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Simulation and Optimization Models to Evaluate Performance of Aquifer Storage and Recovery Wells in Fresh Water Aquifers

机译:评估淡水含水层储水和回收井性能的仿真和优化模型

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摘要

Aquifer storage and recovery (ASR) involves artificially recharging an aquifer through well(s) using surplus water for later recovery in high-demand months. The operators of the studied ASR system developed the system as a means of receiving additional water rights to supplement their pre-existing water rights for extraction in dry months. However, the region's water regulators define the performance of this ASR system as the amount of the injected water that is recoverable from the same wells during extraction periods. The study proposes recovery effectiveness (REN) as the performance index of this ASR system. REN equals the injectate proportion that the same wells can recover. Quantifying the system's achievable REN is required to determine the amount of the additional water rights. Similarity between the injected water and native groundwater, however, prevents an accurate REN estimation using on-field techniques. This necessitates the use of computer modeling for estimating REN in this system. The study employs simulation, statistical, and optimization models to quantify and maximize REN in the studied ASR system in Utah.
机译:含水层的存储和回收(ASR)涉及使用多余的水通过井对人工含水层进行补给,以在以后需求旺盛的月份进行回收。所研究的ASR系统的运营商开发了该系统,将其作为获得额外水权的一种手段,以补充他们先前在干旱月份提取的水权。但是,该地区的水调节器将该ASR系统的性能定义为在开采期间可从同一口井回收的注入水量。该研究提出了恢复效率(REN)作为该ASR系统的性能指标。 REN等于相同井可采出的注入比例。需要量化系统可实现的REN,以确定额外的水权数量。但是,注入水和天然地下水之间的相似性会妨碍使用现场技术进行准确的REN估算。这就需要使用计算机模型来估算该系统中的REN。该研究采用模拟,统计和优化模型来量化和最大化犹他州研究的ASR系统中的REN。

著录项

  • 作者

    Forghani, Ali.;

  • 作者单位

    Utah State University.;

  • 授予单位 Utah State University.;
  • 学科 Civil engineering.;Environmental engineering.
  • 学位 Ph.D.
  • 年度 2018
  • 页码 191 p.
  • 总页数 191
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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