实际工程中常采用抽水试验确定场地水文参数,但由于反演算法各异且缺少判定标准,往往无法证实其参数准确性。同时,由于各类算法本身局限性,在某些复杂水文模型的反演过程中需要不断调整参数以达到收敛精度。采用实测数据为天津市东丽区某场地抽水试验,根据当地水文地质环境采用Hantush-Jacob非稳定流越流模型进行计算。在反演计算过程中,通过引出有效流量概念以减少抽水井及观测井井管中水储量对试验产生的影响,利用多个观测井中实测水位降深与解析解合成目标函数,采用包括EKF算法(扩展Kalman滤波算法)、LM算法(Levenberg-Marquardt算法)及GA算法(遗传算法)3种最优化算法,对该场地的水文参数进行自动化反演。通过反演结果研究分析了3种算法在反演过程中其各自局限性。结果表明,采用GA算法与LM算法联合求解可在全局寻优并得到水文参数准确度较高,且利用该方法反演得到参数计算其他流量下场地水位降深,与实测对比效果较好。此外,在与已发表文献中采用的单一算法相比,GA算法与LM联合算法表现了其在水文参数反演方面的独特优势。
In practice engineering, it is commonly using pumping tests to determine hydraulic parameters, but the previous of estimated parameters cannot be proved due to the lack of unified standard and hard to choose a suitable algorithm. Meanwhile, due the limitation of independent algorithm, in some difficult hydraulic models, the engineers have to adjust parameters continually to meet the convergence criterion which cost lots of time and the accuracy of results cannot be proved. In this study, a series of pumping tests has been conducted in Dongli district of Tianjin city, China. With considering storage effect in the pumping wells and observation wells which has important impact in the early experiment, the effective ration has been proposed to eliminate the effect of well storage. Based on the local hydrogeological environment and measured drawdown, an unsteady leaky seepage model, called Hantush-Jacob model, is used to estimate hydraulic parameters. By combination of measured drawdown and analytical solution,three methods, extend Kalman filter algorithm, LM algorithm and Genetic algorithm, are all adopted to estimate hydraulic parameters in this study. According to the result, three algorithm all shows its limitation in the calculation. Thus, a combination of Genetic algorithm and LM algorithm has been proposed in this study. Based on the result, the combination algorithm shows its superiority in searching the optimal solution accurately and avoiding the defect of the three separate algorithm. According to the comparison, the measured drawdown fit well with the calculated drawdown based on the estimated hydraulic parameter. Furthermore, compared with the single algorithms used in previously published literature, the combined GA-LM algorithm has demonstrated its unique advantages in the inversion of hydrological parameters.
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