Holistic approach of GIS based Multi-Criteria Decision Analysis(MCDA) and WetSpass models to evaluate groundwater potential in Gelana watershed of Ethiopia

Appropriate quantification and identification of the groundwater distribution in a hydrological basin may provide necessary information for effective management,planning and development of groundwater resources.Groundwater potential assessment and delineation in a highly heterogeneous environment with limited Spatiotemporal data derived from Gelana watershed of Abaya Chamo lake basin is performed,using integrated multi-criteria decision analysis(MCDA),water and energy transfer between soil and plant and atmosphere under quasi-steady state(WetSpass)models.The outputs of the WetSpass model reveal a favorable structure of water balance in the basin studied,mainly using surface runoff.The simulated total flow and groundwater recharge are validated using river measurements and estimated baseflow at two gauging stations located in the study area,which yields a good agreement.The WetSpass model effectively integrates a water balance assessment in a geographical information system(GIS)environment.The WetSpass model is shown to be computationally reputable for such a remote complex setting as the African rift,with a correlation coefficient of 0.99 and 0.99 for total flow and baseflow at a significant level of p-value<0.05,respectively.The simulated annual water budget reveals that 77.22%of annual precipitation loses through evapotranspiration,of which 16.54%is lost via surface runoff while 6.24%is recharged to the groundwater.The calibrated groundwater recharge from the WetSpass model is then considered when determining the controlling factors of groundwater occurrence and formation,together with other multi-thematic layers such as lithology,geomorphology,lineament density and drainage density.The selected five thematic layers through MCDA are incorporated by employing the analytical hierarchy process(AHP)method to identify the relative dominance in groundwater potential zoning.The weighted factors in the AHP are procedurally aggregated,based on weighted linear combinations to provide the groundwater potential index.Based on the potential indexes,the area then is demarcated into low,moderate,and high groundwater potential zones(GWPZ).The identified GWPZs are finally examined using the existing groundwater inventory data(static water level and springs)in the region.About 70.7%of groundwater inventory points are coinciding with the delineated GWPZs.The weighting comparison shows that lithology,geomorphology,and groundwater recharge appear to be the dominant factors influence on the resources potential.The assessment of groundwater potential index values identify 45.88%as high,39.38%moderate,and 14.73%as low groundwater potential zones.WetSpass model analysis is more preferable in the area like Gelana watershed when the topography is rugged,inaccessible and having limited gauging stations.

Ranking environmental projects model based on multicriteria decision-making and the weight sensitivity analysis

With the fast growth of Chinese economic, more and more capital will be invested in environmental projects. How to select the environmental investment projects （alternatives） for obtaining the best environmental quality and economic benefits is an important problem for the decision makers. The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria. A model for ranking the projects of municipal sewage treatment plants is proposed by using exports＇ information and the data of the real projects. And, the ranking result is given based on the PROMETHEE method. Furthermore, by means of the concept of the weight stability intervals （WSI）, the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed. The result shows that some criteria, such as “proportion of benefit to project cost”, will influence the ranking result of alternatives very strong while others not. The influence are not only from the value of criterion but also from the changing the weight of criterion. So, some criteria such as “proportion of benefit to project cost” are key critera for ranking the projects. Decision makers must be cautious to them.

Decision variables analysis for structured modeling

Structured modeling is the most commonly used modeling method, but it is not quite addaptive to significant changes in environmental conditions. Therefore, Decision Variables Analysis(DVA), a new modelling method is proposed to deal with linear programming modeling and changing environments. In variant linear programming , the most complicated relationships are those among decision variables. DVA classifies the decision variables into different levels using different index sets, and divides a model into different elements so that any change can only have its effect on part of the whole model. DVA takes into consideration the complicated relationships among decision variables at different levels, and can therefore sucessfully solve any modeling problem in dramatically changing environments.

