bluuebunny/crossref_metadata_2025 huggingface dataset:
Facies Models at the Lake Basin Scale
Authors: Cohen Andrew S.
Published: November 2020

Understanding the historical evolution of sedimentation in a lake requires not only a grounding in facies interpretation but also an understanding of the larger-scale, lakewide linkages between deposition and those factors influencing sedimentation. The facies models we examined in chapter 7 can be linked to understand the differences in deposits between lake basins. Basin-scale facies models focus on the major interactions between climate or tectonic/ volcanic activity and sedimentation, attempting to explain why particular facies types develop in particular areas or at particular times in a lake’s history. Here I will focus on a few examples from the most intensively studied depositional settings, including lake types defined by mode of origin and evolution (rifts, glacial lakes, etc.) as well as saline lakes and playas, which share chemical and climatic attributes. Large-scale facies modeling in rift lakes has been driven by a need to understand the occurrence of hydrocarbons in ancient rifts (Lambiase, 1990; Katz, 2001). This in turn spurred a rapid accumulation of seismic reflection and facies data in the East African rift lakes and Lake Baikal (Russia) during the 1980s and 1990s, as well as attempts to synthesize these data and integrate them into general models. As we saw in chapter 2, the evolution of rift basins involves the development of asymmetric half-grabens and, in larger lake systems, the linkage of these half-grabens in a linear chain. As rift basins age, progressive deformation will eventually cause extensive deformation on both sides of the basin, transforming them into asymmetric full grabens, as seen in Lake Baikal today. This pattern of tectonic development has consequences for geomorphology, sediment delivery rates and locations, and sediment composition, that also vary depending on whether the lake basin is relatively full (high-stand conditions) or empty (low-stand) (Rosendahl et al., 1986; Cohen, 1990; Scholz and Rosendahl, 1990; Tiercelin et al., 1992; Soreghan and Cohen, 1996). Large-scale depositional patterns in a rift lake therefore represent an interplay between tectonic and climatic forces, factors that operate on somewhat different time scales.
Precipitation Rate
Authors: Brock Fred V. , Richardson Scott J.
Published: November 2020

Accurate rainfall measurements are required, usually over broad areas because of the natural variability of rain. Coverage of a large area can be achieved using many distributed point measurement instruments or a remote sensor with large areal coverage, such as radar, or both. This chapter describes several methods for measuring precipitation, both liquid and frozen types. Point measurements, e.g., rain gauges, are emphasized although a section on weather radar is included because this is a very important method of estimating precipitation. Precipitation rate could be specified as the mass flow rate of liquid or solid water across a horizontal plane per unit time: Mw in kg m-2 s-1. Water density is a function of temperature but that can be ignored in this context; then the volume flow rate, or precipitation rate, becomes R = Mw/pw in m s-1 or, more conveniently, in units of mm hr-1 or mm day-1. Precipitation rate is the depth to which a flat horizontal surface would have been covered per unit time if no water were lost by run-off, evaporation, or percolation. Precipitation rate is the quantity used in all applications but, in many cases, the unit of time is not specified, being understood for the application, commonly per day or per storm period. Some gauges measure precipitation, rain, snow and other frozen particles, while others measure only rain. Rainfall can be measured using point measurement techniques which involve measuring a collected sample of rain or measuring some property of the falling rain such as its optical effects. The other general technique is to use remote sensing, usually radar, to estimate rainfall over a large area. Both ground-based and space-based radars are used for rain measurement. A precipitation gage (US) or gauge (elsewhere) could be a simple open container on the ground to collect rain, snow, and hail. However, this is not a practical method for estimating the amount of precipitation because of the need to avoid wind effects, enhance accuracy and resolution, and make a measurement representative of a large area. These issues will be discussed in sect. 9.2.1.6.
Sampling and Analog-to-Digital Conversion
Authors: Brock Fred V. , Richardson Scott J.
Published: November 2020

Along the signal path from the atmosphere, through the sensors and the data logger to the final archive, the signal quality may be irreversibly comprised. These faults include aliasing caused by poor sampling practice and quantization in an analog to- digital converter. Aliasing and quantization will be defined in this chapter. Drift in some of the system parameters, such as temperature sensitivity, is generally preventable but is not always reversible. Sampling of a signal occurs in the time domain and, frequently, in the space domain with one, two, or three dimensions. In the time domain, the time interval between successive points is called the sampling interval and the data logger controls this interval. When two or more sensors are distributed, vertically, along a mast then the system is sampling both in the time domain and in the space domain. When multiple measurements are arrayed along the surface of the earth, the sampling is occurring in time and in two or three space dimensions. Most meteorological systems are undersampled both in time and space. Space undersampling is an economic necessity. The consequence of undersampling is that frequencies above a certain limit, called the Nyquist frequency, will appear at lower frequencies and this is an irreversible effect. Quantization occurs when the signal is converted from analog to digital in the analog-to-digital converter. Since the range of the converter is expressed in a finite number of digital states, signal amplitudes smaller than this quantity will be lost. This is another irreversible effect. These are not the only irreversible effects. For example, drift is caused by physical changes in a sensor or other component of the measurement system. Drift may have a causal component, such as undocumented temperature sensitivity, and a random component such as wearing of an anemometer bearing. The former is theoretically preventable and reversible, whereas the latter is irreversible. Each element of the system may include some signal averaging, and each element may add bias and gain. As noted in earlier chapters, a sensor is a transducer, a device that changes energy from one form to another.
Policy Responses to El Niño 1997-1998 : Implications for Forecast Value and the Future of Climate Services
Authors: Pielke Roger A., Jr.
Published: November 2020

