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首页> 外文期刊>Water and environment journal: Journal of the Chartered Institution of Water and Environmental Management >Water quality-quantity management in river-reservoir system using sustainability-based simulation-optimization meta-model approach
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Water quality-quantity management in river-reservoir system using sustainability-based simulation-optimization meta-model approach

机译：水quality-quantity管理使用sustainability-based river-reservoir系统仿真优化模型的方法

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摘要

The present research, for the first time, introduces a sustainability-based water quality-quantity management model in the river-reservoir system. Vulnerability, resiliency, reliability and maximum deficit are the factors that have been considered in the Sustainability Index (S.I.). The two-dimensional hydrodynamics and water quality simulation model (CE-QUAL-W2) is linked to the multi-objective particle swarm optimization (MOPSO) to develop a simulation-optimization approach. Also, artificial neural network (ANN) model, substituted for the Ce-QUAL-W2 model, reduces the computational time in adaptive dynamically refined routine. The proposed methodology is applied to the Karkheh river-reservoir in Iran. The results showed that using ANN in an adaptive form, replacing CE-QUAL-W2, significantly impacts the computational time, considering accuracy in the developed simulation-optimization model. Moreover, using the S.I. greatly reduces both the severity of failure periods in the water quantity-quality and the sequence of failure periods.
机译：目前的研究中,第一次,介绍了一种sustainability-based水quality-quantity管理模式river-reservoir系统。弹性、可靠性和最大赤字的因素被考虑可持续发展指数(S.I.)。流体动力学和水质模拟模型(CE-QUAL-W2)是多目标有关粒子群优化(MOPSO)开发仿真优化方法。人工神经网络(ANN)模型,代替Ce-QUAL-W2模型,减少了在自适应动态计算时间精致的例行公事。应用于Karkheh river-reservoir伊朗。结果表明,使用安在一个自适应形式,取代CE-QUAL-W2,显著影响计算时间,考虑准确性开发了仿真优化模型。此外,使用S.I.大大减少了严重失败的时间在水里质量好坏和失败的序列期。

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