysics Data System (ADS)

    Brown, M. E.; Osgood, D. E.; McCarty, J. L.; Husak, G. J.; Hain, C.; Neigh, C. S. R.

    2014-12-01

    One of the most immediate and obvious impacts of climate change is on the weather-sensitive agriculture sector. Both local and global impacts on production of food will have a negative effect on the ability of humanity to meet its growing food demands. Agriculture has become more risky, particularly for farmers in the most vulnerable and food insecure regions of the world such as East Africa. Smallholders and low-income farmers need better financial tools to reduce the risk to food security while enabling productivity increases to meet the needs of a growing population. This paper will describe a recently funded project that brings together climate science, economics, and remote sensing expertise to focus on providing a scalable and sensor-independent remote sensing based product that can be used in developing regional rainfed agriculture insurance programs around the world. We will focus our efforts in Ethiopia and Kenya in East Africa and in Senegal and Burkina Faso in West Africa, where there are active index insurance pilots that can test the effectiveness of our remote sensing-based approach for use in the agriculture insurance industry. The paper will present the overall program, explain links to the insurance industry, and present comparisons of the four remote sensing datasets used to identify drought: the CHIRPS 30-year rainfall data product, the GIMMS 30-year vegetation data product from AVHRR, the ESA soil moisture ECV-30 year soil moisture data product, and a MODIS Evapotranspiration (ET) 15-year dataset. A summary of next year's plans for this project will be presented at the close of the presentation.

  11. Assessment of surface winds over the Atlantic, Indian, and Pacific Ocean sectors of the Southern Ocean in CMIP5 models: historical bias, forcing response, and state dependence

    NASA Astrophysics Data System (ADS)

    Bracegirdle, Thomas J.; Shuckburgh, Emily; Sallee, Jean-Baptiste; Wang, Zhaomin; Meijers, Andrew J. S.; Bruneau, Nicolas; Phillips, Tony; Wilcox, Laura J.

    2013-01-01

    An assessment of the fifth Coupled Models Intercomparison Project (CMIP5) models' simulation of the near-surface westerly wind jet position and strength over the Atlantic, Indian and Pacific sectors of the Southern Ocean is presented. Compared with reanalysis climatologies there is an equatorward bias of 3.3° (inter-model standard deviation of ± 1.9°) in the ensemble mean position of the zonal mean jet. The ensemble mean strength is biased slightly too weak, with the largest biases over the Pacific sector (-1.4 ± 1.2 m/s, -19%). An analysis of atmosphere-only (AMIP) experiments indicates that 28% of the zonal mean position bias comes from coupling of the ocean/ice models to the atmosphere. The response to future emissions scenarios (RCP4.5 and RCP8.5) is characterized by two phases: (i) the period of most rapid ozone recovery (2000-2049) during which there is insignificant change in summer; and (ii) the period 2050-2098 during which RCP4.5 simulations show no significant change but RCP8.5 simulations show poleward shifts (0.33, 0.18 and 0.27°/decade over the Atlantic, Indian and Pacific sectors, respectively), and increases in strength (0.07, 0.08 and 0.15 m/s/decade, respectively). The models with larger equatorward position biases generally show larger poleward shifts (i.e. state dependence). This inter-model relationship is strongest over the Pacific sector (r = -0.91) and weakest over the Atlantic sector (r = -0.39). An assessment of jet structure shows that over the Atlantic sector jet shift is not clearly linked to indices of jet structure whereas over the Pacific sector the distance between the sub-polar and sub-tropical westerly jets appears to be important.

