Soil water solute process characterization an integrated approach

SOIL-WATERSOLUTE PROCESS
CHARACTERIZATION
An Integrated Approach



SOIL-WATERSOLUTE PROCESS
CHARACTERIZATION
An Integrated Approach

Edited by

Javier álvarez-benedí
~
rafael munoz-carpena

CRC PR E S S
Boca Raton London New York Washington, D.C.


Library of Congress Cataloging-in-Publication Data
Soil-water-solute process characterization: an integrated approach / [edited by]
Javier A´lvarez Benedı´ and Rafael Mun˜oz-Carpena.
p. cm.
Includes bibliographical references and index.
ISBN 1-56670-657-2 (alk. paper)
1. Soil moisture–Mathematical models. 2. Soils–Solute movement–Mathematical
models. 3. Soil permeability–Mathematical models. 4. Groundwater flow–
Mathematical models. I. A´lvarez-Benedı´ , Javier. II. Mun˜oz-Carpena, Rafael.
III. Title.

S594.S6935 2005
631.4' 32' 011–dc22

2004015853

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Preface
The development and application of methods for monitoring and characterizing soil-water-solute processes are among the most limiting factors in
understanding the soil environment. Experimental methods are a critical part
of scientific papers, and their design and implementation are usually the most
time-consuming tasks in research. When selecting a method to characterize a
property governing a soil process, the practitioner or researcher often faces
complex alternatives. In many cases these alternatives are bypassed in favor of
recommendations from colleagues on well-established methods that might not
be the most suitable for the specific conditions of a study.
Several factors add to the complexity of selecting the best characterization
method for a particular case:
 The governing properties or parameters are referred to by similar names
although in fact their actual values depend greatly on the conceptual
model selected to explain the process (e.g., several empirical models of soil
infiltration have different parameters associated with saturated hydraulic
conductivity).
 The ultimate goal of the characterization effort, whether it be general
classification of the soil, qualitative estimation of an output, exploratory
modeling to gain insight on a process, quantitative modeling prediction,
etc., may determine the method of choice.
 Since many of the soil characteristics are intrinsically variable (spatially
and temporally), the most accurate method might not necessarily be the
best choice when compared with a simpler one that can provide a larger
number of samples with the same or lower investment.

An integrated approach for soil characterization is needed that combines
available methods with the analysis of the conceptual model used to identify
the governing property of a soil process, its intrinsic nature (variability), and
the ultimate use of the values obtained. This holistic approach should be
applied to the selection of methods to characterize energy and mass transfer
processes in the soil (i.e., water and solute flow), sorption, transformation,
and phase changes, including microbiological processes.
This book applies this integrated approach to present a comparative
discussion of alternative methods, their practical application for characterization efforts, and an evaluation of strengths, weaknesses, and trade-offs. This
book is not a laboratory or field handbook. The authors present the
v


vi

Preface

information with a critical spirit, showing benefits, limitations, and alternatives
to the methods when available. Numerous references to some of the excellent
handbooks and publications available are given for details on each of the
methods. Some nontraditional state-of-the-art characterization methods
(NMRI, x-ray tomography, fractals) and modeling techniques are also
presented as alternatives or as integral components.
The book is divided into six sections. (Fig. P.1) The first section defines the
basis for the integrated strategy that will be developed in the following sections
(i.e., need and use, issues of spatial and temporal variability, and modeling as
an integral part of the process). Sections II–IV present the critical evaluation of
methods available for energy and water transfer, chemical transport, and soil
microbiological processes. Different methods of characterization are presented
and compared using numerous tables and diagrams to help the users identify

the most suitable option for their application. Section V discusses tools and
applications to account for the intrinsic temporal and spatial variability and
scale of soil processes. The last section is devoted to modeling aspects including
uncertainty, inverse modeling, and practical recommendations.
Section I contains three chapters. In Chapter 1, Corwin and Loague discuss
the problem of subsurface non-point-source pollution and present the
application of an integrated array of multidisciplinary, advanced information
technologies useful in characterizing the process. This chapter introduces

FIGURE P.1. Book structure and contents roadmap.


