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MILP for Optimizing Water Allocation and Reservoir Location: A Case Study for the Machángara River Basin, Ecuador

1
Department of Earth and Environmental Sciences, University of Leuven, 3001 Heverlee, Belgium
2
Department of Computer Sciences, University of Cuenca, EC010203 Cuenca, Ecuador
3
Flemish Institute for Technological Research–VITO, Boeretang 200, 2400 Mol, Belgium
4
Department of Mechanical Engineering, University of Leuven, 3001 Heverlee, Belgium
5
Geomatics Laboratory–Agricultural Sciences Faculty, University of Cuenca, EC010203 Cuenca, Ecuador
6
Department of Civil Engineering, University of Cuenca, EC010203 Cuenca, Ecuador
*
Author to whom correspondence should be addressed.
Water 2019, 11(5), 1011; https://doi.org/10.3390/w11051011
Received: 16 April 2019 / Revised: 7 May 2019 / Accepted: 10 May 2019 / Published: 14 May 2019
(This article belongs to the Special Issue Insights on the Water–Energy–Food Nexus)
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Abstract

The allocation of water flowing through a river-with-reservoirs system to optimally meet spatially distributed and temporally variable demands can be conceived as a network flow optimization (NFO) problem and addressed by linear programming (LP). In this paper, we present an extension of the strategic NFO-LP model of our previous model to a mixed integer linear programming (MILP) model to simultaneously optimize the allocation of water and the location of one or more new reservoirs; the objective function to minimize only includes two components (floods and water demand), whereas the extended LP-model described in this paper, establishes boundaries for each node (reservoir and river segments) and can be considered closer to the reality. In the MILP model, each node is called a “candidate reservoir” and corresponds to a binary variable (zero or one) within the model with a predefined capacity. The applicability of the MILP model is illustrated for the Machángara river basin in the Ecuadorian Andes. The MILP shows that for this basin the water-energy-food nexus can be mitigated by adding one or more reservoirs. View Full-Text
Keywords: MILP; LP; Network Flow Optimization Problem (NFOP); water allocation; reservoir optimization; Machángara MILP; LP; Network Flow Optimization Problem (NFOP); water allocation; reservoir optimization; Machángara
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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MDPI and ACS Style

Veintimilla-Reyes, J.; De Meyer, A.; Cattrysse, D.; Tacuri, E.; Vanegas, P.; Cisneros, F.; Van Orshoven, J. MILP for Optimizing Water Allocation and Reservoir Location: A Case Study for the Machángara River Basin, Ecuador. Water 2019, 11, 1011.

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