2 edition of Stochastic analysis of aquifer interconnectedness found in the catalog.
Stochastic analysis of aquifer interconnectedness
Graham E. Fogg
1989 by Bureau of Economic Geology, University of Texas at Austin in Austin, Tex .
Written in English
Includes bibliographical references (p. 57-59).
|Statement||Graham E. Fogg.|
|Series||Report of investigations ;, no. 189, Report of investigations (University of Texas at Austin. Bureau of Economic Geology) ;, no. 189.|
|LC Classifications||QE167 .T42 no. 189, GB1199.3.T4 .T42 no. 189|
|The Physical Object|
|Pagination||vii, 68 p. :|
|Number of Pages||68|
|LC Control Number||90624059|
Groundwater hydrology, aquifer characterization, modeling and analysis of contaminant transport in soils and in groundwater, inverse modeling, geostatistics and stochastic methods for hydrogeological site characterization, geophysical methods for subsurface characterization, environmental information management systems. (6) Dagan, G. and Rubin, Y., Stochastic identification of recharge, transmissivity and storativity in aquifer unsteady flow: A quasi-steady approach, Water Resour. Research, 24(10), , (7) Rubin, Y. and Dagan, G., Stochastic analysis of the effects of boundaries on spatial variability in groundwater flows: 2.
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RI Stochastic Analysis of Aquifer Interconnectedness: Wilcox Group, Trawick Area, East Texas, by G. Fogg. 68 p., 41 figs., 4 tables, 5 appendices, ISSN. Stochastic analysis of aquifer interconnectedness.
Austin, Tex.: Bureau of Economic Geology, University of Texas at Austin, (OCoLC) Material Type: Government publication, State or province government publication: Document Type: Book: All Authors / Contributors: Graham E Fogg.
Fogg, G. E.,Stochastic Analysis of Aquifer Interconnectedness: Wilcox Group, Trawick Area, East Texas: The University of Texas at Austin, Bureau of Economic. Mohamed M. Hantush, Miguel A. Mariño, One‐dimensional stochastic analysis in leaky aquifers subject to random leakage, Water Resources Research, /93WR, 30, 2, Cited by: John H.
Cushman, Comment On “Three‐dimensional stochastic analysis of macrodispersion in aquifers” by Lynn W. Gelhar and Carl L. Axness, Water Resources Research, /WRip, 19, 6, (), ().Cited by: A single aquifer system (quartzite-schist formation) has been identified.
• Recharge through precipitation is % to % of the average annual rainfall in the area. Over 90 % of the terrain has hydraulic conductivity (HK) below m day − Over 90 % of the terrain has velocity below m day − The HK and velocity estimates are significant for contaminant transport along. The stochastic analysis is straightforward and exact; it is based on a closed‐form solution obtained using the Laplace transform method.
The solution relates linearly a stochastic perturbation of the aquifer head to uncertainty in the initial aquifer head and stochastic fluctuations of the water table in an overlying phreatic aquifer. The stochastic analysis of the dynamic responses of the groundwater system to its recharge has been carried out in a number of articles (e.g., Duffy and Gelhar,Duffy and Gelhar,Gelhar,Gelhar,Gelhar and Wilson,Li and Graham,Zhang and Li,Zhang and Li,Zhang and Yang, ), where the phreatic.
Stochastic analysis of aquifer interconnectedness book and stochastic methods of three‐dimensional hydrogeologic modeling are applied to characterization of contaminated Eocene aquifers at the Savannah River Site, South Carolina.
The results address several important issues, including the use of multiple types of data in creating high‐resolution aquifer models and the application.
Yoram Rubin, Gedeon Dagan, Stochastic analysis of boundaries effects on head spatial variability in heterogeneous aquifers: 1. Constant head boundary, Water Resources Research, /WRip, 24, 10, (), ().
A stochastic analysis for two‐dimensional steady‐state ground‐water flow through a homogeneous random shallow semiconfined aquifer is presented.
The flow problems through a semiconfined aquifer with a random leakage factor but subject to deterministic boundary conditions and domain recharge are investigated by perturbation techniques. Aquifer characterization is broadly defined as processes by which the three-dimensional structure, hydraulic and transport properties, and chemistry of aquifers are evaluated.
