This document compares two multicriteria decision methods - Brans Promethee and a modified version - for selecting erosion control alternatives in the Chaco area of Salta province, Argentina. It applies the methods to evaluate six alternatives across eight criteria in six subzones. For the subzone of La Estrella, it presents the decision matrices and rankings of alternatives under each method. Alternative E is the top ranked under the original method while Alternative B ranks first under the modified version which incorporates criterion weights.
This document presents a methodological framework for assessing multiple ecosystem services provided by soils at a regional scale. The methodology involves: (1) defining soil-based ecosystem services based on available soil data and societal demands; (2) identifying appropriate indicators and coding; and (3) assessing and mapping the multiple ecosystem services. The framework is applied to a case study in Emilia Romagna, Italy, where 8 soil services are assessed using indicators derived from soil properties mapped at 1km resolution. Maps of individual services show different soil types provide services to different extents. Analysis of service bundles in different soil landscape units highlights tradeoffs and synergies among services. "Hotspots" providing high levels of multiple services are identified and mapped.
This document summarizes a presentation on whole-farm models for quantifying greenhouse gas emissions from temperate grassland farming systems and their potential use in linking climate change mitigation and adaptation strategies. It discusses the main components of ruminant livestock systems that farm models simulate, including sources of GHG emissions. Examples of specific farm models are provided. The document outlines how models can evaluate different mitigation options and their interactions, and the importance of considering farm economics. It concludes with recommendations for improving farm models to better quantify GHGs, mitigate emissions, and assess adaptations to climate change impacts.
Diffuse reflectance spectroscopy to estimate soil attributes of Brazilian wet...Agriculture Journal IJOEAR
Abstract— The study of soils and characterization of its attributes are continually evolving, however, for the condition of wetlands, such information is still scarce and poorly distributed. Thus, the objective of this work was to characterize spectrally the soils of a wetland area. On the study area were collected georeferenced soil samples and sent for chemical and physical analysis routine and then subjected to spectral evaluation. Were identified seven soil classes with hydromorphic characteristics in their spectral curves? The information contained in these curves then led the development of equations for soil attributes. Sand was the physical attribute of a better correlation with laboratory data and Cationic Exchange Capacity (CEC), the chemical attributes that showed better results.
The document discusses the Large Scale Biosphere Atmosphere Experiment in Amazonia (LBA). It addresses key scientific questions about how the Amazon functions as a regional entity and how land use and climate changes affect its biological, chemical, and physical functions. Specific topics covered include the water, carbon, and nutrient cycles; aerosols; anthropogenic activities; susceptibility to stresses; and interactions between climate, land use, fire, hydrology, ecology, and human dimensions. It also provides conceptual diagrams of these interactions and the major uncertainties in quantifying the climate system.
Jacob Johnson, et al, Penn State University - “Case Study to Assess the Costs...Michael Hewitt, GISP
This study aims to assess the costs of the Forest Reclamation Approach (FRA) compared to conventional reclamation methods through a case study analysis. Preliminary results from a site in Pennsylvania show machine cycle times and costs for grading, soil placement, and seeding using the FRA. Total estimated reclamation costs per acre were $4923.13 for the FRA site versus higher expected costs for conventional methods. The results will provide guidance to operators and regulators on cost-effective reforestation techniques that support long-term forest productivity and ecosystem services.
Accurate estimation of runoff and sediment yield amount is not only an important task in physiographic but also important for proper watershed management. Watershed is an ideal unit for planning and management of land and water resources. Direct runoff in a catchment depends on soil type, land cover and rainfall. Of the many methods available for estimating runoff from rainfall, the curve number method (SCS-CN) is the most popular. The curve number depends upon soil and land use characteristics. This study was conducted in the Upper Cauvery Karnataka using remote sensing and GIS. SCSCN method has been used for surface runoff estimation for Eight watersheds of Upper Cauvery. The soil map and land use were created in the GIS environment, because the curve number method is used here as a distributed model. The major advantage of employing GIS in rainfall -runoff modelling is that more accurate sizing and catchment characterization can be achieved. Furthermore, the analysis can be performed much faster, especially when there is a complex mix of land use classes and different soil types. The results showed that the surface runoff ranged from 170.12-599.84 mm in the study area, when rainfall rates were received from 1042.65-1912 mm. To find the relationship between rainfall and runoff rates, The straight line equation was used, That was found there a strong correlation between Runoff and precipitation rates, The value correlation coefficient between them was 86%. The Average depth of runoff is more in watershed A4, Average runoff coefficient is less in Watershed B2, the correlation coefficient is high in A4 to a value of almost 95%. Through of these results, the study recommends take advantage of runoff rates by reserving them at collection of Watershed and then using them for agricultural purposes in the vicinity. This would be better than reserving water from the total area which is 10874.65 square kilometers, and then will evaporate or infiltrate before reaching the dam lake
Poster56: Greenhouse gas fluxes, global warming potential and emergy evaluati...CIAT
This study assessed greenhouse gas fluxes and global warming potential in different land uses in southern Honduras, including a traditional slash-and-burn system, different ages of a slash-and-mulch agroforestry system, and secondary forest. The researchers measured nitrous oxide, methane, and carbon dioxide fluxes from soil in these land uses over time using closed chambers. They calculated annual greenhouse gas accumulation and global warming potential for each land use based on these fluxes and carbon stocks. Their results showed that slash-and-burn agriculture had the highest global warming potential, followed by the younger slash-and-mulch agroforestry system, with the older agroforestry system and secondary forest having lower impacts.
Optimization techniques for a model problem of saltwater intrusion in coastal...Manolis Vavalis
This document summarizes optimization techniques for managing saltwater intrusion in coastal aquifers. It begins with an introduction to the problem of saltwater intrusion caused by pumping fresh water from coastal aquifers. It then presents the mathematical model and equations used to describe water flow. Three types of coastal aquifers are described along with analytical solutions. An optimization algorithm called ALOPEX is introduced for determining optimal well placement and pumping rates. Numerical simulations are shown applying ALOPEX to sample aquifers with 2 and 5 wells. Sensitivity analysis is also presented by varying pumping rates, recharge rates, and ambient water discharge.
This document presents a methodological framework for assessing multiple ecosystem services provided by soils at a regional scale. The methodology involves: (1) defining soil-based ecosystem services based on available soil data and societal demands; (2) identifying appropriate indicators and coding; and (3) assessing and mapping the multiple ecosystem services. The framework is applied to a case study in Emilia Romagna, Italy, where 8 soil services are assessed using indicators derived from soil properties mapped at 1km resolution. Maps of individual services show different soil types provide services to different extents. Analysis of service bundles in different soil landscape units highlights tradeoffs and synergies among services. "Hotspots" providing high levels of multiple services are identified and mapped.
This document summarizes a presentation on whole-farm models for quantifying greenhouse gas emissions from temperate grassland farming systems and their potential use in linking climate change mitigation and adaptation strategies. It discusses the main components of ruminant livestock systems that farm models simulate, including sources of GHG emissions. Examples of specific farm models are provided. The document outlines how models can evaluate different mitigation options and their interactions, and the importance of considering farm economics. It concludes with recommendations for improving farm models to better quantify GHGs, mitigate emissions, and assess adaptations to climate change impacts.