El Niño 97-98 will be remembered as one of the strongest ever recorded (Glantz, 1999). For the first time, climate anomalies associated with the event were anticipated by scientists, and this information was communicated to the public and policy makers to prepare for the “meteorological mayhem that climatologists are predicting will beset the entire globe this winter. The source of coming chaos is El Niño . . .” (Brownlee and Tangley, 1997). Congress and government agencies reacted in varying ways, as illustrated by the headlines presented in Figure 7-1. The link between El Niño events and seasonal weather and climate anomalies across the globe are called teleconnections (Glantz and Tarlton, 1991). Typically, during an El Niño cycle hurricane frequencies in the Atlantic are depressed, the southeast United States receives more rain than usual (chapter 2), and parts of Australia, Africa, and South America experience drought. Global attention became focused on the El Niño phenomenon following the 1982-1983 event, which, at that time, had the greatest magnitude of any El Niño observed in more than a century. After El Niño 82-83, many seasonal anomalies that had occurred during its two years were attributed, rightly or wrongly, to its influence on the atmosphere. As a consequence of the event, societies around the world experienced both costs and benefits (Glantz et al., 1987). Another lasting consequence of the 1982-1983 event was an increase in research into the phenomenon. One result of this research in the late 1990s has been the production of forecasts of El Niño (and La Niña) events and the seasonal climate anomalies associated with them. This chapter discusses the use of climate forecasts by policy makers, drawing on experiences from El Niño 97-98, which replaced the 1982-1983 eventas the” climate event of the century.” The purpose of this chapter is to draw lessons from the use of El Niño -based climate forecasts during the 1997-1998 event in order to improve the future production, delivery, and use of climate predictions. This chapter focuses on examples of federal, state, and local responses in California, Florida, and Colorado to illustrate the lessons.
Soil–Atmosphere Exchange of Trace Gases in the Colorado Shortgrass Steppe
Authors: Mosier Arvin R. , Parton William J.
Published: November 2020

During the past half century, atmospheric concentrations of important greenhouse gases including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) have been increasing at unprecedented rates ( I PCC, 1996, 2007). Trace gases such as methane (CH4), nitric oxide (NO), and nitrous oxide (N2O) are exchanged regularly between the soil and atmosphere, playing important roles in the greenhouse effect, in atmospheric chemistry, and in the redistribution of ecosystem nitrogen (N). Soils can be important sources of greenhouse gases, commonly contributing up to two thirds of atmospheric N2O and more than one third of atmospheric CH4 (Monson and Holland, 2001; Smith et al., 2003). Recent extensive changes in land management and in cultivation, which can stimulate N2O production and/or decrease CH4 uptake, could be contributing to the observed increases of both CH4 and N2O in the atmosphere (IPCC, 2007). Although the absolute amount of trace gases (such as CH4, NO, and N2O) released into the atmosphere from soils may be small, these gases are extremely effective at absorbing infrared radiation (Smith et al., 2003). Methane, for example, is 20 to 30 times more effcient than CO2 as a greenhouse gas (LeMer and Roger, 2001). As a result, even small changes in the production or consumption of these gases by soils could dramatically influence climate change. Of the gases exchanged between the soil and atmosphere, the major reactive ones are oxides of N (NO and NO2, collectively referred to as NOx). Combustion is a major source of NOx, but native and N-fertilized soils also contribute signi3 - cant amounts of NOx to the atmosphere (Williams et al., 1992). Nitric and nitrous oxide play a complex role in atmospheric chemistry. At low concentrations, it catalyzes the breakdown of ozone. At higher concentrations it can interact with carbon monoxide (CO), hydroxyl radicals (OH.), and hydrocarbons to produce ozone. Atmospheric NOx is converted within days to nitric acid, which is an important component (30% to 50%) of acidity in precipitation (Williams et al., 1992).
The Shortgrass Steppe and Ecosystem Modeling
Authors: Parton William J. , Del Grosso Stephen J.
Published: November 2020