  12. Modeling of land use and reservoir effects on nonpoint source pollution in a highly agricultural basin

    USGS Publications Warehouse

    Wu, Yiping; Liu, Shu-Guang

    2012-01-01

    Nonpoint source (NPS) pollution is tightly linked to land use activities that determine the sources and magnitudes of pollutant loadings to stream water. The pollutant loads may also be alleviated within reservoirs because of the physical interception resulting from changed hydrological regimes and other biochemical processes. It is important but challenging to assess the NPS pollution processes with human effects due to the measurement limitations. The objective of this study is to evaluate the effects of human activities such as land uses and reservoir operation on the hydrological and NPS pollution processes in a highly agricultural area-the Iowa River Basin-using the Soil and Water Assessment Tool (SWAT). The evaluation of model performance at multiple sites reveals that SWAT can consistently simulate the daily streamflow, and monthly/annual sediment and nutrient loads (nitrate nitrogen and mineral phosphorus) in the basin. We also used the calibrated model to estimate the trap efficiencies of sediment (~78%) and nutrients (~30%) in the Coralville Reservoir within the basin. These non-negligible effects emphasize the significance of incorporating the sediment and nutrient removal mechanisms into watershed system studies. The spatial quantification of the critical NPS pollution loads can help identify hot-spot areas that are likely locations for the best management practices.

  13. Evaluation of a watershed model to simulate sediment transport in a small agricultural watershed in Indiana

    USGS Publications Warehouse

    Arihood, L.D.

    1989-01-01

    The streamflow and sediment components of the watershed model, ' Hydrologic Simulation Program-Fortran ', were evaluated using 2 years and 9 months of data from a 2.7-sq mi agricultural watershed in Indiana. Hydrographs of simulated sediment concentration generally have smaller peaks and longer recessions than do hydrographs of measured data. The attenuation of simulated peaks was partly caused by difficulties in designing a representative channel system. Simulated surface runoff during low-intensity rainfall was greater than measured surface runoff; this caused an overestimation of sediment concentration and discharge. Rainfalls of low intensity were mostly absorbed by the soil, but the model predicted that the amount of surface runoff from such storms would be large. The overly large volume of simulated surface runoff transported more sediment than actually occurred. The mean absolute error of mean sediment concentrations during storms is 45% of the measured average concentration. The error resulted from a combination of error in recording streamflow and rainfall, in simulating streamflows, and in simulating sedimentation processes. The largest percent errors are associated with simulated maximum streamflows and average sediment discharges. The root-mean-square errors are 93 and 102% of the measured maximum streamflow and average sediment discharges. (USGS)

  14. Characterizing and modeling of extensive atrazine elution tailing for stable manure-amended agricultural soil.

    PubMed

    Akyol, Nihat Hakan

    2015-01-01

    Non-ideal sorption and extensive elution tailing behavior of atrazine was evaluated for an agricultural soil with and without stable manure amendment (10% by weight). A series of laboratory experiments showed that the sorption of atrazine was described by rate-limited, nonlinear reversible processes (Freundlich isotherm) for both non-amended and amended soil. Non-ideal transport of atrazine exhibited extensive low concentration elution tailing due to the most likely organic carbon fraction in the soil. This tailing behavior was more pronounced and extensive for soil with 10% stable-manure amendment. Two-site transport modeling analyses including non-linear sorption and rate-limited sorption-desorption provided a reasonably good match to the atrazine breakthrough curves but were unable to match the long-term concentration tailing, even for non-amended soil. A mathematical model incorporating nonlinear, rate-limited sorption/desorption described by a continuous-distribution function was used to successfully simulate atrazine transport early-time breakthrough and long-term concentration tailing for both non-amended and amended soil conditions. PMID:25303664

  15. Follow-up and modeling of the land use in an intensive agricultural watershed in France

    NASA Astrophysics Data System (ADS)

    Corgne, Samuel; Barbier, Johann; Hubert-Moy, Laurence; Mercier, Gregoire; Solaiman, Basel

    2003-03-01

    In intensive agricultural regions, monitoring land use and cover change represents an important stake. Some land cover changes in agro-systems cause modifications in the management of land use that contribute to increase environmental problems, including an important degradation of water quality. In this context, the identification of land-cover dynamics at high spatial scales constitutes a prior approach for the restoration of water resources. The modeling approach used to study land use and cover changes at a field-scale is adapted from a vector change analysis method generally applied to assess land cover changes from regional to global scales. The main objective of this study is to identify vegetation changes at the field scale during winter, in relation with crop successions. Magnitude and direction of the vector of changes with remote sensing data and GIS, calculated on a small watershed located in Western France for a six-year period (1996-2001) indicate both intensity and nature of observed changes in this area. The results allow to qualify accurately (i.e. at the scale of the field) the type of changes, to quantify them and weigh up their intensity. Then, all the results are integrated in a probabilistic model to build-up a short time land use prediction.