Diffuse reflectance spectroscopy to estimate soil attributes of Brazilian wet...Agriculture Journal IJOEAR
Abstract— The study of soils and characterization of its attributes are continually evolving, however, for the condition of wetlands, such information is still scarce and poorly distributed. Thus, the objective of this work was to characterize spectrally the soils of a wetland area. On the study area were collected georeferenced soil samples and sent for chemical and physical analysis routine and then subjected to spectral evaluation. Were identified seven soil classes with hydromorphic characteristics in their spectral curves? The information contained in these curves then led the development of equations for soil attributes. Sand was the physical attribute of a better correlation with laboratory data and Cationic Exchange Capacity (CEC), the chemical attributes that showed better results.
The document discusses the Large Scale Biosphere Atmosphere Experiment in Amazonia (LBA). It addresses key scientific questions about how the Amazon functions as a regional entity and how land use and climate changes affect its biological, chemical, and physical functions. Specific topics covered include the water, carbon, and nutrient cycles; aerosols; anthropogenic activities; susceptibility to stresses; and interactions between climate, land use, fire, hydrology, ecology, and human dimensions. It also provides conceptual diagrams of these interactions and the major uncertainties in quantifying the climate system.
Jacob Johnson, et al, Penn State University - “Case Study to Assess the Costs...Michael Hewitt, GISP
This study aims to assess the costs of the Forest Reclamation Approach (FRA) compared to conventional reclamation methods through a case study analysis. Preliminary results from a site in Pennsylvania show machine cycle times and costs for grading, soil placement, and seeding using the FRA. Total estimated reclamation costs per acre were $4923.13 for the FRA site versus higher expected costs for conventional methods. The results will provide guidance to operators and regulators on cost-effective reforestation techniques that support long-term forest productivity and ecosystem services.
Accurate estimation of runoff and sediment yield amount is not only an important task in physiographic but also important for proper watershed management. Watershed is an ideal unit for planning and management of land and water resources. Direct runoff in a catchment depends on soil type, land cover and rainfall. Of the many methods available for estimating runoff from rainfall, the curve number method (SCS-CN) is the most popular. The curve number depends upon soil and land use characteristics. This study was conducted in the Upper Cauvery Karnataka using remote sensing and GIS. SCSCN method has been used for surface runoff estimation for Eight watersheds of Upper Cauvery. The soil map and land use were created in the GIS environment, because the curve number method is used here as a distributed model. The major advantage of employing GIS in rainfall -runoff modelling is that more accurate sizing and catchment characterization can be achieved. Furthermore, the analysis can be performed much faster, especially when there is a complex mix of land use classes and different soil types. The results showed that the surface runoff ranged from 170.12-599.84 mm in the study area, when rainfall rates were received from 1042.65-1912 mm. To find the relationship between rainfall and runoff rates, The straight line equation was used, That was found there a strong correlation between Runoff and precipitation rates, The value correlation coefficient between them was 86%. The Average depth of runoff is more in watershed A4, Average runoff coefficient is less in Watershed B2, the correlation coefficient is high in A4 to a value of almost 95%. Through of these results, the study recommends take advantage of runoff rates by reserving them at collection of Watershed and then using them for agricultural purposes in the vicinity. This would be better than reserving water from the total area which is 10874.65 square kilometers, and then will evaporate or infiltrate before reaching the dam lake
Poster56: Greenhouse gas fluxes, global warming potential and emergy evaluati...CIAT
This study assessed greenhouse gas fluxes and global warming potential in different land uses in southern Honduras, including a traditional slash-and-burn system, different ages of a slash-and-mulch agroforestry system, and secondary forest. The researchers measured nitrous oxide, methane, and carbon dioxide fluxes from soil in these land uses over time using closed chambers. They calculated annual greenhouse gas accumulation and global warming potential for each land use based on these fluxes and carbon stocks. Their results showed that slash-and-burn agriculture had the highest global warming potential, followed by the younger slash-and-mulch agroforestry system, with the older agroforestry system and secondary forest having lower impacts.
Optimization techniques for a model problem of saltwater intrusion in coastal...Manolis Vavalis
This document summarizes optimization techniques for managing saltwater intrusion in coastal aquifers. It begins with an introduction to the problem of saltwater intrusion caused by pumping fresh water from coastal aquifers. It then presents the mathematical model and equations used to describe water flow. Three types of coastal aquifers are described along with analytical solutions. An optimization algorithm called ALOPEX is introduced for determining optimal well placement and pumping rates. Numerical simulations are shown applying ALOPEX to sample aquifers with 2 and 5 wells. Sensitivity analysis is also presented by varying pumping rates, recharge rates, and ambient water discharge.
For Domestic Wastewater Treatment, Finding Optimum Conditions by Particle Swa...Agriculture Journal IJOEAR
Abstract— Performing jar test method is used for finding out optimum conditions (coagulant type, coagulant dose, pH etc.)for treatment of domestic wastewater before physicochemical process, or coagulation process. In this study, Response Surface Method (RSM) is applied to determine optimum combinations of coagulant dose and pH value in jar test. Alum, FeCl3 and FeSO4 are used as coagulant and compared with highest removal efficiency of their two responses which turbidity and chemical oxygen demand (COD).Finding equations from RSM are also evaluated with Particle Swarm Optimization (PSO) method by using Matlab Program. Alum and Ferric Chloridedose500 mg/lat pH7 found as optimum conditions for domestic wastewater treatment. COD removal for Alum and Ferric Chloride are 90% and 70%,respectively.In addition, Because of becoming low COD removal (maximum 50%) and ineffectively color removal, Ferric Sulfate coagulant found as inconvenient for treating domestic wastewater.
This document summarizes a strategy for estimating carbon and water budgets for croplands at the plot scale over large areas using remote sensing data and a crop model. The objectives are to analyze ecosystem services like yield, biomass, evapotranspiration, and net CO2 fluxes to calculate annual carbon and water budgets and test the effects of management practices. A multi-temporal remote sensing data assimilation scheme was developed to run the SAFYE-CO2 crop model without needing detailed ground data by using Sentinel satellite imagery. The approach provides good estimates of fluxes compared to observations and performs well compared to other models without requiring management data. It can help quantify the effects of practices like cover crops on carbon storage and other benefits.
This document describes a GIS-based tool developed to prioritize abandoned mine waste sites as potential pollution sources in five river catchments in southwest England. The tool incorporates data on mine locations and waste sites provided by the Environment Agency. It analyzes three risk factors for each waste site: proximity to water bodies, area of the waste site, and slope of the drainage pathway from the site. Risk scores are assigned to each factor based on the potential pollution risk. Weighting is applied to the factors based on their relative importance as determined through expert analysis. The combined risk scores provide a prioritized list of waste sites for further investigation and remediation efforts by the Environment Agency.
This document discusses models for characterizing extreme events data in fields like hydrology, hydraulics, oceanography, and climate change. It provides examples of extreme events data like maximum flood levels and wave heights. There are three main types of extreme events data: complete observations, maxima/minima, and exceedances over a threshold. Commonly used models include the distribution of order statistics for complete data, the generalized extreme value distribution for maxima/minima data, and the generalized Pareto distribution for exceedances over a threshold. The document outlines these models and discusses parameter and quantile estimation of extremes.
