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Optimizing operation and design of aquifer storage and recovery (ASR) wellfields

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dc.contributor.authorAlqahtani, Abdulaziz, author
dc.contributor.authorSale, Tom, advisor
dc.contributor.authorGrigg, Neil, committee member
dc.contributor.authorBailey, Ryan, committee member
dc.contributor.authorRonayne, Michael, committee member
dc.date.accessioned2020-01-13T16:41:26Z
dc.date.available2020-01-13T16:41:26Z
dc.date.issued2019
dc.description.abstractSustained production of groundwater from wells in wellfields can lead to declining water levels at production wells and concerns regarding the sustainability of groundwater resources. Furthermore, minimizing energy consumption associated with pumping groundwater is a growing concern. Aquifer Storage and Recovery (ASR) is a promising approach for maintaining water levels in wells, increasing the sustainability of groundwater resources, and minimize energy consumption during groundwater pumping. Therefore, studying the importance of ASR in sustaining water levels and minimizing energy consumption is critical. In the first part of this dissertation, an analytical model relying on superposition of the Theis equation is used to resolve water levels in 40 wells in three vertically stacked ASR wellfields. Fifteen years of dynamic recovery/recharge data are used to obtain aquifer and well properties. Estimated aquifer and well properties are used to predict water levels at production well. Close agreement between modeled and observed water levels support the validity of the analytical model for estimating water levels at ASR wells. During the study period, 45 million m³ of groundwater is produced and 11 million m3 is recharged leading to a net withdrawal of 34 million m³ of groundwater. Rates of changes in recoverable water levels in wells in the Denver, Arapahoe and Laramie-Fox Hill Aquifers are 0.20, -0.91, and -3.48 m per year, respectively. To quantify the benefits of recharge, the analytical model is applied to predicting water levels at wells absent the historical recharge. Results indicate that during recovery and no-flow periods, recharge has increased water levels at wells up to 60 m compared to the no-recharge scenario. On average, the recharge increased water levels at wells during the study period by 3, 4, and 11 m in the Denver, Arapahoe, and Laramie Fox-Hills Aquifers, respectively. Overall, the analytical model is a promising tool for advancing ASR wellfields and ASR can be a viable approach to sustaining water levels in wells in wellfields. In the second part of this dissertation, a simulation-optimization model (ASRSOM) is developed to optimize ASR wellfield operations. ASRSOM combines an analytical hydraulic model and a numerical optimization model to optimize wellfield operations. The objective function used to minimize energy consumption φ (L⁴) is the temporal integral of the products of temporally varying total dynamic head values and pumping rates. Comparison of ASRSOM results to work by others for idealized aquifer operations supports the validity of ASRSOM. Four scenarios were simulated to evaluate the role that optimization of operations and aquifer recharge play in reducing the energy required to lift groundwater out of aquifer. A 10-year study period is considered using data from a municipal ASR wellfield. Optimization decreased φ by 19.6%, which yields an estimated reduction of 2,179 MW hours of power and 1,541 metric tons of atmospheric carbon. For the condition considered, recharge reduced power by 1%. The limited benefit of recharge is attributed to the small recharge volume in the case study and the short duration of the analysis. Additional opportunities to address economic and environmental impacts associated with lifting groundwater out aquifer include optimizing the position of wells and factors controlling total pumping head. In the third part of this dissertation, the sensitivity of well-spacing in ASR wellfields to critical parameters is studied. The parameters studied are aquifer transmissivity and storativity, wells flowrate and the frequency of recharge and recovery. It has been found that larger well-spacing are appropriate for lower transmissivity and storativity, and larger wells flowrate and frequency. More work is needed to fully understand the optimal well-spacing of wells in ASR wellfields associated with more realistic storage and recovery schedules, and more complex wellfields. Overall, work supported the possibility that wells in ASR wellfields can be spread more closely than wells in conventional production wellfields.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierAlqahtani_colostate_0053A_15701.pdf
dc.identifier.urihttps://hdl.handle.net/10217/199736
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectgroundwater
dc.subjectaquifer storage and recovery
dc.subjectoptimization
dc.titleOptimizing operation and design of aquifer storage and recovery (ASR) wellfields
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineCivil and Environmental Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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