Preface

vii

the methods Sections II–IV. In Chapter 2, Campbell and Garrido explore the
role of deterministic and stochastic approaches to describe soil processes,
and how their intrinsic temporal and spatial variability affect method
selection in field studies. These issues remain the greatest challenges for
field research and limit the quantitative comparison of existing field
studies. This chapter provides the background for the chapters in Section V.
Chapter 3, written by Alvarez-Benedı´ et al., proposes that modeling
(conceptual and mathematical) is at the core of the characterization effort,
affecting not only the method selection but also the final application of
the study. A review of the conceptual building blocks needed to construct
a soil-water-solute mathematical model is presented here to illustrate
current assumptions and limitations when modeling soil-water-solute phenomena. This chapter leads into the final section (VI) of the book.
Section II, devoted to soil physical processes, opens with Chapter 4, in
which Polo et al. offer a review of water and energy exchange processes

between soil-plant and the atmosphere. A comparison of methods to account
for energy and water balance, with emphasis on evapotranspiration, is
presented. This chapter serves as background for the rest of the section, in
which water or energy are discussed. The authors reflect on how the selection
and success of the physically based methods presented require knowledge
of the relevant spatial and temporal scales and a determination of the
uncertainty associated with the variables of interest. In Chapter 5 Mun˜ozCarpena et al. present current field methods to monitor soil water status.
Soil water potential and soil water content devices are presented and
compared in terms of desired moisture range to measure, soil type, accuracy,
soil volume explored by the device, soil salinity levels, device maintenance
and installation issues, and cost. A criterion to select the most suitable
method for a given application is presented. Chapter 6, by Reynolds and
Elrick, introduces current methods to characterize soil hydraulic parameters
that control soil water redistribution and flow. They point out that in situ
measurements are essential for dealing with the extreme complexity of the
field, and that rather than using a single method, the correct approach
seems to use a ‘‘suite’’ of complementary methods. They propose the
infiltrometer, permeameter, and instantaneous profile methods as the core
of such a suite of methods. In Chapter 7, Deurer and Clothier give an indepth look at the complex soil topology using two state-of-the-art methods —
NMRI and x-ray tomography. These complementary techniques provide a
new look at the microscopic scale and topology of pore geometry and of
water and solute transport. Although for most practical applications
these methods are not yet cost-effective, they may be so in the near future.
Chapter 8, by Shirmohammadi et al., offers a critical assessment of one of the
most daunting problems encountered when describing flow and transport
processes in the soil: preferential flow. Preferential flow, probably more often
than not, presents a limit to our classical description of such processes.
Different experimental methods to quantify the presence of preferential
paths are compared. A detailed presentation of the theoretical representation

viii

Preface

of the process and alternative models follows, with emphasis on their
limitations. It is concluded that our handling of the preferential flow either
fails to be properly represented mathematically, or fails in the parametrization
for proper representation of the system.
Within Section III, dedicated to solute processes, Tuller and Islam
present in Chapter 9 an exhaustive review of field methods for characterizing
solute transport. They conclude that our ability to measure and characterize
spatial distribution of chemicals and preferential migration pathways is
restricted due to the application of in situ point measurements with
limited volume and geophysical techniques that only work indirectly or
qualitatively. The authors present electrical methods such as time domain
reflectometry (TDR), electrical resistivity tomography (ERT), and magnetic
induction as the most promising for large-scale and real-time monitoring.
In Chapter 10, Vogeler et al. show the modern application of the TDR
technique to measure not only water content but also saline solute
concentration through soil electrical conductivity (ECa) changes. The method
can be applied reliably and successfully to study nonreactive and reactive
solutes. Although the estimation of ECa with TDR is well established, the
relation of that with solute concentration is soil specific, influenced by
soil texture/structure and bulk density, and not yet fully understood. Two
weaknesses of the method are the relatively small zone of influence and
inability to discriminate between different ionic species. The method should
not replace existing monitoring techniques, but rather complement them.
In Chapter 11, Alvarez-Benedı´ et al. build on Chapters 3, 5, 9, and 10 to discuss
the laboratory characterization of solute transport through miscible displacement experiments. This method is presented as the most important for

characterizing solute transport at small to large lysimeter (column) scale,
especially if several experiments can be performed varying hydrodynamic
conditions and tracers in the same column. However, extending this
methodology to the field scale is usually not feasible, and field experiments
like the ones presented in Chapter 9 are preferred for validation purposes of the
parameters obtained in the column studies. Chapter 12, by Cornejo et al.,
compares methods to determine sorption of pesticides in the soil. This process
controls pesticide transport in different soils and conditions and has important
environmental implications. The selection of the method is governed by the
accuracy required for the intended use and regulatory environment. In Chapter
13, Rochette and McGinn take a critical look at state-of-the-art methods to
quantify another controlling factor in the distribution and degradation of
contaminants from the soil, volatilization. Three types of techniques are
compared: soil mass balance, chambers, and micrometeorology. Because of the
usually significant error associated with any one technique, the authors
recommend the use of two techniques when possible to increase confidence in
the gas flux estimates. Further research is recommended in all these techniques
to reduce current uncertainty in measurements. Chapter 14 completes Section
III. Li et al. present a critical and exhaustive look at one important aspect often
overlooked by field researchers and practitioners in soil solute characterization