  16. Three Dimensional Modeling of Agricultural Contamination of Groundwater: a Case Study in the Nebraska Management Systems Evaluation Area (MSEA) Site

    NASA Astrophysics Data System (ADS)

    Akbariyeh, S.; Snow, D. D.; Bartelt-Hunt, S.; Li, X.; Li, Y.

    2015-12-01

    Contamination of groundwater from nitrogen fertilizers and pesticides in agricultural lands is an important environmental and water quality management issue. It is well recognized that in agriculturally intensive areas, fertilizers and pesticides may leach through the vadose zone and eventually reach groundwater, impacting future uses of this limited resource. While numerical models are commonly used to simulate fate and transport of agricultural contaminants, few models have been validated based on realistic three dimensional soil lithology, hydrological conditions, and historical changes in groundwater quality. In this work, contamination of groundwater in the Nebraska Management Systems Evaluation Area (MSEA) site was simulated based on extensive field data including (1) lithology from 69 wells and 11 test holes; (2) surface soil type, land use, and surface elevations; (3) 5-year groundwater level and flow velocity; (4) daily meteorological monitoring; (5) 5-year seasonal irrigation records; (6) 5-years of spatially intensive contaminant concentration in 40 multilevel monitoring wells; and (7) detailed cultivation records. Using this data, a three-dimensional vadose zone lithological framework was developed using a commercial software tool (RockworksTM). Based on the interpolated lithology, a hydrological model was developed using HYDRUS-3D to simulate water flow and contaminant transport. The model was validated through comparison of simulated atrazine and nitrate concentration with historical data from 40 wells and multilevel samplers. The validated model will be used to predict potential changes in ground water quality due to agricultural contamination under future climate scenarios in the High Plain Aquifer system.

  17. Assessing the impacts of agricultural change on soil erosion over the last century: a multi-model ensemble approach

    NASA Astrophysics Data System (ADS)

    Sellami, Haykel; Smith, Hugh; Sangster, Heather; Riley, Mark; Chiverrell, Richard; Boyle, John

    2016-04-01

    Soil erosion models (SEMs) are valuable tools for understanding the links between past agricultural practices and soil erosion. Use of SEMs allows assessment of impacts from agricultural change over timescales that exceed instrumental records but correspond to periods for which considerable land use and climate information are available. Here, we develop a modelling framework to investigate the potential impacts of changes in agricultural practices and climate on soil erosion and sediment transport over the last 100 years in six lake catchments in Britain spanning upland and lowland environments. The modelling platform comprises a multi-model ensemble of derivatives of the Morgan-Morgan-Finney (MMF) and RUSLE models. Simulation of change in land use/land cover (LULC), drainage features, crop rotation and livestock grazing are accounted for by reconstructing LULC maps from 1888 to 2007. Reconstructions of climatic conditions combine multiple records using regression and artificial neural network techniques to derive long-term daily precipitation and temperature series from 1880 to present. The modelling platform uses a grid-based modelling approach to handle the spatial distribution and heterogeneity in LULC, soil and topographic information. For each soil type, a database of physical parameters was created by combining information from the literature, LandIS soil database and pedotransfer functions. At each grid cell, a rainfall-Runoff (RR) model based on saturation excess runoff generation mechanisms provides daily soil moisture content. Furthermore, the modelling platform encompasses a crop cover model (CC) based on the Heat Unit approach developed to simulate daily Leaf Area Index for each crop type. Both the RR and CC models are used to update the canopy and ground cover parameters. In the absence of long-term river monitoring data, lake sediment records are used to compare the multi-model simulations thus creating a baseline from which to project impacts from

  18. Agriculture and land use issues

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Large-scale biofuels development as a source of renewable energy will shift current dynamics in the agricultural sector that deliver food, feed, and fiber. This chapter examines the potential for modern agriculture to support a biofuels industry without comprimising its critical role for delivering ...