4 Review on Different Evapotranspiration Empirical EquationsINFOGAIN PUBLICATION
This document reviews different empirical equations used to calculate evapotranspiration (ET). It begins by defining ET and describing its importance for irrigation management. It then discusses three categories of empirical ET equations: temperature-based methods, radiation-based methods, and mass-transfer methods. Thirty equations from these categories are analyzed and compared to the FAO 56 Penman-Monteith equation, which is presented as the reference standard. Statistical analyses including R-squared, RMSE, and index of agreement are used to evaluate the performance of the other equations. The document focuses on temperature-based methods, presenting equations developed by Thornthwaite, Linacre, and Blaney-Criddle. It concludes by stating the review aims
An optimal design of current conveyors using a hybrid-based metaheuristic alg...IJECEIAES
This paper focuses on the optimal sizing of a positive second-generation current conveyor (CCII+), employing a hybrid algorithm named DE-ACO, which is derived from the combination of differential evolution (DE) and ant colony optimization (ACO) algorithms. The basic idea of this hybridization is to apply the DE algorithm for the ACO algorithm’s initialization stage. Benchmark test functions were used to evaluate the proposed algorithm’s performance regarding the quality of the optimal solution, robustness, and computation time. Furthermore, the DE-ACO has been applied to optimize the CCII+ performances. SPICE simulation is utilized to validate the achieved results, and a comparison with the standard DE and ACO algorithms is reported. The results highlight that DE-ACO outperforms both ACO and DE.
The document discusses three analysis frameworks for integrating energy and environmental issues:
1) The sensory-motor feedback loop models the assessment-control cycle using monitoring data to inform goals and actions.
2) The biogeochemical cycling loop illustrates the circulation of materials like carbon and nitrogen between environmental compartments.
3) The causality loop links human activities, their impacts on the environment, and feedback through economic and social factors.
2018 National Tanks Conference & Exposition: HRSC Data VisualizationAntea Group
Two of our High-Resolution Site Characterization (HRSC) Data Visualization posters featured at the 2018 NTC Conference in Louisville, KY.
1. Using Data Management and 3-Dimensional Data Visualization to Generate More Complete Conceptual Site Models and Streamline Site Closure
2. High-Resolution Site Characterization (HRSC) and 3-Dimensional Data Visualization for a Fractured Rock Site: A Path to Streamlined Closure
State of the art on Life Cycle Assessment for Solid Waste ManagementYashpujara00955
Life Cycle Assessment for Solid Waste Management- A Peer Review. LCA tool can be used as a decision-making approach for the many companies and especially LCA tool can be employed for finding the Impact assessment on Environment, Human health and vegetations.
Presentation about the use of Social Metabolism and Complex Systems Theory to analysethe water-Food-Energy Nexus with an application of MuSIASEM to the Indian Punjab.
Oral Presentation ot the Biannual COnference of the International Society for Industrial Ecology, 10 July 2015, University of Surrey, UK.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Fao modelling system for agricultural impacts of climate changeMaroi Tsouli Fathi
The MOSAICC (MOdelling System for Agricultural Impacts of Climate Change) system uses an integrated modelling approach to assess the impacts of climate change on agriculture. It includes models for climate, hydrology, crops, forestry, and economic impacts. Climate models are downscaled and bias-corrected to provide climate projections at a high resolution. Hydrology, crop, forestry, and economic models use climate data to project changes in water availability, crop yields, forestry outputs, and economic indicators. Results are made available through a web portal to support climate change impact assessment and adaptation planning.
eMAST aims to integrate data from TERN and other sources to model ecosystems at all scales in Australia from 2013-2015. This will be done using data assimilation, model evaluation and optimization tools to further ecosystem science and help address questions about topics like carbon, water, climate change, fire, and biodiversity. Key products being delivered include high resolution climate and productivity datasets as well as tools for data analysis, interpolation and modeling. Progress includes the development and delivery of ANUClimate climate datasets and the ePiSaT model for estimating primary productivity across Australia using flux tower and satellite data.
The document discusses using life cycle assessment (LCA) as a tool for designing more sustainable cities. LCA can help address environmental problems by assessing the full life cycle impacts of city infrastructure and design. The document presents an LCA of natural gas distribution networks in neighborhoods with varying densities. Results show the environmental impact is four times higher in a low-density neighborhood compared to medium and high-density neighborhoods, mainly due to differences in network length. LCA is presented as an appropriate tool for guiding urban ecodesign and decision-making by providing a comprehensive view of environmental impacts.
Computer model simulations are widely used in the investigation of complex hydrological systems. In particular, hydrological models are tools that help both to better understand hydrological processes and to predict extreme events such as floods and droughts. Usually, model parameters need to be estimated through calibration, in order to constrain model outputs to observed variables.
Relevant model parameters used for calibration are usually selected based on expert knowledge of the modeller or by using a local one-at-a-time (OAT) sensitivity analysis (SA). However, in case of complex models those approaches may not result in proper identification of the most sensitive parameters for model calibration. In particular local OAT SA methods are only effective for assessing the relative importance of input factors when the model is linear, monotonic, and additive, which is rarely the case for complex environmental models. In contrast Global Sensitivity Analysis (GSA)
is a formal method for statistical evaluation of relevant parameters that contribute significantly to model performance. GSA techniques explore the entire feasible space of each model parameter, and they do not require any assumptions on the model nature (such as linearity or additivity).
In this work we apply the GSA to LISFLOOD, a fully-distributed hydrological model used for flood forecasting at Pan-European scale within the European Flood Awareness System (EFAS). Two case studies are considered, snowmelt- and evapotranspiration-driven catchments, to identify sensitive parameters for both types of hydrological regimes. Results of the GSA will then be used for selecting parameters that need to be estimated during model calibration. Considering the large
number of parameters of a fully-distributed model, a two-step GSA framework is applied. First, we implement the computationally efficient screening method of Morris. This method requires a limited number of simulations and produces a qualitative ranking and selection of important factors. As a second step, we apply the variance-based method of Sobol, only to the subset of factors determined as important during the previous screening. The method of Sobol provides quantitative estimates for first order and total order sensitivity indexes of input factors.
The calibration results after the GSA will be described for both case studies and compared against those obtained by using only prior expert knowledge
An ecological assessment of food waste composting using a hybrid life cycle a...Ramy Salemdeeb
A conference paper published at the 8th Conference of the International Society for Industrial Ecology, At University of Surrey, Guildford, UK, At Surrey
CAN CROP MANAGEMENT IMPROVE EMISSIONS SAVINGS?: PRELIMINARY RESULTS OF THE OP...Bioenergy Crops
This document evaluates the effects of different crop management practices on greenhouse gas emissions and energy balances of rye grown as an energy crop for electricity production in Spain. Six management practices were tested, combining two seeding doses (typical and low) with three fertilization doses (zero, low, and typical). Results showed lower fertilization improved emissions but reduced yields, potentially depleting soil nitrogen over time. Using low seeding doses also reduced yields without offsetting lower inputs. A nitrogen balance assessment found most practices led to annual soil nitrogen losses. Overall, the study aims to optimize rye management for electricity production while maintaining soil sustainability.
This document summarizes a presentation on a cross-disciplinary watershed management project. The project aims to integrate biophysical and social factors to better target management practices. It develops a diagnostic decision support system to identify areas exporting high pollutant levels ("critical source areas") and prescribe targeted best management practices (BMPs). Modeling evaluates how climate change may increase polluted areas and impact BMP effectiveness. Interviews identify competing views between scientists and farmers on water issues. The work seeks to overcome divergent stakeholder perspectives and better engage communities in watershed management.
Este documento presenta 12 ejercicios de geometría analítica que involucran puntos en el plano cartesiano, segmentos de recta, ecuaciones de rectas y determinación de puntos de intersección y alineación. Los ejercicios se resuelven encontrando pendientes, ecuaciones de rectas paralelas y perpendiculares, y sistemas de ecuaciones.