A Risk-Based Multi-Criteria Decision Analysis Approach to Evaluating Transboundary Water Development—The Case of Lower Mekong River Basin

The Lower Mekong River basin (LMB) covers the lower part of the Mekong river basin, including Laos, Thailand, Cambodia and Vietnam. Due to numerous pressures from high population growth and intensive hydropower development, the LMB has been facing significant challenges concerning its biodiversity and ecosystem. In 2017, Mekong River Commission (MRC), an intergovernmental organisation founded in 1995 among LMB countries, established the Council Study, which analysed the impacts of water development scenarios concerning the environmental, socioeconomic aspects of the LMB. This paper explores the nature of risks to the LMB water development and subsequently evaluates LMB’s water development scenarios described in the Council Study by using a multi-criteria decision analysis (MCDA) method. MCDA method has been widely applied in the field of water resource management in order to assist the decision-making process by systematically evaluating a certain number of alternatives against well-selected criteria through a preference rating scheme. By implementing a risk-based comprehensive assessment of the LMB transboundary water, this study provides insights into the impacts of the increasing risks to the ecosystem and human beings on the water development of the basin over time, which assists to change the awareness and the perspective toward humans’ risks and transboundary river ecosystem of decision-makers. This paper provides valuable recommendations for MRC to improve their policy concerning benefit-sharing scheme, water planning and risk mitigation strategies.

Multi-Criteria Decision Analysis for Usage Based Optimization of Powertrains

The electrification of powertrains leads to an increasing diversification of powertrain configurations. Each single configuration has its specific advantages which appear depending on the usage profile. To find the usage based optimal powertrain in consideration of a variety of evaluation criteria, the powertrains have to be optimized for the usage profile and characteristics have to be extracted from the usage profile. The carbon dioxide emissions of the optimized powertrains and usage based criteria are used in a multi-criteria decision analysis to determine the optimal powertrain for a specific usage profile. The description of characteristic maps forms the objective function of a minimization problem. The determined carbon dioxide emissions are one criterion in a multi-criteria decision process. All considered criteria are at least partly objective so that subjective ratings are eliminated as far as possible. The result is an optimized powertrain for a desired usage under the consideration of objective criteria that are extracted from the usage profile.

“AniFair”:A GUI Based Software Tool for Multi-Criteria Decision Analysis--An Example of Assessing Animal Welfare

Multi-criteria decision analysis deals with decision problems in which multiple criteria need to be considered. The criteria might be measured on different scales so that comparability is difficult. One approach to help the user to organize the problem and to reflect on his or her assessment on the decision is Measuring Attractiveness by a Categorical Based Evaluation TecHnique (MACBETH). Here the user needs to provide qualitative judgment about differences of attractiveness regarding pairs of options. MACBETH was implemented in the M-MACBETH software using the additive aggregation model. The present article introduces the software tool “AniFair” which combines the MACBETH approach with the Choquet integral as an aggregation function, because the Choquet integral enables the modeling of interaction between criteria. With the Choquet integral, the user can define constraints on the relative importance of criteria (Shapley value) and the interaction between criteria. In contrast to M-MACBETH, with every instance of “AniFair” the user is made available at least two aggregation level. “AniFair” provides Graphical User Interfaces for the entering of information. The software tool is introduced via an example from the Welfare Quality Assessment protocol for pigs. With this, “AniFair” is applied to real data that were collected from thirteen farms in Northern Germany by an animal welfare expert. The “AniFair” results enabled a division of the farms into five groups of comparable performance concerning the welfare principle “Good feeding”. Hereby, the results differed in how much the interaction between criteria contributed to the Choquet integral values. The shares varied from 5% to 55%. With this, the vulnerability of aggregation results towards relative importance of and interaction between criteria was stressed, as changes in the ranking due to the definition of constraints could be shown. All results were exported to human readable txt or csv files for further analyses, and advice could be given to the farmers on how to improve their welfare situation.

