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4
Hazards and Resources
Geological processes affect the sustenance and safety of the human population. For example, earthquakes and volcanic eruptions can cause widespread damage and loss of life. Mineral and water resources are necessary to maintain our complex societies, and waste products from resource use must somehow be returned to Earth in a manner that does not unnecessarily foul the environment and that can be sustained for the indefinite future. The catastrophic nature of some Earth processes and the wise use of our land, water, and mineral resources present a special set of challenging research issues. It is likely that Earth will remain habitable to humans for millions of years into the future, barring insurmountable environmental degradation or a catastrophe of the type that struck 65 million years ago. This last chapter deals with fundamental Earth science that must be advanced to ensure and enhance the future of humankind. We are most concerned as a society about the next decades and centuries, but it is interesting, instructive, and scientifically challenging to think much farther ahead (and to look back in deep geological time) to fully comprehend the range of possibilities.
This chapter comprises two grand questions. Question 9 addresses earthquakes and volcanic eruptions, essential planetary processes that sometimes are deleterious to humankind but are intrinsic to Earth and probably inseparable from its habitability. Both of these geological phenomena are catastrophic in the sense that they represent the sudden release of energy stored inside Earth. The best approach to minimize the loss of life and property from these events is to understand both the causative processes well enough to forecast or predict them and their effects well enough to address them. Question 10 is aimed at addressing the fundamental science that underlies many of the issues related to land, mineral, and water resource use, as well as waste disposal. We have focused this question on the science of Earth fluids, which arguably represents the single most central, fundamental, and crosscutting research area for environmental management and sustainability.
QUESTION 9:
CAN EARTHQUAKES, VOLCANIC ERUPTIONS, AND THEIR CONSEQUENCES BE PREDICTED?
Earthquakes and volcanic eruptions are sudden and hazardous manifestations of the normally gradual movements of Earth’s interior (Questions 4 and 5). Although much research is stimulated by the dangers these events pose to human populations, they are of special interest to Earth scientists for other reasons as well. They constitute a class of phenomena that can be observed in action and monitored at many different scales and that recur frequently. The fact that we know they will happen, and also (for the most part) where, creates a natural desire to be able to predict them. The imperative for improved predictive power is escalated as human populations increasingly concentrate in areas prone to earthquakes and volcanic eruptions. But prediction remains difficult because of the inherent complexity of the processes and the special demands imposed by attempting to specify exactly when these
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events will occur. And since even highly accurate predictions will not prevent widespread damage, an improved ability to forecast the consequences of catastrophic events, and hence to prepare for them, is at least as important as predicting them.
Earthquake Hazards
Earthquakes at their worst are extreme catastrophes. The 1556 Shaanxi, China, earthquake killed over 800,000 people in a matter of minutes. By some estimates the next large earthquake under Tokyo could cause trillions of dollars in direct economic losses. These consequences could be mitigated if earthquakes could be predicted over timescales short enough to allow an effective response. However, this goal remains elusive.
The nature of earthquakes makes them uniquely terrifying. No one sees an earthquake coming. It is a matter of seconds from the time shaking first becomes perceptible until it becomes violent. At any locale, damaging earthquakes occur infrequently on human timescales, which means that most people caught in a major earthquake have no previous experience. It is also profoundly disturbing when our usually stable reference frame, the planet beneath us, does not hold still. The unpredictability and sudden onset of earthquakes also mean that once an earthquake begins, it is generally too late to do much more than duck and cover. The combination of unpredictability, abrupt onset, rarity, and unfamiliarity means that the risk posed by earthquakes is difficult to manage, for both individuals and governments.
Earthquake Prediction: Where, When, and How Big?
The goal of earthquake prediction is to specify where and when a significant earthquake will occur. Where future earthquakes will occur is largely understood, with some important exceptions (summarized in Beroza and Kanamori, 2007). Predicting when they will strike is much more difficult, though progress has been made and promising avenues of research have emerged. The term “significant” is a subtle but important part of the definition of earthquake prediction, and it brings up the important question of what controls earthquake size. Finally, even the word “earthquake” needs definition. Scientists use the term to describe the fault rupture that generates seismic waves. However, the public views an earthquake more broadly as both the faulting and the waves. We will use this more general definition and discuss prediction of the faulting event and the shaking that accompanies it.
Predicting Where Earthquakes Happen
Scientists have long recognized that some regions are seismically active, while others are not. By the middle of the 20th century, seismologists had produced a remarkably complete earthquake atlas (Gutenberg and Richter, 1954) that chronicled systematic features of global seismicity, but they lacked a framework to understand those features. The advent of plate tectonics soon changed that and also enabled the first steps toward earthquake prediction to be taken. For example, plate tectonics theory led to the recognition that Cascadia should be subject to large earthquakes, despite no history of earthquake activity. This expectation was confirmed by the discovery, using stratigraphic and other evidence, of a magnitude (M) ~ 9 earthquake in Cascadia in January 1700 (Figure 4.1; Atwater, 1987).
Plate tectonics holds that Earth’s lithosphere consists of large plates that move relative to one another at speeds of several centimeters per year (Question 5). Relative plate motion is accommodated on plate-boundary faults or, more typically, on complex fault systems. These faults are frictionally locked between earthquakes, causing ongoing plate motion to deform the crust around them, storing elastic strain energy in the process. Once friction is overcome and the fault starts slipping in an earthquake, this stored energy is converted to other forms, most notably energy radiated away from the fault as seismic waves.
Most earthquakes occur at plate boundaries, and the type of boundary plays a role in controlling the nature of earthquake activity. Extension at divergent boundaries is accommodated by normal faulting and formation of new crust through basaltic volcanism, with much of the deformation taking place aseismically. Horizontal motion across transcurrent plate boundaries takes place on strike-slip faults. Most transcurrent boundaries are oceanic, but when they traverse continents, they pose significant seismic hazard. All of the largest earth-
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FIGURE 4.1 A “ghost forest” near the mouth of the Copalis River, Washington, that was killed by saltwater tides after a M ~ 9 earthquake in January 1700 caused the land to subside. SOURCE: <http://soundwaves.usgs.gov/2005/07/outreach.html>. See also Atwater et al. (2005).
quakes and most of Earth’s seismicity occur at convergent plate boundaries. The subduction of relatively cool oceanic crust increases the depth of the elastic-brittle regime in which earthquakes occur. Moreover, when the subducted slab crosses the elastic-brittle regime at a shallow angle (e.g., in Sumatra, Alaska, and Chile), the seismogenic zone can be hundreds of kilometers wide. The hazard at convergent boundaries is not always commensurate with earthquake size because much of the faulting and the strongest shaking occur underwater. However, the 2004 tsunami (Figure 4.2) illustrates the destructive potential and global reach of large subduction zone earthquakes.
Earthquakes that occur within a tectonic plate account for less than 1 percent of the world’s earthquakes, but they pose a significant seismic hazard and can be quite large. For example, a sequence of strong earthquakes with magnitudes as high as 8 shook New Madrid, Missouri, for eight weeks in 1811-1812, destroying the town and causing widespread destruction across the central United States. Intraplate earthquakes are not readily explained by plate tectonics. Some occur within broad plate boundary deformation zones, such as those across south Asia and western North America, while others are not clearly associated with any plate boundary, such as those in Australia or eastern North America. Half of all intraplate earthquakes occur in failed continental rifts (Johnston and Kanter, 1990), but their underlying cause remains a mystery. Putative explanations for intraplate earthquakes include localized stresses induced by emplacement and crystallization of magma below the surface, postglacial rebound, and weak zones in otherwise strong crust.
