A New Paradigm for Groundwater Modeling

We present in this paper an innovative and sophisticated software environment, called Interactive Groundwater (IGW), for unified deterministic and stochastic groundwater modeling. Based on a set of efficient and robust computational algorithms, IGW allows simulating complex, 3D unsteady flow and solute transport in saturated porous media subject to both systematic and “random” stresses and geological and chemical heterogeneity. Adopting a new paradigm, IGW eliminates major bottlenecks inherent in the traditional, highly fragmented modeling schemes and allows fully utilizing today’s dramatically increased computing power. For many problems, the new computational environment enables real-time modeling, visualization, analysis, and presentation. IGW functions as a “numerical research laboratory” in which an investigator may freely explore: creating visually an aquifer system of desired configurations, interactively applying desired stresses and boundary conditions, and then investigating and visualizing on the fly the geology and the dynamic processes of flow and contaminant transport and transformation. At any time, a researcher can pause to edit and interact on-line with virtually any aspects of the modeling process and then resume the integrated visual exploration; he or she can initiate or stop particle tracking, plume modeling, hierarchical subscale modeling, stochastic modeling, monitoring, and mass balance analyses. IGW continually provides results that are intelligently processed, organized, overlaid, and displayed. It seamlessly and dynamically merges heterogeneous geospatial data and modeling inputs and outputs into composite 2D or 3D graphical images -integrating related data to provide a more complete view of the complex interplay among the geology, hydrology, flow system, and reactive transport dynamics. These unique capabilities of real-time modeling, dynamic steering, and visual analysis significantly expand the utility of groundwater models as tools for research, education, and professional investigation. This paper is the first of a sequence of articles that introduce systematically the IGW software environment, including the new modeling paradigm, capabilities, algorithmic innovations, verifications, stochastic and hierarchical modeling, and applications. a Department of Civil and Environmental Engineering Michigan State University, East Lansing, MI 48824 Introduction Despite an exponential growth of computational capability over the last two decades (see Figure 1) -one that has allowed computational science and engineering to become a unique, powerful tool for scientific discovery-the significant cost of groundwater modeling continues to limit its use. This occurs, for many problems, because the modeling paradigm that has been employed for decades fails to take full advantage of recent developments in computer, communication, graphic, and visualization technologies. A new paradigm that dynamically integrates modeling, analysis, and visualization into a single, sophisticated, and object-oriented program promises to substantially alleviate the current bottlenecks and significantly expand the utility of computational tools for research, education, and practical problem solving related to groundwater. Figure 1. The exponential growth in computer power. The computer processing speed increases by approximately an order of magnitude every five years. (source: Moravec, Oxford, 1998) Opportunities and Limits The enormous increases in computational speed and capacity achieved over the last two decades are responsible for both the development of computational science and engineering and its current status as a unique and powerful tool for scientific discovery. Model-based simulation, a key branch of this new discipline, provides the capability for simulating the behavior of complex systems under realistic environmental conditions. Model-based simulation creates a new window into the natural world [Sack, 1999]. Our understanding of subsurface flow and contaminant transport stands to benefit immensely from model-based research [Anderson and Woessner, 1992]. Models provide the ability to simulate the behavior of integrated, large-scale systems and interactions; they permit prediction of future outcomes based on previously studied events. Modeling can provide fundamental insights into the complex field-scale behavior of heterogeneous processes, the nonlinear effects of scale, the interactions between different aquifer systems, the influence of groundwater/surface water connections, and the interactions between geological, hydrological, and biochemical processes. Model-based simulation provides a systematic framework for assimilating and synthesizing field information and prioritizing sampling activities. Modeling becomes particularly useful for addressing ”what-if” types of questions, testing hypothesis, assessing data-worth and model uncertainty, and evaluating management, monitoring, and cleanup options. Modeling makes it possible for scientists and engineers to see the unseen, to develop new understanding, and to predict the future [Anderson and Woessner, 1992; Bear, 1979; Bredehoeft, 2002; Zheng and Bennett, 2002; Kinzelbach, 1986]. Of course, practical implementation of groundwater models can be difficult and costly, especially for integrated problem solving and investigations. This is so, in many cases, not because the problems we are solving today are simply too large and complex, the computers available today are too slow and expensive, the solvers and numerical schemes used in most software are inefficient, the graphical user interfaces for individual models are still too difficult to employ, or the utility programs for post-processing, intermediate analyses, data reformatting, visualization and presentation are still not sufficiently sophisticated. This is so often because the basic modeling paradigm that has been used for decades and perhaps taken for granted is unable to take full advantage of recent developments in computer, communication, graphic, and visualization technologies.