Preface

ix

studies, i.e., the chemical analysis of the samples. There is a multitude of
available techniques to analyze any given element or compound. The selection
of the appropriate method is often complex, since new methods and techniques
are continuously entering the market. In addition, the intrinsic uncertainty,

interferences, and method detection limit (MDL) are not always taken into
account when interpreting the results, although these can vary greatly across
methods. Comparison of results obtained with a standard method is the
important criterion in the selection of an appropriate method. Laboratory
accreditation is discussed as a growing trend that will benefit the scientist and
clientele of analyses.
Section V (and Chapter 15) is devoted to the emerging area of soil
microbiological processes. Pell and Stenstroăm discuss the fact that, although
soil quality is closely related to soil microbiology, the latter has received little
attention. This common oversight is at the root of many of the difficulties
found in measuring or predicting reactive solute transport of important
contaminants such us pesticides and fertilizers. The authors describe how
microbial respiration and nitrification/denitrification processes affect soil
sample handling, soil reactive behavior, and how microbial parameters can
be used in soil function description and assessment of special variability at
different scales. The authors conclude that cooperation between soil physicists,
chemists, and microbiologists is needed to advance our understanding of
soil processes.
Section VI reviews available techniques that could be incorporated in
methods to address the intrinsic soil variability. In Chapter 16, Van Meirvenne
et al. give a comprehensive review of available geostatistical techniques and
how to incorporate them in field and laboratory methods. Despite its promise,
there is no single solution for all situations, and the user must understand the
underlying hypotheses and limitations before embarking on a geostatistical
analysis. In Chapter 17, Kravchenko and Pachepsky present the use of fractals
as an innovative technique to address scaling issues in soil processes. Fractal
and multifractal techniques show promise in identifying scaling laws in soil
science. Although soils are not ideal fractals and because fractal scaling is only
applicable within a range of scales, these models present limitations. One
important advantage of fractal models of variability is their ability to better

simulate ‘‘rare’’ occurrences in soils (i.e., large pores, preferential pathways,
very high conductivities, localized bacteria habitats, etc.). These rare
occurrences often define soil behavior at scales coarser than observational
ones. Corwin provides in Chapter 18 an overview of the characterization of soil
spatial variability using ECa-directed soil sampling for three different
landscape-scale applications: (1) solute transport modeling in the vadose
zone, (2) site-specific crop management, and (3) soil quality assessment.
Guidelines, methodology, and strengths and limitations are presented for
characterizing spatial and temporal variation in soil physicochemical properties using ECa-directed soil sampling. Fast geospatial ECa measurements can
be made with available mobile electrical resistivity (ER) or electromagnetic
induction (EMI) equipment coupled with GPS. The author stresses that


x

Preface

without ground-truthing with soil samples, the interpretation of measurements
is questionable and is not advised.
Section VI is devoted to modeling tools. In Chapter 19, Trevisan and
Vischetti present the issue of modeling uncertainty across different scales.
Uncertainty analysis techniques are presented as well as sources of errors. Data
availability, choice of model, parameter estimation error, error propagation
in model linkages, and upscaling are presented as significant sources of error
that must be controlled in the modeling application. Chapter 20, by Lambot
et al., examines the utility of inverse modeling (IM) techniques to obtain
parameters for characterizing a soil process. Although IM is attractive, since it
can reduce the cost associated with experimental measurement of model
parameters, the success of the procedure depends on the suitability of the
forward model, objective function, identifiability of parameters, uniqueness

and stability of the inverse solution, and robustness of the IM algorithm.
A comparison of available techniques and possible pitfalls of this promising
technique are presented. Finally, Chapter 21 by Jantunen et al. discusses
the practical aspects of choosing a suitable model for a given purpose and how
to use it correctly and also reviews recent pesticide-fate models and their
practical applications.
In the words of D. Hillel (1971, Soil and Water, Physical Principles and
Processes), ‘‘No particular book by one or even several authors is likely to
suffice. The field [. . .] is too important, too complex and too active to be
encapsulated in any one book, which necessarily represents a particular point
of view.’’ We hope that the views presented herein by the excellent group of
authors will spark a critical sense in the reader when discussing methods for
soil process characterization.
R. Mun˜oz-Carpena
J. A´lvarez-Benedı´


