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Allan L. Gutjahr
Researcher at New Mexico Institute of Mining and Technology
Publications - 21
Citations - 1245
Allan L. Gutjahr is an academic researcher from New Mexico Institute of Mining and Technology. The author has contributed to research in topics: Covariance & Stochastic modelling. The author has an hindex of 11, co-authored 21 publications receiving 1216 citations.
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Stochastic Analysis of Unsaturated Flow in Heterogeneous Soils: 2. Statistically Anisotropic Media With Variable α
TL;DR: In this paper, the authors analyzed unsaturated flow in heterogeneous soil with an arbitrarily oriented mean hydraulic gradient using spectral solutions of the stochastic perturbation equation which describes the capillary pressure head ψ.
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A comparison of seven geostatistically based inverse approaches to estimate transmissivities for modeling advective transport by groundwater flow
D. A. Zimmerman,G. de Marsily,G. de Marsily,C. A. Gotway,Melvin G. Marietta,C. L. Axness,R. L. Beauheim,Rafael L. Bras,Jesús Carrera,Gedeon Dagan,P. B. Davies,D. P. Gallegos,A. Galli,J. Jaime Gómez-Hernández,P. Grindrod,Allan L. Gutjahr,Peter K. Kitanidis,A. M. Lavenue,Dennis McLaughlin,Shlomo P. Neuman,Banda S. RamaRao,C. Ravenne,Yoram Rubin +22 more
TL;DR: In this article, the authors compared seven different inverse approaches for identifying aquifer transmissivity and found that the linearized methods were more accurate than those of nonlinear methods in predicting travel times and travel paths.
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Stochastic analysis of spatial variability in two‐dimensional steady groundwater flow assuming stationary and nonstationary heads
TL;DR: In this paper, a two-dimensional steady groundwater flow in a confined aquifer with spatially variable transmissivity T is analyzed stochastically using spectral analysis and the theory of intrinsic random functions.
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Stochastic models of subsurface flow: infinite versus finite domains and stationarity
Allan L. Gutjahr,Lynn W. Gelhar +1 more
TL;DR: In this paper, the authors developed stochastic solutions of the differential equation describing one-dimensional flow through a porous medium with spatially variable hydraulic conductivity which is represented by a stationary (statistically homogeneous) random process.
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An Iterative Cokriging‐Like Technique for Ground‐Water Flow Modeling
TL;DR: In this article, the authors developed an iterative method which combines classical cokriging and a numerical flow model to obtain optimum estimates of transmissivity and head distributions and to alleviate the limitations of classical kriging.