Intermediate (70 to 300 km deep) and deep (300 to 700 km deep) focus earthquakes occur at convergent plate boundaries within subducting lithosphere (Figure 2.10). Although they pose less of a threat than shallow, plate-boundary earthquakes, intermediate-depth earthquakes can be quite destructive (Beck et al., 1998). What causes them is unclear because Earth materials are expected to deform plastically at the depths where they occur (Question 4). Candidate mechanisms to explain intermediate and deep earthquakes include elevated fluid pressures, accelerating deformation and frictional heating, and mineral phase changes (Kirby et al., 1996).
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FIGURE 4.2 Topography and bathymetry of the West Sunda subduction zone showing the location of the trench and the earthquake fracture zones (colored lines). The red dot shows the epicenter of the M 9.1 December 2004 earthquake that ruptured the India/Eurasia plate boundary (area between the trench and Sumatra) and caused the devastating Indian Ocean tsunami. Rupture propagation was primarily northward, toward the lower left of the figure, extending hundreds of kilometers beyond the figure. Subsequent earthquakes have ruptured parts of the plate boundary to the south. SOURCE: Courtesy of Mohamed Chlieh, Caltech. See also Chlieh et al. (2007) and <http://today.caltech.edu/gps.sieh/>. Used with permission.
Predicting When Earthquakes Will Happen
Just as plate tectonics explains where most earthquakes occur, it has much to say about how often they occur. The velocity of relative motion across plate boundaries is known to within several millimeters per year, which provides a boundary condition on fault-slip rates, and thus on how frequently earthquakes must occur over the long term. The utility of this boundary condition for earthquake prediction is confounded by the fact that plate boundaries typically comprise complex fault systems, and the partitioning of slip among faults is difficult to unravel, even in well-studied systems such as the San Andreas. In some cases, slip rates are well known, but even then the irregular recurrence of earthquakes makes forecasting difficult.
Earthquake predictions are commonly classified by time frame. The types of predictions discussed below are:
Long-term forecasts of events of an uncertain magnitude that have a low probability of occurrence over a large window of time. Long-term forecasts based on probabilistic methods are an active area of research.
Short-term prediction of events of a specific size that have a high probability of occurrence within a narrow range of space and time, weeks or months in advance. There is currently no way to predict the days or months when
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an event will occur in any specific location, and it is not clear whether it will ever be possible.
Early warning that seismic waves from a developing event will arrive in seconds, ideally enabling an alert to be issued before damaging strong ground motions begin. This emerging area of research shows promise for reducing seismic risk.
Long-Term Forecasting
Earthquakes can be forecast by assuming that they occur randomly in time but at known long-term rates. If no historical record of large earthquakes exists, the long-term rate is extrapolated from the frequency-magnitude relationship of small earthquakes. Unfortunately, the assumption that earthquakes occur randomly in time is highly suspect. Earthquakes are observed to cluster in both space and time. Moreover, the elastic-rebound hypothesis suggests that once a large earthquake releases the accumulated stress on a fault, that same fault segment is unlikely to experience a large earthquake until strain has reaccumulated. Such considerations have led to time-dependent earthquake forecasts.
Perhaps the simplest time-dependent, long-term forecast is that offered by the seismic gap hypothesis, which posits that a future earthquake is more likely on a part of a fault that has not ruptured recently (Fedotov, 1965). Implicit in this hypothesis is the notion of a “characteristic earthquake,” that is, a large earthquake that defines a fault segment and dominates the slip budget. According to the seismic gap hypothesis, the probability of an earthquake will be small immediately after the previous earthquake, and the conditional probability that a characteristic earthquake will occur can be determined from the time of the previous earthquake. The evidence for characteristic earthquake behavior is equivocal, and tests of the seismic gap theory have called its utility into question (Kagan and Jackson, 1991). However, the notion that a fault must keep up with geological slip rates over the long term seems inescapable, so there ought to be information in the system that can inform earthquake forecasts. Developing accurate forecast models that use this information is an area of ongoing research.
A number of time-dependent models take some account of how fault systems are thought to operate. Because they need to draw on diverse aspects of fault system behavior, long-term earthquake forecast models form a framework for integrative research. Paleoseismology—the investigation of individual earthquakes in the geological record—provides critical information documenting the frequency and variability of earthquake occurrence over the long term. Geodetic measurements (e.g., Figure 4.3) constrain the distribution of strain accumulation. Earthquake source models constrain the amount of slip expected in large earthquakes. Computer algorithms that scan seismicity catalogs and account for fault slip and interaction, in concert with historical earthquake catalogs, constrain spatial and temporal earthquake probabilities. Finally, models of static and dynamic triggering help us understand how earthquakes interact, including how the probability of one earthquake increases or lessens the probability of another (see below). A longstanding and difficult problem that would benefit from further research is how we validate long-term earthquake forecasts.
The discussion above concerns shallow earthquakes for which we understand the factors influencing the frequency of recurrence, such as fault-slip rates that must be satisfied over the long term. For both intermediate and deep-focus earthquakes, we lack the kinematic fault-slip boundary conditions that enable us to constrain the long-term probabilities of shallow earthquakes. Until a better understanding of intermediate and deep-focus earthquake recurrence is achieved, long-term forecasting of such events will remain empirical.
Are Short-Term Predictions Possible?
The challenge of short-term earthquake prediction can be illustrated by drawing an analogy with lightning. Both phenomena involve the abrupt conversion of accumulated potential energy to kinetic energy. In the case of lightning, gradually accumulated electrical charge suddenly flows as electric current in a lightning bolt and radiates sound waves as thunder. For earthquakes it is gradually accumulated elastic strain energy that accelerates the crust on both sides of the fault and radiates energy as seismic waves. Based on the relative timescales, predicting the size, location, and time of an earthquake to within a week corresponds to predicting the size, location, and time of a lightning bolt to within a millisecond. The latter sounds hopeless but would ac-
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FIGURE 4.3 Estimates of crustal movement near the San Andreas fault based on decadal-scale measurements. Color combines information from Global Positioning System (GPS) measurements and spaceborne radar interferometry (InSAR). Scale at the top shows velocity in the satellite line of sight as it passes over the region. The blue region in the lower left, southwest of the San Andreas and San Jacinto (SJF) faults, is moving away from the satellite track at ~ 14 mm/yr, which corresponds to northwestward motion at ~ 45 mm/yr relative to the region in red to the northeast of the faults. This suggests that strain is accumulating on the San Andreas fault in this region, where no large earthquake has occurred in over 250 years. (CCF = Coyote Creek fault, EDM = Electro-optical Distance Measurement, SCEC = Southern California Earthquake Center, SCIGN = Southern California Integrated GPS Network, SHF = Superstition Hills fault). SOURCE: Fialko (2006). Reprinted by permission from Macmillan Publishers, Ltd.: Nature, copyright 2006.
tually be straightforward because lightning is preceded by an easily observable nucleation process—the formation of a channel of ionized air, known as a stepped leader, that provides a conductive path for the current in the main lightning bolt. The stepped leader precedes the lightning strike over its entire length. Prediction of the time and location of a lightning bolt to within a millisecond is easy once the stepped leader forms. Do earthquakes have a similar nucleation process?