Editors
Javier A´lvarez-Benedı´ obtained his Science and Doctoral
Degrees at the University of Valladolid (Spain) in 1988
and 1992. His doctoral work was related to the
characterization and modeling of soil heat flux and
heat balance at the soil surface in greenhouses with
energy support at a fixed soil depth. After completing his
Ph.D. degree, he worked as a researcher at the Servicio
de Investigacio´n Agraria in Valladolid (Spain). In this
research center, he was involved in the characterization
of soil–solute processes such as sorption, transport, and
volatilization of soil applied pesticides at different working scales. The focus of his research has been modeling
and characterization as close-coupled topics. In 2003,

Dr. A´lvarez-Benedı´ joined Instituto Tecnolo´gico
Agrario de Castilla y Leo´n, Valladolid, Spain, where he
provides technical oversight and program management.
Dr. A´lvarez-Benedı´ has been an active member of the
Scientific Committee of the Spanish Vadose Zone Group
‘‘Zona no Saturada,’’ and he was the president of the
organizing committee at the biannual meeting held at
Valladolid in November 2003. He is a member of the Soil
Science Society of America and the International
Association of Hydrogeologists.
Rafael Mun˜oz-Carpena is an assistant professor in
hydrology and water quality at the University of
Florida’s IFAS/TREC and Department of Agricultural
and Biological Engineering (United States), and tenured
researcher on leave at the Instituto Canario de Investigaciones Agrarias (Spain). He obtained his professional engineering degree at Universidad Polite´cnica de
Madrid (Spain) and his Ph.D. at North Carolina State
University (United States), where he developed and
tested a surface water quality numerical model,
VFSMOD. He has taught courses internationally in
hydrology, soil physics for irrigation, and instrumentation for hydrological research. Currently his work is
focused in hydrological and water quality issues
xi


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The Editors

surrounding the Everglades restoration effort in Florida (United States), one of
the most expensive and ambitious environmental projects in history. His work

involves field and computer modeling activities to understand water flow and
quality in the area, including solute transport in the soil. He has been an active
member of the Scientific Committee of the Spanish Vadose Zone Group for the
last 10 years, where soil characterization research has been a central issue. Dr.
Mun˜oz-Carpena serves as Associate Editor for Transactions of ASAE and
Applied Engineering in Agriculture and is a member of the American Society of
Agricultural Engineers and the American Geophysical Union.


Contributors
Javier Alvarez-Bened
Instituto Tecnologico Agrario de Castilla y Leon
Valladolid, Spain
Lars Bergstroăm
Division of Water Quality Management
Swedish University of Agricultural Sciences
Uppsala, Sweden
S. Bolado
Departamento de Ingenierı´ a Quı´ mica
Universidad de Valladolid
Valladolid, Spain
David Bosch
Research Hydraulic Engineer
USDA-ARS, SEWRL
Tifton, Georgia
Moira Callens
Laboratory of Hydrology and Water Management
Ghent University
Gent, Belgium
Chris G. Campbell

Earth Sciences Division
Lawrence Livermore National Laboratory
Livermore, California
Ettore Capri
Istituto di Chimica Agraria ed Ambientale
Universita` Cattolica del Sacro Cuore
Piacenza, Italy
Rafael Celis
Instituto de Recursos Naturales y Agrobiologı´ a
de Sevilla, CSIC
Sevilla, Spain
xiii


xiv

Brent E. Clothier
Environment and Risk Management Group
HortResearch Institute
Palmerston North, New Zealand
Juan Cornejo
Instituto de Recursos Naturales y Agrobiologı´ a
de Sevilla, CSIC
Sevilla, Spain
Dennis L. Corwin
USDA-ARS
George E. Brown, Jr. Salinity Laboratory
Riverside, California
Lucı´ a Cox
Instituto de Recursos Naturales y Agrobiologı´ a

de Sevilla, Sevilla
CSIC
Spain
Markus Deurer
Institute for Soil Science
University of Hannover
Hannover, Germany
Ahmed Douaik
Department of Soil Management and Soil Care
Ghent University
Gent, Belgium
Marı´ a P. Gonza´lez-Dugo
Department of Soils and Irrigation
CIFA, Alameda del Obispo, IFAPA
Co´rdoba, Spain
David E. Elrick
Department of Land Resource Science
University of Guelph
Guelph, Ontario, Canada
Fernando Garrido
Department of Soils
Centro de Ciencias Medioambientales, CSIC
Madrid, Spain
Juan Vicente Gira´ldez
Department of Agronomy
University of Co´rdoba
Co´rdoba, Spain