Travel modal choice analysis for traffic corridors based on decision-theoretic approaches

The rapid development of multimodal transportation system prompts travellers to choose multiple transportation modes, such as private vehicles or taxi, transit(subways or buses), or park-and-ride combinations for urban trips. Traffic corridor is a major scenario that supports travellers to commute from suburban residential areas to central working areas. Studying their modal choice behaviour is receiving more and more interests. On one hand, it will guide the travellers to rationally choose their most economic and beneficial mode for urban trips. On the other hand, it will help traffic operators to make more appropriate policies to enhance the share of public transit in order to alleviate the traffic congestion and produce more economic and social benefits. To analyze the travel modal choice, a generalized cost model for three typical modes is first established to evaluate each different travel alternative. Then, random utility theory(RUT) and decision field theory(DFT) are introduced to describe the decision-making process how travellers make their mode choices. Further, some important factors that may influence the modal choice behaviour are discussed as well. To test the feasibility of the proposed model, a field test in Beijing was conducted to collect the real-time data and estimate the model parameters. The improvements in the test results and analysis show new advances in the development of travel mode choice on multimodal transportation networks.

Benefit-Risk Assessment of Chinese Medicine Injections for Primary Liver Cancer Based on Multi-criteria Decision Analysis

ObjectiveTo evaluate the benefit-risk of 3 commonly used Chinese medicine injections, Aidi Injection (ADI), Cinobufagin Injection (CINI) and Compound Kushen Injection (CKI), in the treatment of primary liver cancer (PLC), so as to provide a reference for clinical decision-making.MethodsRandomized controlled trials (RCTs) of ADI, CINI and CKI in the treatment of PLC published in the databases of China National Knowledge Infrastructure, Wanfang, China Science and Technology Journal Database, SinoMed, PubMed, Cochrane Library, and Web of Science were retrieved from January 2020 to October 2022. The data of benefit and risk indicators were combined to obtain the effect value. The multi-criteria decision analysis (MCDA) model was applied to build the decision tree. The benefit value, risk value and benefit risk value of the 3 injections in PLC treatment were calculated. Monte Carlo simulation was carried out to calculate the 95% confidence interval and probability of differences among the 3 injections, so as to optimize the evaluation results.ResultsA total of 71 RCTs were included. The benefit values of ADI, CINI and CKI combined with transcatheter arterial chemoembolization (TACE) were 42, 38 and 36, respectively. The risk values were 42, 25 and 37, respectively. The benefit risk values were 42, 31 and 37, respectively. The benefit risk differences of ADI vs. CINI, ADI vs. CKI, and CKI vs. CINI were 11 (−0.86, 17.75), 5 (−5.01, 11.09), and 6 (−1.87, 12.63), respectively. The probability that ADI superior to CINI, ADI superior to CKI, and CKI superior to CINI was 96.26%, 77.27%, and 92.62%, respectively.ConclusionBased on the results of MCDA model, CINI combined with TACE has the greatest risk in the treatment of the PLC. Considering the efficacy and safety, the possible priority of the 3 Chinese medicine injections combined with TACE in the treatment of PLC is ADI, CKI and CINI.

Groundwater Exploration Using Multi Criteria Decision Analysis and Analytic Hierarchy Process in Federal Capital Territory, Abuja, Central Nigeria

There exists a growing demand for potable water resources to fill the abysmally insufficient water needs for domestic and industrial especially in the Basement Complex terrains of Nigeria. This situation is attributable to its complex hydrogeologic character. The present challenge has worsened due to the non-incorporation of integrated methods in groundwater exploration campaigns. To effectively combat the challenge of unacceptable failure rates in drilled water well development, there is a need for innovative scientific principles and quantitative assessment of groundwater resources to enhance sustainable and proper utilisation of these resources. Hence, it is the objective of this research to exploit the potential application of remote sensing, Geographic Information System (GIS), and Multi-Criteria Decision Analysis (MCDA) techniques and freely open datasets in mapping groundwater potential zones. Seven thematic maps have been produced based on factors that are deemed to influence and deemed to have significant control on the occurrence and movement of groundwater. These factors are geology, lineament density, slope, drainage density, rainfall, land-use/land cover, and soil class. Analytic Hierarchy Process (AHP) was used to assign normalised weights to the thematic maps based on the various relative contributions to groundwater occurrence and movement. These thematic maps were then processed in a GIS environment using the Weighted Overlay tool which implements the MCDA. The resulting Groundwater Potential Zones (GPZ) of the area gave rise to Five classes viz: Very good, Good, Moderate, Poor and Very Poor representing 19%, 8%, 14%, 47% and 13% respectively. It is recommended that the GPZ map should be used as a reconnaissance tool for selecting prospective sites for detailed groundwater resource exploitation.