Laboratory studies (e.g., Dieterich, 1979) and theoretical models (e.g., Andrews, 1976) of earthquake nucleation indicate that unstable fault slip should be preceded by an aseismic nucleation process. It seems likely that nucleation of some sort must occur before
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earthquakes, but if so, how extensive is the nucleation process? If it occurs over a limited part of the fault, and thereafter earthquake rupture becomes self-sustaining, then earthquake prediction will be practically impossible. If, on the other hand, nucleation scales with the size of the eventual earthquake (e.g., if the size of the nucleation zone is proportional to the size of the eventual earthquake), prediction would be a good deal more likely, though still extremely challenging (Ellsworth and Beroza, 1995). The nature of earthquake nucleation is a key unknown that is central to the question of short-term earthquake predictability.
Another possible way to predict earthquakes in the short term is through patterns of earthquake interaction. Large shallow earthquakes are immediately followed by aftershocks that are triggered by the main shock. Large earthquakes sometimes trigger other large earthquakes, most famously in the sequence of large earthquakes that ruptured most of the North Anatolian fault during the 20th century (Toksöz et al., 1979). Thus, the study of aftershocks provides insight on how large earthquakes might interact and on how small earthquakes might trigger large earthquakes.
Aftershocks reflect the response to a stress change imposed by the main shock (Scholz, 1990), but this is not a complete explanation because static, elastic effects by themselves cannot explain the observed gradual decay of aftershock rates. The mechanisms proposed to explain aftershock decay include pore fluid flow, viscoelastic relaxation, and earthquake nucleation under rate- and state-variable friction. A better understanding of these mechanisms would improve prediction of earthquake interaction.
Less obvious than the triggering of earthquakes by static stress changes is their suppression when the stress necessary for earthquakes is relieved by a nearby earthquake. A well-known example of this stress shadow effect is the nearly complete absence of major earthquakes in northern California following the 1906 San Francisco earthquake (Ellsworth et al., 1981). Dramatically fewer earthquakes have occurred in this region in the 100+ years since that earthquake than occurred in the 50 years leading up to it. An obvious conclusion is that the 1906 earthquake suppressed subsequent earthquakes by relieving the shear stress in Earth’s crust.
Following the 1992 Landers earthquake, small earthquakes occurred more than 1,000 km away (Hill et al., 1993). Static stress changes over such distances are negligible, but dynamic stress changes transmitted by seismic waves have been documented in the 1999 Izmit, 2002 Denali, and 2004 Sumatra earthquakes. In the case of Sumatra, earthquakes were triggered in Alaska, a distance of 11,000 miles (West et al., 2005). The Landers trigger was synchronous with the maximum vertical displacement of large and extremely long-period surface waves, indicating a direct role for dynamic stresses. This is a new concept of earthquake interaction, and dynamic stress changes can presumably trigger earthquakes at short distances as well.
Whether by static triggering, dynamic triggering, or other mechanisms, the occurrence of an earthquake affects the probability of future earthquakes nearby. In aftershock sequences, triggered earthquakes can themselves trigger other earthquakes in a cascade of failures. Models that quantify these so-called epidemic-type aftershock sequence interactions form the basis for a variety of probabilistic short-term earthquake forecasts. Improving these forecasts and testing their skill at prediction are areas of active research (Field, 2007).
Complexity
Earthquake processes span a tremendous range of temporal and spatial scales, which makes them intrinsically difficult to characterize, let alone predict. Spatial scales range from the size of individual mineral grains to the size of tectonic plates. The smallest microearthquakes rupture faults for milliseconds, whereas strain accumulation during the earthquake cycle can be thousands of years. Physical mechanisms that are dominant at one scale might become negligible at others. Superimposed on the scale variations is the complexity of geological structures and materials.
Earthquakes and fault systems have been held up as an example of a complex natural system that exhibits self-organized criticality (Bak et al., 1988). Despite the complexity, earthquake phenomena exhibit certain types order. Earthquake stress drop and radiation efficiency are similar for both large and small earthquakes. Gutenberg-Richter statistics, a power-law description of the relative number of large and small earthquakes, appear to apply for all earthquake populations. Omori’s Law provides a universal description of the rate of
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aftershock decay. The geometry of fault networks is typically treated using a fractal description. Methods of statistical physics are used to understand how these relationships emerge from the earthquake process and to predict their behavior (e.g., Turcotte et al., 2007). If fault systems behave chaotically, as suggested by some models, there may be an intrinsic limit to predictability (NRC, 2003b). This limit might be years or months if we could fill gaps in our knowledge of the physical laws governing fault motion and if it were possible to measure accurately all the stresses and strains in and around the fault.
How Much Warning Can Be Given Before an Earthquake?
Real-time seismology, which became possible with the regional deployment of high-quality instrumentation and rapid, continuous telemetry, provides reliable estimates of the location and size of earthquakes within a few minutes of the initiation of rupture. For nearby earthquakes, ground shaking will have already begun before these estimates can be made. Earthquake early warning systems focus on the seconds after an earthquake rupture has already started. These systems exploit the fact that the speed of telecommunications exceeds that of seismic waves. If seismographs can quickly determine that an earthquake is under way, and importantly that it is a large earthquake, then regions likely to be subject to dangerous shaking can be alerted before the seismic waves arrive. Earthquake early warning systems are operational in Japan (Figure 4.4), Mexico, and Taiwan and are in various stages of development in Romania, Turkey, and the United States. The key to earthquake warning systems is rapid determination that a large earthquake is under way before the earthquake has fully developed (Allen and Kanamori, 2003). The extent to which this is possible is closely tied to the nature of earthquake nucleation discussed above. The amount of warning that earthquake early warning systems can provide for large earthquakes can be tens of seconds under favorable circumstances.
Strong Ground Motion Prediction
Predicting the level of damaging shaking from seismic waves in an earthquake is a critical aspect of both earthquake prediction and risk mitigation. But even if short-term earthquake prediction ever became a reality, it would still be impossible to protect most of the built environment from damage. Predicting strong ground motion is itself a considerable scientific challenge. Earth’s crust is strongly heterogeneous at all scales, so earthquake waves are strongly distorted as they propagate through it. The faulting process is also complex and may represent the dominant source of uncertainty in strong ground motion prediction. Predictions of strong ground motions are generally made using probabilistic methods and computer simulations.
Probabilistic seismic hazard analysis. The probability of strong ground motions is commonly calculated using probabilistic seismic hazard analysis. The analysis may yield, for example, an estimate of ground motion intensity that has a 2 percent probability of being exceeded over a 50-year time interval. Probabilistic seismic hazard analysis combines information on earthquake likelihoods from long-term forecasts and data on peak ground acceleration, spectral acceleration, and peak ground velocity to create a map of intensities at the specified exceedence probability. Such maps can be used to develop design criteria for buildings and to set priorities among risk reduction measures. As with other earthquake prediction tools, it will be difficult to test the validity of these predictions until the instrumental record is considerably longer. However, observations of precariously balanced rocks (Figure 4.5) have recently been used to place bounds on maximum exceeded ground motion amplitudes over time intervals as long as thousands of years (Brune, 1996).
