When the Whole is Greater than the Sum of its Parts: Transport + Reaction in the Subsurface
Many significant problems in hydrogeology and environmental subsurface science require that we understand the transport of multiple constituents that undergo geochemical and biogeochemical reactions. Over the past several decades, our research has tended to be either 'transport-centric,' in which multi-dimensional spatially variable flow is considered while the reaction processes are lumped into a source/sink term; or 'reaction- centric,' in which a large number of coupled equilibrium and kinetic reactions are considered while transport processes are represented as a series of batch reactors. These distinct approaches fail to recognize that strong coupling of transport with reactions can lead to novel organized patterns of behavior, even for seemingly complicated systems with multiple nonlinear reactions. This presentation will include several examples of how the feedback among transport and reaction processes can lead to simplified self-organized patterns of behavior. For a mixture of chemical species undergoing competitive ion exchange and sorption reactions, this feedback leads to chromatographic separation into a series of traveling fronts, separated by zones of constant composition. Traveling wave behavior also emerges when reaction is controlled by the advective and dispersive mixing of two or more chemicals. Non-equilibrium sorption reactions can be manifested as enhanced spreading of a field-scale contaminant plume, which needs to be compared with other processes that lead to enhanced spreading, such as small-scale physical heterogeneity. These behavior patterns can be calculated with simple analytical formulas, allowing assessment of practical problems such as prediction of contaminant transit time, stable plume size for natural attenuation, and effectiveness of engineered in situ bioremediation.
Improving Model Identification: Reconciling Theory with Observations and The Problem of Sufficient Statistics
Three decades of attempts to improve the procedures by which we reconcile models with observational data have been driven by efforts such as that of Johnston and Pilgrim (WRR 1976) who reported that "A true optimum set of (parameter) values was not found in over 2 years of full-time work concentrated on one watershed, although many apparent optimum sets were readily obtained." Since that time, we have played with statistical theory (Likelihood, Bayesian and Multiple-Criteria methods) and optimization theory (Deterministic and Stochastic Global Search methods). But compared with the degree of effort expended, the improvements in model reliability have been relatively small, and the power to discriminate between alternative model hypotheses remains so weak that many people now prefer to talk about multiple 'equally likely' models. In this talk I will argue that for three decades we have effectively been putting the cart before the horse. With improved computational tools, our main focus has been on trying to improve model identification via improved mathematical rigor and through better and more robust statistics. However, the real problem of reconciling theory with observations (models with data) is not so much one of statistics as it is of information flow, a process that is bi-directional. On the one hand, the modeling problem is one of explicitly stating the hypothesis to be tested, along with a clear statement of what kinds of tests will unambiguously challenge the hypothesis. On the other hand, the observational problem is one of extracting diagnostically useful information from the data, information that directly supports or challenges the model hypothesis. The reconciliation problem is therefore more properly approached as one of a) making robust inferences regarding which aspects of the model hypothesis are (are not) supported by the observations, b) diagnostically guiding improvements to the theory (model), and c) suggesting what would constitute improvements to the process of acquiring observations. Recent work suggests that a general and robust theory of "Diagnostic Model Evaluation & Improvement" can be achieved through an improved understanding of the role of "Sufficient Statistics", which can be used to confront the model with relevant information extracted from the data. This task will require the active collaboration of process scientists, modelers and systems theorists alike.
Climate Information Responding to User Needs (CIRUN)
For the past several decades many different US agencies have been involved in collecting Earth observations,
e.g., NASA, NOAA, DoD, USGS, USDA. More recently, the US has led the international effort to design a Global
Earth Observation System of Systems (GEOSS). Yet, there has been little substantive progress at the synthesis
and integration of the various research and operational, space-based and in situ, observations. Similarly,
access to such a range of observations across the atmosphere, ocean, and land surface remains fragmented.
With respect to prediction of the Earth System, the US has not developed a comprehensive strategy. For
climate, the US (e.g., NOAA, NASA, DoE) has taken a two-track strategy. At the more immediate time scale,
coupled ocean-atmosphere models of the physical climate system have built upon the tradition of daily
numerical weather prediction in order to extend the forecast window to seasonal to interannual times scales.
At the century time scale, the nascent development of Earth System models, combining components of the
physical climate system with biogeochemical cycles, are being used to provide future climate change
projections in response to anticipated greenhouse gas forcings. Between these to two approaches to
prediction lies a key deficiency of interest to decision makers, especially as it pertains to adaptation, i.e.,
deterministic prediction of the Earth System at time scales from days to decades with spatial scales from
global to regional. One of many obstacles to be overcome is the design of present day observation and
prediction products based on user needs. To date, most of such products have evolved from the technology
and research "push" rather than the user or stakeholder "pull". In the future as planning proceeds for a
national climate service, emphasis must be given to a more coordinated approach in which stakeholders'
needs help design future Earth System observational and prediction products, and similarly, such products
need to be tailored to provide decision support.
Hydrosphere, Atmosphere, Lithosphere, Biosphere: A Global Geophysical Union
Water moves freely among the major spheres of the earth system, and, in so doing, it unites them. The atmosphere is driven, moistened and clouded by water in its changing phases, with ubiquitous climatic consequences. The biosphere's organisms depend on the "universal solvent" for access to and internal transport of nutrients, so much so that water availability defines the very geography of photosynthesis and life. The lithosphere is variously loaded, inflated, lubricated and eroded by water, with geodynamic consequences of all sorts. The ever-changing gravitational pull of earth's wandering waters is felt even in the exosphere. The movement of water among the spheres is partially regulated by, and has enormous consequences for, the anthroposphere. The influence of the hydrosphere on the other spheres creates interesting opportunities (indeed, necessities) for hydrologists to play with puzzles and problems beyond their own traditional sphere. In the experience of the speaker, the American Geophysical Union has been a playground that promotes such play, and the future promises more interdisciplinary fun; we have nothing to fear but spheres by themselves.