An Agricultural Decision Support System for optimal land use regarding Groundwater Vulnerability

The availability of good quality water is worldwide a basic condition to pursue the socioeconomic development. The agriculture water demand can be damaged by contamination of groundwater resources. This paper proposes a tool to preserve the groundwater quality by using groundwater vulnerability assessment methods and a decision support system (DSS). Vulnerability map could be used for planning, policy, management, and contamination assessment. The mapping of intrinsic groundwater vulnerability was based on reliable methods, i.e., the DRASTIC and the SINTACS methods. A vulnerability map could be used for planning, policy, management, and contamination assessment. A DSS was developed in order to assess the groundwater vulnerability and pollution risk due to agricultural activities and land use changes. The proposed DSS software package was designed using the Matlab language. The software is a friendly application for everyone ranging from the novice user, e.g., a student, to an operations research scientist. It quickly and efficiently performs the task that is scheduled to carry out, and it can incorporate new maps in order to cover new areas. The tool was tested using two study areas located in the Mediterranean area. The test sites are dominated by different prevalent hydrogeological features, i.e., the typical porous features of alluvial deposits in the Greek study area and the typical fissured and karstic features of limestones and dolostones in the Italian study area.Published66-79N/A or not JCRrestricte

An agricultural decision support system for optimal land use regarding groundwater vulnerability

The availability of good quality water is worldwide a basic condition to pursue the socioeconomic development. The agriculture water demand can be damaged by contamination of groundwater resources. This paper proposes a tool to preserve the groundwater quality by using groundwater vulnerability assessment methods and a decision support system (DSS). Vulnerability map could be used for planning, policy, management, and contamination assessment. The mapping of intrinsic groundwater vulnerability was based on reliable methods, i.e., the DRASTIC and the SINTACS methods. A vulnerability map could be used for planning, policy, management, and contamination assessment. A DSS was developed in order to assess the groundwater vulnerability and pollution risk due to agricultural activities and land use changes. The proposed DSS software package was designed using the Matlab language. The software is a friendly application for everyone ranging from the novice user, e.g., a student, to an operations research scientist. It quickly and efficiently performs the task that is scheduled to carry out, and it can incorporate new maps in order to cover new areas. The tool was tested using two study areas located in the Mediterranean area. The test sites are dominated by different prevalent hydrogeological features, i.e., the typical porous features of alluvial deposits in the Greek study area and the typical fissured and karstic features of limestones and dolostones in the Italian study area.Published274-286ope

Preventing Overloading Incidents on Smart Grids: A Multiobjective Combinatorial Optimization Approach

Cable overloading is one of the most critical disturbances that may occur in smart grids, as it can cause damage to the distribution power lines. Therefore, the circuits are protected by fuses so that, the overload could trip the fuse, opening the circuit, and stopping the flow and heating. However, sustained overloads, even if they are below the safety limits, could also damage the wires. To prevent overload, smart grid operators can switch the fuses on or off to protect the circuits, or remotely curtail the over-producing/over-consuming users. Nevertheless, making the most appropriate decision is a daunting decision-making task, notably due to contractual and technical obligations. In this paper, we define and formulate the overloading prevention problem as a Multiobjective Mixed Integer Quadratically Constrained Program. We also suggest a solution method using a combinatorial optimization approach with a state-of-the-art exact solver. We evaluate this approach for this real-world problem together with Creos Luxembourg S.A., the leading grid operator in Luxembourg, and show that our method can suggest optimal countermeasures to operators facing potential overloading incidents

Preface to the Special Issue on Matheuristics and Metaheuristics

info:eu-repo/semantics/publishe