El documento resume la historia del internet desde 1963 hasta 2007, mencionando hitos como el desarrollo del protocolo TCP/IP en 1974, la creación de la World Wide Web por Tim Berners-Lee en 1991, el lanzamiento de Amazon en 1994, el nacimiento de Google en 1998, y el surgimiento de redes sociales como Facebook en 2004 y Twitter en 2006.
For Domestic Wastewater Treatment, Finding Optimum Conditions by Particle Swa...Agriculture Journal IJOEAR
Abstract— Performing jar test method is used for finding out optimum conditions (coagulant type, coagulant dose, pH etc.)for treatment of domestic wastewater before physicochemical process, or coagulation process. In this study, Response Surface Method (RSM) is applied to determine optimum combinations of coagulant dose and pH value in jar test. Alum, FeCl3 and FeSO4 are used as coagulant and compared with highest removal efficiency of their two responses which turbidity and chemical oxygen demand (COD).Finding equations from RSM are also evaluated with Particle Swarm Optimization (PSO) method by using Matlab Program. Alum and Ferric Chloridedose500 mg/lat pH7 found as optimum conditions for domestic wastewater treatment. COD removal for Alum and Ferric Chloride are 90% and 70%,respectively.In addition, Because of becoming low COD removal (maximum 50%) and ineffectively color removal, Ferric Sulfate coagulant found as inconvenient for treating domestic wastewater.
This document summarizes a strategy for estimating carbon and water budgets for croplands at the plot scale over large areas using remote sensing data and a crop model. The objectives are to analyze ecosystem services like yield, biomass, evapotranspiration, and net CO2 fluxes to calculate annual carbon and water budgets and test the effects of management practices. A multi-temporal remote sensing data assimilation scheme was developed to run the SAFYE-CO2 crop model without needing detailed ground data by using Sentinel satellite imagery. The approach provides good estimates of fluxes compared to observations and performs well compared to other models without requiring management data. It can help quantify the effects of practices like cover crops on carbon storage and other benefits.
This document describes a GIS-based tool developed to prioritize abandoned mine waste sites as potential pollution sources in five river catchments in southwest England. The tool incorporates data on mine locations and waste sites provided by the Environment Agency. It analyzes three risk factors for each waste site: proximity to water bodies, area of the waste site, and slope of the drainage pathway from the site. Risk scores are assigned to each factor based on the potential pollution risk. Weighting is applied to the factors based on their relative importance as determined through expert analysis. The combined risk scores provide a prioritized list of waste sites for further investigation and remediation efforts by the Environment Agency.
This document discusses models for characterizing extreme events data in fields like hydrology, hydraulics, oceanography, and climate change. It provides examples of extreme events data like maximum flood levels and wave heights. There are three main types of extreme events data: complete observations, maxima/minima, and exceedances over a threshold. Commonly used models include the distribution of order statistics for complete data, the generalized extreme value distribution for maxima/minima data, and the generalized Pareto distribution for exceedances over a threshold. The document outlines these models and discusses parameter and quantile estimation of extremes.
4 Review on Different Evapotranspiration Empirical EquationsINFOGAIN PUBLICATION
This document reviews different empirical equations used to calculate evapotranspiration (ET). It begins by defining ET and describing its importance for irrigation management. It then discusses three categories of empirical ET equations: temperature-based methods, radiation-based methods, and mass-transfer methods. Thirty equations from these categories are analyzed and compared to the FAO 56 Penman-Monteith equation, which is presented as the reference standard. Statistical analyses including R-squared, RMSE, and index of agreement are used to evaluate the performance of the other equations. The document focuses on temperature-based methods, presenting equations developed by Thornthwaite, Linacre, and Blaney-Criddle. It concludes by stating the review aims
An optimal design of current conveyors using a hybrid-based metaheuristic alg...IJECEIAES
This paper focuses on the optimal sizing of a positive second-generation current conveyor (CCII+), employing a hybrid algorithm named DE-ACO, which is derived from the combination of differential evolution (DE) and ant colony optimization (ACO) algorithms. The basic idea of this hybridization is to apply the DE algorithm for the ACO algorithm’s initialization stage. Benchmark test functions were used to evaluate the proposed algorithm’s performance regarding the quality of the optimal solution, robustness, and computation time. Furthermore, the DE-ACO has been applied to optimize the CCII+ performances. SPICE simulation is utilized to validate the achieved results, and a comparison with the standard DE and ACO algorithms is reported. The results highlight that DE-ACO outperforms both ACO and DE.
The document discusses three analysis frameworks for integrating energy and environmental issues:
1) The sensory-motor feedback loop models the assessment-control cycle using monitoring data to inform goals and actions.
2) The biogeochemical cycling loop illustrates the circulation of materials like carbon and nitrogen between environmental compartments.
3) The causality loop links human activities, their impacts on the environment, and feedback through economic and social factors.
2018 National Tanks Conference & Exposition: HRSC Data VisualizationAntea Group
Two of our High-Resolution Site Characterization (HRSC) Data Visualization posters featured at the 2018 NTC Conference in Louisville, KY.
1. Using Data Management and 3-Dimensional Data Visualization to Generate More Complete Conceptual Site Models and Streamline Site Closure
2. High-Resolution Site Characterization (HRSC) and 3-Dimensional Data Visualization for a Fractured Rock Site: A Path to Streamlined Closure
State of the art on Life Cycle Assessment for Solid Waste ManagementYashpujara00955
Life Cycle Assessment for Solid Waste Management- A Peer Review. LCA tool can be used as a decision-making approach for the many companies and especially LCA tool can be employed for finding the Impact assessment on Environment, Human health and vegetations.
Presentation about the use of Social Metabolism and Complex Systems Theory to analysethe water-Food-Energy Nexus with an application of MuSIASEM to the Indian Punjab.
Oral Presentation ot the Biannual COnference of the International Society for Industrial Ecology, 10 July 2015, University of Surrey, UK.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Fao modelling system for agricultural impacts of climate changeMaroi Tsouli Fathi
The MOSAICC (MOdelling System for Agricultural Impacts of Climate Change) system uses an integrated modelling approach to assess the impacts of climate change on agriculture. It includes models for climate, hydrology, crops, forestry, and economic impacts. Climate models are downscaled and bias-corrected to provide climate projections at a high resolution. Hydrology, crop, forestry, and economic models use climate data to project changes in water availability, crop yields, forestry outputs, and economic indicators. Results are made available through a web portal to support climate change impact assessment and adaptation planning.
eMAST aims to integrate data from TERN and other sources to model ecosystems at all scales in Australia from 2013-2015. This will be done using data assimilation, model evaluation and optimization tools to further ecosystem science and help address questions about topics like carbon, water, climate change, fire, and biodiversity. Key products being delivered include high resolution climate and productivity datasets as well as tools for data analysis, interpolation and modeling. Progress includes the development and delivery of ANUClimate climate datasets and the ePiSaT model for estimating primary productivity across Australia using flux tower and satellite data.
The document discusses using life cycle assessment (LCA) as a tool for designing more sustainable cities. LCA can help address environmental problems by assessing the full life cycle impacts of city infrastructure and design. The document presents an LCA of natural gas distribution networks in neighborhoods with varying densities. Results show the environmental impact is four times higher in a low-density neighborhood compared to medium and high-density neighborhoods, mainly due to differences in network length. LCA is presented as an appropriate tool for guiding urban ecodesign and decision-making by providing a comprehensive view of environmental impacts.
