Quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems : implications for predictive uncertainty and data collection

Groundwater systems of different densities are often mathematically modeled to understand and predict environmental behavior such as seawater intrusion or submarine groundwater discharge. Additional data collection may be justified if it will cost-effectively aid in reducing the uncertainty of a mod...

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Main Author: Dausman, Alyssa Marie
Format: Others
Published: FIU Digital Commons 2008
Subjects:
Online Access:http://digitalcommons.fiu.edu/etd/2740
http://digitalcommons.fiu.edu/cgi/viewcontent.cgi?article=4040&context=etd
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spelling ndltd-fiu.edu-oai-digitalcommons.fiu.edu-etd-40402018-01-05T15:34:20Z Quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems : implications for predictive uncertainty and data collection Dausman, Alyssa Marie Groundwater systems of different densities are often mathematically modeled to understand and predict environmental behavior such as seawater intrusion or submarine groundwater discharge. Additional data collection may be justified if it will cost-effectively aid in reducing the uncertainty of a model's prediction. The collection of salinity, as well as, temperature data could aid in reducing predictive uncertainty in a variable-density model. However, before numerical models can be created, rigorous testing of the modeling code needs to be completed. This research documents the benchmark testing of a new modeling code, SEAWAT Version 4. The benchmark problems include various combinations of density-dependent flow resulting from variations in concentration and temperature. The verified code, SEAWAT, was then applied to two different hydrological analyses to explore the capacity of a variable-density model to guide data collection. The first analysis tested a linear method to guide data collection by quantifying the contribution of different data types and locations toward reducing predictive uncertainty in a nonlinear variable-density flow and transport model. The relative contributions of temperature and concentration measurements, at different locations within a simulated carbonate platform, for predicting movement of the saltwater interface were assessed. Results from the method showed that concentration data had greater worth than temperature data in reducing predictive uncertainty in this case. Results also indicated that a linear method could be used to quantify data worth in a nonlinear model. The second hydrological analysis utilized a model to identify the transient response of the salinity, temperature, age, and amount of submarine groundwater discharge to changes in tidal ocean stage, seasonal temperature variations, and different types of geology. The model was compared to multiple kinds of data to (1) calibrate and verify the model, and (2) explore the potential for the model to be used to guide the collection of data using techniques such as electromagnetic resistivity, thermal imagery, and seepage meters. Results indicated that the model can be used to give insight to submarine groundwater discharge and be used to guide data collection. 2008-11-03T08:00:00Z text application/pdf http://digitalcommons.fiu.edu/etd/2740 http://digitalcommons.fiu.edu/cgi/viewcontent.cgi?article=4040&context=etd FIU Electronic Theses and Dissertations FIU Digital Commons Earth Sciences Geology
collection NDLTD
format Others
sources NDLTD
topic Earth Sciences
Geology
spellingShingle Earth Sciences
Geology
Dausman, Alyssa Marie
Quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems : implications for predictive uncertainty and data collection
description Groundwater systems of different densities are often mathematically modeled to understand and predict environmental behavior such as seawater intrusion or submarine groundwater discharge. Additional data collection may be justified if it will cost-effectively aid in reducing the uncertainty of a model's prediction. The collection of salinity, as well as, temperature data could aid in reducing predictive uncertainty in a variable-density model. However, before numerical models can be created, rigorous testing of the modeling code needs to be completed. This research documents the benchmark testing of a new modeling code, SEAWAT Version 4. The benchmark problems include various combinations of density-dependent flow resulting from variations in concentration and temperature. The verified code, SEAWAT, was then applied to two different hydrological analyses to explore the capacity of a variable-density model to guide data collection. The first analysis tested a linear method to guide data collection by quantifying the contribution of different data types and locations toward reducing predictive uncertainty in a nonlinear variable-density flow and transport model. The relative contributions of temperature and concentration measurements, at different locations within a simulated carbonate platform, for predicting movement of the saltwater interface were assessed. Results from the method showed that concentration data had greater worth than temperature data in reducing predictive uncertainty in this case. Results also indicated that a linear method could be used to quantify data worth in a nonlinear model. The second hydrological analysis utilized a model to identify the transient response of the salinity, temperature, age, and amount of submarine groundwater discharge to changes in tidal ocean stage, seasonal temperature variations, and different types of geology. The model was compared to multiple kinds of data to (1) calibrate and verify the model, and (2) explore the potential for the model to be used to guide the collection of data using techniques such as electromagnetic resistivity, thermal imagery, and seepage meters. Results indicated that the model can be used to give insight to submarine groundwater discharge and be used to guide data collection.
author Dausman, Alyssa Marie
author_facet Dausman, Alyssa Marie
author_sort Dausman, Alyssa Marie
title Quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems : implications for predictive uncertainty and data collection
title_short Quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems : implications for predictive uncertainty and data collection
title_full Quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems : implications for predictive uncertainty and data collection
title_fullStr Quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems : implications for predictive uncertainty and data collection
title_full_unstemmed Quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems : implications for predictive uncertainty and data collection
title_sort quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems : implications for predictive uncertainty and data collection
publisher FIU Digital Commons
publishDate 2008
url http://digitalcommons.fiu.edu/etd/2740
http://digitalcommons.fiu.edu/cgi/viewcontent.cgi?article=4040&context=etd
work_keys_str_mv AT dausmanalyssamarie quantifyingtheeffectsoftemperatureandconcentrationonvariabledensityflowinnumericalmodelingofgroundwatersystemsimplicationsforpredictiveuncertaintyanddatacollection
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