Can catastrophic events be tamed? Technology has done plenty to protect us, but much more remains to be done.
by Mohamed Gad-el-Hak
Predictions of the weather can warn us that we may need an umbrella, or that we should batten down and head for the cellar. A forecast can often help us stay drier and more comfortable. In extreme instances, it can save our lives.
Once a storm system has formed, the course and intensity of a hurricane, for instance, which typically lasts a couple of weeks from inception to dissipation, can be predicted about a week in advance. The path of a tornado can be predicted only about 15 minutes in advance, although weather conditions favoring its formation can be predicted hours ahead.
An earthquake of magnitude 7.6 hit Kashmir in 2005. Success in efforts to predict earthquakes has remained elusive.
Hurricanes and tornadoes, even when they do not kill, leave a wake of damage and disruption. They qualify as disasters, and the sooner we are warned of their approach, the better preparation we can make to protect ourselves and our property.
There are many other extreme events besides storms that cause widespread harm. Throughout human history, populations have been struck by disasters natural and otherwise—disease, earthquake, and fire; war, terrorism, and crime. The degree of success in predicting their occurrence and behavior varies more widely than it does even for the weather.
MITIGATION AND CONTROL
A scientist or an engineer can look at a disaster as a dynamical system that can in principle, though not always in practice, be modeled using the Newtonian framework of nature. If potential disasters can be predicted, their effects can be mitigated. Sometimes the events can even be controlled.
This is essentially the subject of a book that I edited, Large-Scale Disasters: Prediction, Control and Mitigation, published earlier this year by Cambridge University Press. In it, dozens of contributors describe issues that science and engineering can address in the management and control of extreme events.
Science and technology can help greatly in predicting the course of certain types of disasters. When, where, and how intense will a severe weather phenomenon strike? Are weather conditions favorable to extinguishing a particular wildfire? What is the probability of a particular volcano erupting? How much air and water pollution is going to be caused by the addition of a factory cluster to a community? How would a toxic chemical or biological substance disperse in the atmosphere or in a body of water? Below a specific concentration, certain dangerous substances are harmless, and a safe zone could be established based on the dispersion forecast.
Earthquake prediction is far from satisfactory, but is seriously attempted nevertheless. The accuracy of predicting volcanic eruptions is somewhere in between those of earthquakes and severe weather. Scientists are able to monitor Italy’s Mount Etna, for example, and forecast its eruption using seismic tomography, a technique similar to that used in computed tomography scans in the medical field. The method yields time photographs of the three-dimensional movement of rocks to detect their internal changes. The success of the technique is in no small part due to the fact that Mount Etna, Europe’s biggest volcano, is equipped with a high-quality monitoring system and seismic network, tools not readily available for most other volcanoes.
REALITY VS. SCIENCE FICTION
Science and technology can also help to control the severity of a disaster, but here the achievements to date are much less spectacular than those in the prediction arena. Cloud seeding to avert drought is still far from being a practical tool. Slinging a nuclear device toward an asteroid or a meteor to avert its imminent collision with Earth remains solidly in the realm of science fiction. (In the 1998 film Armageddon, a Texas-size asteroid was courageously nuked from its interior.)
On the other hand, employing scientific principles to combat a wildfire is doable. So is the development of scientifically based strategies to reduce air and water pollution, moderate urban sprawl, evacuate a large city, and minimize the probability of accident for air, land, and water vehicles.
Satellite photographs show the same island before and after the 2004 Indian Ocean earthquake and its tsunami. Advance warning might have reduced the death toll.
Structures are designed to withstand an earthquake of a given magnitude, wind of a given speed, and so on. Dams are constructed to moderate the flood/drought cycles of rivers, and levees and dikes are erected to protect lands below sea level from the vagaries of the weather. Storm drains, fire hydrants, fire-retardant materials, sprinkler systems, pollution control, simple hygiene, strict building codes, traffic rules, and regulations governing air, land, and sea travel are the types of measures a society takes to mitigate or even eliminate the adverse effects of certain natural and manmade disasters.
Of course, there are limits to what a government can do. While much better fire safety will be achieved if a fire station is built on every city block, and fewer earthquake casualties will occur if every house is built to withstand the strongest possible tremor, clearly the cost of such efforts cannot be justified or even afforded by society.
In contrast to natural disasters, manmade ones are generally somewhat easier to control, but more difficult to predict. The war on terrorism is a case in point. Who could predict the behavior of a crazed suicide bomber? A civilized society spends its valuable resources on intelligence gathering, internal security, border control, and screening to prevent such devious behavior, whose dynamics obviously cannot be distilled into a differential equation to be solved.