Ground motion prediction through simulation. Very few recordings exist of strong ground motion close to large earthquakes. This is unfortunate because large earthquakes often dominate seismic hazard. Computer simulation of strong ground motion provides a possible means to fill this data gap, as long as we can be confident the simulations are accurate. Major sources of uncertainty in these calculations include characterization of the earthquake source (Figure 4.6), the ability to model the effects of wave propagation through Earth’s crust, changes to the wavefield due to near-surface nonlinearity, and earthquake-to-earthquake variability in the rupture characteristics. Physics-based predic-
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FIGURE 4.4 Schematic representation of the Japanese earthquake early warning system developed by the Japan Meteorological Agency. This system calculates the location and magnitude of the earthquake from recordings near the epicenter and then estimates the distribution of shaking more widely before the arrival of the strongest shaking, which is typically comprised of S waves. Earthquake early warnings will be broadcast through media outlets such as TV and radio. The system went public in October 2007. SOURCE: Courtesy of the Japan Meteorological Agency. <http://www.jma.go.jp/jma/en/Activities/eew1.html>. Used with permission.
FIGURE 4.5 The ground motion intensity thresholds at which precariously balanced rocks, such as the one shown at left, would be toppled provide an important test on ground motion exceedence probabilities determined from probabilistic seismic hazard analysis. SOURCE: <http://www.seismo.unr.edu/PrecRock/DSC00335.JPG>. Used with permission.
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FIGURE 4.6 Ground motion intensities (warm colors correspond to high intensities) for a simulated M 7.7 earthquake with southeast to northwest rupture on 200-km section of the San Andreas fault. There is a strong rupture directivity effect and strong amplification due to funneling of seismic waves through sedimentary basins south of the San Bernardino and San Gabriel mountains. The simulation on the left assumes a kinematic rupture model, and the one on the right assumes a dynamic (physics-based) rupture model. The extreme difference in the predicted intensities underscores the importance of properly characterizing earthquake source processes. SOURCE: <http://visservices.sdsc.edu/projects/scec/terashake/compare/>. Visualization courtesy of Amit Chourasia, San Diego Supercomputer Center, based on data provided by Kim Olsen and colleagues, Southern California Earthquake Center. Used with permission.
tion of strong ground motions through simulations is an area of intense research. Creating simulations that reach high enough frequencies for structural engineering purposes requires high-performance computing. Further improvements, particularly in the validation of simulation results, are required before they will have an impact on engineering practice.
Dynamic rupture modeling. The evolution of rupture on faults can be modeled either in terms of the displacements or as a function of the stresses. The former, the so-called kinematic description, is most common, but the latter “dynamic” approach provides a more complete description of the process of fault failure and hence is an ongoing research focus. In dynamic rupture models the redistribution of stored strain energy leads to shear failure that becomes unstable and self-sustaining—the process that is believed to occur in an earthquake. If the assumptions that go into them are correct, dynamic models can serve as a foundation for better predictions of both fault behavior and strong ground motion (Figure 4.6). However, the models are computationally intensive and require an understanding of fault behavior over a wide range of conditions (e.g., slip, slip-rate, temperature, pressure, pore pressure) and physical mechanisms (e.g., slip-weakening, rate- and state-variable friction, thermal pressurization, flash heating).
What Is the Role of Slow Earthquakes?
Over the past decade seismologists and geodesists have discovered an entirely new family of unusual earthquakes that range in size from M 1 to at least M 7.5. They occur in diverse geological environments—from the subduction zones of Japan, Mexico, Cascadia, and Alaska, to the slopes of Kilauea volcano in Hawaii, to the San Andreas fault in California. They appear to be caused by the same mechanism as ordinary earthquakes but take such a long time to happen that they are described as “slow.” Because these earthquakes are slow, the waves they generate, if they generate waves at all, are weak and were only detectable after highly sensitive earthquake monitoring networks were deployed. Unlike ordinary earthquakes that grow explosively in size with increasing duration, slow earthquakes, whether large or small, grow at a constant rate proportional to their duration. This raises the interesting question: What puts the brake on slow earthquakes? There are many other important unanswered questions about slow earthquakes, but the one most relevant for this discussion is their possible relation to ordinary earthquakes.
Slow earthquakes occur on the deep extension of large faults (Figure 4.7). This location is “strategic” for earthquake prediction because the adjoining, shallower
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FIGURE 4.7 Different types of earthquakes along the Nankai Trough, under Shikoku, Japan. Red and orange features show small low-frequency earthquakes (M < 2) and very-low-frequency earthquakes (magnitudes shown), respectively. Green rectangles and focal mechanisms show fault-slip models of larger slow-slip events (magnitudes shown). Purple features show the mechanism and slip of the M 8 1946 Nankai earthquake. The top of the Philippine Sea plate is shown by dashed contours. The blue arrow represents the direction of relative plate motion in this area. The slow earthquakes occur on the down-dip extension of the fault that ruptured in the 1946 earthquake. SOURCE: Ide et al. (2007). Reprinted by permission from Macmillan Publishers, Ltd.: Nature, copyright 2007.
parts of these faults generate the dangerous earthquakes we are more familiar with. Because of their location and sense of slip, slow earthquakes ought to drive the dangerous part of the fault toward failure. At least in theory, slow earthquakes have the potential to trigger large earthquakes. For this reason alone they merit intense study. Their recent discovery also demonstrates that there is still much to be learned about earthquakes and that further fundamental discoveries are sure to lie in our future.
Tsunamis
Tsunamis are generated by shallow subduction zone earthquakes and large submarine landslides (Satake, 2007). While extremely fast compared to wind-driven ocean waves, tsunami waves are more than 10 times slower than seismic waves. This is a big advantage for early warning systems, which have been operational for decades. Tsunami warnings rely on rapid analysis of seismic waves and sea-level information from tide
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to minimize or mitigate the undesirable consequences of human activities.
Perhaps the most fundamental underlying scientific theme for resource and environmental issues is the behavior of fluids in the soils, sediments, and rocks that constitute Earth’s uppermost crust. Water is the most common fluid of concern. Water in the ground generally comes from water at the surface, and the behavior of surface water and ultimately, precipitation, is an important aspect of environmental geology. In addition to water, various gases, organic liquids, and both gaseous and liquid carbon dioxide are important geological fluids. Mixtures of fluids—immiscible liquids like water and hydrocarbons, gas-liquid mixtures (two-phase fluids), and mixtures of a gas phase plus two immiscible liquids (multiphase fluids)—can be particularly challenging materials to understand in natural underground settings. Some of the scientific issues associated with fluids in shallow crustal environments also apply to deeper-Earth processes, and many of them also overlap with issues of earthquake prediction, climate prediction, the evolution of continents, the behavior of volcanoes, the formation of ore deposits, and the properties of Earth materials.
Since water, as the best example, is a commodity of critical importance to humankind, and also an agent for so many important geological, chemical, physical, and biological processes, there is a continuing desire to better understand how it works—especially underground where we cannot see it directly, but also as an agent of erosion and sediment transport at the surface. Ultimately, it is desirable to be able to manipulate water and other fluids in the environment. Such manipulation has been done for millennia in the case of surface water and is also done in the subsurface, although still with modest efficiency, in petroleum extraction and subsurface remediation of contaminants. To improve our ability to control, or at least predict, the effects of subsurface fluids, and to better manage surface water and sediment, will require major advances in our understanding of how fluids transport materials and modify their environment by chemical and physical interactions.
