17 research outputs found

    Decision support model for the selection of asphalt wearing courses in highly trafficked roads

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    The suitable choice of the materials forming the wearing course of highly trafficked roads is a delicate task because of their direct interaction with vehicles. Furthermore, modern roads must be planned according to sustainable development goals, which is complex because some of these might be in conflict. Under this premise, this paper develops a multi-criteria decision support model based on the analytic hierarchy process and the technique for order of preference by similarity to ideal solution to facilitate the selection of wearing courses in European countries. Variables were modelled using either fuzzy logic or Monte Carlo methods, depending on their nature. The views of a panel of experts on the problem were collected and processed using the generalized reduced gradient algorithm and a distance-based aggregation approach. The results showed a clear preponderance by stone mastic asphalt over the remaining alternatives in different scenarios evaluated through sensitivity analysis. The research leading to these results was framed in the European FP7 Project DURABROADS (No. 605404).The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under Grant Agreement No. 605404

    A systematic review on the ecosystem services provided by green infrastructure

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    Urbanization and climate change are endangering the sustainability of public spaces through increased land artificialization, ecological fragmentation, reduced resource availability, and limited accessibility to natural and seminatural areas. Properly managing Green Infrastructure (GI) can contribute to mitigating these challenges by delivering multiple provisioning, regulating, supporting and cultural Ecosystem Services (ES). This would facilitate the implementation of strategically planned GI networks in cities for urban regeneration purposes. In this context, this study developed a systematic review on the ES provided by GI using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The analysis of 199 eligible articles indicated that more efforts should be made to address more ES at once, which connects to the need for conceiving GI as a strategically planned network of areas aimed at delivering diverse benefits. Based on the methods used in the items reviewed, geoprocessing tools and multi-criteria decision analysis are proposed to develop systems of indicators capable of accounting for multiple ES. These systems should also rely on multidisciplinary and participative procedures to encompass various facets of GI and represent the priorities of all relevant stakeholders

    Prediction of Evapotranspiration in a Mediterranean Region Using Basic Meteorological Variables

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    A critical need for farmers, particularly those in arid and semiarid areas is to have a reliable, accurate and reasonably accessible means of estimating the evapotranspiration rates of their crops to optimize their irrigation requirements. Evapotranspiration is a crucial process because of its influence on the precipitation that is returned to the atmosphere. The calculation of this variable often starts from the estimation of reference evapotranspiration, for which a variety of methods have been developed. However, these methods are very complex either theoretically and/or because of the large amount of parameters on which they are based, which makes the development of a simple and reliable methodology for the prediction of this variable important. This research combined three concepts such as cluster analysis, multiple linear regression (MLR), and Voronoi diagrams to achieve that end. Cluster analysis divided the study area into groups based on its weather characteristics, whose locations were then delimited by drawing the Voronoi regions associated with them. Regression equations were built to predict daily reference evapotranspiration in each cluster using basic climate variables produced in forecasts made by meteorological agencies. Finally, the Voronoi diagrams were used again to regionalize the crop coefficients and calculate evapotranspiration from the values of reference evapotranspiration derived from the regression models. These operations were applied to the Valencian region (Spain), a Mediterranean area which is partly semiarid and for which evapotranspiration is a critical issue. The results demonstrated the usefulness and accuracy of the methodology to predict the water demands of crops and hence enable farmers to plan their irrigation needs.This paper was possible thanks to the research project RHIVU (Ref. BIA2012-32463), financed by the Spanish Ministry of Economy and Competitiveness with funds from the State General Budget (PGE) and the European Regional Development Fund (ERDF). The authors also wish to express their gratitude to the Spanish Ministry of Agriculture, Food and Environment (MAGRAMA) for providing the data necessary to develop this study

    A review of modelling methodologies for flood source area (FSA) identification

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    Flooding is an important global hazard that causes an average annual loss of over 40 billion USD and affects a population of over 250 million globally. The complex process of flooding depends on spatial and temporal factors such as weather patterns, topography, and geomorphology. In urban environments where the landscape is ever-changing, spatial factors such as ground cover, green spaces, and drainage systems have a significant impact. Understanding source areas that have a major impact on flooding is, therefore, crucial for strategic flood risk management (FRM). Although flood source area (FSA) identification is not a new concept, its application is only recently being applied in flood modelling research. Continuous improvements in the technology and methodology related to flood models have enabled this research to move beyond traditional methods, such that, in recent years, modelling projects have looked beyond affected areas and recognised the need to address flooding at its source, to study its influence on overall flood risk. These modelling approaches are emerging in the field of FRM and propose innovative methodologies for flood risk mitigation and design implementation; however, they are relatively under-examined. In this paper, we present a review of the modelling approaches currently used to identify FSAs, i.e. unit flood response (UFR) and adaptation-driven approaches (ADA). We highlight their potential for use in adaptive decision making and outline the key challenges for the adoption of such approaches in FRM practises
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