Computer model simulations are widely used in the investigation of complex hydrological systems. In particular, hydrological models are tools that help both to better understand hydrological processes and to predict extreme events such as floods and droughts. Usually, model parameters need to be estimated through calibration, in order to constrain model outputs to observed variables.
Relevant model parameters used for calibration are usually selected based on expert knowledge of the modeller or by using a local one-at-a-time (OAT) sensitivity analysis (SA). However, in case of complex models those approaches may not result in proper identification of the most sensitive parameters for model calibration. In particular local OAT SA methods are only effective for assessing the relative importance of input factors when the model is linear, monotonic, and additive, which is rarely the case for complex environmental models. In contrast Global Sensitivity Analysis (GSA)
is a formal method for statistical evaluation of relevant parameters that contribute significantly to model performance. GSA techniques explore the entire feasible space of each model parameter, and they do not require any assumptions on the model nature (such as linearity or additivity).
In this work we apply the GSA to LISFLOOD, a fully-distributed hydrological model used for flood forecasting at Pan-European scale within the European Flood Awareness System (EFAS). Two case studies are considered, snowmelt- and evapotranspiration-driven catchments, to identify sensitive parameters for both types of hydrological regimes. Results of the GSA will then be used for selecting parameters that need to be estimated during model calibration. Considering the large
number of parameters of a fully-distributed model, a two-step GSA framework is applied. First, we implement the computationally efficient screening method of Morris. This method requires a limited number of simulations and produces a qualitative ranking and selection of important factors. As a second step, we apply the variance-based method of Sobol, only to the subset of factors determined as important during the previous screening. The method of Sobol provides quantitative estimates for first order and total order sensitivity indexes of input factors.
The calibration results after the GSA will be described for both case studies and compared against those obtained by using only prior expert knowledge
An ecological assessment of food waste composting using a hybrid life cycle a...Ramy Salemdeeb
A conference paper published at the 8th Conference of the International Society for Industrial Ecology, At University of Surrey, Guildford, UK, At Surrey
CAN CROP MANAGEMENT IMPROVE EMISSIONS SAVINGS?: PRELIMINARY RESULTS OF THE OP...Bioenergy Crops
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1. Comparison of Brans Promethee multicriteria
decision method and Promethee modified by authors
for the optimization of an erosion control integral
plan in Chaco area in Salta province (Argentine)
J. B. Grau (1), J. M. Antón (1), F. Colombo (2), L. de los Ríos (2), J. M. Cisneros (3), A. Tarquis (1)
(1) E. T. S. I. Agrónomos- Universidad Politécnica de Madrid (Spain) (2) Escuela de Negocios- Universidad Católica de
Salta (Argentina) (3) Facultad de Agronomía y Veterinaria-Universidad Nacional de Río Cuarto (Argentina)
E-mail: j.grau@upm.es
Abstract- Chaco area is situated in the Province of Salta at
North West of Argentine. The desertification is a big problem.
In order to mitigate the problem it is necessary to take into
account not only pedologic criteria but the economical,
environmental, cultural and sociological criteria. Six sub zones
have been established following previous studies. Eight criteria
and six alternatives have been introduced in the model.
Following the results of the study carried out by a collaborative
project between UPM and UCS financed by AECID (1) were
established several initial matrix. Brans Promethee Multicriteria
Decision Method (MCDM) was applied and the authors
modified that method introducing weights like in Electre
Method.
I. INTRODUCTION
The Salta Province has 155.000 km2
and 1 million
population, it is at NW of Argentine (NOA) having latitudes
around 25ºS, it has rain from 400 to 800 mm/year. It has a
low density of population in small cities and Indian places
“puestos” or “colonias”. It has low standards for roads and it
has an environment that is “deteriorating progressively”.
Water is the most critical factor, as much for human and
animal consumption, as for the production system in general
and for the flooding and lack of appropriated infrastructures.
Besides the water, other factors have an important influence
in the erosion and progressive desertification of this region
and environment degradation. Historically the human
exploitation of natural forest to use in the railway and other
activities produced an environment degradation process.
Later on the autochthonous population followed the irrational
wood extraction an over pasture as "modus vivendi"
contributing to make the situation worse. Actually the farms
and big single-crop exploitations in some locations do not
give solution to the desertification problem. Only one integral
plan considering all factors involved and the differences
among sub zones will be an initial point to change the
direction of the desertification process.
A. Criteria, alternatives and Sub zones
The following eight criteria were defined:
Water erosion (WE): The water erosion is important. The
relative water erosion indexes figures in the decisional
matrix.
Eolian erosion (EE): Winds erode, transport and deposit
materials and are effective agents in several areas of this
region.
Implementation Facility (IF): They have been established
taking into account actors’ opinions.
Water Resources (WR): By each alternative have been
considered and the relative results have been taken into this
criterion.
Economical benefits EB): The relative economical benefits
using each alternative in a period of 25 years have been
obtained as shown in the matrix with figures from 1 to 10.
Hand power (HP): We have considered that would be
satisfactory to give employment to the majority of it
population. For that, we have considered this criterion as of
“more is better” kind.
Environmental Impacts (EI): They have been considered in
each sub zone the environmental impacts according with the
alternative adopted.
Social Acceptance (SA): The figures included in this
criterion have been obtained from the results of different
forums and meeting with institutions, organizations and
native people.
Five alternatives have been retained:
A) Autochthonous forest: mainly “Quebracho Blanco” and
“Quebracho Colorado” forest species.
B) High value forest: mainly teak, ebony, walnut tree, cherry
tree, lignum vitae, eucalyptus, etc
C) Traditional farms with extensive agriculture and
livestock mixed with autochthonous forest modified and
several foraging plants.
D) Erosion control Crop with agriculture use.
E) Erosion control crop with industrial use (biomass).
Following the experience and the local acknowledge, the area
has been divided in 6 sub zones: Las Lajitas, La Estrella,
Pichanal, Martin Hickmann, Rivadavia banda sur and Joaquín
V. Gonzalez.
II. METHODOLOGY
We have used the Preference Ranking Organization Method
(The PROMETHEE Method for Multiple Criteria Decision-
Making) by Ref. [4, 13, 14]. This is an outranking method, as
516978-1-4244-3760-3/09/$25.00 c 2009 IEEE
2. ELECTRE due to Roy [11, 12] or A.H.P. due to Saaty [15,
16, 17]. Following Ref. [4, 13, 14] two possibilities are
offered, PROMETHEE I provides a partial preorder and
PROMETHEE II a total preorder on the set of possible
alternatives. Different types of criteria have been adopted.
Type I and Type III with different threshold (m). Type I is the
usual Criterion. With this criterion if f(a) = f(b) this is
indifference between a and b. If this is not the case the
decision-maker has a strict preference for the action having
greatest value. Type III is the Criterion with Linear
Preference. Such an extension of the notion of criterion
allows the decision-maker to prefer progressively a to b for
progressively larger deviations between f(a) and f(b). The
preference increases linearly until deviation equals m, after
this value the preference is strict. For m the values 2, 4 and 6
have been taken.
The authors have modified the PROMETHEE method using
the weights of the criteria following the ELECTRE I Method
[6, 1, 2, 3, 7, 8, 9, 10]. In the case I have been adopted the
same weights for all sub zones and in the case II different
weights
Besides, some modifications have been considered in the data
of the initial matrixes.
Finally, MathCad has been used to program the calculus.
We show below, like example, the application to sub zone
"La Estrella".