Ecological modeling has played a key role in scientific investigations of the SGS LTER during the past several decades. The SGS LTER site, focused initially on the Central Plains Experimental Range (CPER), was the main grassland research site for the Grassland Biome component of the U.S. IBP effort (Lauenroth et al., this volume, chapter 1). Initial development of ecosystem models occurred from 1 970 to 1 975 as p art of t he I BP . All the U.S. I BP projects (grassland, tundra, desert, deciduous forest, and coniferous forest biomes) included research on the development of ecosystem models, with the goals of using models to help formulate and interpret field experiments, and of projecting the impact of changes in management practices on ecosystem dynamics. Models were developed as part of the Grassland Biome project (Bledsoe et al., 1971; Innis, 1978), and included modeling specialists who worked with research biologists on the development and formulation of the ecosystem models. The modeling activities of t he U.S. IBP Grassland Biome project included developing the ELM Grassland model (Innis, 1978). The ELM model was a complex process-oriented model that was intended to be used at all the Grassland Biome sites in the United States. This model was developed by postdoctoral fellows who were to formulate the different submodels, and then link the submodels using software that was developed as part of the program. The submodels included a plant production submodel, a cattle production submodel, a linked nutrient cycling and soil organic matter submodel, a grasshopper dynamics submodel, and a soil temperature and water submodel. Biophysical and biological data from the different sites were collected to develop and test the model. Model development was constrained by lack of knowledge about the biological processes that control ecosystem behavior, and by lack of appropriate data to test the ability of the model to simulate ecosystem responses to changes in grazing and fertility management practices. However, the ELM Grassland model was quite successful at investigating the interactions of different components of the ecosystem, and at helping to formulate new research efforts.
The Future of the Shortgrass Steppe
Authors: Burke Ingrid C. , Lauenroth William K.
Published: November 2020

Where lies the future of the shortgrass steppe? In prior chapters we have described the remarkable resilience of the shortgrass steppe ecosystem and its organisms to past drought and grazing, and their sensitivity to other types of change. Emerging from this analysis is the idea of vulnerability to two main forces: future changes in precipitation or water availability, and direct human impacts. What are the likely changes in the shortgrass steppe during the next several decades? Which of the changes are most likely to affect major responses in the plants, animals, and ecosystem services of the shortgrass steppe? In this chapter we evaluate the current status of the shortgrass steppe and its potential responses to three sets of factors that will be driving forces for the future of the steppe: land-use change, atmospheric change, and changes in diseases. Referring to the early 1900s, James Michener in his novel Centennial (1974) wrote the following:… The old two-part system that had prevailed at the end of the nineteenth century— rancher and irrigator—was now a tripartite cooperation: the rancher used the rougher upland prairie; the irrigation farmer kept to the bottom lands; and the drylands gambler plowed the sweeping 0 eld in between, losing his seed money one year, reaping a fortune the next, depending on the rain. It was an imaginative system, requiring three different types of man, three different attitudes toward life. . . . (p. 1081)… Even today, because of the strong water limitation for cropping, the shortgrass steppe remains relatively intact, or at least unplowed, in contrast to other grassland ecosystems (Samson and Knopf, 1994). More than half of the shortgrass steppe remains in untilled, landscape-scale tracts, compared with only 9% of tallgrass prairie and 39% of mixed-grass prairie (The Nature Conservancy, 2003). These large tracts, including those in the national grasslands (Pawnee, Cimarron, Comanche, and Kiowa/Rita Blanca), provide the greatest opportunity for preserving key ecological processes and biological diversity.
Who Got There First
Authors: Lienhard John H.
Published: November 2020

Years ago, a curator at the Smithsonian Institution said to me, “Scientists and engineers are nutty on the subject of priority.” That was before I realized just how far-reaching that nuttiness was or how misguided the very concept of priority is. As an example, try searching out the inventor of the telephone. Instead of Alexander Graham Bell, you may get the name of a German, Johann Philipp Reis. The common wisdom is that Reis invented a primitive telephone that was only marginally functional, while Bell’s phone really worked. Reis was a twenty-six-year-old science teacher when he began work on the telephone in 1860. His essential idea came from a paper by a French investigator named Bourseul. In 1854 Bourseul had explained how to transmit speech electrically. He wrote: . . . Speak against one diaphragm and let each vibration “make or break” the electric contact. The electric pulsations thereby produced will set the other diaphragm working, and [it then reproduces] the transmitted sound. . . . Only one part of Bourseul’s idea was shaky. To send sound, the first diaphragm should not make and break contact; instead it should vary the flow of electricity to the second diaphragm continuously. While Reis had used Bourseul’s term “make or break,” his diaphragm actually drove a thin rod to varying depth in an electric coil. Instead of making and breaking the current, he really did vary it continuously. Bell faced the same problem when he began work on his telephone a decade later. First, he used a diaphragm-driven needle that entered a water-acid solution to create a continuously variable resistance and a smoothly varying electrical current. Bell got the idea from another American, inventor Elisha Gray. Of course, a liquid pool comes with two problems. One is evaporation; the other is immobility. Bell soon gave it up in favor of a system closer to Reis’ electromagnet. Still, it is clear that Gray’s variable-resistance pool had pointed the way for Bell. Next we must ask whether Bell was influenced by Reis’ invention. Reis died two years before Bell received his patent. (He was only forty, and he never got around to seeking a patent of his own.)
Being There
Authors: Lienhard John H.
Published: November 2020