  19. Integrated Modeling to Assess the Impacts of Changes in Climate and Socio Economics on Agriculture in the Columbia River Basin

    NASA Astrophysics Data System (ADS)

    Rajagopalan, K.; Chinnayakanahalli, K.; Adam, J. C.; Malek, K.; Nelson, R.; Stockle, C.; Brady, M.; Dinesh, S.; Barber, M. E.; Yorgey, G.; Kruger, C.

    2012-12-01

    The objective of this work is to assess the impacts of climate change and socio economics on agriculture in the Columbia River basin (CRB) in the Pacific Northwest region of the U.S. and a portion of Southwestern Canada. The water resources of the CRB are managed to satisfy multiple objectives including agricultural withdrawal, which is the largest consumptive user of CRB water with 14,000 square kilometers of irrigated area. Agriculture is an important component of the region's economy, with an annual value over 5 billion in Washington State alone. Therefore, the region is relevant for applying a modeling framework that can aid agriculture decision making in the context of a changing climate. To do this, we created an integrated biophysical and socio-economic regional modeling framework that includes human and natural systems. The modeling framework captures the interactions between climate, hydrology, crop growth dynamics, water management and socio economics. The biophysical framework includes a coupled macro-scale physically-based hydrology model (the Variable Infiltration Capacity, VIC model), and crop growth model (CropSyst), as well as a reservoir operations simulation model. Water rights data and instream flow target requirements are also incorporated in the model to simulate the process of curtailment during water shortage. The economics model informs the biophysical model of the short term agricultural producer response to water shortage as well as the long term agricultural producer response to domestic growth and international trade in terms of an altered cropping pattern. The modeling framework was applied over the CRB for the historical period 1976-2006 and compared to a future 30-year period centered on the 2030s. Impacts of climate change on irrigation water availability, crop irrigation demand, frequency of curtailment, and crop yields are quantified and presented. Sensitivity associated with estimates of water availability, irrigation demand, crop

  20. Uncertainty and sensitivity assessments of an agricultural-hydrological model (RZWQM2) using the GLUE method

    NASA Astrophysics Data System (ADS)

    Sun, Mei; Zhang, Xiaolin; Huo, Zailin; Feng, Shaoyuan; Huang, Guanhua; Mao, Xiaomin

    2016-03-01

    Quantitatively ascertaining and analyzing the effects of model uncertainty on model reliability is a focal point for agricultural-hydrological models due to more uncertainties of inputs and processes. In this study, the generalized likelihood uncertainty estimation (GLUE) method with Latin hypercube sampling (LHS) was used to evaluate the uncertainty of the RZWQM-DSSAT (RZWQM2) model outputs responses and the sensitivity of 25 parameters related to soil properties, nutrient transport and crop genetics. To avoid the one-sided risk of model prediction caused by using a single calibration criterion, the combined likelihood (CL) function integrated information concerning water, nitrogen, and crop production was introduced in GLUE analysis for the predictions of the following four model output responses: the total amount of water content (T-SWC) and the nitrate nitrogen (T-NIT) within the 1-m soil profile, the seed yields of waxy maize (Y-Maize) and winter wheat (Y-Wheat). In the process of evaluating RZWQM2, measurements and meteorological data were obtained from a field experiment that involved a winter wheat and waxy maize crop rotation system conducted from 2003 to 2004 in southern Beijing. The calibration and validation results indicated that RZWQM2 model can be used to simulate the crop growth and water-nitrogen migration and transformation in wheat-maize crop rotation planting system. The results of uncertainty analysis using of GLUE method showed T-NIT was sensitive to parameters relative to nitrification coefficient, maize growth characteristics on seedling period, wheat vernalization period, and wheat photoperiod. Parameters on soil saturated hydraulic conductivity, nitrogen nitrification and denitrification, and urea hydrolysis played an important role in crop yield component. The prediction errors for RZWQM2 outputs with CL function were relatively lower and uniform compared with other likelihood functions composed of individual calibration criterion. This

