地下水污染在我国已经相当严重。通过水质监测点快速准确的确定污染源排放强度及其动态变化具有重要意义。基于SCE-UA优化算法，通过将地下水流和溶质运移数值模型耦合到优化模型，数值模型模拟计算的结果作为约束条件返回到优化模型中，优化过程通过SCE-UA算法进行反射、收缩和突变3个过程求解。实例分析表明：①在足够种群进化代数条件下，优化模型可以有效反演污染源排放强度及其动态变化；②优化模型对多污染源分别在稳定流和非稳定流下、定浓度和不定浓度排放的反演均可以有效、 快速地搜索到全局最优解, 具有较强的优化性能。
Abstract
Groundwater pollution is a very serious problem in China. It is of great significance to fast and accurately identify characteristics of groundwater sources through monitor data. Based on SCE-UA optimization algorithm, for the structure of groundwater inverse problem, combines groundwater flow numerical model, solute transport numerical model and SCE-UA optimization algorithm and design an optimization model. The numerical models simulate solute transport in groundwater and produces constraint conditions and the solution can be obtained through reflection, contraction and mutation of SCE-UA algorithm. Case studies show that this S/O model: ① with sufficient evolution generations, optimization model can effectively and accurately determine groundwater contaminant characteristics; ② the proposed identification model can fast get globally optimal solutions both to multiple pollution sources under steady-state flow and transient flow conditions, constant concentration discharges and non-constant concentration discharges.
关键词
SCE-UA算法 /
优化模型 /
地下水数值模拟 /
污染源反演
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Key words
SCE-UA algorithm /
optimization model /
groundwater numerical simulation /
groundwater pollution identification
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