We come at last to the forbidden first person, the I am. No story is right until the teller is part of it. Yet a peculiar mischief is abroad in the land of science and engineering. It is a mischief born out of the noblest of intentions. For decades it has spread like the flu, far beyond the technical journals that gave it birth. The intention is to let us stand like blindfolded Justice—pure, objective, and aloof. To do this, we write about our work without ever speaking in the first person. We try to let fact speak for itself. Instead of saying, “I solved the equation and got y = log x”, we write, “The solution of the equation is y = log x”. We turn our actions into facts that are untouched by human hands. To some extent we must do that. Our facts should be sufficiently solid that we do not need to prop them up with our desires. Third-person detachment has its place, but my own person is not so easy to erase. Suppose I think another engineer, whom I shall call Hoople, is wrong. I am not objective about Hoople, but I must appear to be. So I write, “It is believed that Hoople is incorrect.” That’s a cheap shot. I express my thoughts without taking responsibility for them. I seem to be reporting general disapproval of Hoople. In the unholy name of objectivity, I make it sound as though the whole profession thinks that Hoople is a fool. Now radio and TV journalists are doing it. I cringe every time I hear, “It is expected that Congress will pass the bill. “Who expects that? The announcer? The Democrats? A government official? Maybe the soy sauce lobby is the expectant source. So instead of objectivity we get obfuscation. If our work really occurred in objective isolation, we could write about it that way. But people are present. They think and they act. If we fail to represent human intervention accurately, we are dishonest, and objectivity becomes meaningless. The things we make tell the world what we are.
Information Ages Past and Present
Authors: Headrick Daniel R.
Published: November 2020

Politicians may hark back to our founding fathers, the fall of the Bastille, the Battle of Trafalgar, and other such historical events to legitimize their actions, but the pundits who bombard us with hype would have us think the information age was born yesterday, the product of the latest machines. Ours is not the first information age in history, for hu­mans have always needed and used information. Yet in certain periods the methods used to handle information changed dramatically. We live in such an age, but it is not the first. The appearance of spoken languages must have been a momentous event, although we can only guess at it. Writing is a method we know much more about, as we do about other innovations like the alphabet, geometry, and Arabic numerals. We can also identify information machines in ancient times (e.g., the sundial and clepsydra) and even more so in the Middle Ages (the mechanical clock and the printing press). The purpose of this book is to argue that the information revolution in which we live is the result of a cultural change that began roughly three centuries ago, a change as important as the political and industrial revolutions for which the eighteenth and early nineteenth centuries are so well known. The cultural change, itself closely intertwined with the demographic, economic, and social transformations of the period, manifested itself in an increasing interest in information of all sorts—about nature, people, events, business, and other secular and practical topics. Public officials and private citizens alike not only demanded more information but also wanted it more readily accessible and easier to understand and apply—hence the development of information systems that the Age of Bastille, the Battle of Trafalgar, and other such historical events to legitimize their actions, but the pundits who bombard us with hype would have us think the information age was born yesterday, the product of the latest machines. Ours is not the first information age in history, for humans have always needed and used information. Yet in certain periods the methods used to handle information changed dramatically.
A Two-Dimensional Cellular Automaton Crystal with Irrational Density
Authors: Griffeath David , Hickerson Dean
Published: November 2020