How Do Fluids Flow in Geological Media?
The flow of fluids through soils and rocks is easily understood in the abstract but continues to present roadblocks to understanding in natural settings. We have a general understanding of how fluid moves through a granular solid (i.e., the mineral grains or rock fragments are packed together but separated by pore space), based on models of fluid flow through a medium of homogeneous grain size and pore structure. Natural materials are not homogeneous, however, especially on the 100- to 100,000-m scale of groundwater systems, but even on scales of microns to meters. The rate of flow through porous materials varies exponentially with porosity and grain size, so predicting the spatial pattern of fluid flow even in a relatively simple, but heterogeneous, porous material can be difficult. At the pore scale of individual mineral grains, surface tension also affects flow; the liquid phase present at the boundaries of multiple grains has different properties than a bulk liquid and can effectively be held in place by capillary forces. At larger scales, Earth’s subsurface is composed of a variety of rock types, with greatly varying porosity and permeability, that are further complicated by faults and fractures.
When a rock medium is not granular but crystalline, the pore space is typically not visible to the naked eye and its distribution within the rock is exceedingly variable. Most of the pore space in crystalline rock is attributable to fractures, so the flow of fluid can be almost entirely limited to a few fractures that happen to be connected. Many geological media, especially volcanic rocks, are both porous and fractured. In these cases much of the fluid flow may be confined to fractures, but there is also chemical and heat exchange by diffusion (and slow flow) between the fractures and the porous rock between the fractures.
Given this battery of uncertainties, geologists have developed a number of strategies to predict fluid flow patterns in rocks, including some that are largely empirical. A more promising approach is to treat the structural variability with statistical methods, based on observations of analogous rocks that can be studied at the surface. But the flow of fluids through rocks underground remains exceptionally difficult to predict. Generally the best results are mere estimates, and even these are obtainable only from direct observations, usually by drilling into the subsurface and making measurements of returned fluids and rock cores. Still, there is cause for optimism because increasingly powerful measuring tools are being developed—using approaches such as isotope geochemistry and geophysics—and more effec-
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tive mathematical modeling allows geologists to wring more information from the data obtained.
How Do Fluid-Rock Chemical and Biological Interactions Affect Fluid Flow?
As fluids flow through soils and rocks, chemical reactions inevitably occur with the minerals of the rocks, sometimes catalyzed by microorganisms. The most familiar interaction is adsorption, or ion exchange, by which ions carried in solution in water are adsorbed and desorbed from mineral surfaces. This process, which happens everywhere in nature, has been successfully exploited by humans to create water purification systems. Fluids moving through rocks also act as weak acid solutions, often due to dissolved carbon dioxide, that slowly dissolve the original minerals, which are then replaced by secondary minerals such as rusty iron oxides and clays. As rocks and soils chemically react with fluids, changes occur not only in mineralogical and chemical composition, but also in ion exchange and hydrological properties. For soils, the activities of plants, animals, and microbes are important. In deeper groundwater systems, where temperatures are higher and fluids can be more corrosive, chemical reactions can be quite fast. But because chemical reactions between fluids and minerals occur only at mineral surfaces, the structure of the fluid flow through rocks and the geochemistry are inextricably linked. If fluid flow is confined to a few fractures, it may be fast, with little contact area between fluid and minerals and little chemical interaction. If there is grain-scale porous flow, however, flow velocity will be low, the contact area large, and fluid-rock interaction extensive.
Geological studies of fluid flow, chemical reactions, and their interplay are grouped under the heading of reactive chemical transport (e.g., Steefel et al., 2005; Figure 4.10). A major goal of this subfield is to describe, with advanced computational techniques, how the characteristics of fluid-rock systems affect their physical, chemical, and biological development. The computer models require large inputs of basic materials property data, and the complexity of the interactions is a conceptual as well as a computing challenge. One crucial feature of the models is mineral surface properties and their role in chemical reaction kinetics, which are increasingly explored at synchrotron X-ray facilities. Other inputs come from benchtop experiments that produce and observe coupled processes in a realistic, controlled environment. In addition to modeling, efforts are being made to document the role of microbes in altering mineral surfaces and chemical microenvironments (Figure 4.10). And the role of hydrology in chemical reactions is being approached with a combination of numerical models, such as approaches that include multiphase flow in complex geometries and microfluidic experiments, both of which can address the roles of chemical transport and pore structure on chemical reactions. For multiphase fluids there are additional considerations because the presence of each phase interferes with the flow of the other phases, and the detailed distribution of each phase within the pores can affect the surface area that is available for fluid-rock chemical interactions. There is also partitioning of chemical elements between multiple flowing phases (e.g., gas, oil, water), which is important in many subsurface processes but difficult to model because of its dependence on the physical relationships between the phases.
How Do Thermal and Mechanical Reactions Affect Fluid Flow?
Chemical reactions are not the only processes that complicate fluid flow. As fluids move through rocks they redistribute heat as well as material, and both the heat and materials affect the subsequent fluid flow. For example, buoyant upwelling of groundwater heated by magma can cause rainwater that has percolated into the ground to circulate to depths of several kilometers in areas of active volcanism and mountain building, as well as in sedimentary basins. At midocean ridges, cold seawater circulates through hot rocks to depths of several kilometers, and magma at the shallow depths of midocean ridges causes such rapid heating of water that it is expelled back into the ocean at temperatures above 350°C. Base metal ore deposits associated with magmatic intrusions in the crust are products of “fossil” hydrothermal systems where circulating water attained temperatures of 200°C to over 500°C (Hedenquist and Lowenstern, 1994; Sillitoe and Hedenquist, 2003). Some of these systems persisted for tens to hundreds of thousands of years at depths of 3 to 10 km. Any magma that makes
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FIGURE 4.10 Schematic illustration of coupled transport, chemical, and biological processes in a hypothetical aquifer downstream of an organic-rich landfill. Closest to the landfill is a zone of methane generation, which is progressively followed downstream by sulfate reduction, iron reduction, denitrification, and aerobic respiration that develop as the flowing fluid becomes progressively oxidized by mixing with oxygenated water. Within the iron reduction zone, a pore-scale image (magnified about 10,000 times relative to the cross section) is shown in which the influx of dissolved organic molecules provides electrons for iron reduction mediated by a biofilm. Dissolution of the organic phase leads to the release of Fe2+, HCO3−, and OH− into the pore fluid, which then causes siderite or calcite to precipitate, reducing the porosity and permeability of the material. Sorption of Fe2+ may also occur on clays, displacing other cations originally present on the mineral surface. Where reactions are fast relative to local transport, gradients in concentration, and thus in reaction rates, may develop at the pore scale. SOURCE: Steefel et al. (2005). Copyright 2005 by Elsevier Science and Technology Journals. Reproduced with permission.
its way to within several kilometers of Earth’s surface will stimulate groundwater convection, and it is now believed that this convection plays a major role in accelerating the cooling and crystallization of magma in the crust (Fournier, 1999).
