Predicting Effects of Artificial Recharge using Groundwater Flow and Transport Models with First Order Uncertainty Analysis

Persistent Link:
http://hdl.handle.net/10150/191349
Title:
Predicting Effects of Artificial Recharge using Groundwater Flow and Transport Models with First Order Uncertainty Analysis
Author:
Murphy, David.
Issue Date:
1997
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Groundwater flow, particle tracking, and solute transport models were developed for the Sweetwater Recharge Facility (SRF) of Tucson, Arizona. The SRF is an underground storage and recovery facility for reclaimed water, which relies on S oil- Aquifer Treatment (SAT) to improve effluent quality during the recharge process. The groundwater flow model was used to strengthen estimates of hydrogeologic parameters, and computes the effects of artificial recharge and groundwater extraction on the natural hydrologic system. Modeling results indicate that the validity of boundary conditions becomes questionable under regional declines in groundwater levels. This problem may be minimized by modeling time-variant head boundaries or nesting the model within a regional-scale model. The particle tracking and transport models were used to locate monitor wells at designated travel-time distances from the recharge basins and investigate effluent breakthrough at monitoring points downgradient of the basins. Uncertainty in the model outputs hydraulic head and travel time are caused by uncertainty in parameters such as hydraulic conductivity, storage properties, dispersive properties, recharge rates, and pumping rates. First order uncertainty analyses were used, in addition to standard sensitivity analyses, to test the effects of uncertainty on model results. Quantifying uncertainty is important in modeling of recharge systems for two reasons. First, the research in this field will be used to direct regulatory decisions which stipulate the length of time recharged water must be in the subsurface prior to extraction. Second, models may be used to plan the layout of systems; for example, monitor wells were located in this study. The results of the first order uncertainty analysis indicate chat uncertainties of hydraulic conductivity and dispersivity likely influence model output more than uncertainties of storage properties and recharge and pumping rates. Future data collection should focus on estimating values of hydraulic conductivity and dispersivity.
Type:
Thesis-Reproduction (electronic); text
LCSH Subjects:
Hydrology.; Artificial groundwater recharge.; Groundwater flow -- Mathematical models.; Uncertainty (Information theory)
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Hydrology and Water Resources; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Lansey, Kevin

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titlePredicting Effects of Artificial Recharge using Groundwater Flow and Transport Models with First Order Uncertainty Analysisen_US
dc.creatorMurphy, David.en_US
dc.contributor.authorMurphy, David.en_US
dc.date.issued1997en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractGroundwater flow, particle tracking, and solute transport models were developed for the Sweetwater Recharge Facility (SRF) of Tucson, Arizona. The SRF is an underground storage and recovery facility for reclaimed water, which relies on S oil- Aquifer Treatment (SAT) to improve effluent quality during the recharge process. The groundwater flow model was used to strengthen estimates of hydrogeologic parameters, and computes the effects of artificial recharge and groundwater extraction on the natural hydrologic system. Modeling results indicate that the validity of boundary conditions becomes questionable under regional declines in groundwater levels. This problem may be minimized by modeling time-variant head boundaries or nesting the model within a regional-scale model. The particle tracking and transport models were used to locate monitor wells at designated travel-time distances from the recharge basins and investigate effluent breakthrough at monitoring points downgradient of the basins. Uncertainty in the model outputs hydraulic head and travel time are caused by uncertainty in parameters such as hydraulic conductivity, storage properties, dispersive properties, recharge rates, and pumping rates. First order uncertainty analyses were used, in addition to standard sensitivity analyses, to test the effects of uncertainty on model results. Quantifying uncertainty is important in modeling of recharge systems for two reasons. First, the research in this field will be used to direct regulatory decisions which stipulate the length of time recharged water must be in the subsurface prior to extraction. Second, models may be used to plan the layout of systems; for example, monitor wells were located in this study. The results of the first order uncertainty analysis indicate chat uncertainties of hydraulic conductivity and dispersivity likely influence model output more than uncertainties of storage properties and recharge and pumping rates. Future data collection should focus on estimating values of hydraulic conductivity and dispersivity.en_US
dc.description.notehydrology collectionen_US
dc.typeThesis-Reproduction (electronic)en_US
dc.typetexten_US
dc.subject.lcshHydrology.en_US
dc.subject.lcshArtificial groundwater recharge.en_US
dc.subject.lcshGroundwater flow -- Mathematical models.en_US
dc.subject.lcshUncertainty (Information theory)en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineHydrology and Water Resourcesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairLansey, Kevinen_US
dc.identifier.oclc213873020en_US
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