Contributors

Contributors

Marı´ a P. Gonza´lez-Dugo
Department of Soils and Irrigation
CIFA, Alameda del Obispo, IFAPA
Co´rdoba, Spain
Steve Green
HortResearch Institute
Palmerston North, New Zealand
Ma Carmen Hermosı´ n
Instituto de Recursos Naturales y Agrobiologı´ a
de Sevilla CSIC, Sevilla, Spain
F. Hupet
Department of Environmental Sciences and Land Use Planning
Catholic University of Louvain
Louvain-la-Neuve, Belgium
Mohammed R. Islam
Soil and Land Resources Division
University of Idaho, Moscow, Idaho
Anna Paula Karoliina Jantunen
Department of Biology, University of Joensuu
Joensuu, Finland
M. Javaux
Department of Environmental Sciences and Land Use Planning
Catholic University of Louvain
Louvain-la-Neuve, Belgium
A. N. Kravchenko
Department of Crop and Soil Sciences
Michigan State University

East Lansing, Michigan
S. Lambot
Department of Environmental Sciences and Land Use Planning
Catholic University of Louvain
Louvain-la-Neuve, Belgium
Yuncong Li
Department of Soil and Water Sciences
Tropical Research and Education Center
University of Florida
Homestead, Florida

xv


xvi

Keith Loague
Department of Geological and Environmental Sciences
Stanford University
Stanford, California
Sean M. McGinn
Lethbridge Research Centre
Agriculture and Agri-Food Canada
Lethbridge, Alberta, Canada
H. Montas
Biological Resources Engineering Department
University of Maryland
College Park,
Maryland
Rafael Mun˜oz-Carpena

Agricultural and Biological Engineering Department
IFAS/TREC
University of Florida
Homestead, Florida
Y. A. Pachepsky
USDA-ARS Environmental Microbial Safety Laboratory
Beltsville, Maryland
Mikael Pell
Swedish University of Agricultural Sciences
Department of Microbiology
Uppsala, Sweden
Marı´ a Jose´ Polo
Department of Agronomy
University of Co´rdoba
Co´rdoba, Spain
Carlos M. Regalado
Departamento de Suelos y Riegos
Instituto Canario de Investigaciones Agrarias (ICIA)
La Laguna, Tenerife, Spain
W. Daniel Reynolds
Greenhouse and Processing Crops Research Centre
Agriculture and Agri-Food Canada
Harrow, Ontario
Canada

Contributors


Contributors

Axel Ritter
Departamento de Suelos y Riegos
Instituto Canario de Investigaciones Agrarias
La Laguna, Tenerife, Spain
Philippe Rochette
Soils and Crops Research and Development Centre
Agriculture and Agri-Food Canada
Sainte-Foy, Quebec,
Canada
Ali Sadeghi
Environmental Quality Laboratory
USDA-ARS, Beltsville, Maryland
Adel Shirmohammadi
Biological Resources Engineering Department
University of Maryland
College Park, Maryland
John Stenstroăm
Department of Microbiology
Swedish University of Agricultural Sciences
Uppsala, Sweden
Marco Trevisan
Istituto di Chimica Agraria ed Ambientale
Universita` Cattolica del Sacro Cuore
Piacenza, Italy
Markus Tuller
Soil and Land Resources Division
University of Idaho
Moscow, Idaho
M. Vanclooster
Department of Environmental Sciences and Land Use Planning

Catholic University of Louvain
Louvain-la-Neuve, Belgium
Karl Vanderlinden
Department of Soils and Irrigation
CIFA, Las Torres-Tomejil, IFAPA
Sevilla, Spain

xvii


xviii

Marc Van Meirvenne
Department of Soil Management and Soil Care
Ghent University
Gent, Belgium
Niko E.C. Verhoest
Laboratory of Hydrology and Water Management
Ghent University
Gent, Belgium
Lieven Vernaillen
Department of Soil Management and Soil Care
and Laboratory of Hydrology and Water Management
Ghent University
Gent, Belgium
Costantino Vischetti
Dipartimento di Scienze Ambientali e delle Produzioni Vegetali
Universita` Politecnica delle Marche
Ancona, Italy
I. Vogeler

Environment and Risk Management Group
HortResearch Institute
Palmerston North, New Zealand
Jianqiang Zhao
Bureau of Pesticide
Division of Agricultural Environmental Services
Florida Department of Agriculture and Consumer Services
Tallahassee, Florida
Meifang Zhou
Water Quality Analysis Division
Environmental Monitoring & Assessment Department
South Florida Water Management District
West Palm Beach, Florida