Heat transfer can affect fluid flow in several ways. Simple heating can cause the rocks to swell and may cause fractures to close, decreasing permeability and slowing flow. Water that is heating, however, can also become pressurized as it expands, which can fracture the rocks or expand and lengthen existing cracks, thereby increasing permeability and flow. Alternatively, thermal contraction of rocks due to cooling by infiltrating groundwater will also induce fracturing and promote permeability increases (Majer et al., 2007). Water that is warming is usually dissolving minerals; water that is cooling tends to precipitate minerals. Dissolution and precipitation both affect permeability and compete with temperature changes and hydrofracture in modifying fluid flow (Haneberg et al., 1999). If hot water is close to Earth’s surface and hence at low confining pressure, it can boil, and this phase change introduces additional complications. Water vapor cannot hold as much dissolved rock as hot water, so boiling tends to cause mineral precipitation. Boiling also lowers a fluid’s viscosity and leads to a two-phase fluid. Some geothermal systems are hot and deep enough to support supercritical fluids, whose properties and behavior are much less well known than those of their subcritical counterparts. Better knowledge of these obscure regimes may be essential
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for understanding geothermal systems (Fridleifsson and Elders, 2004).
Geothermal fluid-rock circulation systems typically have scales of meters to tens of kilometers, which ensures that they will encounter a range of temperatures, pressures, rock compositions, and permeability. In real systems the fluids are often saline, acidic, or toxic, and high temperature and pressure gradients result in rapid mineral precipitation that reduces porosity and fluid flow. Nevertheless, it is highly desirable to understand and predict their behavior for a variety of practical and scientific reasons. For example, there is an abundance of hot rock not far below the surface in the western United States (Blackwell and Richards, 2004), and if water, CO2, or some other fluid could be circulated through it and returned to the surface, a sizable amount of thermal energy could be harvested. So far, efforts to do this have been only partially successful because the evolution of this thermal-hydrological-mechanical-chemical (THMC) system is highly complex, and we lack the expertise to control these processes in a way that permits manipulation of fluid flow in the subsurface (MIT, 2006).
An interesting example of a proposed man-made THMC system, which exhibits many of the complexities of fluid-rock systems in a compact form, is the planned underground nuclear waste repository at Yucca Mountain, Nevada. The radioactive materials that would be stored in the ground produce heat, and both models and experiments show that this heat will generate groundwater convection, boiling, mineral dissolution and precipitation, as well as potentially corrosive conditions around the waste canisters themselves (see Box 4.2). Each of these effects is understood individually at a reasonable level, but the evolution of the overall system is sufficiently uncertain that it affects our assessment of the risk of burying the waste. Other examples of THMC systems are those used to enhance petroleum recovery, where steam or other fluids are pumped into the ground to produce lower-viscosity oil, to enhance permeability, and to push residual oil toward existing wells.
Can the Behavior of Subsurface Fluids Be Predicted?
Because of the complexity of fluid-rock systems, we cannot yet predict how they will change over time—a critical requirement for addressing groundwater recharge, waste movement, and other issues. This limitation means that monitoring is required, but the effectiveness of subsurface monitoring systems is still limited. One way to track subsurface fluids and processes, and still perhaps the most reliable approach, is to drill wells and take samples of fluids and rock. Drilling is expensive and time consuming, however, and can never provide a complete picture of the subsurface. However, new methods are being developed to translate the chemistry and isotopic composition of sampled fluids into physical and chemical characteristics of the regions between the well samples. For example, fluid sampling now makes possible estimates of in situ chemical weathering rates; the sources, age, and velocity of the fluids; and the importance of fracture flow and even the spacing between flowing fractures.
There is hope that noninvasive geophysical methods will yield increasing amounts of information about subsurface fluid-rock systems. Geophysical methods can help detect subsurface fluids, either from the surface or between bore holes. These methods combine electrical and mechanical signals with tomographic analysis to provide three-dimensional maps of subsurface properties. The challenge is to detect the relatively weak signals and then convert them into reliable estimates of hydrological quantities such as fluid content, fluid composition, and porosity. Figure 4.11 shows an example of tomographic imaging, which can assess the connectivity of pore spaces or determine in situ spatially distinct densities. Such imaging provides a powerful new tool for understanding the spatial characteristics of Earth materials.
Still, the uncertainties in predicting long-term fluid-rock system performance are so daunting that we need much more accurate and efficient monitoring methods. The extent to which such monitoring can be done remotely or by noninvasive methods will determine just how useful they can be in monitoring contaminated groundwater sites and other systems. In general, improvement of monitoring methods hinges on fundamental advances in the chemistry and physics of geological materials. This is because the chemical, electrical, and seismic behavior of the bulk media is often determined by the details of minerals, mineral surfaces, phase boundaries, and phase compositions. And these advances, in turn, must be optimized
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BOX 4.2
Thermal-Hydrological-Mechanical-Chemical Processes in Yucca Mountain
An interesting example of coupled thermal-hydrological-mechanical-chemical (THMC) processes is the anticipated behavior of the water-under-saturated rock mass surrounding the proposed horizontal tunnels (drifts) at the Yucca Mountain site in southern Nevada. Small amounts of groundwater are present in the porous volcanic rocks, even above the water table, and the primary unknown is whether this water will enter the drifts and cause the waste canisters to corrode (Long and Ewing, 2004). Such corrosion could eventually allow the release of radioactive elements into solution, and the dissolved constituents could percolate slowly downward toward the water table and the regional groundwater aquifer.
To test the likelihood of this outcome, mathematical models have been developed to simulate the combined effects of heat and material transport around the drifts (conceptual model shown below). For these models the radioactive waste containers are considered to be only a heat source, and the amount of heat they produce can be estimated accurately. This heat will keep rock temperatures near the drifts above the boiling point of water for a considerable period of time. Boiling of groundwater would generate vapor that migrates away from the drifts and then condenses in cooler regions and drains through the fracture network. This elevated temperature and moisture redistribution would cause changes in pore water and gas compositions, as well as mineral dissolution and precipitation. Mineral dissolution and precipitation can result in porosity and permeability changes in the rock, which lead to altered flow paths and flow focusing.
The models suggest that in some circumstances very little water can enter the drift but that in other circumstances some water can enter. The scientific unknowns reflect the basic and overlapping questions that characterize the broader field of fluid flow: how to represent the processes in the model, how the rock properties change as mineral dissolution and precipitation proceed, how fast the minerals actually dissolve and precipitate, how water is distributed between fractures and the porous matrix rock separating them, and the effects of heating and cooling on fracture porosity and permeability.
Conceptual model of processes in a fracture within volcanic tuff above a heat source with the properties of a radioactive waste container. Temperature is highest at the bottom of the fracture, nearest the heat source, and decreases upward. Heating of the fluid near the base of the fracture causes boiling (production of steam) and release of gaseous CO2. The vapor phase rises upward due to gravity, condenses at a higher level, and flows downward as a liquid. The CO2 dissolves into the colder groundwater near the top of the system, making it more acidic and causing it to dissolve silicates. The dissolved constituents are carried downward in the liquid phase and precipitated, eventually causing the fractures to narrow or become sealed. Although the general features of this system can be established, the time evolution is highly dependent on the rates of flow, the rates of the dissolution reactions, and resultant changes in porosity and permeability. SOURCE: Sonnenthal et al. (2001).