  1. Leaf chlorophyll constraint on model simulated gross primary productivity in agricultural systems

    NASA Astrophysics Data System (ADS)

    Houborg, Rasmus; F. McCabe, Matthew; Cescatti, Alessandro; A. Gitelson, Anatoly

    2015-12-01

    Leaf chlorophyll content (Chll) may serve as an observational proxy for the maximum rate of carboxylation (Vmax), which describes leaf photosynthetic capacity and represents the single most important control on modeled leaf photosynthesis within most Terrestrial Biosphere Models (TBMs). The parameterization of Vmax is associated with great uncertainty as it can vary significantly between plants and in response to changes in leaf nitrogen (N) availability, plant phenology and environmental conditions. Houborg et al. (2013) outlined a semi-mechanistic relationship between Vmax25 (Vmax normalized to 25 °C) and Chll based on inter-linkages between Vmax25, Rubisco enzyme kinetics, N and Chll. Here, these relationships are parameterized for a wider range of important agricultural crops and embedded within the leaf photosynthesis-conductance scheme of the Community Land Model (CLM), bypassing the questionable use of temporally invariant and broadly defined plant functional type (PFT) specific Vmax25 values. In this study, the new Chll constrained version of CLM is refined with an updated parameterization scheme for specific application to soybean and maize. The benefit of using in-situ measured and satellite retrieved Chll for constraining model simulations of Gross Primary Productivity (GPP) is evaluated over fields in central Nebraska, U.S.A between 2001 and 2005. Landsat-based Chll time-series records derived from the Regularized Canopy Reflectance model (REGFLEC) are used as forcing to the CLM. Validation of simulated GPP against 15 site-years of flux tower observations demonstrate the utility of Chll as a model constraint, with the coefficient of efficiency increasing from 0.91 to 0.94 and from 0.87 to 0.91 for maize and soybean, respectively. Model performances particularly improve during the late reproductive and senescence stage, where the largest temporal variations in Chll (averaging 35-55 μg cm-2 for maize and 20-35 μg cm-2 for soybean) are observed. While

  2. Assessing irrigated agriculture's surface water and groundwater consumption by combining satellite remote sensing and hydrologic modelling.

    PubMed

    Peña-Arancibia, Jorge L; Mainuddin, Mohammed; Kirby, John M; Chiew, Francis H S; McVicar, Tim R; Vaze, Jai

    2016-01-15

    Globally, irrigation accounts for more than two thirds of freshwater demand. Recent regional and global assessments indicate that groundwater extraction (GWE) for irrigation has increased more rapidly than surface water extraction (SWE), potentially resulting in groundwater depletion. Irrigated agriculture in semi-arid and arid regions is usually from a combination of stored surface water and groundwater. This paper assesses the usefulness of remotely-sensed (RS) derived information on both irrigation dynamics and rates of actual evapotranspiration which are both input to a river-reach water balance model in order to quantify irrigation water use and water provenance (either surface water or groundwater). The assessment is implemented for the water-years 2004/05-2010/11 in five reaches of the Murray-Darling Basin (Australia); a heavily regulated basin with large irrigated areas and periodic droughts and floods. Irrigated area and water use are identified each water-year (from July to June) through a Random Forest model which uses RS vegetation phenology and actual evapotranspiration as predicting variables. Both irrigated areas and actual evapotranspiration from irrigated areas were compared against published estimates of irrigated areas and total water extraction (SWE+GWE).The river-reach model determines the irrigated area that can be serviced with stored surface water (SWE), and the remainder area (as determined by the Random Forest Model) is assumed to be supplemented by groundwater (GWE). Model results were evaluated against observed SWE and GWE. The modelled SWE generally captures the observed interannual patterns and to some extent the magnitudes, with Pearson's correlation coefficients >0.8 and normalised root-mean-square-error<30%. In terms of magnitude, the results were as accurate as or better than those of more traditional (i.e., using areas that fluctuate based on water resource availability and prescribed crop factors) irrigation modelling. The RS

