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ASSESSMENT OF RESILIENCE IN IRRIGATION NETWORKS USING OPTIMIZATION ALGORITHMS
* 1 , 2
1  Departamento de Ingeniería Civil, Universidad Técnica Particular de Loja, San Cayetano Alto 1101608, Ecuador
2  Dpto. de Ingeniería Hidráulica y Medio Ambiente, Universitat Politècnica de València, Camino de Vera, s/n 46022 Valencia, España
Academic Editor: Carmen Teodosiu

Abstract:

The world is facing increasing pressure over the water resources. One of the main water uses is agricultural irrigation. Therefore, the ever-increasing demand for food, coupled with the effects of climate change, is putting increasing pressure on the water resources used for irrigation. Traditional design methods used for irrigation networks only look for economical optimization. This study presents a methodology for the evaluation of the resilience of irrigation networks. It uses two indicators of resilience: RSYS and PHRI indicators. These indicators will be calculated for a pressurized irrigation network that was designed using an optimization method based on dynamic programming, known as the Granados optimization method. The network was operated using the on-demand scheme and the Clément's formulation for demands was used. The values of the supply guarantee (probability of non-exceedance) of the network were modified, allowing us to know its influence on the results of the indicators.

The decision variables in the design problem were the size of the pipes and the objective function, the capital cost of the project, etc. The methodology was applied to an irrigation network in Ecuador, and the resilience indicators at the level of both pressures and demands measured the behavior of the network in the face of disruptive events. The results of the research indicate that the implementation of resilience indicators in irrigation networks allows the irrigation network to be efficiently managed when the operational conditions differ from the design parameters. A suitable combination of economy and resilience during the design process can be an effective strategy when using optimization algorithms. This work evidences this statement.

Keywords: Resilience; Irrigation networks; Optimization algorithms; Indicators
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