We solve a problem posed recently by Gravner and Griffeath [4]: to find a finite seed A0 of 1s for a simple {0, l}-valued cellular automaton growth model on Z2 such that the occupied crystal An after n updates spreads with a two-dimensional asymptotic shape and a provably irrational density. Our solution exhibits an initial A0 of 2,392 cells for Conway’s Game Of Life from which An cover nT with asymptotic density (3 - √5/90, where T is the triangle with vertices (0,0), (-1/4,-1/4), and (1/6,0). In “Cellular Automaton Growth on Z2: Theorems, Examples, and Problems” [4], Gravner and Griffeath recently presented a mathematical framework for the study of Cellular Automata (CA) crystal growth and asymptotic shape, focusing on two-dimensional dynamics. For simplicity, at any discrete time n, each lattice site is assumed to be either empty (0) or occupied (1). Occupied sites after n updates grows linearly in each dimension, attaining an asymptotic density p within a limit shape L: . . . n-1 A → p • 1L • (1) . . . This phenomenology is developed rigorously in Gravner and Griffeath [4] for Threshold Growth, a class of monotone solidification automata (in which case p = 1), and for various nonmonotone CA which evolve recursively. The coarse-grain crystal geometry of models which do not fill the lattice completely is captured by their asymptotic density, as precisely formulated in Gravner and Griffeath [4]. It may happen that a varying “hydrodynamic” profile p(x) emerges over the normalized support L of the crystal. The most common scenario, however, would appear to be eq. (1), with some constant density p throughout L. All the asymptotic densities identified by Gravner and Griffeath are rational, corresponding to growth which is either exactly periodic in space and time, or nearly so. For instance, it is shown that Exactly 1 Solidification, in which an empty cell permanently joins the crystal if exactly one of its eight nearest (Moore) neighbors is occupied, fills the plane with density 4/9 starting from a singleton.
Growth Phenomena in Cellular Automata
Authors: Gravner Janko
Published: November 2020

We illustrate growth phenomena in two-dimensional cellular automata (CA) by four case studies. The first CA, which we call Obstacle Course, describes the effect that obstacles have on such features of simple growth models as linear expansion and coherent asymptotic shape. Our next CA is random-walk-based Internal Diffusion Limited Aggregation, which spreads sublinearly, but with a shape which can be explicitly computed due to hydrodynamic effects. Then we propose a simple scheme for characterizing CA according to their growth properties, as indicated by two Larger than Life examples. Finally, a very simple case of Spatial Prisoner’s Dilemma illustrates nucleation analysis of CA. In essence, analysis of growth models is an attempt to study properties of physical systems far from equilibrium (e.g., Meakin [34] and more than 1300 references cited in the latter). Cellular automata (CA) growth models, by virtue of their simplicity and amenability to computer experimentation [25], have become particularly popular in the last 20 years, especially in physics research literature [40, 42]. Needless to say, precise mathematical results are hard to come by, and many basic questions remain completely open at the rigorous level. The purpose of this chapter, then, is to outline some successes of the mathematical approach and to identify some fundamental difficulties. We will mainly address three themes which can be summarized by the terms: aggregation, nucleation, and constraint-expansion transition. These themes also provide opportunities to touch on the roles of randomness, monotonicity, and linearity in CA investigations. We choose to illustrate these issues by particular CA rules, with little attempt to formulate a general theory. Simplicity is often, and rightly, touted as an important selling point of cellular automata. We have, therefore, tried to choose the simplest models which, while being amenable to some mathematical analysis, raise a host of intriguing unanswered questions. The next few paragraphs outline subsequent sections of this chapter. Aggregation models typically study properties of growth from a small initial seed. Arguably, the simplest dynamics are obtained by adding sites on the boundary in a uniform fashion.
Recent El Niños and Their Manifestations: Evolving Understanding
Authors: Rosenzweig Cynthia , Hillel Daniel
Published: November 2020

Since the 1970s, there has been a growing global awareness of the El Niño–Southern Oscillation (ENSO) phenomenon, especially in regard to its impacts on humans, natural ecosystems, and agriculture. The three strongest events of these decades (1972–73, 1982–83, and 1997–98) each marked a milestone in this progression. To be sure, not all climate extremes during any given ENSO year are necessarily due to that phenomenon; for example, the intense drought that occurred in 1982–83 in the West African Sahel does not appear to be causally linked to the strong ENSO event of that period (Glantz, 1987). However, even unrelated climate anomalies can exacerbate the effects of an El Niño or La Niña on world food supplies. Here we summarize the major effects of the three most recent very strong El Niño events (see box 4.1) with a focus on their agricultural manifestations. Table 4.1 summarizes the effects by region and continent and for the world food system as a whole. Evolving understanding of ENSO (and its related phenomena) appears to be contributing to the development of improved resilience to such major climate shocks in some regions (see chapter 6 for use of ENSO predictions in agriculture and chapter 8 on building adaptive capacity). However, continuing progress in affected regions is needed for agriculture to withstand (or benefit from) very strong El Niño events in the future, especially since global climate change may be affecting conditions as well. The El Niño of 1972–73 awakened international attention to the ENSO cycle. Besides the failure of the fishery industry in Peru, there were droughts, floods, and food shortages in various locations around the world that also appeared to be associated with El Niño. Consequently, scientists and the public began to realize that El Niño teleconnections and their impacts could extend beyond the West Coast of South America (Glantz, 2001). During the El Niño event of 1972–73, the reduced anchoveta harvest, combined with overfishing, caused the collapse of the Peruvian fishmeal industry and the dislocation of entire fishing communities.
Introduction
Authors: Rubin Yoram
Published: November 2020