A Decision Support System for Spatial Analysis of Agricultural Production in Madagascar

In this article, our research aims to set up a geo-decisional system, more precisely we are particularly interested in the spatial analysis system of agricultural production in Madagascar. For this, we used the spatial data warehouse technique based on the SOLAP spatial analysis tool. After having defined the concepts underlying these systems, we propose to address the research issues related to them from four points of view: needs study of the Malagasy Ministry of Agriculture, modeling of a multidimensional conceptual model according to the MultiDim model and the implementation of the system studied using GeoKettle, PostGIS, GeoServer, SPAGO BI and Géomondrian technologies. This new system helps improve the decision-making process for agricultural production in Madagascar.

Decision modelling for economic evaluation of liver transplantation

As the gap between a shortage of organs and the immense demand for liver grafts persists, every available donor liver needs to be optimized for utility, urgency and equity. To overcome this challenge, decision modelling might allow us to gather evidence from previous studies as well as compare the costs and consequences of alternative options. For public health policy and clinical intervention assessment, it is a potentially powerful tool. The most commonly used types of decision analytical models include decision trees, the Markov model, microsimulation, discrete event simulation and the system dynamic model. Analytic models could support decision makers in the field of liver transplantation when facing specific problems by synthesizing evidence, comprising all relevant options, generalizing results to other contexts, extending the time horizon and exploring the uncertainty. For modeling studies of economic evaluation for transplantation, understanding the current nature of the disease is crucial, as well as the selection of appropriate modelling techniques. The quality and availability of data is another key element for the selection and development of decision analytical models. In addition, good practice guidelines should be complied, which is important for standardization and comparability between economic outputs.

Suitability Analysis of Satellite Towns Using Saaty Model and Geographical Information System (GIS)

Dar es Salaam is one of the fastest growing cities in East Africa, with a population of 4,364,541 whose annual growth rate is 4.5%. The population increase is mainly caused by rural to urban migration causing traffic congestion, unemployment, emerging of unplanned settlements, inadequate infrastructure, and social and housing services. In order to overcome these challenges there is an urgent need to establish and determine suitable locations of satellite towns to the outskirts of the central business district (CBD) to strengthen economic and social activities using reliable techniques. Selecting suitable locations of satellite towns has been determined by using distance from the CBD and population growth indicators. The limitations of using these indicators include unsuitable locations, which ultimately failed to attract economic growth in such areas. In this study, we introduce a new approach of selecting suitable location of satellite towns in fast growing cities. This approach uses Saaty Model and Geographic Information Systems techniques, whereby a pair wise comparison matrix, consistency index and consistency ratio are employed to determine suitable locations of satellite towns in Ubungo and Kinondoni Municipalities. Also, seven criteria were used to produce suitability maps for water, power line, road, communication line, elevation, slope and land use. The results obtained from this study show that about 5.31% of the area was classified as highly suitable, 29.82% as moderately suitable, 24.27% as marginally suitable and 40.6% permanently unsuitable. Locations of satellite towns determined using Saaty model was found to be on highly suitable areas whereas locations of satellite towns proposed by the Dar es Salaam master plan were located on marginally suitable areas. The study concludes that Saaty Model, if integrated with GIS, can be effectively used to determine suitable locations for satellite towns in urban areas.

