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Colorado State University (2019)

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

Alqahtani, Abdulaziz

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

Auteur : Alqahtani, Abdulaziz

Université de soutenance : Colorado State University

Grade : Doctor of Philosophy (PhD) 2019

Résumé partiel
Sustained 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.


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