Advances in Hydrogeology

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  1. Seminal advances in hydrogeology, 1963 to 2013: The O.E. Meinzer Award legacy
  2. Recent advances and themes in hydrology
  3. Recommended for you
  4. Advances in Hydrology and Hydraulic Engineering | Book
  5. Advances in Hydrology and Hydraulic Engineering

Anderson, Donald I. Siegel, During the twentieth century, the science of hydrogeology focused on establishing and refining fundamental principles and developing tools to study groundwater flow, well hydraulics, hydrogeochemistry, and contaminant hydrogeology. By the end of the century, the science evolved to assimilate principles and expertise from other disciplines, including surface water hydrology, chemistry, microbiology, geophysics, and ecology.

In this chapter, we review seminal achievements in hydrogeology from to , focusing on work by recipients of the Hydrogeology Division's O. Meinzer Award, one of the most prestigious and coveted awards in hydrogeology. The canon of Meinzer Award papers, reports, and books reflects the trends in hydrogeological research since the early s.

Seminal advances in hydrogeology, 1963 to 2013: The O.E. Meinzer Award legacy

We also discuss other contributory papers by Meinzer awardees and related work by other scientists, and cover some research areas that have not been recognized by the Meinzer Award. We anticipate that the contributions of future Meinzer awardees will continue to document leadership in hydrogeology, perhaps in areas that have not yet been recognized by the award, including hydrogeoecology and hyporheic processes, submarine groundwater discharge, multilevel slug tests and hydraulic tomography, heat as a groundwater tracer, hydrogeophysics including remote sensing, and regional groundwater hydrology applied to issues of climate change.

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Recent advances and themes in hydrology

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Conceptual advances are further tempered by insights arising from observations from both field and laboratory work. JavaScript is currently disabled, this site works much better if you enable JavaScript in your browser. Free Preview. Represents different types of progress in hydrogeology This book includes several sub-themes that connect all of the chapters This book is based upon a group of invited speakers and their topics from presentations and poster sessions at the Fall American Geophysical Union AGU Meeting see more benefits.

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Advances in Hydrology and Hydraulic Engineering | Book

Buy Hardcover. Buy Softcover. This makes it possible to identify the functional form and estimate all parameters of corresponding models based solely on sample structure functions of the first and second orders. The purpose of this investigation is to implement a new constitutive law of saturation—capillary pressure into a fractional flow-based multiphase flow model to simulate compressible subsurface flow problems. Using the new constitutive law to describe the saturation—capillary pressure relations alleviates an undue constraint on pressure distributions inherent in a widely used law.

This makes the present model able to include all possible solutions of pressure distributions in subsurface flow modeling.

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Finite element methods FEM are used to discretize the three governing equations for three primary variables—saturation of water, saturation of total liquid, and total pressure. Four examples with different pressure distributions are presented to show the feasibility and advantage of using the new constitutive law. The results verify the feasibility and capability of the present model for subsurface flow systems to cover all possible pressure distributions.

Cellular automata CA models employ local rules to simulate large-scale behavior.

Advances in Hydrology and Hydraulic Engineering

A previously developed CA model of fluid pressure redistribution events within a 2D planar fault system undergoing compression is used to model the size distribution of these events over time. Local fluid pressures exceeding a threshold value cause a rupture failure of the surrounding rock, and the fluid pressure is redistributed to surrounding cells. The spatially and temporally uniform pattern of events seen in the uncorrelated model rapidly evolve to exhibit emergent behavior as the correlation length increases beyond the grid cell size.

Increasing spatial correlation leads to delays in the time to first failure and decreases the time necessary for the ruptures to coalesce and span the fault domain. Vertical effective permeability of the fault system at the point where connected failures span the domain shows that effective permeability is a nonlinear function of the correlation length and is strongly controlled by the size area of the domain-spanning failed cluster.

Identification of heterogeneous hydraulic aquifer properties from limited dynamic flow measurements typically leads to underdetermined nonlinear inverse problems that can have many solutions, including solutions that are geologically implausible and fail to predict future performance of the system.

The problem is usually regularized by incorporating implicit or explicit prior information to stabilize the solution techniques and to obtain plausible solutions. A meaningful regularization must be informed by the physics of the problem, distinct properties of the formation under investigation, and other available sources of information e. This chapter proposes sparsity as an intrinsic property of spatially distributed aquifer hydraulic properties that can be used to regularize the solution of the related ill-posed inverse problem.

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Inspired by recent advances in sparse signal processing, formalized under the compressed sensing paradigm, proper sparsifying bases are introduced to describe aquifer hydraulic conductivity distribution. Such descriptions give rise to a sparse reconstruction formulation of the subsurface flow model calibration inverse problem, which can be efficiently solved following recent algorithmic developments in sparse signal processing.

The compressed sensing paradigm specifies the conditions under which unique solutions to underdetermined linear system of equations exist and can be computed efficiently. Sparsity is a fundamental notion in compressed sensing, and is often present in many natural images. In particular, sparsity is prevalent in describing many spatially correlated aquifer properties.

The practical implications of compressed sensing are as far reaching as the solution of underdetermined system of equations is in science and engineering.