Data from pumping tests is a noisy process, and therefore, performing the pumping test numerous times will not get the same drawdown values. As a consequence, various pumping experiments lead to different values for aquifer parameter estimates. The data of pumping tests are usually analyzed using traditional methods (aquifer tests and AQtesolv software), which depend on trial and error technique. During these methods, non-unique values of hydraulic parameters are selected, which usually have a high level of uncertainty. Uncertainty must be taken into account in determining aquifer parameters, especially when using groundwater models for decision makers. The main goal of this study is to build a comprehensive tool for quantifying uncertainty associated with hydraulic parameter estimation from different pumping test conditions for fully penetrating wells in confined and semi-confined aquifers. To achieve the previous objective, a FORTRAN code was developed to apply the Markov Chain Monte Carlo (MCMC) algorithm using different likelihood functions (exponential, inverse, and log). This developed tool can be used to detect the most probable range of aquifer parameters that are consistent with pumping test data with a high degree of confidence. The tool was successfully used to several hypothetical cases to demonstrate the uncertainty in the quantification of aquifer parameters and compare the findings to the standard method's results. Also, the concept was verified numerically (using Modflow program) with satisfactory results using a hypothetical case with well-known aquifer parameters. Finally, the tool was applied for actual pumping test data with good results.

来自泵送测试的数据是一个嘈杂的过程，因此多次执行泵送测试将不会获得相同的下降值。因此，不同的抽水实验会导致含水层参数估计值不同。抽水测试的数据通常使用传统方法（含水层测试和AQtesolv软件）进行分析，这依赖于试错技术。在这些方法中，选择的水力参数的非唯一值通常具有高度的不确定性。在确定含水层参数时必须考虑不确定性，特别是在决策者使用地下水模型时。本研究的主要目标是建立一个综合工具，用于量化与承压和半承压含水层全渗透井的不同抽水测试条件下的水力参数估计相关的不确定性。为了实现先前的目标，开发了 FORTRAN 代码来应用使用不同似然函数（指数、逆函数和对数）的马尔可夫链蒙特卡罗 (MCMC) 算法。该开发的工具可用于检测最可能的含水层参数范围，这些参数与抽水测试数据高度一致。该工具已成功用于几个假设案例，以证明含水层参数量化的不确定性，并将结果与​​标准方法的结果进行比较。此外，使用具有众所周知的含水层参数的假设案例，对这一概念进行了数值验证（使用 Modflow 程序），并获得了令人满意的结果。最后将该工具应用于实际抽水试验数据，取得了良好的效果。