Contributors


Table of Contents
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
v
Editors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii

Section I
Integration of Soil Process Characterization
Chapter 1

1.1

1.2

Multidisciplinary Approach for Assessing Subsurface
Non-Point Source Pollution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Dennis L. Corwin and Keith Loague
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.1.1 Definition and Characteristics of NPS Pollution. . . . . . . . . . . .
1.1.2 The NPS Pollution Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.1.2.1 The Issue of Health. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.1.2.2 Global Scope and Significance . . . . . . . . . . . . . . . . . . . .
1.1.2.3 Common NPS Pollutants . . . . . . . . . . . . . . . . . . . . . . . . .
1.1.3 Justification for Assessing NPS Pollution in Soil . . . . . . . . . . .
Multidisciplinary Approach for Assessing Subsurface
NPS Pollutants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.1 Deterministic Modeling Process . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.1.1 Model Conceptualization . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.1.2 Model Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.1.3 Verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.1.4 Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.1.5 Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.1.6 Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.1.7 Simulation and Uncertainty Analysis. . . . . . . . . . . . . .
1.2.2 Spatial Factors to Consider When Modeling NPS
Pollutants in Soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.2.1 Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.2.2 Spatial Variability and Structure . . . . . . . . . . . . . . . . . .
1.2.3 Modeling NPS Pollutants in Soil. . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.3.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.3.1.1 Measured Data . . . . . . . . . . . . . . . . . . . . . . . .
1.2.3.1.2 Estimated Data . . . . . . . . . . . . . . . . . . . . . . . .

1.2.3.1.3 Existing Data . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.3.2 GIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1
2
3
4
4
5
8
9
11
13
14
15
16
16
18
19
21
23
23
25
30
31
31
32
33
34

xx

Table of Contents

1.2.3.3

Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.3.3.1 GIS-Based Deterministic Models . . . . . . .
1.2.3.3.2 GIS-Based Stochastic Models . . . . . . . . . .
1.2.4 Role of Geostatistics and Fuzzy Set Theory . . . . . . . . . . . . . . . .
1.3 Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.3.1 San Joaquin Valley Groundwater Vulnerability Study . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

36
37
38
39
42
42
46

Spatial and Temporal Variability of Soil Processes:
Implications for Method Selection and
Characterization Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

59

Chris G. Campbell and Fernando Garrido

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1.1 Need for Field Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1.2 Preliminary Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1.2.1 Determinism in Soil Processes. . . . . . . . . . . . . . . . . . . . .
2.1.2.2 Stochasticity in Soil Processes . . . . . . . . . . . . . . . . . . . . .
2.2 On Spatial Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.3 On Temporal Variability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.4 Issues in Field Study Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.4.1 Issues of Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.4.2 Characterizing Scale of Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.4.3 Irrigation, Solute Delivery, and Three-Dimensional Flow. . .
2.5 Summary and Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Appendix: Breakthrough Curve Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . .
Moment Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Temporal Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

60
60
61
63
63
64
67
69
69
71
73
75

79
79
79
80
80

Modeling as a Tool for the Characterization of Soil
Water and Chemical Fate and Transport . . . . . . . . . . . . . . . . . . .

87

Chapter 2

2.1

Chapter 3

3.1
3.2

3.3

Javier A´lvarez-Benedı´ , Rafael Mun˜oz-Carpena and
Marnik Vanclooster
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
General Conceptualization of Soil Processes. . . . . . . . . . . . . . . . . . . . . . .
3.2.1 Instantaneous Equilibrium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.2 Irreversible Kinetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.3 Reversible kinetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.4 Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Soil-Water Transport Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3.1 Classical Description of Water Movement . . . . . . . . . . . . . . . . .
3.3.2 Characterization of Water Content–Pressure Head and
Hydraulic Conductivity–Pressure Head Relationships . . . . . .

88
90
91
92
94
95
96
96
98


Table of Contents

3.3.3 Dual Porosity Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Soil-Solute Transport Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4.1 Classical Description of Solute Movement . . . . . . . . . . . . . . . . .
3.4.2 Nonequilibrium Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4.3 Solute Dispersion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4.4 Sorption. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4.5 Volatilization and Gas Solubility. . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4.6 Transformation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.5 Modeling Soil Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.5.1 Building Soil Processes Models . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.5.2 Inverse Characterization of Soil Processes. . . . . . . . . . . . . . . . . .
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Notation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3.4

xxi

100
101
101
102
104
107
109
111
113
113
115
115
116
117

Section II
Soil and Physical Processes: Energy and Water
Chapter 4

4.1

4.2

Techniques for Characterizing Water and Energy
Balance at the Soil-Plant-Atmosphere Interface . . . . . . . . . . . . . 123