Other topics covered in this landmark volume include stochastic optimization, moment analysis, carbon dioxide modelling and rainfall prediction. Audience The book is of interest to researchers, teachers, students and practitioners who wish to be at the leading edge of stochastic and statistical modelling in the environmental sciences.
Abstract. The Stochastic analysis of aquifer interconnectedness book of stochastic methods to the analysis and prediction of the large-scale behavior of heterogeneous natural porous earth materials is reviewed emphasizing recent results for solute transport in saturated and unsaturated media.
Ali A.I., Lall U. () Stochastic Characterization of Aquifer Heterogeneity from Drill Log Data. In: Hipel K.W. (eds) Stochastic and Statistical Methods in Hydrology and Environmental Engineering. Water Science and Technology Library, vol 10/4. HYDROGEOLOGY LECTURE NOTES PRINTED ON 5 MAY 1 Chapter 1 – Introduction to Hydrogeology The Properties of Water Pure water (H 2O) is: Clear, colorless - No discernable taste or smell - At 1 atmosphere.
Stochastic analysis of oxygen-limited biodegration in three dimensionally in heterogeneous aquifers. Water Resour. Res., 33 (6)] and this work for hypothesized field conditions shows that the effects of transient microbial growth on the effective retardation factor and macrodispersivities are minor, while the effects are modest for the.
Shripad Tuljapurkar, David Steinsaltz, in Handbook of Statistics, Abstract. This chapter deals with stochastic models for structured populations whose dynamics depend crucially on individual characteristics such as age, size, or location.
We deal with linear stochastic models, and their analysis is also essential to the analysis of nonlinear stochastic models, particularly their boundary. This has led to the development of new theoretical models whose parameters, representing the aquifer characteristics, are treated as stochastic variables rather than deterministic functions of space.
In this paper, the state of the art in stochastic modeling is reviewed, and the experience and new knowledge gained with these models are summarized. AQUIFER-TEST DESIGN, OBSERVATION AND DATA ANALYSIS By Robert W. Stallman Book 3 APPLICATIONS OF HYDRAULICS -1 - Link back to USGS publications.
UNITED STATES DEPARTMENT OF THE INTERIOR THOMAS S. KLEPPE, Secretary GEOLOGICAL SURVEY V. McKelvey, Director. First printing Alberto Guadagnini, Daniel M. Tartakovsky, "Stochastic analysis of groundwater pumping from bounded, randomly heterogeneous aquifers", Theory, modeling, and field investigation in hydrogeology: a special volume in honor of Shlomo P.
Neumans 60th birthday, Dongxiao Zhang, C. Larry Winter. Aquifer characterization starts with an initial conceptual geological model development, followed by evaluations of the type and scale of aquifer heterogeneity and the values of petrophysical and hydraulic parameters, and finally, data analysis and synthesis, and.
aquifer is extremely heterogeneous on the megascopic scale and connectivity of 8 Detailed sedimentologic analysis on 3 continuously cored holes Fogg, G. E., Stochastic Analysis of Aquifer Interconnectedness: Wilcox Group, Trawick Area, East Texas: Univ.
TX Bureau of Economic Geology, Report of Investigations68 p. A total of stochastic models of the aquifer were created using fluvsim. The question of whether or not realizations are enough to get stable estimates of the groundwater-flow performance measures is addressed by calculating the running average of several of.
The overall quality of this textbook is exceptional. The book presents the topic of aquifer test analysis in a simple and easy-to-understand manner. --Journal of the American Water Resources Association, vol. 34, No. 5, Oct. Set pair analysis (SPA) and kriging methods were used to build the ensemble surrogate model.
The probability distributions of the residuals of the outputs between the ensemble surrogate model and the simulation model, run on testing samples, were analyzed to ascertain the uncertainty of the surrogate model, which was found to be less than %. Analysis modeling and software.
The process of damper configuration design and damper parameter definition required the development of an analysis methodology and customized software that could estimate stochastic performance of the structure for 1-year return period wind events, given the nonlinear constitutive relation of the viscous dampers.
