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Stochastic methods for modeling the ...
~
Lawrence, Alison Elaine.
Stochastic methods for modeling the transport of kinetically sorbing solutes in heterogeneous groundwater aquifers.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Stochastic methods for modeling the transport of kinetically sorbing solutes in heterogeneous groundwater aquifers.
作者:
Lawrence, Alison Elaine.
面頁冊數:
199 p.
附註:
Chair: Yoram Rubin.
附註:
Source: Dissertation Abstracts International, Volume: 65-09, Section: B, page: 4760.
Contained By:
Dissertation Abstracts International65-09B.
標題:
Engineering, Environmental.
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3146928
ISBN:
049605256X
Stochastic methods for modeling the transport of kinetically sorbing solutes in heterogeneous groundwater aquifers.
Lawrence, Alison Elaine.
Stochastic methods for modeling the transport of kinetically sorbing solutes in heterogeneous groundwater aquifers.
- 199 p.
Chair: Yoram Rubin.
Thesis (Ph.D.)--University of California, Berkeley, 2004.
Heterogeneity is prevalent in aquifers and has an enormous impact on contaminant transport in groundwater. In addition to affecting the contaminant velocity, heterogeneity contributes to immobile water regions into which contaminants slowly diffuse. This diffusion effect can be modeled with the equations that describe rate-limited sorption, which is another important process in aquifers.
ISBN: 049605256XSubjects--Topical Terms:
212478
Engineering, Environmental.
Stochastic methods for modeling the transport of kinetically sorbing solutes in heterogeneous groundwater aquifers.
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Source: Dissertation Abstracts International, Volume: 65-09, Section: B, page: 4760.
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Thesis (Ph.D.)--University of California, Berkeley, 2004.
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Heterogeneity is prevalent in aquifers and has an enormous impact on contaminant transport in groundwater. In addition to affecting the contaminant velocity, heterogeneity contributes to immobile water regions into which contaminants slowly diffuse. This diffusion effect can be modeled with the equations that describe rate-limited sorption, which is another important process in aquifers.
520
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Moments of contaminant travel times can measure the effects of heterogeneity. The travel time variance measures both the spread of the contamination due to heterogeneity and the uncertainty in the arrival time due to the fact that a complete description of the subsurface is not available. Equations are derived for the temporal moments of contaminants experiencing rate-limited sorption or diffusion based on the temporal moments of conservative tracers. Conditioning on transmissivity measurements is incorporated, and the general equations are specified to the rate-limited sorption models found to be applicable in the literature.
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Numerical simulations are an effective way to deal with heterogeneity directly by assigning different hydraulic property values to each numerical grid block. Because hydraulic properties vary on many scales, but they cannot be sampled exhaustively and the number of numerical grid blocks is limited by computational considerations, dispersion tensors are required to model the dispersive effects of unmodeled heterogeneity. Ensemble average block-scale macrodispersion tensors account for all of the pertinent length scales and do not include the effects of heterogeneity modeled on the numerical grid. Numerical simulation results are presented showing that the tensors can be used to accurately model the spread of contaminants when limited measurements are available and hydraulic conductivity is modeled on a numerical grid with large blocks, resulting in less computational demand than typical numerical simulations. The tensors are derived for reactive contaminants with spatially variable retardation factors and for contaminants experiencing spatially uniform rate-limited sorption or diffusion. The applicability of the concept depends on the ratio of the transverse size of the contaminant plume to the size of the regions modeled with uniform hydraulic properties and on the portion of the plume asymmetry caused by small-scale variability. Results show that the concept is widely applicable.
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