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INTEGRATED MANAGEMENT OF RIVER WATER QUALITY UNDER UNCERTAINTY USING OPTIMIZATION MODEL

机译:优化模型在不确定性下的河流水质综合管理

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摘要

A multiobjective optimization model is developed to explore management alternatives on allocation of COD (Chemical Oxygen Demand) load issuing from point sources to outfalls on Yasu River, Japan. Uncertainty inherent in the water quality environment is accounted for with twelve scenarios corresponding to months in a year. Two measures of robustness based on the framework of robust optimization are introduced to control effects of variable and imperfect input data. Employment of Geographic Information System facilitates deriving catchment boundaries associated with the river, finding outlets of wastewater, and estimating uncontrollable discharge and COD load from nonpoint sources. A finite element model for COD and DO transport, contained as equality constraints in the optimization model, is calibrated using observed data in Yasu River. Other constraints of the optimization problem are effluent limitation standards for wastewater and water quality standards in the river. Five alternatives obtained by optimization are shown, which are advantageous over the current COD loading activity in conserving river water quality and/or increasing allowable COD load. The presented method could be applied to other river systems to assist decision-makers in evolving better policies on water quality management.
机译:建立了一个多目标优化模型,以探索在日本Yasu河上从点源到排污口分配COD(化学需氧量)负荷分配的管理替代方案。在水质环境中固有的不确定性可通过与一年中的几个月相对应的十二种情况进行解释。引入了基于鲁棒性优化框架的两种鲁棒性度量来控制变量和不完美输入数据的影响。地理信息系统的使用有助于推导与河流相关的集水区边界,寻找废水出口,并估计非点源的不可控制的排放量和化学需氧量。使用Yasu河中的观测数据,对优化模型中包含为等式约束的COD和DO传输的有限元模型进行了校准。优化问题的其他限制因素是河流废水排放限制标准和河流中的水质标准。显示了通过优化获得的五个替代方案,它们在保护河流水质和/或增加允许的COD负荷方面优于当前的COD负荷活动。所提出的方法可以应用于其他河流系统,以帮助决策者制定更好的水质管理政策。

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