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Sci Total Environ ; 717: 137264, 2020 May 15.
Artículo en Inglés | MEDLINE | ID: mdl-32092809


Achieving the UN Sustainable Development Goals depends on using resources efficiently, avoiding fragmentation in decision-making, recognising the trade-offs and synergies across sectors and adopting an integrated Nexus thinking among policymakers. Nexus Informatics develops the science of recognising and quantifying nexus interlinkages. Nexus-coherent solutions enhance the effect of policymaking in achieving adequate governance, leading to successful strategic vision and efficient resource management. In this article, we present the structure of a System Dynamics Model-the Nexus_SDM-that maps sector-specific data from major databases (e.g., EUROSTAT) and scenario models (e.g., E3ME-FTT OSeMOSYS and SWIM) for the national case study of Greece. Disaggregation algorithms are employed on annual national-scale data, turning them into detailed spatial and temporal datasets, by converting them to monthly values spread among all 14 River Basin Districts (RBDs). The Nexus_SDM calculates Nexus Interlinkage Factors and quantifies interlinkages among Water, Energy, Food, Built Environment, Natural Land and greenhouse gas (GHG) emissions. It simulates the nexus in the national case study of Greece as a holistic multi-sectoral system and provides insights into the vulnerability of resources to future socio-economic scenarios. It calculates the link between crop type/area, irrigation water and agricultural value, revealing which crops have the highest agricultural value with the least water and crop area. It demonstrates that fossil fuel power generation and use of oil for transportation are responsible for the most GHG emissions in most RBDs and presents projections for years 2030 and 2050. The analysis showcases that to move from a general nexus thinking to an operational nexus concept, it is important to focus on data availability and scale. Advanced Sankey and Chord diagrams are introduced to show distribution of resource use among RBDs and an innovative visualisation tool is developed, the Nexus Directional Chord plot, which reveals Nexus hotspots and strong interlinkages among sectors, facilitating stakeholder awareness.

Water Sci Technol ; 62(7): 1479-90, 2010.
Artículo en Inglés | MEDLINE | ID: mdl-20935364


Artificial Neural Networks (ANNs) comprise a powerful tool to approximate the complicated behavior and response of physical systems allowing considerable reduction in computation time during time-consuming optimization runs. In this work, a Radial Basis Function Artificial Neural Network (RBFN) is combined with a Differential Evolution (DE) algorithm to solve a water resources management problem, using an optimization procedure. The objective of the optimization scheme is to cover the daily water demand on the coastal aquifer east of the city of Heraklion, Crete, without reducing the subsurface water quality due to seawater intrusion. The RBFN is utilized as an on-line surrogate model to approximate the behavior of the aquifer and to replace some of the costly evaluations of an accurate numerical simulation model which solves the subsurface water flow differential equations. The RBFN is used as a local approximation model in such a way as to maintain the robustness of the DE algorithm. The results of this procedure are compared to the corresponding results obtained by using the Simplex method and by using the DE procedure without the surrogate model. As it is demonstrated, the use of the surrogate model accelerates the convergence of the DE optimization procedure and additionally provides a better solution at the same number of exact evaluations, compared to the original DE algorithm.

Inteligencia Artificial , Redes Neurales de la Computación , Agua de Mar/análisis , Abastecimiento de Agua/estadística & datos numéricos , Algoritmos , Geografía , Grecia , Modelos Químicos