A Decision Tool for the Water-Energy Nexus in Jordan

2020 ◽  
Author(s):  
Mats Danielson ◽  
Love Ekenberg ◽  
Nadejda Komendantova
Keyword(s):  
Decision Support ◽  
Water Supply ◽  
Water Scarcity ◽  
Decision Support Tool ◽  
Support Tool ◽  
Water Energy Nexus ◽  
The World ◽  
Criteria Weights ◽  
Stakeholder Preferences ◽  
Water Scarce

Jordan is currently facing a serious problem of water scarcity. It is the fourth water-scarce country in the world. The sustainability of water supply in Jordan is affected not only by the depletion of water reserves but also by increasing electricity tariffs. In this paper, we present some results regarding the water-energy nexus governance in Jordan using a computer-supported co-creative approach for evaluating stakeholder preferences on criteria and possible scenarios of development for the sectors. We describe a decision support tool and a methodology for evaluating stakeholder preferences for both sectors and on possible scenarios of development for the water and energy sectors. We rank possible energy and water futures ranked under a set of sector-relevant criteria while considering entire ranges of possible alternative values and criteria weights. Using second-order probabilistic considerations, we furthermore analyse how plausible it is that a scenario outranks the others.

scholarly journals A decision support tool for rural water supply planning

2020 ◽  
Vol 10 (3) ◽  
pp. 447-457
Author(s):  
Joseph Cook ◽  
Jake Wagner ◽  
Gunnar Newell
Keyword(s):  
Decision Support ◽  
Water Supply ◽  
Current Model ◽  
Decision Support Tool ◽  
Community Members ◽  
Rural Water Supply ◽  
Support Tool ◽  
Rural Water ◽  
Supply Planning ◽  
Using Data

Abstract Over a dozen studies have examined how households who travel to collect water (about one-quarter of humanity) make choices about where and how much to collect. There is little evidence, however, that these studies have informed rural water supply planning in anything but a qualitative way. In this paper, we describe a new web-based decision support tool that planners or community members can use to simulate scenarios such as (1) price, quality, or placement changes of existing sources, (2) the closure of an existing source, or (3) the addition of a new source. We describe the analytical structure of the model and then demonstrate its possibilities using data from a recent study in rural Meru County, Kenya. We discuss some limits of the current model, and encourage readers and practitioners to explore it and suggest ways in which it could be improved or used most effectively.

scholarly journals A Decision Support Tool for Water Supply System Decentralization via Distribution Network Sectorization

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 642
Author(s):  
Oscar T. Vegas Niño ◽  
Fernando Martínez Alzamora ◽  
Velitchko G. Tzatchkov
Keyword(s):  
Decision Support ◽  
Water Supply ◽  
Industrial Development ◽  
Distribution Network ◽  
Network Models ◽  
Decision Support Tool ◽  
Supply System ◽  
Water Supply System ◽  
Water Supply Systems ◽  
Support Tool

Many water supply systems, conceived to operate in centralized manner, face difficulties to adapt to dynamic changes, such as population growth, city extension, and industrial development. Decentralization of these systems may be an effective solution. Known techniques for distribution network sectorization design can help to achieve such a goal, but this has not been recognized in the literature. None of those known techniques considers the conversion of a centralized system to a decentralized one. In this paper, two new distinct yet complementary methodologies for water supply system decentralization by distribution network sectorization are proposed and implemented in a software decision support tool freely available on internet. The first methodology identifies the main flow paths from water sources to some strategic nodes and considers the nodes in these paths as new potential sources for dividing the rest of the network. The second methodology sectorizes the network according to the contribution of sources to the consumption at nodes, based on mass balance equations for the transport of a hypothetical conservative constituent in a steady state. Both methods were applied to two real network models. The results obtained were better, for decentralizing the supply, compared to those obtained by other methodologies proposed in the literature.

Spatio-topological network analysis of hydrological infrastructure as a decision support tool for flood mitigation in coastal mega-cities

2016 ◽  
Vol 44 (4) ◽  
pp. 718-739 ◽  
Author(s):  
Robert Ogie ◽  
Tomas Holderness ◽  
Michelle Dunbar ◽  
Etienne Turpin
Keyword(s):  
Decision Support ◽  
Decision Support Tool ◽  
Water Levels ◽  
Decision Makers ◽  
Support Tool ◽  
Network Nodes ◽  
Topological Network ◽  
The World ◽  
Flooding Events ◽  
Mega Cities

Hydrological infrastructure components such as pumps, floodgates, and flood gauges are invaluable assets for mitigating flooding, which threatens millions of lives and damages property worth billions of dollars in coastal mega-cities around the world. By improving the understanding of how these hydrological infrastructure components are both spatially and topologically connected through waterways (rivers, canals, streams, etc.) within coastal mega-cities, more precise decisions can be made regarding the most appropriate hydrological infrastructure components required to mitigate flooding during emergency conditions. This paper explores the use of graph theory to create a spatio-topological model of a real world hydrological infrastructure network for one of the most representative coastal mega-cities—Jakarta, Indonesia. The network is modeled as a directed multigraph, with hydrological infrastructure represented as network nodes and waterways as edges. The article demonstrates how the network model can be used as a real-time decision support tool for responding to flooding events by alerting decision makers to the occurrence of rising water levels in any given area and, suggesting the most appropriate infrastructure components to engage in order to prevent a given area from flooding.

A Decision Support Tool for Evaluating Big Data Investment in Transport: Empirical evidence from European use cases of NOESIS project

2020 ◽  
Author(s):  
Christos Katrakazas ◽  
Natalia Sobrino ◽  
Ilias Trochidis ◽  
Jose Manuel Vassallo ◽  
Stratos Arampatzis ◽  
...  
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Empirical Evidence ◽  
Decision Support Tool ◽  
Use Cases ◽  
Support Tool
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