  3. Exploring agricultural production systems and their fundamental components with system dynamics modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Agricultural production in the United States is undergoing marked changes due to rapid shifts in consumer demands, input costs, and concerns for food safety and environmental impact. Agricultural production systems are comprised of multidimensional components and drivers that interact in complex wa...

  4. Collaborative Evaluation and Market Research Converge: An Innovative Model Agricultural Development Program Evaluation in Southern Sudan

    ERIC Educational Resources Information Center

    O'Sullivan, John M.; O'Sullivan, Rita

    2012-01-01

    In June and July 2006 a team of outside experts arrived in Yei, Southern Sudan through an AID project to provide support to a local agricultural development project. The team brought evaluation, agricultural marketing and financial management expertise to the in-country partners looking at steps to rebuild the economy of the war ravaged region. A…

  5. Whole System Integration and Modeling Essential to Agricultural Science and Technology for the 21st Century

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In the 21st century, agricultural research has more difficult and complex problems to solve. The continued increase in population in the developing countries requires continued increases in agricultural production. However, the increased use of fertilizers, pesticides, and water required for the new...

  6. Aligning Kolb's Experiential Learning Theory with a Comprehensive Agricultural Education Model

    ERIC Educational Resources Information Center

    Baker, Marshall A.; Robinson, J. Shane; Kolb, David A.

    2012-01-01

    Experiential learning has been a foundational tenant of agricultural education since its inception. However, the theory of experiential education has received limited attention in the permanent agricultural education literature base. As such, this philosophical manuscript examined Kolb's experiential learning process further, and considered the…

  7. Atrazine transport within a coastal zone in Southeastern Puerto Rico: a sensitivity analysis of an agricultural field model and riparian zone management model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Water quality models are used to predict effects of conservation practices to mitigate the transport of herbicides to water bodies. We used two models - the Agricultural Policy/Environmental eXtender (APEX) and the Riparian Ecosystem Management Model (REMM) to predict the movement of atrazine from ...

  8. Modeling phosphorus transport in an agricultural watershed using the WEPP model.

    PubMed

    Perez-Bidegain, Mario; Helmers, Matthew J; Cruse, Rick

    2010-01-01

    The Water Erosion Prediction Project (WEPP) model has been tested for its ability to predict soil erosion, runoff, and sediment delivery over a wide range of conditions and scales for both hillslopes and watersheds. Since its release in 1995, there has been considerable interest in adding a chemical transport element to it. Total phosphorus (TP) loss at the watershed outlet was simulated as the product of TP in the soil, amount of sediment at the watershed outlet, and an enrichment ratio (ER) factor. WEPP can be coupled with a simple algorithm to simulate phosphorus transport bound to sediment at the watershed outlet. The objective of this work was to incorporate and test the ability of WEPP in estimatingTP loss with sediment at the small watershed scale. Two approaches were examined. One approach (P-EER) estimated ER according to an empirical relationship; the other approach used the ER calculated by WEPP (P-WER).The data used for model performance test were obtained from two side-by-side watersheds monitored between 1976 and 1980. The watershed sizes were 5.05 and 6.37 ha, and each was in a corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotation. Measured and simulated results were compared for the period April to October in each year. There was no statistical difference between the mean measured and simulated TP loss. The Nash-Sutcliffe coefficient was 0.80 and 0.78 for the P-EER and P-WER methods, respectively. It was critical for both methods that WEPP adequately represent the biggest sediment yield events because sediment is the main driver for TP loss so that the model can adequately simulate TP losses bound to sediment. The P-WER method is recommended because it does not require use of empirical parameters to estimate TP loss at the watershed outlet. PMID:21284310