EROSION AND DESERTIFICATION INTEGRAL CONTROL PLAN USING PROMETHEE
1( )SUB ZONE LA ESTRELLA ORIGIN 1
CRITERION: 1.-water erosion index 2.- eolian erosion index, 3.- Implementation
facility 4.-Water Resources, 5.- Economical Benefits, 6.- Hand power,
7.-Environmental Impacts, 8.- Social Acceptance
Indice Isubj:
más es mejor Isubj = 1
más es peor Isubj = -1
alternatives i
1 2 3 4 5
t
7
6
1
8
5
2
8
6
7
6
5
4
5
9
6
5
3
3
6
4
8
9
3
9
2
2
6
4
5
6
5
6
3
2
8
5
8
6
4
8
W
0.20
0.15
0.15
0.10
0.10
0.10
0.10
0.10
I
1
1
1
1
1
1
1
1
Alternatives:
i = 1 ....5 . with x >= 0, if not with |x|
A- functions of criterion-parameter and type elected for each criterion j:
following Ref. [4]
j = 1 type III, m=2, j = 2 type III, m=4, j=3 type III, m=4, j=4 type I j = 5 type I ,
j = 6 type III, m=6 , j=7 type III,m=6 j=8 type III, m=2
p1 x( ) if x 2
x
2
, 1,
p2 x( ) if x 4
x
4
, 1,
p4 x( ) if x 0 0, 1,( )
p3 x( ) if x 6
x
6
, 1,
p j x,( ) y x
z p1 y( ) j 1if
z p2 y( ) j 2if
z p2 y( ) j 3if
z p4 y( ) j 4if
z p4 y( ) j 5if
z p3 y( ) j 6if
z p3 y( ) j 7if
z p1 y( ) j 8if
z
x 8 7.9, 8..
10 5 0 5 10
0
0.5
1
p 2 x,( )
x
With this outranking graph,
functión of preference adopted:
P i ii, j,( ) if Ij
tj i,
tj ii,
. 0 0, p j tj i,
tj ii,
,,
A.- Results following initial methods of Ref [4]:
Índixes q(i,ii) of preferences (π(i,ii) Brans&Vincke),
giving outranking graphs according with values:
q i ii,( )
1
8
j
P i ii, j,( )
=
8
i 1 5.. ii 1 5.. qqi ii,
q i ii,( )
qq
0
0.25
0.5
0.208
0.458
0.229
0
0.281
0.094
0.469
0.448
0.281
0
0.042
0.208
0.438
0.333
0.406
0
0.5
0.458
0.354
0.156
0.021
0
=
Outgoing flow: fp i( )
1
5
ii
q i ii,( )
=
fppi
fp i( )
fpp
1.573
1.219
1.344
0.365
1.635
=
fm i( )
1
5
ii
q ii i,( )
=
fmmi
fm i( ) fmm
1.417
1.073
0.979
1.677
0.99
=
Incoming flow:
PROMETHEE II (clasification of alternatives by Total Preorder,
Each alternative obtain one value(more is better):
fd i( ) fp i( ) fm i( ) fddi
fd i( ) fdd
0.156
0.146
0.365
1.313
0.646
=
PROMETHEE I (clasification of alternatives by Partial Preorden):
pr i ii,( ) z 1
z 0 fp i( ) fp ii( )( ) fm i( ) fm ii( )( ).if
z 1 fp i( ) fp ii( )>( ) fm i( ) fm ii( )<( ).( ) fp i( ) fp ii( )>( ) fm i( ) fm ii( )( ).( ) fp i( ) fp ii( )( ) fm i( ) fm ii( )<( ).( )if
prri ii,
pr i ii,( )
Alternative E is preferred (E C A B D).
prr
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
=
B Results following the method modified by Ref [6] in order to weigh comparativment the criteria
with similar weights to ELECTRE-I:
q Preference Index (π Ref. [4]), gives outranking graph by values:
q i ii,( )
1
8
j
P i ii, j,( ) Wj
.
=
qqi ii,
q i ii,( ) 5.
i 1 5.. ii 1 5..
qq
0
1.25
2.25
1.083
2.083
0.917
0
1.188
0.438
2.063
2.479
1.813
0
0.167
0.958
2.5
2.083
1.938
0
2.375
2.583
2.167
0.688
0.083
0
=
:Outgoing flow: fp i( )
1
5
ii
q i ii,( )
=
fppi
fp i( )
fpp
1.696
1.463
1.213
0.354
1.496
=
Incoming flow: fm i( )
1
5
ii
q ii i,( )
=
fmmi
fm i( ) fmm
1.333
0.921
1.083
1.779
1.104
=
PROMETHEE II (clasification of alternatives by Total Preorder)
fd i( ) fp i( ) fm i( ) fddi
fd i( ) fdd
0.363
0.542
0.129
1.425
0.392
=
PROMETHEE I (clasification of alternatives by Partial Preorden):
pr i ii,( ) z 1
z 0 fp i( ) fp ii( )( ) fm i( ) fm ii( )( ).if
z 1 fp i( ) fp ii( )>( ) fm i( ) fm ii( )<( ).( ) fp i( ) fp ii( )>( ) fm i( ) fm ii( )( ).( ) fp i( ) fp ii( )( ) fm i( ) fm ii( )<( ).( )if
where, pr(i,ii) = 1 tell us that alternative i is preference (outranks) to alternative j, pr(i,ii) = 0 is
indifference, y pr(i,ii) = -1 are incomparable, that may be obtained by pr(ii,i) .
prri ii,
pr i ii,( )
prr
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
= Alternative B is preferred (B E A C D).
2009 7th IEEE International Conference on Industrial Informatics (INDIN 2009) 517
3. III. RESULTS
1. Sub zone Martin Hickman
1.1. ALTERNATIVE1:
Table I shows the values to Martin Hickman sub-zone. It has
been included the type of pseudo-criteria used and the
threshold (m) for the type III [4].
TABLE I
DECISIONAL MATRIX FOR MARTIN HICKMAN, ALTERNATIVE 1
Alternative WE EE IF WR EB HP EI SA
A 9 8 5 8 7 2 8 2
B 7 5 7 5 6 8 6 5
C 4 2 8 4 8 8 1 9
D 3 3 6 4 6 7 5 6
E 3 3 2 6 8 6 5 8
Weight 0,2 0,2 0,05 0,1 0,1 0,1 0,15 0,1
Type of criterion III III III I I III III III
Thresholds 2 4 4 2 2 4
Two procedures have been applied in order to obtain
alternative preorder:
A: Initial method of Ref. [4].
B: Method modified by Ref. [6].
1.1.A. Results by Ref. [4] method. The preorder is shown in
Fig. 1.
A B C E D
Fig. 1 Graph sub zone Martin Hickman, alternative 1.1A, Promethee II.
1.1. B Results following Ref. [9] method are shown in Fig. 2.
A B E C D
Fig. 2: Graphs sub zone Martin Hickman 1.1B Promethee II, modified.
1.2 ALTERNATIVE 2: Other value of criteria, same weight,
pseudocriteria and thresholds (Table II andy Fig. 3 and 4).
TABLE II
DECISIONAL MATRIX FOR MARTIN HICKMAN, ALTERNATIVE 2.