Stochastic hydrogeology is the study of hydrogeology using physical and probabilistic concepts. It is an applied science because it is oriented toward applications. Its goal is to develop tools for analyzing measurements and observations taken over a sample region in space, and extract information which can then be used for evaluating and modeling the properties of physical processes taking place in this domain, and make risk-qualified predictions of their outcome. By invoking probabilistic concepts to deal with problems of physics, stochastic hydrogeology joins a well-established tradition followed in mining (Matheron, 1965; David, 1977; Journel and Huijbregts, 1978), turbulence (Kolmogorov, 1941; Batchelor, 1949), acoustics (Tatarski, 1961), atmospheric science (Lumley and Panofsky, 1964), composite materials and electrical engineering (Beran, 1968; Batchelor, 1974), and of course statistical mechanics. Stochastic hydrogeology broadens the scope of the deterministic approach to hydrogeology by considering the last as an end member to a wide spectrum of states of knowledge, stretching from deterministic knowledge at one end all the way to maximum uncertainty at the other, with a continuum of states, representing varying degrees of uncertainty in the hydrogeological processes, in between. It provides a formalism for addressing this continuum of states systematically. The departure from the confines of determinism is an important and intuitively appealing paradigm shift, representing the maturing of hydrogeology from an exploratory into an applied discipline. Deterministic knowledge of a site’s hydrogeology is a state we rarely, if ever, find ourselves in, although from a fundamental point of view there is no inherent element of chance in the hydrogeological processes. For example, we know that mass conservation is a deterministic concept, and we are also confident that Darcy’s law works under conditions which are fairly well understood. However, the application of these principles involves a fair amount of conjecture and speculation, and hence when dealing with real-life applications, determinism exists only in the fact that uncertainty and ambiguity are unavoidable, and might as well be studied and understood. The other end of the spectrum is where uncertainty is the largest. Generally speaking, two types of uncertainty exist: intrinsic variability and epistemic uncertainty.
Fundamentals of Stochastic Site Characterization
Authors: Rubin Yoram
Published: November 2020

A few schematic representations of heterogeneous geological formations are depicted in figure 2.1. These and similar types of images, often encountered in geological site investigations, demonstrate the complexity of subsurface geology. Each image shows several blocks, all nearly homogeneous in terms of some physical or chemical property z, but with possibly strong variations in properties in between. The patterns of spatial variability shown in these images are difficult to capture in the absence of a large number of measurements adequately distributed over the domain. However, the high cost of procuring such databases renders deterministic image reconstruction an elusive goal, one which is largely abandoned in favor of approaches which try to formulate the laws which govern the pattern of spatial variability. These models are known as space random functions (or SRFs, for short). Besides deconstructing complex spatial variability patterns into simple, quantitative laws, SRFs can be used to construct images which have these spatial laws in common, and to estimate z at specific locations. Constructing a SRF for a spatially variable z is based on analysis of z measurements. The goal of that analysis is to reduce the ensemble of measurements to a few useful statistics which capture mathematically the pattern of spatial variability. A few statistics were found to be very useful for exposing the laws of variability, and will be explored in detail. The data analysis includes single (univariate), two-point (bivariate), and multipoint (multivariate) analyses. Univariate analysis focuses on the same-point statistical behavior of the variable z, regardless of the behavior of its neighbors. It answer questions such as “What is the average value of Z?” or “What are the chances that Z will exceed 1000 units?” Bivariate and multivariate analyses explore the simultaneous behavior of z at two or more locations. They provide tools which answer questions such as “What is the likelihood that a region of high permeability will stretch between the contamination source and some environmentally sensitive target?” or “What is the probability to observe z larger than 1500 units at x given that a value of 1300 was measured 5 meters away from x?”
Moments of the Flow Variables,Part I :The Flow Equation and the Hydraulic Head
Authors: Rubin Yoram
Published: November 2020

