17 Wrap-up
This book is intended to provide the reader with the conceptual, mathematical, and practical foundation of hydraulic testing and how it is used to obtain hydrogeologic properties of groundwater systems. It provides basic concepts and methods to conduct and analyze hydraulic tests. Field‑scale values of hydraulic conductivity, transmissivity, and storativity derived from hydraulic testing underpin all site‑ and regional‑scale hydrogeological investigations.
This book presents methods used to analyze test data in addition to laying out the mechanics of conducting pumping, slug, and packer tests. We emphasized the constraints of applying analytical models (analytical equations) to forecast future aquifer responses to pumping and to fit observed hydraulic‑test responses to existing basic models. Explaining and illustrating manual curve‑matching methods was purposefully presented so that the reader clearly understands the processes used to derive hydrogeologic properties when applying automated analysis tools.
Responsible application of basic analytical models is a goal of this book. Available pumping‑ and slug‑test‑analysis software applies these same models. When preparing to analyze pumping tests it is easy to open a commercial software program with 20 available analytical methods describing a wide variety of settings, and then without properly accounting for aquifer type, well design, or test conditions, “magically” generate estimates of hydrogeologic parameters using best‑fit approaches. We contend that without knowing the constraints under which the individual models were developed (assumptions and limits) and understanding nuances of the curve‑matching process (fitting of the type curves and observed data set), the easy‑to‑use software can be easily misused. Such actions occur even though the software developers go to extensive lengths to provide users with detailed information, including describing assumptions and limitations of each analytical tool provided. The hydrogeological context of each test site determines the possible appropriate conceptual models, not the other way around (i.e., getting a good fit in automated software does not mean that the analysis is appropriate for a site). The selected conceptual model must be carefully evaluated to determine if it appropriately describes the field setting that is being evaluated. In many cases, field conditions do not result in data that fit well with analytical models. This is because assumptions such as the tested unit being homogeneous, isotropic, and infinite in lateral extent may not accurately represent conditions at the test site.
As with pumping test approaches, slug‑ and packer‑testing methods must also fit the hydrogeologic setting. When conducting these types of tests is important that the formational properties are being tested instead of perforated‑interval conditions and skin effects. The formation should be freely connected to the screened/open interval. Data collection in some cases requires recording head changes in fractions of a second, while others require months.
The section on analyzing results of single‑well pumping tests is presented because groundwater investigations are costly. Allocated project funds may not allow drilling of new wells specifically for pumping and slug testing. Pumping a single well and recording time‑drawdown data during a step test and constant‑discharge test provide well‑loss information and reasonable estimates of transmissivity. Evaluation of a number of performance test results as reported on driller’s logs is often adequate to estimate order of magnitude transmissivity values of a system without conducting new well tests.
Many authors have formulated additional analytical models for a wide variety of hydrogeologic conditions since Theis (1935) initially developed his analytical solution and curve‑matching method. Analytical solutions are still the primary tools used to analyze pumping‑test data. When conditions are more complex, fewer analytical models are available. This can sometimes be addressed by combining analytical solutions (e.g., superposition to include well interference and hydraulic boundaries; or analytic element methods as described by Haitjema (1995)). In other settings, numerical groundwater‑flow modeling tools calibrated to hydraulic‑test data are used to evaluate hydraulic‑parameter magnitudes and distributions, as well as the effect of boundary conditions in complex hydrogeological settings (e.g., Anderson et al., 2015). Such tools are more flexible in representing anisotropic and heterogeneous settings with complex boundary conditions and multiple layers. However, relatively simple analytical models are most often used to analyze hydraulic‑test results for estimation of K, T, S and Ss. When applied with care, the analytical results provide hydrogeologists with aquifer and aquitard characteristics needed to quantify groundwater flows, and to forecast responses to pumping and naturally occurring perturbations of the groundwater system.