Application of exponential bandwidth harmony search with centralized global search for advanced nonlinear Muskingum model incorporating lateral flow

Young Hoon Kim
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Abstract

Muskingum, a hydrologic channel flood routing, is a method of predicting outflow by using the relationship between inflow, outflow, and storage. As many studies for Muskingum model were suggested, parameters were gradually increased and the calculation process was complicated by many parameters. To solve this problem, an optimization algorithm was applied to the parameter estimation of Muskingum model. This study applied the Advanced Nonlinear Muskingum Model considering continuous flow (ANLMM-L) to Wilson flood data and Sutculer flood data and compared results of the Linear Nonsingum Model incorporating Lateral flow (LMM-L), and Kinematic Wave Model (KWM). The Sum of Squares (SSQ) was used as an index for comparing simulated and observed results. Exponential Bandwidth Harmony Search with Centralized Global Search (EBHS-CGS) was applied to the parameter estimation of ANLMM-L. In Wilson flood data, ANLMM-L showed more accurate results than LMM-L. In the Sutculer flood data, ANLMM-L showed better results than KWM, but SSQ was larger than in the case of Wilson flood data because the flow rate of Sutculer flood data is large. EBHS-CGS could be appplied to be appplicable to various water resources engineering problems as well as Muskingum flood routing in this study.
指数带宽协调搜索与集中全局搜索在含横向流动的高级非线性Muskingum模型中的应用
Muskingum是一种水文通道洪水路线,是一种利用流入、流出和储存之间的关系来预测流出的方法。随着对Muskingum模型研究的增多,参数逐渐增多,计算过程因参数较多而变得复杂。为了解决这一问题,将一种优化算法应用于Muskingum模型的参数估计。本研究将考虑连续流的高级非线性Muskingum模型(ANLMM-L)应用于Wilson和Sutculer洪水数据,并比较了考虑横向流的线性非singum模型(LMM-L)和运动波模型(KWM)的结果。平方和(SSQ)作为比较模拟和观测结果的指标。将带集中全局搜索的指数带宽和谐搜索(EBHS-CGS)应用于ANLMM-L的参数估计。在Wilson洪水数据中,ANLMM-L的结果比LMM-L更准确。在Sutculer洪水数据中,ANLMM-L的效果优于KWM,但由于Sutculer洪水数据的流量较大,SSQ大于Wilson洪水数据。EBHS-CGS在本研究中可应用于各种水资源工程问题,也可应用于Muskingum的洪水调度。
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