The parameters and boundary conditions which control the flow processes vary greatly over short distances and over time, and it is inevitable that flow variables such as the hydraulic head and the fluid’s velocity are spatially variable. It is reasonable to model them as SRFs, not only because of the spatial variability, but also due to our inability to model them in detail with only the limited number of measurements usually available. This chapter presents the basic principles and a few methods for modeling flow variables as SRFs, while showing how these moments reflect the physics of the flow and how to use them in applications. The starting point in our derivations will be the moments that characterize the medium variability, such as σ2γ and I γ, and our goal is to develop the SRF models of flow variables such as the head and the velocity in terms of the media parameters and boundary conditions. To drive this point home, let us consider Darcy’s law for isotropic hydraulic conductivity: where qi is the specific flux in the ith direction, K is the isotropic hydraulic conductivity, and H is the hydraulic head. For a spatially variable K, the flux qi is also spatially variable (with the exception of the one-dimensional flow case). An SRF model for K can be used to construct an SRF for qi through (4.1), with the aid of the flow equation. SRFs can be characterized through their low-order statistical moments, but preferably through their pdfs. For example, the hydraulic head will be defined by its expected value (H) and its variance σ2 H = ((H - ( H ) ) 2 ) , but also through its pdf fH(h) where fH(h) dh is the probability of having H in the vicinity dh of h. SRFs may or may not be stationary depending on the nature of the hydrogeological variables such as K and on the boundary conditions. For example, the head is always nonstationary, except when there is no flow.
The Lagrangian Picture, Part II : Models and Applications of the Lagrangian Approach to Solute Transport
Authors: Rubin Yoram
Published: November 2020

This chapter explores applications of the ideas which we explored in chapter 7 and developed in chapter 9. It presents tools for applications and demonstrates some applications through field and numerical studies. This section discusses the statistics of particle displacements in heterogeneous flow fields. Some applications of these statistics are discussed in sections 7.1 and 9.2. We will show later in this chapter that they can also be used for computing dispersion coefficients (sections 10.2-10.5) and travel time statistics (section 10.6), which will be used later (sections 10.7) for modeling reactive transport, and for conditional modeling of transport (section 10.8). An experimental database for the Lagrangian velocity VL (9.1) is difficult but not impossible to obtain (cf. Wilson and Linderfelt, 1994, Woodbudy and Rubin, 2000). But the next best thing for an insight of the nature of VL is to compute its statistics either numerically or analytically. The emphasis in this section will be on low-order analytical approximations. Although some results are of limited applicability, they are of a fundamental nature in terms of the insight they provide.
Vadose Zone, Part I : Characterization and Flow Processes
Authors: Rubin Yoram
Published: November 2020

Many of the principles guiding stochastic analysis of flow and transport processes in the vadose zone are those which we also employ in the saturated zone, and which we have explored in earlier chapters. However, there are important considerations and simplifications to be made, given the nature of the flow and of the governing equations, which we explore here and in chapter 12. The governing equation for water flow in variably saturated porous media at the smallest scale where Darcy’s law is applicable (i.e., no need for upscaling of parameters) is Richards’ equation (cf. Yeh, 1998)
Quantifying and Accounting for Uncertainty
Authors: Rubin Yoram
Published: November 2020

This chapter deals with a wide range of issues with a common theme: coping with uncertainty. To this end, we look at the sources of uncertainty and the types of errors we need to deal with. We then explore methods for identifying these errors and for incorporating them into our predictions. This chapter extends our discussion on these topics in chapter 1, the discussion in chapter 3 on estimation under conditions of uncertainty, and image simulation using MC techniques. A comprehensive treatment of uncertainty needs to address two different types of errors. The first type is the model error, which arises from incorrect hypotheses and unmodeled processes (Gaganis and Smith, 2001), for example, from poor choice of governing equations, incorrect boundary conditions and zonation geometry, and inappropriate selection of forcing functions (Carrera and Neuman, 1986b). The second type of error is parameter error. The parameters of groundwater models are always in error because of measurement errors, heterogeneity, and scaling issues. Ignoring the effects of model and parameter errors is likely to lead to errors in model selection, in the estimation of prediction uncertainty, and in the assessment of risk. Parameter error is treated extensively in the literature: once a model is defined, it is common practice to quantify the errors associated with estimating its parameters (cf. Kitanidis and Vomvoris, 1983; Carrera and Neuman, 1986a, b; Rubin and Dagan, 1987a,b; McLaughlin and Townley, 1996; Poeter and Hill, 1997). Modeling error is well recognized, but is more difficult to quantify. Let us consider, for example, an aquifer which appears to be of uniform conductivity. Parameter error quantifies the error in estimating this conductivity. Modeling error, on the other hand, includes elusive factors such as missing a meandering channel somewhere in the aquifer. This, in essence, is the difficulty in determining modeling error; parameter error can be roughly quantified based on measurements if one assumes that the model is correct, but modeling error is expected to represent all that the measurements and/or the modeler fail to capture. To evaluate model error, the perfect model needs to be known, but this is never possible.
Introduction The Environment, the People, and the State: The Connecticut River Valley, 1790-7930
Authors: Cumbler John T.
Published: November 2020

