Elements of complexity in subsurface modeling, exemplified with three case studies; [Eléments de complexité dans la modélisation du sous-sol, illustrés par trois études de cas]; [Elementos de complexidade na modelagem subsuperficial, exemplificado com três estudos de caso]; [Elementos de complejidad en el modelado del subsuelo, ejemplificados con tres estudios de caso]

There are complexity elements to consider when applying subsurface flow and transport models to support environmental analyses. Modelers balance the benefits and costs of modeling along the spectrum of complexity, taking into account the attributes of more simple models (e.g., lower cost, faster execution, easier to explain, less mechanistic) and the attributes of more complex models (higher cost, slower execution, harder to explain, more mechanistic and technically defensible). In this report, modeling complexity is examined with respect to considering this balance. The discussion of modeling complexity is organized into three primary elements: (1) modeling approach, (2) description of process, and (3) description of heterogeneity. Three examples are used to examine these complexity elements. Two of the examples use simulations generated from a complex model to develop simpler models for efficient use in model applications. The first example is designed to support performance evaluation of soil-vapor-extraction remediation in terms of groundwater protection. The second example investigates the importance of simulating different categories of geochemical reactions for carbon sequestration and selecting appropriate simplifications for use in evaluating sequestration scenarios. In the third example, the modeling history for a uranium-contaminated site demonstrates that conservative parameter estimates were inadequate surrogates for complex, critical processes and there is discussion on the selection of more appropriate model complexity for this application. All three examples highlight how complexity considerations are essential to create scientifically defensible models that achieve a balance between model simplification and complexity. © 2017, Springer-Verlag Berlin Heidelberg.