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Title: Complex Systems Science for Subsurface Fate and Transport Report from the August 2009 Workshop

Technical Report ·
DOI:https://doi.org/10.2172/977127· OSTI ID:977127

The subsurface environment, which encompasses the vadose and saturated zones, is a heterogeneous, geologically complex domain. Believed to contain a large percentage of Earth's biomass in the form of microorganisms, the subsurface is a dynamic zone where important biogeochemical cycles work to sustain life. Actively linked to the atmosphere and biosphere through the hydrologic and carbon cycles, the subsurface serves as a storage location for much of Earth's fresh water. Coupled hydrological, microbiological, and geochemical processes occurring within the subsurface environment cause the local and regional natural chemical fluxes that govern water quality. These processes play a vital role in the formation of soil, economically important fossil fuels, mineral deposits, and other natural resources. Cleaning up Department of Energy (DOE) lands impacted by legacy wastes and using the subsurface for carbon sequestration or nuclear waste isolation require a firm understanding of these processes and the documented means to characterize the vertical and spatial distribution of subsurface properties directing water, nutrient, and contaminant flows. This information, along with credible, predictive models that integrate hydrological, microbiological, and geochemical knowledge over a range of scales, is needed to forecast the sustainability of subsurface water systems and to devise ways to manage and manipulate dynamic in situ processes for beneficial outcomes. Predictive models provide the context for knowledge integration. They are the primary tools for forecasting the evolving geochemistry or microbial ecology of groundwater under various scenarios and for assessing and optimizing the potential effectiveness of proposed approaches to carbon sequestration, waste isolation, or environmental remediation. An iterative approach of modeling and experimentation can reveal powerful insights into the behavior of subsurface systems. State-of-science understanding codified in models can provide a basis for testing hypotheses, guiding experiment design, integrating scientific knowledge on multiple environmental systems into a common framework, and translating this information to support informed decision making and policies. Subsurface behavior typically has been investigated using reductionist, or bottom-up approaches. In these approaches, mechanisms of small-scale processes are quantified, and key aspects of their behaviors are moved up to the prediction scale using scaling laws and models. Reductionism has and will continue to yield essential and comprehensive understanding of the molecular and microscopic underpinnings of component processes. However, system-scale predictions cannot always be made with bottom-up approaches because the behaviors of subsurface environments often simply do not result from the sum of smaller-scale process interactions. Systems exhibiting such behavior are termed complex and can range from the molecular to field scale in size. Complex systems contain many interactive parts and display collective behavior including emergence, feedback, and adaptive mechanisms. Microorganisms - key moderators of subsurface chemical processes - further challenge system understanding and prediction because they are adaptive life forms existing in an environment difficult to observe and measure. A new scientific approach termed complex systems science has evolved from the critical need to understand and model these systems, whose distinguishing features increasingly are found to be common in the natural world. In contrast to reductionist approaches, complexity methods often use a top-down approach to identify key interactions controlling diagnostic variables at the prediction scale; general macroscopic laws controlling system-scale behavior; and essential, simplified models of subsystem interactions that enable prediction. This approach is analogous to systems biology, which emphasizes the tight coupling between experimentation and modeling and is defined, in the context of Biological Systems Science research programs under DOE's Office of Biological and Environmental Research (BER), as ''the holistic, multidisciplinary study of complex interactions that specify the function of an entire biological system - whether single cells or a multicellular organism - rather than the reductionist study of individual components.'' In August 2009, BER held the Subsurface Complex System Science Relevant to Contaminant Fate and Transport workshop to assess the merits and limitations of complex systems science approaches to subsurface systems controlled by coupled hydrological, microbiological, and geochemical processes.

Research Organization:
DOESC (USDOE Office of Science (SC) (United States))
Sponsoring Organization:
USDOE; Office of Biological and Environmental Research
OSTI ID:
977127
Report Number(s):
DOE/SC-0123; TRN: US1004147
Country of Publication:
United States
Language:
English