Even though water is very abundant on much of the Earth, 1.2 billion people lack access to clean, safe freshwater. This problem is critical, and even more critical in densely populated urban areas. Here human activities affect the quality of the water while increasing demand for it. There are many complex competing forces at play, all of which make this a difficult problem to address, much less to solve effectively with a coordinated policy.
Research from biology, hydrology, and geography, among other disciplines, helps scientists understand the basic nature of watershed ecology. However, a watershed is part of a larger, complex socio/environmental/economic system. Watersheds, or catchments, such as the Chesapeake Bay Watershed in the United States, serve millions of people. Each person depends on the watershed for basic human needs and yet contributes to the stresses on the watershed through his or her daily actions. Likewise the increasing demands for water from agriculture, transportation, energy, and industry strain a watershed's capacity to support a rapidly increasing and urbanized population. In studying the Chesapeake Bay Watershed, water quantity is not an issue; however, water quality is. One significant factor is that nitrogen and phosphorus nutrients flow from the land into the bay creating oxygen-starved "dead zones". A result is a decline in vegetation (sea grasses) and aquatic life such as the blue crab (callinectes sapidus). As these are stressed, the impacts are both environmental and economic.
The natural elements of watershed systems have been studied and modeled in great detail, both in terms of quantity and quality of the water for consumptive purposes. What has had less attention in modeling and simulation is the role of human activity as it affects water resources. This is partly because of the sheer size of the problem, but also because of the challenge of forecasting environmental and behavioral outcomes.
The goal of properly understanding and effectively managing a complex watershed system requires not only the representation of its natural processes but also explicit representation of the human actors in that system. Agent-based modeling and simulation is a tool well-suited to address this goal. An agent-based model does not predict a future outcome of a complex system; rather, it allows researchers to gain deeper understanding into the nature and dynamic behavior of the system through the very process of building the model. Via a large set of simulations spanning a wide variety of potential assumptions, it is possible to see how futures might unfold. This sort of experimentation provides an opportunity to generate hypotheses based on different assumptions and thus to discover interesting, unanticipated system responses.
The scientists at the University of Virginia started their study by developing a participatory simulation model of the Chesapeake Bay, the UVA Bay GameÃÂ® (www.virginia.edu/baygame). That project used a relatively simple simulation model of the natural elements and dynamics of the Chesapeake Bay. Human activity was captured through the decisions of live agents (game players) acting as crop farmers, land developers, watermen, and assorted regulators.
The UVA Bay Game was successful in providing a learning platform. To better understand the complex natural and human dynamics at work in this complex system, the researchers needed to develop a much more detailed simulation model. This model, without live players, captures the actions of some four million households with approximately 16.7 million persons living in the 64,000 square mile Chesapeake Bay Watershed. Each run of the model proceeds through a virtual time span of 20 years, simulating the effects of natural and human behaviors based on a specific set of assumptions. Millions of such simulation runs are required, each starting with a different set of assumptions. The assumptions vary many factors such as waste runoff, fertilizer usage, consumption of fresh water, human activity patterns, and many more. By studying the results of the millions of "what if" simulations, the scientists expect to develop insight into how these assumptions about the relevant natural and human processes affect the overall health of the Chesapeake Bay. With these insights, they will be able to better inform policy makers and suggest how prudent actions can lead to the restoration and sustainability of this important watershed.
Because of the amount of computational resources required to run the required simulations, the scientists have turned to World Community Grid for assistance. Using the resources available to them, this project would have taken about 90 years, and would not have been attempted. The power of World Community Grid will speed up the computation portion to just about one year.
Beyond the Chesapeake Bay in the United States, watersheds and catchments worldwide face similar stresses as population grows and urbanization increases. There are at least 400 major watersheds globally, with more than half of them already under stress. The methods and results developed in the Computing for Sustainable Water project should be applicable to these other regions across the globe facing similar challenges of sustainable water.
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