Decision Support System Based on Genetic Algorithms to Optimize the Daily Management of Water Abstraction from Multiple
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Decision Support System Based on Genetic Algorithms to Optimize the Daily Management of Water Abstraction from Multiple Groundwater Supply Sources Rafael Gonzalez Perea, et al. [full author details at the end of the article] Received: 6 December 2019 / Accepted: 30 September 2020/ # Springer Nature B.V. 2020
Abstract
The use of irrigation water extracted from aquifers with submerged pumps is essential to ensure agricultural production mainly in water-scarce regions.. However, the use of the water source requires of a considerable energy consumption by water user associations (WUAs) being key factor to consider due to their high share of total management, operation, and maintenance costs. In this work, a new tool (MOPWE, model to optimize water extraction) to optimize the water and energy use of wells in WUAs was developed. MOPWE was applied to a real WUA located in Castilla-La Mancha region (southeast of Spain). This WUA utilizes groundwater as water source that is extracted from several different wells of different characteristics (discharges, water table levels, efficiency, variable speed drives…).. Therefore, these kind of WUAs must decide not only which well to activate at a certain time but also at what frequency the variable-speed drive should run the pump. With the aim of aiding decision-making in groundwater abstraction, a new management model (MOPWE), which is based on multi-objective genetic algorithms and is implemented in MATLAB®. This model helps determine the optimal daily management of a WUA with multiple underground supply sources and focuses on the management of wells while considering the water reservoir level. After 18,000 generations of the genetic algorithm, the pareto front was obtained with the best WUA managements achieving a water and energy savings of 25% and 54%, respectively. At the end of the irrigation season, the optimal total energy consumption per unit of water applied was 38% lower than that achieved by the current management. Results showed that a more realistic approach can be implemented when several water supplies operate jointly under a collaborative principle. Keywords Irrigation network . Water and energy optimization . Variable speed . Well . Water depth
1 Introduction Globally, irrigated agriculture is the primary use of freshwater, accounting for nearly 85% of total water consumption (Jury and Vaux 2007), ensuring food supply. One in three hectares of irrigated agriculture in the world is irrigated by groundwater, reaching a value of 67%, 58% and 45% of total irrigated agriculture in Algeria, Iran, and the USA, respectively (Carrión et al.
Perea R. et al.
2016). In the Castilla-La Mancha region (Spain), this source of water represents more than 65% of irrigation and urban water in this region (Moreno et al. 2010a, b). The growing demand for water in some sectors, such as industry, urban areas and agriculture, are leading to aquifer over-exploitation. Consequently, the optimization of the water-energy nexus in WUAs (as main consumer of this resource), particularly in
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