Global sensitivity analysis for choosing the main soil parameters of a crop model to be determined

The use of a crop model like STICS for appropriate management decision support requires a good knowledge of all the parameters of the model. Among them, the soil parameters are difficult to know at each point of interest and costly techniques may be used to measure them. It is therefore important to know which soil parameters need to be determined. It can be stated that those which affect significantly the output variable deserve an accurate determination while those which slightly affect the model output variable do not. This paper demonstrates how a global sensitivity analysis method based on variance decomposition can be applied on soil parameters in order to divide them in the two categories. The Extended FAST method applied to the crop model STICS and a set of 13 soil parameters first allows to calculate the part of variance explained by each soil parameter (giving global sensitivity indices of the soil parameters) and the coefficient of variation of the output variables (measuring the effect of the parameter uncertainty on each variable). These metrics are therefore used for deciding on the importance of the parameter value measurement. Different output variables (Leaf Area Index and chlorophyll content) are evaluated at different stages of interest while others (crop yield, grain protein content, soil mineral nitrogen) are evaluated at harvest. The analysis is applied on two different annual crops (wheat and sugar beet), two contrasted weather and two types of soil depth. When the uncertainty of the output generated by the soil parameters is large (coefficient of variation > 1/3), only the parameters having a significant global sensitivity indices (higher than 10%) are retained. The results show that the number of soil parameters which deserve an accurate determination can be significantly reduced by the use of this relevant method for appropriate management decision support.

Development and Application of Decision Support Model for the Performance Optimization of Office Buildings Based on Grasshopper

With the expansion of the office building area,the energy consumption of office buildings is growing.High⁃performance building design contributes to energy saving and the development of green buildings.However,there is a lack of high⁃performance building tools and the workflow is often time⁃consuming.The building performance simulation,multiple objective optimizations,and the decision support model are the new approaches of high⁃performance building design.This paper proposes a newly developed decision support model,a high⁃performance building decision model named HPBuildingDSM,which integrates the building performance simulation,building performance multiple objective optimizations,building performance sampling,and parameter sensitivity analysis to design high⁃performance office buildings.In this research,the HPBuildingDSM was operated to search for the desirable office building design results with low⁃energy and high⁃quality daylighting performances.The simulated results had better daylighting performance and lower energy consumption,whose UDI100-2000 was 37.94%and annual energy consumption performance was 76.28 kWh/(m2·a),indicating a better building performance than the optimized results in the previous case study.

Multi-Criteria Wildfire Risk Hazard Assessment in GIS Environment: Projection for the Future and Impact on RES Projects Installation Planning

It is alarming for the fact that Wildfires number, severity and consequently impact have significantly increased during the last years, an aftermath of the Climate Change. One of the most affected areas worldwide is Mediterranean, due to the unique combination of its type of vegetation and demanding climatic conditions. This research is focused on the Region of Epirus in Greece, an area with significant natural vegetation and a range of geomorphological aspects. In order to estimate the Wildfire Risk Hazard, several factors have been used: geomorphological (slope, aspect, elevation, TWI, Hydrographic network), social (Settlements and landfils, roads, overhead lines and substations), environmental (land cover) and climatic (Fire Weather Index). Through a multi-criteria decision analysis (MCDA) and an analytic hierarchy process (AHP) in a GIS environment, the Wildfire Risk Hazard has been estimated not only for current conditions but also for future projections for the near future (2031-2060) and the far future (2071-2100). The selected case study includes the potential impact of the Wildfires to the installed (or targeted to be installed) RES projects in the studied region.

A Multi-Criteria Decision Making for the Unrelated Parallel Machines Scheduling Problem

In this paper, we propose a multi-criteria machine-schedules decision making method that can be applied to a produc-tion environment involving several unrelated parallel machines and we will focus on three objectives: minimizing makespan, total flow time, and total number of tardy jobs. The decision making method consists of three phases. In the first phase, a mathematical model of a single machine scheduling problem, of which the objective is a weighted sum of the three objectives, is constructed. Such a model will be repeatedly solved by the CPLEX in the proposed Multi-Objective Simulated Annealing (MOSA) algorithm. In the second phase, the MOSA that integrates job clustering method, job group scheduling method, and job group – machine assignment method, is employed to obtain a set of non-dominated group schedules. During this phase, CPLEX software and the bipartite weighted matching algorithm are used repeatedly as parts of the MOSA algorithm. In the last phase, the technique of data envelopment analysis is applied to determine the most preferable schedule. A practical example is then presented in order to demonstrate the applicability of the proposed decision making method.

