Date of Award:

5-2018

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Civil and Environmental Engineering

Advisor/Chair:

Richard C. Peralta

Abstract

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.

Checksum

f4e688861a4ca92285f83462f2a68c18

Share

COinS