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FIGURE 4.11 Tomographic image of residual fluid saturation in a sintered bead pack after free drainage. The beads have been rendered transparent and were 1.63 mm in diameter. SOURCE: Sakellariou et al. (2004). Copyright 2004 by Elsevier Science and Technology Journals. Reproduced with permission.
by improvements in data analysis and computing capabilities.
What Are the Effects of Multiple Timescales and Length Scales on Fluid-Rock Systems?
As with other Earth materials and processes, the behavior of fluid-rock systems varies enormously with length scales and timescales. Although some processes can be studied in the laboratory, experiments must generally be limited to systems that are centimeters to meters in size and days to months in duration. In this setting it is possible to characterize the average properties of fluid flow and accurately predict both flow and chemical interactions, but as we have seen throughout this report, laboratory results cannot faithfully reflect those of natural systems that are much larger and persist for thousands or millions of years. In general, larger systems exhibit faster flow, greater dispersion, and much slower chemical interactions between fluids and solids than we expect on the basis of laboratory experience.
The problems of scale are more than technicalities; they are fundamental scientific challenges, as noted also for material properties (Question 6), earthquake prediction (Question 9), and global weathering rates (Question 7). Geological features that are present at one scale—for example, faults and lithologic changes at scales of thousands of meters—are not present at smaller scales. Consequently, it is not justifiable to extrapolate material properties like hydraulic conductivity from small to large scales. With regard to fluid-mineral chemical reactions, reaction rates depend on the fluid’s chemical composition, the mineral-fluid contact area, and the microscopic characteristics of the mineral surfaces (Question 6). All of these parameters can vary, and the range of variation can be large at both small and large spatial scales. Also, the chemical reactions that are significant at geological timescales proceed at ultraslow rates (Question 7), and it is obvious that the factors that control these rates are not the same as those that control laboratory reactions that proceed a million or a billion times faster.
Variation of material properties and reaction rates at different timescales and length scales is an important issue for large-scale geological sequestration of carbon dioxide (Box 4.3). Typical plans are to inject CO2 into sedimentary rock formations deep underground at hundreds of sites over periods of tens of years. The injected CO2, which is lighter than saline aqueous fluid, can displace the fluids but at the same time will tend to mix with the ambient fluid to produce a carbonic acid-rich dense fluid. Since the CO2 must be retained underground for hundreds of years for geological sequestration to be effective, and because the fluids will be confined only by geological barriers, it is important to understand how the fluid will move and react with the rocks and to have the capability to monitor the movement and reactions (DOE, 2007).
Can the Effects of Water on Earth Processes Be Predicted?
Water, in both gaseous and liquid forms, is a uniquely pervasive fluid in the ways it supports life and otherwise influences the structure and evolution of the planet—and yet we only partially understand most of these processes. For example, humans depend on the balance between the extraction of groundwater and the recharge of groundwater reservoirs, but the factors affecting this balance are complex. They depend on how rainfall is partitioned between evaporation back to the atmosphere, surface runoff, and infiltration into deeper reservoirs where evaporation is no longer important. In
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BOX 4.3
Geological Sequestration of CO2
Several techniques have been proposed to capture CO2 at the source and sequester it from the atmosphere. One approach under active investigation is storage in geological reservoirs. Current feasible options for geological sequestration include oil and gas reservoirs, coal beds, and saline formations (i.e., saline aquifers and brine-saturated sedimentary rock). Although nature has stored CO2 in these geological structures for millions of years, the human use of this technique has other advantages. For example, injecting CO2 into an oil or a natural gas reservoir can enhance hydrocarbon production, and about 35 million tons of CO2 per year is already used for this purpose in the United States (Stevens et al., 2000). Limited field tests suggest that CO2 injection would also enhance extraction of methane from coal beds by displacing methane with CO2. Although these techniques have the potential to enhance resource recovery and offset the costs of CO2 capture, transport, and injection, questions of reservoir availability (for oil and gas) and technological readiness (for coal beds) limit their widespread use.
CO2 can also be injected into saline formations in sedimentary basins and on the continental shelves and trapped by displacement or compression of brine in the porous rocks. Disposal under several hundred meters of deep-sea sediment is another option. The limiting factors on storage volume include sediment layer thickness and permeability, as well as the potential for ground perturbations, such as landslides (House et al., 2006).
To what extent will CO2 move within or beyond the geological formation? What physical and chemical changes are likely to occur in the formation when CO2 is injected? A better understanding of the implications of CO2 injection and sequestration is critical to determining its viability as a mitigation option for atmospheric CO2 emissions. Key questions that must be answered include the location, capacity, and availability of storage sites; the permanence of storage; and the risks to humans and ecosystems. Long-term monitoring, measurement, and verification technologies must also be developed to improve the storage prediction models used to estimate storage capacity and to design storage areas.
Leakage of CO2 from storage sites, as well as migration within the sites, could pose local and global environmental hazards; in 1986 the sudden venting of CO2 from the bottom of Lake Nyos, Cameroons, killed 1,800 people. Escaped CO2 can infiltrate the shallow subsurface, with potential adverse effects on groundwater chemistry, the vadose zone, and ambient air quality above ground. Large-scale storage failure could return CO2 to the global atmosphere. Understanding the fate of these gases and fluids on timescales of thousands of years and longer is crucial to decisions on the wise use of carbon-based fuels.
Approaches for geological sequestration of carbon dioxide. SOURCE: Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC). Used with permission.
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regions of thick vegetation, plants recycle much of the water back to the atmosphere. In arid regions there is both little rainfall and little vegetation, which in some ways simplifies the analysis, but because little rainfall infiltrates in these regions, it is difficult to estimate the amount accurately. In addition, water in the form of rain is a weathering agent, which in combination with microbial processes and dust deposition produces soil. Because soil is removed or modified by land use changes, the rates of soil formation are critical in predicting the future character of the land available for agriculture, home sites, and industry. Finally, the potential effects of global warming on groundwater availability and quality may alter the living patterns of human populations in the future, but by how much is virtually unknown (IPCC, 2007b).
Some of the ways in which water influences gross planetary structure and evolution are equally obscure. We know that the presence of water in the subsurface, in particular its retention in soils and unconsolidated rocks, tends to lower internal friction and promote landslides. Water also plays a key role in determining the strength of faults and the deformability of rocks deep in the crust and mantle (Question 9), but the details are too complex to facilitate the prediction of earthquakes. Little is yet known about how fluids, primarily water and carbon dioxide, are distributed in and move through the continental crust at depths greater than a few kilometers. Water also promotes melting in planetary interiors (Question 4), and at moderate pressure and temperature inside Earth, water and silicates may be completely miscible. The behavior of such high-temperature hydrosilicate fluids is poorly known but is likely to be important for understanding both the distribution of water within planets and the origin of magmatism. Magmas constitute a class of fluids whose flow and thermal, mechanical, and reactive behavior are only crudely understood.
Beyond Earth, water and other liquids may be important for understanding geological history and the present structure of other planets and moons in the Solar System. A compelling example is Mars, where the past and present distributions of water are guiding our search for other life forms. Subsurface water is also likely to have been critical to Martian landforms, and the amount of water in the Martian mantle and deep crust is likely to have influenced the planet’s evolution.