Sanitary Landfill Site Selection Using Multi-criteria Analysis Evaluation:Case Study of Dibra Region,Albania

Landfill is a common solution for the final disposal of MSW(Municipal Solid Waste)in Albania.Landfill sitting is an extremely difficult task to accomplish because the site selection process depends on different factors and regulations.To ensure that an appropriate site is chosen,a systematic process should be developed and followed.In this study,10 candidate sites for an appropriate landfill area in Dibra Region are determined by using the MCE(Multi-criteria Evaluation).From the application of the exclusion criteria provided in the study methodology,it was able to find the best three alternatives.The statistical processing for the determination of the best place was accomplished through MCA(Multi-criteria Analysis)and Environmental Management,for three scenarios with different weights of criteria.The application of this method has led to the identification of the most suitable site for the construction of sanitary landfill in the Dibra Region.

Spatial Analysis and Modelling of Wind Farm Site Suitability in Nasarawa State, North-Central Nigeria

There has been an increasing global and local interest in developing renewable, clean, and cheap energy towards achieving Goal number 7 of the Sustainable Development Goals (SDG). However, decisions involving suitable and sustainable locations for renewable energy projects remain an important task. This study employed Geographic Information System (GIS) and Multi-Criteria Decision Analysis (MCDA) to spatially analyze and model wind farm site suitability in Nasarawa State. The aim is to integrate the environmental, social, and economic aspects of decision-making for identifying sustainable wind farm sites. The study distinguished between two sets of decision criteria: decision constraints and decision factors. The former defined the exclusion zones while the latter were standardized based on fuzzy logic to depict varying degrees of suitability across the State. The MCDA applied the weighted linear combination method, with relative weights generated through pairwise comparisons of the analytic hierarchy process to analyze three policy scenarios: equal weights, environmental/social priority, and economic priority scenario. A combination of resulting composite maps from the constraints and the factors gave the final suitability maps. The resulting suitability index (SI) for the respective policy scenario describes the degrees of suitability: Ideal locations were denoted by one (1) and the not suitable locations by zero (0), with values in-between depicting varying degrees of wind farm site suitability. Based on the SI, priority locations indicating areas with good prospects, in addition to the most suitable parcels of land, were identified and delineated. The composite decision constraint revealed that wind farm projects would not be viable in more than half (57.58%) of the State. Wind speed was the major constraint and accounted for the exclusion of 46.25%, with a mean fuzzy membership value of 0.2008 indicating low suitability across the State. Also, the average acceptable wind farm location for the three-policy scenario was 33.33% of the entire study area. Lafia, Obi, Keana, Awe, Nasarawa-Eggon, Wamba and Kokona LGAs were the identified priority Local Government Areas (LGAs). However, only Lafia, Obi, and Nasarawa-Eggon were consistent with changes in the policy objectives. All the priority LGAs have one or more of the most suitable parcels within their administrative boundaries except for Wamba. Despite the severe limitations of wind speed, substantial parts of Nasarawa State still provide great development potentials for wind energy. The “most suitable” locations in Lafia, Nasarawa-Eggon, and Obi LGAs should have first consideration for the development of wind energy in the State.

基于Analysis Services的数据挖掘模型的研究与应用

SQL Server 2000 Analysis Services是一整套的决策支持引擎和工具。本文介绍了Analysis Services的体系结构,讨论了用其进行数据挖掘的方法。阐述了一个构建数据挖掘模型、训练挖掘模型以及应用该模型进行预测的实例。