A satellite image of Katrina, a category 5 hurricane, was taken over the Gulf of Mexico in August 2005. Many flood- and storm-control systems failed to protect populations living on the Gulf of Mexico.
However, even in certain disastrous situations that depend on human behavior, predictions can sometimes be made. Crowd dynamics are a prime example. The behavior of a crowd in an emergency can to some degree be modeled and anticipated, so that adequate escape or evacuation routes can be properly designed. Panic situations and other crowd disasters have been modeled as nonlinear dynamical systems.
For disasters that involve fluid transport phenomena, such as severe weather, fire, or release of a toxic substance, the governing equations can be formulated subject to some assumptions—the fewer, the better. Modeling is usually in the form of nonlinear partial differential equations with the appropriate number of initial and boundary conditions. But those field equations are typically impossible to solve analytically, particularly if the fluid flow is turbulent, which unfortunately is the norm for the high Reynolds number flows encountered in the atmosphere and oceans.
MODELING TO THE RESCUE?
Furthermore, initial and boundary conditions are required for both analytical and numerical solutions. Computers have their practical limits, so numerical integration of the instantaneous equations (direct numerical simulations) for high Reynolds number natural flows is prohibitively expensive, if not outright impossible, at least for now.
Modeling comes to the rescue, but at a price. Large-eddy simulations, spectral methods, probability density function models, and the more classical Reynolds-stress models are examples of such closure schemes that are not as computationally intensive as direct numerical simulations, but are not as reliable either. This type of second-tier modeling is phenomenological in nature and does not stem from first principles. The more heuristic the modeling is, the less accurate the expected results.
Together with massive ground, sea, and sky data to provide at least in part the initial and boundary conditions, the models are entered into supercomputers that come out with a forecast. It may be a prediction of a severe thunderstorm that is yet to form, the future path and strength of an existing hurricane, or the impending concentration of a toxic gas that was released in a faraway location some time in the past. For other types of disasters such as earthquakes, the precise laws are not even known, mostly because proper constitutive relations are lacking. Additionally, deep underground data are difficult to gather, to say the least. Predictions in those cases become more or less a black art.
The important issue is to precisely state the assumptions needed to write the evolution equations, which are basically statements of the conservation of mass, momentum, and energy, in a certain form. The resulting equations and their eventual analytical or numerical solutions are valid only under those assumptions. This seemingly straightforward fact is often overlooked and wrong answers readily result when the situation we are trying to model is different from the one assumed.
The prediction of weather-related disasters has had spectacular successes within the last few decades. The pains-taking advances made in fluid mechanics in general and turbulence research in particular, together with the exponential growth of computer memory and speed, no doubt contributed immeasurably to those successes. A generation ago, the next day’s weather was hard to predict. Today, the 10-day forecast is available 24/7 on weather.com for almost any city in the world.
Imagine what we might do for the world if we could engineer systems as accurate as that to predict earthquake, famine, or war.
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Extensive literature exists on the application of engineering and physical science to the prediction and control of disasters. Here are a few that relate to points made in this article.
The seismic monitoring of Mount Etna is described in a paper, “Magma Ascent and the Pressurization of Mount Etna’s Volcanic System,” written by Domenico Patanè, Pasquale De Gori, Claudio Chiarabba, and Alessandro Bonaccorso, published in the journal Science in March 2003.
Andrew Adamatzky discusses crowd dynamics in his 2005 book, Dynamics of Crowd-Minds: Patterns of Irrationality in Emotions, Beliefs and Actions, published by World Scientific in London.
The Science of Disasters: Climate Disruptions, Heart Attacks, and Market Crashes, published by Springer of Berlin in 2002, contains a contribution by D. Helbing, I.J. Farkas, and T. Vicsek, “Crowd Disasters and Simulation of Panic Situations,” which also reports on the modeling of panic behavior in crowds.
Mohamed Gad-el-Hak discusses more ideas from Large-Scale Disasters: Prediction, Control and Mitigation, in a companion article, “Large-Scale Disasters as Dynamical Systems,” which is published exclusively on Mechanical Engineering Online.
Mohamed Gad-el-Hak, an ASME Fellow, is the Inez Caudill Eminent Professor of Biomedical Engineering and chair of mechanical engineering at Virginia Commonwealth University in Richmond.