Data integration is challenging where there are different levels of support between primary and secondary data that need to be correlated in various ways. A geostatistical method is described, which integrates the hydraulic conductivity (K) measurements and electrical resistivity data to better estimate the K distribution in the Upper Chicot Aquifer of southwestern Louisiana, USA.
Microbial ecological processes are frequently studied in the presence of perturbations rather than in undisturbed environments, despite the relatively stable conditions dominating many microbial habitats. To examine processes influencing microbial community structuring in the absence of strong external perturbations, three unperturbed aquifers in Ohio (Greene, Licking, and Athens) were sampled.
Most stochastic analyses of reactive transport in physically and geochemically heterogeneous aquifers have focused on the analysis of a single reactive species. Here we conduct the stochastic analysis of multicomponent competitive monovalent cation exchange.
The results of aquifer tests conducted at a karst aquifer are first introduced. A MODFLOW groundwater flow model was developed to perform numerical pumping tests, and the heterogeneous hydraulic conductivity (K) field was generated using the Monte Carlo method.
The K was estimated by the Theis solution for an unconfined aquifer. Stochastic Analysis of Aquifer Interconnectedness: Wilcox Group, Trawick Area, East Texas: RI Stratigraphy and Influence of Effective Porosity on Ground-Water Flow in the Wolfcamp Brine Aquifer, Palo Duro Basin, Texas Panhandle: RI Gelhar, L.
W.," Stochastic Subsurface Downloaded by [The University of Manchester Library] at 09 October J.C. Wen et al.: Induced Pressure-Variation Transport in Unconfined. The uncertainty of predicting stochastic solute transport in an aquifer with heterogeneous hydraulic conductivity was quantified.
Two sources of uncertainty were considered in the analysis including uncertainty that stems from inability to exactly predict the hydraulic conductivity at unmeasured locations and uncertainty that results from. Fogg, G.
E.,Stochastic analysis of aquifer interconnectedness: Wilcox Group, Trawick area, East Texas: The University of Texas at Austin, Bureau of. WATER RESOURCES RESEARCH, VOL. 22, NO. 5, PAGESMAY Groundwater Flow and Sand Body Interconnectedness in a Thick, Multiple-Aquifer System.
Stochastic analysis is commonly used to address uncertainty in the modeling of flow and transport in porous media. In the stochastic approach, the properties of porous media are treated as random functions with statistics obtained from field measurements.
A stochastic analysis permits a more realistic evaluation of water flow problems and can be useful in defining zones of uncertainty, which can be used to identify the parts of the flow region that are prone to significant variations in properties such as the hydraulic head and hydraulic gradient, as is illustrated in Figures 16 and MAIN LIBRARY.
Perry-Castañeda Library East 21st St. Austin, TX. Phone: () An aquifer test (or a pumping test) is conducted to evaluate an aquifer by "stimulating" the aquifer through constant pumping, and observing the aquifer's "response" in observation r testing is a common tool that hydrogeologists use to characterize a system of aquifers, aquitards and flow system boundaries.
A slug test is a variation on the typical aquifer test where an. () Stochastic analysis of the concentration variability in a three-dimensional heterogeneous aquifer. Water Resources Research() Supercomputers and their use in modeling subsurface solute transport.Get this from a library!
Stochastic modeling of groundwater systems. [L W Gelhar; Peter Yuk-Lam Ko; Herman H Kwai; John L Wilson; Massachusetts Institute of Technology. Department of Civil Engineering.; Ralph M. Parsons Laboratory for Water Resources and Hydrodynamics.;] -- This research developed important new results on the use of spectral analysis techniques to evaluate groundwater resources.Lu, C, Zhang, Y, Shu, L, Chen, X, Chen, S, Li, S, Wang, G & Li, JStochastic analysis of the hydraulic conductivity estimated for a heterogeneous aquifer via numerical modelling.
in Y Chen, I Cluckie, Z Su, C Neale, Z Xu, J Zhou & Q Huang (eds), Remote Sensing and GIS for Hydrology and Water Resources. IAHS-AISH Proceedings and Reports, vol.Copernicus GmbH, pp.