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Towards optimal sampling schedules for integral pumping tests

机译:为整体抽水测试制定最佳采样时间表

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Conventional point sampling may miss plumes in groundwater due to an insufficient density of sampling locations. The integral pumping test (IPT) method overcomes this problem by increasing the sampled volume. One or more wells are pumped for a long duration (several days) and samples are taken during pumping. The obtained concentration-time series are used for the estimation of average aquifer concentrations C-(av) and mass flow rates Mcp. Although the IPT method is a well accepted approach for the characterization of contaminated sites, no substantiated guideline for the design of IPT sampling schedules (optimal number of samples and optimal sampling times) is available. This study provides a first step towards optimal IPT sampling schedules by a detailed investigation of 30 high-frequency concentration-time series. Different sampling schedules were tested by modifying the original concentration-time series. The results reveal that the relative error in the C(av) estimation increases with a reduced number of samples and higher variability of the investigated concentration-time series. Maximum errors of up to 22% were observed for sampling schedules with the lowest number of samples of three. The sampling scheme that relies on constant time intervals At between different samples yielded the lowest errors.
机译:由于采样位置密度不足,常规点采样可能会漏掉地下水中的羽流。积分泵测试(IPT)方法通过增加采样量来克服此问题。一口或多口井的抽水时间很长(几天),抽水时需要取样。所获得的浓度时间序列用于估算平均含水层浓度C-(av)和质量流量Mcp。尽管IPT方法是用于表征污染场所的公认方法,但尚无用于设计IPT采样时间表(最佳采样数和最佳采样时间)的可靠指南。这项研究通过对30个高频集中时间序列进行详细研究,为朝着最佳IPT采样时间表迈出了第一步。通过修改原始浓度-时间序列测试了不同的采样计划。结果表明,随着样品数量的减少和所研究浓度-时间序列的较高变异性,C(av)估计中的相对误差会增加。对于采样计划,以最少的三个样本数量观察到的最大误差高达22%。依赖于恒定时间间隔的采样方案在不同样本之间产生的误差最低。

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