Alternative WE EE IF WR EB HP EI SA
A 9 8 5 8 7 7 8 2
B 7 5 7 5 8 8 6 5
C 7 5 8 4 8 8 6 9
D 3 3 6 4 6 7 5 6
E 3 3 8 6 8 6 5 8
Weight 0,2 0,2 0,05 0,1 0,1 0,1 0,15 0,1
Type of criterion III III III I I III III III
Thresholds 2 4 4 2 2 4
1.2. A. Results by method of Ref. [4] method. The preorder
is shown in Fig. 3.
C A B E D
Fig. 3: Graphs sub zone Martin Hickman, alternative 1.2.A . Promethee II
1.2. B. Results following Ref [9] method are shown in Fig. 4.
A C B E D
Fig. 4: Graphs sub zone Martin Hickman, alternative 1.2.B. Promethee II,
modified.
Changing the weights (0,2 – 0,15 – 0,15 – 0,10 – 0,10 – 0,10
– 0,10 – 0,10), the results are:
1.1.A
A B C E D
1.1.B
A B C E D
1.2.A
C A B E D
1.2.B
A C B E D
2. Sub zone LA ESTRELLA
2.1. ALTERNATIVE 1: Decisional matrix is shown in Table
III.
TABLE III
DECISIONAL MATRIX FOR LA ESTRELLA, ALTERNATIVE 1.
Alternative WE EE IF WR EB HP EI SA
A 7 6 1 8 5 2 8 6
B 7 6 5 4 5 9 6 5
C 3 3 6 4 8 9 3 9
D 2 2 6 4 5 6 5 6
E 3 2 8 5 8 6 4 8
Weight 0,15 0,15 0,15 0,1 0,15 0,1 0,1 0,1
Type of criterion III III III I I III III III
Thresholds 2 4 4 6 6 2
2.1A. Results by Ref [4] method. The preorder is shown in
Fig. 5.
E C A B D
Fig. 5: Graph sub zone La Estrella alternative 2.1A Promethee II
2.1B. Results following Ref [6] method are shown in Fig. 6.
E C B A D
Fig. 6: Graphs sub zone La Estrella alternative 2.1B Promethee II, modified.
2.2. ALTERNATIVE 2: Changing some criteria values and
maintaining weights (Table IV).
TABLE IV
DECISIONAL MATRIX FOR LA ESTRELLA, ALTERNATIVE 2.
Alternative WE EE IF WR EB HP EI SA
A 7 6 5 8 5 6 8 6
B 7 6 5 4 5 9 6 5
C 3 3 6 4 8 9 3 9
D 2 2 6 4 5 6 5 6
E 3 2 8 5 8 6 4 8
Weight 0,15 0,15 0,15 0,1 0,15 0,1 0,1 0,1
Type of criterion III III III I I III III III
Thresholds 2 4 4 6 6 2
2.2A. Results by Ref. [4] method. The preorder is shown in
Fig. 7.
A E C B D
Fig. 7: Graph sub zone La Estrella, alternative 2.2A, Promethee II.
2.2B.Results following Ref [6] method is shown in Fig. 8.
A E C B D
Fig. 8: Graph sub zone La Estrella alternativa 2.2B, Promethee II modified.
Changing weights (0,20 – 0,15 – 0,15 – 0,10 – 0,10 – 0,10 –
0,10 – 0,10) the results are:
2.1.A
E C A B D
518 2009 7th IEEE International Conference on Industrial Informatics (INDIN 2009)
4. 2.1.B
B E A C D
2.2.A
A E C B D
2.2.B
A B E C D
3. Sub zone RIVADAVIA SUR
3.1. ALTERNATIVA 1: Initial matrix is shown in Table V.
TABLE V
DECISIONAL MATRIX FOR RIVADAVIA SUR, ALTERNATIVE 1.
Alternative WE EE IF WR EB HP EI SA
A 8 5 1 9 5 7 9 6
B 6 6 6 5 5 8 6 5
C 3 2 2 4 8 9 1 9
D 2 2 5 4 6 7 5 6
E 3 3 8 5 8 6 4 8
Weight 0,25 0,1 0,1 0,05 0,1 0,1 0,2 0,1
Type of criterion III III III I I III III III
Thresholds 2 4 4 2 2 4
3.1A. Results following Ref [4] method is shown in Fig. 9.
E A B C D
Fig. 9: Graph sub zone Rivadavia Sur, alternative 3.1A, Promethee II.
3.1B. Results following Ref. [6] method in Fig. 10.
A B E C D
Fig. 10: Graph sub zone Rivadavia Sur, alternative 3.1B, Promethee II,
modified.
3.2. ALTERNATIVE 2: Changing some criteria values and
maintaining weights (Table VI).
TABLE VI
DECISIONAL MATRIX FOR RIVADAVIA SUR, ALTERNATIVE 2.
Alternative WE EE IF WR EB HP EI SA
A 8 5 6 9 5 7 9 6
B 6 6 6 5 5 8 6 5
C 3 2 2 4 8 9 1 9
D 2 2 5 4 6 7 5 6
E 3 3 8 5 8 6 4 8
Weight 0,25 0,1 0,1 0,05 0,1 0,1 0,2 0,1
Type of criterion III III III I I III III III
Thresholds 2 4 4 2 2 4
3.2A. Results following Ref. [4] method in shown in Fig. 11.
A E B C D
Fig. 11: Graph sub zone Rivadavia Sur, alternative 3.2A, Promethee II.
3.2B. Results following Ref. [6] is in Fig. 12.
A B E C D
Fig. 12: Graph sub zone Rivadavia Sur, alternative 3.2B, Promethee II,
modified.
Changing weights (0,2 – 0,15 – 0,15 – 0,10 – 0,10 – 0,10 –
0,10 – 0,10) the results are:
3.1.A
E A B C D
3.1.B
A B E C D
3.2.A
A E B C D
3.2.B
A B E C D
4. Sub zone PICHANAL
4.1. ALTERNATIVE 1: Initial matrix is shown in Table VII.
TABLE VII
DECISIONAL MATRIX FOR PICHANAL, ALTERNATIVE 1.
Alternative WE EE IF WR EB HP EI SA
A 6 6 1 7 5 2 8 2
B 6 5 4 4 5 8 6 5
C 3 2 9 4 8 9 1 9
D 2 2 6 4 5 7 5 6
E 3 2 8 5 8 6 4 8
Weight 0.20 0.15 0.10 0.10 0.20 0.05 0.05 0.15
Type of criterion III III III I I III III III
Thresholds 2 2 4 4 2 2 4
4.1A. Results following Ref. [4] is shown in Fig. 13.
E C B A D
Fig. 13: Graph sub zone Pichanal, alternative 4.1A, Promethee II.
4.1B. Results following Ref [6] is shown in Fig. 14.
E C A B D
Fig. 14: Graph sub zone Pichanal, alternative 4.1B, Promethee II, modified.
4.2. ALTERNATIVE 2: With other values same weights
(Table VIII).
TABLE VIII
DECISIONAL MATRIX FOR PICHANAL, ALTERNATIVE 2.
Alternative WE EE IF WR EB HP EI SA
A 6 6 5 7 5 7 8 2
B 6 5 4 4 5 8 6 5
C 5 2 9 4 8 9 1 9
D 2 2 6 4 5 7 5 6
E 3 2 8 5 8 6 4 8
Weight 0.20 0.15 0.10 0.10 0.20 0.05 0.05 0.15
Type of criterion III III III I I III III III
Thresholds 2 2 4 4 2 2 4
4.2A. Results following Ref [4] is in Fig. 15.
C A E B D
Fig. 15: Graph sub zone Pichanal, alternative 4.2A, Promethee II.