  9. A modeling approach to simulate the role of anecic and endogeic earthworms in soil structure dynamics of two agricultural systems

    NASA Astrophysics Data System (ADS)

    Le Couteulx, Alexis; Wolf, Cédric; Pérès, Guénola; Hallaire, Vincent

    2015-04-01

    In agriculture, one of the main purposes of innovative systems is to preserve and improve soil quality and noticeably their physical quality. This physical quality of a soil is intimately linked with its structure, i.e. the spatial arrangement of voids and solids. It is well-known that agricultural systems may deeply impact on soil structure through their effect on various structuring processes, in particular (i) the mechanical action of soil tillage and (ii) the burrowing activity and casts production of earthworms. As the assessment of agricultural systems needs long term experiments, it is not feasible to assess them all. However, the modeling approach has been used seldom despite it seems promising. As a first step towards the modeling of agricultural systems, we propose a model that simulates the impact of earthworm bioturbation and several tillage practices on soil structure dynamics. The proposed model accounts for two earthworm ecological categories: anecics and endogeics. Anecics are split into epi-anecics and true anecics and endogeics are kept at the specific level. The model takes into account their physiological and morphological features such as their diapause period, their gut transit time or their body size. In order to simulate the bioturbation activity of earthworms, they can make six different actions: (i) burrow new paths by ingesting soil particles, (ii) move inside existing paths, (iii) move to soil surface, (iv) wait, (v) produce a subsurface cast or (vi) produce a surface cast. For the various species and groups of earthworms, the probability of these actions was adjusted from experiments and published results. This part of the model dedicated to earthworms allows to build and study their network of burrows but also the position and volume of their subsurface and surface casts. This network may be couple with models of water conductivity to assess the role of earthworm on this soil functional property. To better simulate soil structure

  10. Monthly water balance model for climate change analysis in agriculture with R

    NASA Astrophysics Data System (ADS)

    Kalicz, Péter; Herceg, András; Gribovszki, Zoltán

    2015-04-01

    For Hungary regional climate models projections suggest a warmer climate and some changes in annual precipitation distribution. These changes force the whole agrarian sector to consider the traditional cropping technologies. This situation is more serious in forestry because some forest populations are on their xeric distributional limits (Gálos et. al, 2014). Additionally, a decision has an impact sometimes longer than one hundred years. To support the stakeholder there is a project which develops a GIS (Geographic Information System) based decision support system. Hydrology plays significant role in this system because water is often one of the most important limiting factor in Hungary. A modified Thorntwaite-type monthly water balance model was choosen to produce hydrological estimations for the GIS modules. This model is calibrated with the available data between 2000 and 2008. Beside other meteorological data we used mainly an actual evapotranspiration map in the calibration phase, which was derived with the Complementary-relationship-based evapotranspiration mapping (CREMAP; Szilágyi and Kovács, 2011) technique. The calibration process is pixel based and it has several stochastic steps. We try to find a flexible solution for the model implementation which easy to automatize and can be integrate in GIS systems. The open source R programming language was selected which well satisfied these demands. The result of this development is summarized as an R package. This publication has been supported by AGRARKLIMA.2 VKSZ_12-1-2013-0034 project. References Gálos B., Antal V., Czimber K., Mátyás Cs. (2014) Forest ecosystems, sewage works and droughts - possibilities for climate change adaptation. In: Santamarta J.C., Hernandez-Gutiérrez L.E., Arraiza M.P. (eds) 2014. Natural Hazards and Climate Change/Riesgos Naturales y Cambio Climático. Madrid: Colegio de Ingenieros de Montes. ISBN 978-84-617-1060-7, D.L. TF 565-2014, 91-104 pp Szilágyi J., Kovács Á. (2011