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Transport modeling and multivariate adaptive regression splines for evaluating performance of ASR systems in freshwater aquifers

机译:用于评估淡水含水层ASR系统性能的运输建模与多变量自适应回归曲线

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Highlights?REN is the proportion of the injected water that the same ASR wells can recover.?The study estimates REN in freshwater aquifers using a transport model.?The study details the process to prepare a reliable refined flow model.?The study reports the first application of MARS regression to manage an ASR system.?Results show the importance of having preexisting water rights for high RENs (~100%).AbstractThe study presents a procedure using solute transport and statistical models to evaluate the performance of aquifer storage and recovery (ASR) systems designed to earn additional water rights in freshwater aquifers. The recovery effectiveness (REN) index quantifies the performance of these ASR systems. REN is the proportion of the injected water that the same ASR well can recapture during subsequent extracti
机译:<![cdata [ 亮点 ren是相同ASR孔可以恢复的注入水的比例。 研究估计使用运输模型在淡水含水层中。 研究详细说明了准备可靠的精细流模型的过程。 研究报告了火星回归的第一个应用管理ASR系统。 结果表明,对高rens的预先存在的水权(〜100%)的重要性。 抽象< / ce:section-title> 该研究提供了一种使用溶质运输的程序统计模型评估含水层储存和恢复(ASR)系统的性能,旨在在淡水含水层中获得额外的水权。恢复有效性(REN)指数量化了这些ASR系统的性能。 REN是注射水的比例,即在后续提取物期间可以重新恢复

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