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A balanced calibration of water quantity and quality by multi-objective optimization for integrated water system model

机译:a balanced calibration of water quantity and quality by multi-objective optimization for integrated water system model

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摘要

Due to the high interactions among multiple processes in integrated water system models, it is extremely difficult, if not impossible, to achieve reasonable solutions for all objectives by using the traditional stepby-step calibration. In many cases, water quantity and quality are equally important but their objectives in model calibration usually conflict with each other, so it is not a good practice to calibrate one after another. In this study, a combined auto-calibration multi-process approach was proposed for the integrated water system model (HEQM) using a multi-objective evolutionary algorithm. This ensures that the model performance among inseparable or interactive processes could be balanced by users based on the Pareto front. The Huai River Basin, a highly regulated and heavily polluted region of China, was selected as a case study. The hydrological and water quality parameters of HEQM were calibrated simultaneously based on the observed series of runoff and ammonia-nitrogen (NH4-N) concentrations. The results were compared with those of the step-by-step calibration to demonstrate the rationality and feasibility of the multi-objective approach. The results showed that a Pareto optimal front was formed and could be divided into three clear sections based on the elastic coefficient of model performance between NH4-N and runoff, i.e., the dominated section for NH4-N improvement, the trade-off section between NH4-N and runoff, and the dominated section for runoff improvement. The trade-off of model performance between runoff and NH4-N concentration was clear. The results of the step-by-step calibration fell in the dominated section for NH4-N improvement, where just the optimum of the runoff simulation was achieved with a large potential to improve NH4-N simulation without a significant degradation of the runoff simulation. The overall optimal solutions for all the simulations appeared in the trade-off section. Therefore, the Pareto front provided different satisfactory solutions for users to choose according to their specific objectives. This study is expected to promote the application of multi-objective calibration in water system modeling, and provide scientific and technological supports for the implementation of integrated river basin management. (C) 2016 Elsevier B.V. All rights reserved.
机译:由于集成水系统模型中多个过程之间的高度交互作用,因此使用传统的逐步校准很难(即使不是不可能)为所有目标实现合理的解决方案。在许多情况下,水的数量和水质同等重要,但是它们在模型校准中的目标通常会相互冲突,因此,一个接一个地校准不是一个好习惯。在这项研究中,提出了一种使用多目标进化算法的综合自校准多过程方法用于综合水系统模型(HEQM)。这确保了用户可以基于Pareto前沿平衡不可分割或交互过程之间的模型性能。案例研究选择了淮河流域(中国高度管制,污染严重的地区)。根据观测到的一系列径流和氨氮(NH4-N)浓度,同时校准HEQM的水文和水质参数。将结果与逐步校准的结果进行比较,以证明多目标方法的合理性和可行性。结果表明,根据NH4-N与径流之间模型性能的弹性系数,形成了帕累托最优前沿,可以将其划分为三个清晰的区间,即NH4-N改善的主导区间,NH4-N改善的权衡区间。 NH4-N和径流,以及用于径流改善的主要部分。模型性能在径流和NH4-N浓度之间的权衡是显而易见的。逐步校准的结果落在主要部分,以改善NH4-N,在该区域中,仅实现了径流模拟的最佳选择,并具有很大的潜力来改善NH4-N模拟,而不会显着降低径流模拟。所有模拟的总体最佳解决方案出现在权衡部分。因此,帕累托阵线为用户提供了各种令人满意的解决方案,供用户根据其特定目标进行选择。该研究有望促进多目标标定在水系统建模中的应用,为实施流域综合管理提供科学技术支持。 (C)2016 Elsevier B.V.保留所有权利。

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