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Automatic Calibration of Water Quality and Hydrodynamic Model (CE-QUAL-W2)

机译:水质和水动力模型的自动校准(CE-QUaL-W2)

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摘要

One of the most important purposes of surface water resource management is to develop predictive models to assist in identifying and evaluating operational and structural measures for improving water quality. To better understand the effects of external and internal nutrient and organic loading and the effects of reservoir operation, a model is often developed, calibrated, and used for sensitivity and management simulations. The importance of modeling and simulation in the scientific community has drawn interest towards methods for automated calibration. This study addresses using an automatic technique to calibrate the water quality model CE-QUAL-W2 (Cole and Wells, 2013). CE-QUAL-W2 is a two-dimensional (2D) longitudinal/vertical hydrodynamic and water quality model for surface water bodies, modeling eutrophication processes such as temperature-nutrient-algae-dissolved oxygen-organic matter and sediment relationships. The numerical method used for calibration in this study is the particle swarm optimization method developed by Kennedy and Eberhart (1995) and inspired by the paradigm of birds flocking. The objective of this calibration procedure is to choose model parameters and coefficients affecting temperature, chlorophyll a, dissolved oxygen, and nutrients (such as NH4, NO3, and PO4). A case study is presented for the Karkheh Reservoir in Iran with a capacity of more than 5 billion cubic meters that is the largest dam in Iran with both agricultural and drinking water usages. This algorithm is shown to perform very well for determining model parameters for the reservoir water quality and hydrodynamic model. Implications of the use of this procedure for other water quality models are also shown.
机译:地表水资源管理的最重要目的之一是建立预测模型,以帮助识别和评估改善水质的操作和结构措施。为了更好地了解外部和内部养分和有机负荷的影响以及水库运行的影响,通常会开发,校准模型并将其用于敏感性和管理模拟。在科学界,建模和仿真的重要性引起了人们对自动校准方法的兴趣。本研究致力于使用自动技术校准水质模型CE-QUAL-W2(Cole和Wells,2013年)。 CE-QUAL-W2是用于地表水体的二维(2D)纵向/垂直水动力和水质模型,用于模拟富营养化过程,例如温度-营养-藻类-溶解氧-有机质和沉积物之间的关系。在这项研究中用于校准的数值方法是肯尼迪和埃伯哈特(1995)提出并受到鸟类聚集范例启发的粒子群优化方法。该校准程序的目的是选择影响温度,叶绿素a,溶解氧和养分(例如NH4,NO3和PO4)的模型参数和系数。提出了一个针对伊朗Karkheh水库的案例研究,该水库的容量超过50亿立方米,是伊朗最大的同时使用农业和饮用水的大坝。结果表明,该算法在确定储层水质和水动力模型的模型参数方面表现出色。还显示了将该程序用于其他水质模型的含义。

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    Shojaei Nasim;

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  • 年度 2014
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