Consequences of Groundwater-Model Vertical Discretization in Risk-Based Decision-Making.

One of the first and most important decisions facing practitioners when constructing a numerical groundwater model is vertical discretization. Several factors will influence this decision, such as the conceptual model of the system and hydrostratigraphy, data availability, resulting computational burden, and the purpose of the modeling analysis. Using a coarse vertical discretization is an attractive option for practitioners because it reduces data requirements and model construction efforts, can increase model stability, and can reduce computational demand. However, using a coarse vertical discretization as a form of model simplification is not without consequence; this may give rise to unwanted side-effects such as biases in decision-relevant simulated outputs. Given its foundational role in the modeled representation of the aquifer system, herein we investigate how vertical discretization may affect decision-relevant simulated outputs using a paired complex-simple model analysis. A Bayesian framework and decision analysis approach are adopted. Two case studies are considered, one of a synthetic, linked unsaturated-zone/surface-water/groundwater hydrologic model and one of a real-world linked surface-water/groundwater hydrologic-nitrate transport model. With these models, we analyze decisions related to abstraction-induced changes in ecologically important streamflow characteristics and differences in groundwater and surface-water nitrate concentrations and mass loads following potential land-use change. We show that for some decision-relevant simulated outputs, coarse vertical discretization induces bias in important simulated outputs, and can lead to incorrect resource management action. For others, a coarse vertical discretization has little or no consequence for resource management decision-making.

Some Challenges Posed by Coal Bed Methane Regional Assessment Modeling.

Coal measures (coal bearing rock strata) can contain large reserves of methane. These reserves are being exploited at a rapidly increasing rate in many parts of the world. To extract coal seam gas, thousands of wells are drilled at relatively small spacing to depressurize coal seams to induce desorption and allow subsequent capture of the gas. To manage this process effectively, the effect of coal bed methane (CBM) extraction on regional aquifer systems must be properly understood and managed. Groundwater modeling is an integral part of this management process. However, modeling of CBM impacts presents some unique challenges, as processes that are operative at two very different scales must be adequately represented in the models. The impacts of large-scale gas extraction may be felt over a large area, yet despite the significant upscaling that accompanies construction of a regional model, near-well conditions and processes cannot be ignored. These include the highly heterogeneous nature of many coal measures, and the dual-phase flow of water and gas that is induced by coal seam depressurization. To understand these challenges, a fine-scale model was constructed incorporating a detailed representation of lithological heterogeneity to ensure that near-well processes and conditions could be examined. The detail of this heterogeneity was at a level not previously employed in models built to assess groundwater impacts arising from CBM extraction. A dual-phase reservoir simulator was used to examine depressurization and water desaturation processes in the vicinity of an extractive wellfield within this fine-scale model. A single-phase simulator was then employed so that depressurization errors incurred by neglecting near-well, dual-phase flow could be explored. Two models with fewer lithological details were then constructed in order to examine the nature of depressurization errors incurred by upscaling and to assess the interaction of the upscaling process with the requirement for adequate representation of near-source, dual-phase processes.