M. J. Polo, J. V. Gira´ldez, M. P. Gonza´lez-Dugo and
K. Vanderlinden
The Components of Water and Energy Balances:
Description and Nature of Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.1 Description and Nature of Processes and
Associated Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.2 Different Approaches and Spatiotemporal Scales . . . . . . . . . . .
4.1.3 Remote Sensing: Potential as a Global Data Source. . . . . . . .
Modeling of the Water and Energy Balance at the
Soil-Plant-Atmosphere Interface and Scale Effects. . . . . . . . . . . . . . . . .
4.2.1 The Use of Models for the Description of
Soil-Plant-Atmosphere Exchange Processes. . . . . . . . . . . . . . . . .
4.2.1.1 A Simple Water and Energy Balance Model:
The Interaction between Land and
Atmosphere . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.1.2 The Force Restore Approach . . . . . . . . . . . . . . . . . . . . .
4.2.1.3 Dynamics of Soil Moisture Using a Simple
Water Balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.1.4 Exploration of Optimal Conditions for
Vegetation through a Water Balance Model . . . . . . .
4.2.1.5 Strengths and Weaknesses . . . . . . . . . . . . . . . . . . . . . . . .
4.2.2 Interaction of Model Development and Temporal and
Spatial Scales. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.3 Hydrologic Data Assimilation . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

124
125

127
128
129
129

129
131
132
133
136
137
138


xxii

Table of Contents

4.3

140
140
141
141
142
142
144
146
147
147

The Vegetation Components: Measurement Methods. . . . . . . . . . . . . .
4.3.1 Interception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.3.1.1 Methods of Estimation of Interception . . . . . . . . . . . .
4.3.1.2 Strengths and Weaknesses . . . . . . . . . . . . . . . . . . . . . . . .
4.3.2 Evapotranspiration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.3.2.1 Conservation of Mass Approach . . . . . . . . . . . . . . . . . .
4.3.2.2 Conservation-of-Energy Approach . . . . . . . . . . . . . . . .
4.3.2.3 Plant Physiology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.3.2.4 ET Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.3.2.5 Strengths and Weaknesses . . . . . . . . . . . . . . . . . . . . . . . .
4.3.3 Recharge and Temporal Soil Water
Content Variations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.4 The Remote Sensing Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.4.1 Relations between Spectral Measurements and
Biophysical Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.4.1.1 VIS-NIR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.4.1.2 Thermal Infrared . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.4.1.3 Microwave . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.4.1.4 Strengths and Weaknesses . . . . . . . . . . . . . . . . . . . . . . . .
4.5 Recommendations and Future Research . . . . . . . . . . . . . . . . . . . . . . . . . .
Notation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Chapter 5

5.1
5.2

148

150
151
151
152
153
154
155
155
158

Field Methods for Monitoring Soil Water
Status. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167

Rafael Mun˜oz-Carpena, Axel Ritter and David Bosch
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Methods of Characterization: Trade-offs: Comparative Study . . . . .
5.2.1 Volumetric Field Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.1.1 Neutron Moderation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.1.2 Dielectric Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.1.2.1 Time Domain Reflectometry
(TDR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.1.2.2 Frequency Domain (FD): Capacitance
and FDR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.1.2.3 Amplitude Domain Reflectometry
(ADR): Impedance . . . . . . . . . . . . . . . . . . . . .
5.2.1.2.4 Phase Transmission (Virrib) . . . . . . . . . . . .
5.2.1.2.5 Time Domain Transmission (TDT) . . . . .
5.2.1.3 Other Volumetric Field Methods. . . . . . . . . . . . . . . . . .
5.2.2 Tensiometric Field Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.2.1 Tensiometer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5.2.2.2 Resistance Blocks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.2.2.1 Gypsum (Bouyoucos) Block . . . . . . . . . . . .

168
170
170
170
172
173
175
176
178
179
179
181
181
182
183


Table of Contents

xxiii

5.2.2.2.2 Granular Matrix Sensors (GMS) . . . . . . .
5.2.2.3 Heat Dissipation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.2.4 Soil Psychrometer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.3 Recommendations and Future Research . . . . . . . . . . . . . . . . . . . . . . . . . .
Acknowledgment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

184
185
186
188
193
193

Chapter 6

6.1
6.2
6.3

Measurement and Characterization of Soil
Hydraulic Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197

W. D. Reynolds and D. E. Elrick
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Principles of Soil Water Flow and Parameter Definitions . . . . . . . . . .
Field Methods for In Situ Measurement of
Soil Hydraulic Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.1 Ring Infiltrometers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.1.1 Ring Infiltration Theory . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.1.1.1 Steady-State Infiltration . . . . . . . . . . . . . . . .
6.3.1.1.2 Transient Infiltration . . . . . . . . . . . . . . . . . . .
6.3.1.2 Single-Ring and Double-Ring
Infiltrometer Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.1.2.1 Traditional Steady Flow Analyses . . . . . .
6.3.1.2.2 Updated Steady Flow Analyses. . . . . . . . .

