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dc.contributor.advisorSale, Tom
dc.contributor.authorAlqahtani, Abdulaziz A.
dc.contributor.committeememberBailey, Ryan
dc.contributor.committeememberRonayne, Michael
dc.date.accessioned2015-08-28T14:34:58Z
dc.date.available2015-08-28T14:34:58Z
dc.date.issued2015
dc.descriptionIncludes bibliographical references.
dc.description2015 Summer.
dc.description.abstractWater storage is an essential part of water resources management schemes. Due to the high cost and escalating risks of building new surface reservoirs, water managers are becoming interested in employing more effective alternatives. Subsurface water storage is getting attention as one of these alternatives. However, due to lack of experience and tools to estimate the cost and effectiveness of subsurface water storage, water managers are reluctant to adopt this alternative. Available tools/models are only case specific; hence in this study, we develop a general model for subsurface storage and recovery. The model estimates the cost of the subsurface water storage and recovery using wells in bedrock. The model takes monthly river flow, population, and per capita demand as inputs to determine capital cost and operation and maintenance costs for the lifespan of the proposed project. To account for uncertainty in the input parameters, the model has the capability to perform stochastic analyses as well. Furthermore, the model includes the option of modular expansion of infrastructure through time, potentially reducing total and operation and maintenance costs. An application of the model is advanced based on the conditions in the vicinity of Fort Collins, Colorado. Critically, work presented herein should not be taken as a rigorous analysis of the issues faced by the city of Fort Collins. The application is simply a demonstration of what can be done with the tools developed in this thesis. The general premise of the application is creating new water storage in the Fountain Formation, north of Fort Collins. This model uses either deterministic or stochastic inputs. Since the deterministic model's inputs and outputs are both fixed numbers, the model is relatively simple. However, this type of input will yield specific results and does not consider the possibility of inputs varying through time. It misses a key challenge of water projects, the temporal variability in available water and demand. In Stochastic Analysis, inputs are varies from year to year and from month to month, allowing the system to accommodate wet or drought years, making the model more reliable for calculating the cost of system. One hundred simulations were performed using the stochastic model to estimate the range of variability of outputs. Except total pumping and additional storage, other outputs have small coefficients of variation, which show that they are less sensitive to uncertainity in input variables. The coefficient of variation for cost variables are around 0.1 (i.e., costs are expected to vary within ±10% of the estimated mean cost). As different cost components estimated by deterministic model are within ±10% of estimated mean cost from stochastic model. Therefore, we conclude that the deterministic model estimates different cost components fairly well. Both models, deterministic and stochastic, have been applied to a scenario predicted on conditions faced by the city of Fort Collins. At thirtieth year, the system can deliver 7.8×10⁶ m³/year of water (6.4×10³acre-ft/year) in an average year and up to 15.7×10⁶m³/year of water (12.7×10³acre-ft /year) in a drought year. The estimated present value cost from deterministic and stochastic models of the entire project was $ 23.1 million U.S and $ 22.5 million U.S., respectively. Not considered in the cost analysis is the value of the water saved due to reduced losses of evaporation and seepage losses, inherent with surface water storage. The model shows high reliability in meeting demand through the lifespan of the project, with no failure anticipated. The deterministic model added 9.12 million m³ to the aquifer, while the stochastic model shows an average addition of 16.8 million m³ to the aquifer. Greater stored water with the stochastic model is attributed to less pumping of groundwater. Further study is needed to resolve the basis for the stochastic model pumping less groundwater. The capital cost of the project is predicted to be approximately $ 6.0 million U.S. by both models. Both models estimated the need for 10 ASR wells and two alluvium inflow drain units through the lifespan of the project. The case study of Fort Collins shows the potential of subsurface water storage as a viable and cost effective alternative to surface water storage.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.identifier.urihttp://hdl.handle.net/10217/167062
dc.languageEnglish
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019 - CSU Theses and Dissertations
dc.rightsCopyright of the original work is retained by the author.
dc.titleSubsurface water storage assessment model
dc.typeText
dcterms.rights.dplaThe copyright and related rights status of this item has not been evaluated (https://rightsstatements.org/vocab/CNE/1.0/). Please refer to the organization that has made the Item available for more information.
thesis.degree.disciplineCivil and Environmental Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.S.)


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