Automatic estimation of aquifer parameters using long-term water supply pumping and injection records
Automatic estimation of aquifer parameters using long-term water supply pumping and injection records
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DOI：
10.1007/s10040-016-1407-x
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发表时间：
2016-04
影响因子：
2.8
通讯作者：
Ning Luo;W. Illman
中科院分区：
文献类型：
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作者：
Ning Luo;W. Illman
分析了加拿大安大略省滑铁卢地区一个市政供水井场承压含水层中受可变抽水/注水事件扰动的长期水文过程。这种记录通常不被考虑用于含水层测试分析。在这里，水位变化是指纹的抽水/注水速率的变化使用泰斯模型实施的威尔斯代码与PEST相结合。对这些记录的分析得出了每个监测和生产井之间的一套导水率(T)和储存量(S)估计。这些单独的估计被发现不能很好地预测附近监测钻孔的水位变化，而不是在校准工作中使用。另一方面，单项T值和S值的几何平均值与以前在同一地点进行的抽水试验得到的结果相似，并充分预测了其他钻孔的水位变化。分析表明，城市长期水位记录可以用一种简单的解析解来估计含水层参数。然而，用解析解估计的均匀参数应被视为第一次粗略估计。应该通过校准三维数值模型来获得更准确的水力参数，该模型严格地利用这些数据来捕捉现场的复杂性。
Analyses are presented of long-term hydrographs perturbed by variable pumping/injection events in a confined aquifer at a municipal water-supply well field in the Region of Waterloo, Ontario (Canada). Such records are typically not considered for aquifer test analysis. Here, the water-level variations are fingerprinted to pumping/injection rate changes using the Theis model implemented in the WELLS code coupled with PEST. Analyses of these records yield a set of transmissivity (T) and storativity (S) estimates between each monitoring and production borehole. These individual estimates are found to poorly predict water-level variations at nearby monitoring boreholes not used in the calibration effort. On the other hand, the geometric means of the individualTandSestimates are similar to those obtained from previous pumping tests conducted at the same site and adequately predict water-level variations in other boreholes. The analyses reveal that long-term municipal water-level records are amenable to analyses using a simple analytical solution to estimate aquifer parameters. However, uniform parameters estimated with analytical solutions should be considered as first rough estimates. More accurate hydraulic parameters should be obtained by calibrating a three-dimensional numerical model that rigorously captures the complexities of the site with these data.