6.3.1.2.3 Traditional Transient Flow
Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.1.2.4 Updated Transient Flow Analyses . . . . . .
6.3.1.3 Twin-Ring and Multiple-Ring Infiltrometer
Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.1.4 Generalized Steady Flow Analysis for
Ring Infiltrometers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.1.5 Calculation of Matric Flux Potential,
Sorptivity, and Wetting Front Pressure Head. . . . . .
6.3.1.6 Strengths and Weaknesses of Ring
Infiltrometer Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.2 Well or Borehole Permeameters. . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.2.1 Well Permeameter Flow Theory. . . . . . . . . . . . . . . . . . .
6.3.2.2 Original Well Permeameter Analysis . . . . . . . . . . . . . .
6.3.2.3 Updated Well Permeameter Analyses . . . . . . . . . . . . .
6.3.2.3.1 Improved Steady Flow Analyses. . . . . . . .
6.3.2.3.2 Transient Flow Analyses . . . . . . . . . . . . . . .
6.3.2.4 Strengths and Weaknesses of Well
Permeameter Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.3 Tension or Disc Infiltrometers . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.3.1 Tension Infiltrometer Flow Theory. . . . . . . . . . . . . . . .
6.3.3.2 Steady Flow — Multiple Head Tension
Infiltrometer Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . .

198
199
203
204
204
204

206
207
207
208
210
212
213
215
216
216
217
220
221
222
222
224
226
227
228
232


xxiv

Table of Contents

6.3.3.3

Transient Flow — Single Head Tension
Infiltrometer Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.3.3.4 Accounting for Contact Sand . . . . . . . . . . . . . . . . . . . . .
6.3.3.5 Strengths and Weaknesses of the Tension
Infiltrometer Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.4 Other Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.4.1 Instantaneous Profile Method. . . . . . . . . . . . . . . . . . . . .
6.3.4.2 Strengths and Weaknesses of the Instantaneous
Profile Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.4 Recommendations for Further Research . . . . . . . . . . . . . . . . . . . . . . . . . .
6.5 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Chapter 7

7.1
7.2

7.3

236
238
240
242
242
245
246
247
247

Unraveling Microscale Flow and Pore Geometry:
NMRI and X-Ray Tomography. . . . . . . . . . . . . . . . . . . . . . . . . . . . 253

Markus Deurer and Brent E. Clothier
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Nuclear Magnetic Resonance Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2.1 Measurement Principle: The Behavior of Spins in
Magnetic Fields . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2.2 Fourier Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2.2.1 Pulse Sequence Design . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2.2.2 Key Hardware Components . . . . . . . . . . . . . . . . . . . . . .
7.2.2.2.1 NMR Magnet. . . . . . . . . . . . . . . . . . . . . . . . . .
7.2.2.2.2 NMR Probe . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2.2.2.3 Magnetic Field Gradient Coils . . . . . . . . .
7.2.2.2.4 NMR Imaging Spectrometer . . . . . . . . . . .
7.2.3 Applications of NMRI to Soil-Plant-Water Processes . . . . . .
7.2.4 Strengths and Weaknesses of NMR Imaging . . . . . . . . . . . . . . .
7.2.4.1 Strengths . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2.4.2 Weaknesses. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
X-Ray Computed Tomography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.3.1 Measurement Principle: Attenuation of X-Ray
Photon Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.3.2 Measurement Components. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.3.3 Analysis of Measured Attenuation . . . . . . . . . . . . . . . . . . . . . . . . .
7.3.3.1 Interpretation of Attenuation Coefficients . . . . . . . . .
7.3.3.1.1 Homogeneous Object and
Monochromatic X-Rays. . . . . . . . . . . . . . . .
7.3.3.1.2 Heterogeneous Object and
Monochromatic X-Rays. . . . . . . . . . . . . . . .
7.3.1.1.3 Heterogeneous Object and
Polychromatic X-Rays . . . . . . . . . . . . . . . . .
7.3.3.2 Image Reconstruction. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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