4.2B. Results following Ref [4] is shown in Fig. 16.
C E A B D
Fig. 16: Graph sub zone Pichanal, alternative 4.2B, Promethee II, modified.
With other weights (0,2 – 0,15 – 0,15 – 0,10 – 0,10 – 0,10 –
0,10 – 0,10) the results are:
4.1.A
E C B A D
4.1.B
E B C A D
4.2.A
C A E B D
4.2.B
A C E B D
5. Sub zone JOAQUIN V. GONZALEZ
5.1. ALTERNATIVE 1: Initial matrix is shown in Table IX.
2009 7th IEEE International Conference on Industrial Informatics (INDIN 2009) 519
5. TABLE IX
DECISIONAL MATRIX FOR JOAQUIN V. GONZÁLEZ, ALTERNATIVE 1.
Alternative WE EE IF WR EB HP EI SA
A 6 6 1 7 7 2 9 2
B 6 5 6 4 7 8 6 5
C 3 4 9 4 8 9 4 9
D 2 2 7 4 5 7 5 6
E 3 2 8 4 8 6 4 8
Weight 0,2 0,15 0,1 0,1 0,15 0,1 0,1 0,1
Type of criterion III III III I I III III III
Thresholds 2 4 4 2 2 4
5.1A. Results following Ref. [4] is shown in Fig. 17.
C B E A D
Fig. 17: Graph sub zone Joaquin V. Gonzalez, alternative 5.1A, Promethee
II.
5.1B. Results following Ref. [6] is in Fig. 18.
C B A E D
Fig. 18: Graph sub zone Joaquin V. Gonzalez, alternative 5.1B, Promethee II,
modified.
5.2. ALTERNATIVE 2: Other values and same weights
(Table X).
TABLE X
DECISIONAL MATRIX FOR JOAQUIN V. GONZÁLEZ, ALTERNATIVE 2.
Alternative WE EE IF WR EB HP EI SA
A 6 6 3 7 7 4 9 2
B 6 5 6 4 7 8 6 5
C 5 4 9 4 8 9 4 9
D 2 2 7 4 5 7 5 6
E 3 2 8 4 8 6 4 8
Weight 0,2 0,15 0,1 0,1 0,15 0,1 0,1 0,1
Type of criterion III III III I I III III III
Thresholds 2 4 4 2 2 4
5.2A. Results following Ref. [4] is shown in Fig. 19.
C B A E D
Fig. 19: Graph sub zone Joaquin V. Gonzalez, alternative 5.2A, Promethee
II.
5.2B. Results following Ref. [6] is in Fig. 20.
C A B E D
Fig. 20: Graph sub zone Joaquin V. Gonzalez, alternative 5.2B, Promethee II,
modified.
With other weights (0,2 – 0,15 – 0,15 – 0,10 – 0,10 – 0,10 –
0,10 – 0,10) the results are:
5.1.A
C B E A D
5.1.B
C B A E D
5.2.A
C B A E D
5.2.B
C B A E D
6. Sub zone LAS LAJITAS:
6.1. ALTERNATIVE 1: Initial matrix is shown in Table XI.
TABLE XI
DECISIONAL MATRIX FOR LAS LAJITAS, ALTERNATIVE 1.
Alternative WE EE IF WR EB HP EI SA
A 3 6 1 3 3 3 4 2
B 3 4 3 3 5 8 3 5
C 2 3 9 4 8 9 1 9
D 2 2 6 4 5 7 1 6
E 2 2 8 4 8 6 1 8
Weight 0,2 0,05 0,1 0,2 0,2 0,15 0,05 0,1
Type of criterion III III III I I III III III
Thresholds 2 4 4 6 6 2
6.1A. Results following Ref. [4] method is in Fig. 21.
C E D B A
Fig. 21: Graph sub zone Las Lajitas, alternative 6.1A, Promethee II.
6.1B. Results following Ref. [6] method is shown in Fig. 22.
C E D B A
Fig. 22: Graph sub zone Las Lajitas, alternative 6.1B, Promethee II,
modified.
6.2. ALTERNATIVE 2: Other values and same weights
(Table XII).
TABLE XII
DECISIONAL MATRIX FOR LAS LAJITAS, ALTERNATIVE 2.
Alternative WE EE IF WR EB HP EI SA
A 3 6 1 3 3 2 4 2
B 3 4 3 3 5 8 3 5
C 2 3 9 4 8 9 1 9
D 2 2 6 4 5 7 1 6
E 2 2 8 4 8 6 1 8
Weight 0,2 0,05 0,1 0,2 0,2 0,15 0,05 0,1
Type of criterion III III III I I III III III
Thresholds 2 4 4 6 6 2
6.2A. Results following Ref. [4] method is shown in Fig. 23.
C E D B A
Fig. 23: Graph sub zone Las Lajitas, alternative 6.2A, Promethee II.
6.2B. Results following Ref. [6] method is in Fig. 24.
C E D B A
Fig. 24: Graph sub zone Las Lajitas, alternative 6.2B, Promethee II,
modified.
Changing weights (0,2 – 0,15 – 0,15 – 0,10 – 0,10 – 0,10 –
0,10 – 0,10) the results are:
6.1.A
C E D B A
6.1.B
C E B D A
6.2.A
C E D B A
6.2.B
C E B D A
IV. CONCLUSIONS
Following the results mentioned above (Table XIII), we can
obtain as conclusions that the PROMETHEE method is a
very useful tool to elaborate a erosion control integral Plan. It
is robust as we have confirmed changing a little the relative
preference. Besides, with both methods similar results have
been obtained.
520 2009 7th IEEE International Conference on Industrial Informatics (INDIN 2009)
6. TABLE XIII
SUMMARY RESULTS OF PROMETHEE METHODS APPLICATION TO EROSION
CONTROL PLANS IN SALTA PROVINCE (ARGENTINE).
Subzone Martin
Hickman
La
Estrella
Rivadavia
Banda Sur
Pichanal J. V.
González
Las
LajitasMethod
PROMETHEE, applying variable weights in each sub zone
1.A A E E E C C
1.B A E A E C C
2.A C A A C C C
2.B A A A C C C
PROMETHEE, applying the same weights in each sub zone
1.A A E E E C C
1.B A B A E C C
2.A C A A C C C
2.B A A A A C C
Note: 1.A and 2.A : Following the initial method of Ref. [4], 1.B and 2.B:
Following method modified by the authors [6].
For this purposes, we would recommend to use Promethee II
modified using the ELECTRE I weights. Besides, with usual
criterion and type III pseudocriterion have been obtained the
best results. We could recommend to Salta Government the
following actions:
Las Lajitas: extensive farming and livestock. If it is only
farming it could be with crop rotation. The livestock should
be with natural forestry and foraging plants.
La Estrella: We can combine Autochthonous and high value
forestry with biomass production.
Pichanal: Similar to Las Lajitas.
Martin Hickman: Autochthonous forestry, combined with
some crop rotation and livestock like Las Lajitas.
Rivadavia Banda Sur: Similar to La Estrella.
Joaquin V. Gonzalez: Similar to Las Lajitas combined in
some areas with high value forestry.
ACKNOWLEDGMENT
We thank to “Agencia Española para la Cooperación
Internacional y el Desarrollo” (AECID) by the financing
support of the project A/013294/07 titled "ELABORACION
DE UN PLAN INTEGRAL DE LUCHA CONTRA LA
DESERTIZACION Y LA EROSION EN EL CHACO
SALTEÑO (ARGENTINA)"
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