Can Landscapes Be Managed to Sustain Human Populations and Ecosystems?
Water flowing at the surface in rivers and streams transports dissolved ions, sediment, and organic material and constitutes a longstanding focus of geological study. Surface water, through erosion and sediment redistribution, is the primary sculptor of Earth’s landscapes—or was until the rapid population growth over the past century. We are living on a planet that we have “engineered” over the millennia. Humans have caused massive changes in the shape of landscapes as well as the distribution of plants, animals, water, sediments, and chemicals. These changes have been caused by resource extraction, as well as attempts to ensure water availability, promote agriculture, build roads, and decrease the risk of floods and landslides. Recently we have learned that these changes generate new risks in the longer term. If we are to protect and sustain the planetary systems that provide us with essential services, we must base our future “engineering” decisions on a thorough understanding of the fundamental processes that govern how Earth works.
A sustainable landscape is one that supports the continued use of resources while maintaining critical natural processes and ecosystem functions. Humans will always need to extract resources, but minimizing damage to the environment will require a more effective capability to link specific actions to quantifiable consequences. In a single watershed, for example, actions such as timber harvesting, plowing, and road construction are known to cause downstream changes in sediment transport, water flow, and nutrient availability. But models of watershed processes, linking physical, biological, and geochemical processes, are poorly developed. New technologies are emerging that should improve those models, including high-resolution topographic data from airborne laser swath mapping, which can be used to measure even small changes in landscape morphology; new sediment tracers and dating methods; inexpensive wireless sensors that enable spatially distributed, intensive monitoring; and more powerful computational capabilities
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that allow the integration of these diverse data into mathematical models.
The desire to restore landscapes and ecosystems to their “predisturbance” states has led to an emerging field of restoration geomorphology. A key question is whether it is possible to help a dynamic landscape persist through human-induced changes and retain its most important and desirable attributes. A good example is stream restoration (Bernhardt et al., 2005), which presents a surprisingly complicated set of objectives. In a typical situation the desired state might be a laterally migrating, self-maintaining stream channel that passes the sediment it receives, rather than allowing it to accumulate in undesirable places; maintains habitat for plants and animals; and maintains its dissolved load and nutrient content at appropriate levels. Although we are learning how to address some of these objectives, we lack mechanistic models for river channels that represent their morphology, sediment load, and interaction with vegetation. And even a good design for current conditions might not be useful through flood-drought cycles and longer term climate changes. Another example of landscape change is dam building. While this kind of change is completely human caused and initially local, it is now recognized to have effects that are global in scale (Syvitski et al., 2003, 2005; see Box 4.4).
Given the inevitability of environmental change, whether natural or human induced, stream systems need to be managed for the desirable ecosystem characteristics even if, for example, sea level rises, precipitation changes, or mountain glaciers disappear. For example, global warming brings permafrost melting in polar regions, along with a range of hydrological, ecological, and geochemical changes (Chapin et al., 2006). Because warming will continue well into the future no matter how we attempt to manage greenhouse gases today, human societies need the capability to predict the consequences and take actions that preserve functions and resources (e.g., see Box 4.3).
Hazards from surface processes include landsliding, flooding, and coastal retreat. Hazard mitigation has traditionally relied on the use of maps that delineate some aspect of risk, but such maps tend to rely on the intuitive skill of the mapmaker and are typically based on a fixed environmental state. This means that the maps rapidly become inaccurate. With advances in weather and climate forecasting, the availability of digital topography, and improved understanding of processes, hazard prediction is becoming spatially explicit, up to date, and much more useful for mitigation efforts. With today’s 10-day forecasts of weather, flood forecasts are becoming commonplace as well, although not yet achieving good spatial extent and accuracy. Scientists are also beginning to forecast landslides in response to predicted rainfalls, but they still lack the ability to predict landslide size, location, travel distance, or speed. Sea-level rise, changes in storminess, and reductions in sediment due to dams may influence the effects of large storms on lowland river, delta, and coastal systems. However, we cannot yet predict how sea-level rise will affect levees or the flood heights on lowland rivers or determine whether artificial levees could be removed while still retaining flood protection. Answering these and many other such questions will require a body of field studies, experiments, theory, and numerical modeling sufficient to build the predictive science of watershed resiliency and hazard mitigation.
Summary
Our ability to manage natural resources, safely dispose of wastes, and sustain the environment depends on our understanding of fluids, both at the surface and below ground. In particular, we need a better grasp of how fluids flow, how they transport materials and heat, and how they interact with and modify their surroundings. The list of significant fluids begins with water, the most abundant and important Earth fluid, and includes steam, hydrocarbons, liquid and gaseous carbon dioxide, other organic liquids, and multiphase fluids (gas plus liquid, immiscible liquids, and gas plus immiscible liquids). For subsurface processes we need to understand how these fluids are distributed in heterogeneous rock and soil formations, how fast they flow, and how they are affected by chemical and thermal exchange with the host formations. At Earth’s surface we are concerned with the flow of water in rivers and streams, how stream erosion and sediment transport change landscapes, and how human activities and climate change affect the evolution of streams and landscapes.
Decades of research have brought substantial knowledge about the flow and transport of fluids, but application of this knowledge is strained by increased
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BOX 4.4
Global Impact of Dams
Humans have constructed more than 45,000 dams above 14 m in height, which together are capable of holding back about 15 percent of the total global annual river runoff (Vörösmarty et al., 2003). Dams have reduced the total amount of sediment carried to the ocean by about 20 to 30 percent, even though human activities have increased the total sediment production by 30 percent. And dam building continues; between 160 and 320 new dams are built annually, especially in Asia. Dams cause major changes to local, and ultimately worldwide, physical, chemical, and ecological systems and in many cases simply terminate river ecosystem functions.
Despite the negative impacts of dams, demand for power, flood control, and water supply means that many will remain and more will be built. Nonetheless, much can be done to preserve the desired physical, chemical, and ecological characteristics of affected watersheds. For example, the release of water from reservoirs could be designed to mimic important natural functions, such as sediment transport, recruitment of riparian vegetation, and fish reproduction. As we learn more about the long-term consequences of sediment depletion in downstream rivers and coastal environments, we can take action to compensate.
Summary of the impacts of dams on major global river systems. (Top) Geographical distribution of 633 large reservoirs (i.e., those with a storage capacity of 0.5 km3 or greater). (Bottom) Efficiency of basins in trapping suspended sediment. In some basins sediment load is severely restricted by dams along the river course; in some cases virtually all sediment is trapped. SOURCE: Vörösmarty et al. (2003). Copyright 2003 by Elsevier Science and Technology Journals. Reproduced with permission.
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population, resource demands, and the environmental consequences of our own success as a species. Meeting these planetwide challenges will require a major advance in our ability to understand fluids in and on Earth, manipulate them, and monitor their where-abouts and effects. These challenges are being met by new experimental tools that can illuminate what happens at the microscopic scale on mineral surfaces, new geochemical and geophysical field techniques, and airborne and spaceborne sensors that offer an unprecedented view of how water and other fluids are shaping our planet. The ultimate objective of this research is robust mathematical models that can simulate natural fluid-bearing systems and predict far into the future how they will behave and change. Only by building and skillfully using such models will we be able to make informed decisions about the land and resources that support humankind and all life on Earth.