Early twentieth-century conservation in the United States has been identified in the public mind with the West and the protection of wilderness, parks, and national forests. Some scholars have explored conservation through the writings of naturalists and antimodernists like Henry David Thoreau. What we have only recently come to appreciate is that there was a whole generation of reformers very much concerned about the environment who were neither antimodernists nor wilderness protectors. They were modernists who rejected not the modern world, but the way the modern world was being fashioned. They did not retreat or long to retreat into the wilderness but lived in cities and towns. And they struggled to make the environment of the most settled parts of the nation more amenable to human habitation. It was in New England where these reformers first began to make their claims for the rights of citizens to clean air, clean water, and clean soil. The Massachusetts board of health argued, less than five years after the Civil War, for aggressive state action on the claim that “all citizens have an inherent right to the enjoyment of pure and uncontaminated air, and water, and soil, that this right should be regarded as belonging to the whole community, and that no one should be allowed to trespass upon it by his carelessness or his avarice.” And the New Hampshire board, in its first report, stated that “every person has a legitimate right to nature’s gifts—pure water, air, and soil—a right belonging to every individual, and every community upon which no one should be allowed to trespass through carelessness, ignorance, or other cause.” New England’s first environmental crisis was brought on by its people’s fecundity and by their material practices in the late eighteenth century. Out of that crisis emerged a changed New England with concentrated manufacturing centers and increasingly market-oriented agriculture. Although not all New Englanders enthusiastically supported this change all were affected by it. Within three generations, New Englanders saw their region transformed. That transformation created a new set of troubles. The emergence of those new problems, and the solutions nineteenthcentury Yankees offered, is the story of this book.
From Milling to Manufacturing From Villages to Mill Towns
Authors: Cumbler John T.
Published: November 2020

The new world of New England was one of factories and factory towns, as well as farms and forests. It was a world where farmers, looking to those factory towns for markets, plowed their fields deep and intensively managed their land. It was a world where lumbermen stripped mountainsides of their forest cover to meet the cities’ growing appetite for lumber. It was a world of managed and controlled nature. It was also a world of rapid change, and increasingly after 1800, the force behind that change was the coming of the manufacturing mills. Levi Shepard’s 1788 duck-cloth factory was of a different type than the traditional mills of New England. Although mills that spun or fulled cloth had long been part of rural New England, Levi Shepard had a different market in mind when he encouraged local farmers to bring him their flax. Shepard wanted to take material from the countryside and, with the help of “workers employed,” “manufacture” it into a commodity for sale. Shepard’s decision to focus on manufacturing for distant markets represented a new world. Manufacturing in rural New England began small. And although it made a huge impact on travelers such as Timothy Dwight, it grew out of, while at the same time it transformed, traditional rural society. The processing of goods of the countryside was an integral part of traditional New England life, whether in 1650 or 1800. In 1790, the Hampshire Gazette commented that although “a large quantity of woollen cloth are made in private families and brought to market in our trading towns, a great part of [the woollen cloth] is not calculated for market.” The shift from milling produce for local use to manufacturing occurred initially for most of rural New England with the shift of small traders, merchants, and millers from processing for local farmers to processing for external markets. Edmund Taylor of Williamsburg on the Mill River, for example, at the turn of the century added carding and picking machines to his gristmill. As he did for grain, Taylor processed the material from the countryside, keeping a portion of it as his pay.
Fish, the People, and Theodore Lyman The Moderate Approach
Authors: Cumbler John T.
Published: November 2020

On November 3, 1865, Theodore Lyman III handed his report for the River Fishery Commission to Massachusetts governor John Andrew. Then he headed north from Boston to Lawrence, where he met with newly elected New Hampshire governor Frederick Smyth and the fishery commissioners from other New England states. At that meeting, Governor Smyth, in Lyman’s words, “undertook the high horse and said they would shut down the water from Lake Winnepiseogee [the nineteenth century name for Lake Winnipesaukee] if we did not give the fishways.” Smyth was no one to take lightly. As the son of a New Hampshire farmer, he knew the importance offish to the rural diet, and as a founding member of the Republican Party, he was a politician of some significance. Smyth was also under pressure from rural farmers in the Connecticut and Merrimack River Valleys who had depended upon spring fish runs and now faced depleted rivers. Regarding the New Hampshire governor, Lyman wrote in his diary: “The threats of New Hampshire were some of my business as commissioner.” These threats were Lyman’s business in more than just his role as fish commissioner. The waters of Lake Winnipesaukee fed into the Winnipesaukee River, one of the main sources of the Merrimack River, which provided the power for the mills at Lowell and Lawrence. Without that water, those mills could not function. Lyman enjoyed healthy returns on his holdings in those mills. He not only held stock in these companies and in mills in Holyoke, he was also on several of their boards of directors. As he stated when he later ran for Congress, “I have been connected, and my father before me with the manufacturing interest.” As a major stockholder, Lyman had reason to be concerned about the waterpower of the mills along the Merrimack. Yet when he met with the governor and fish commissioners, he thought of himself not as the representative of the manufacturing interests but as a scientist and public servant. It was a role for which he had been preparing for a long time.