8.8 Slug Tests
Pumping tests are not always feasible for various reasons. It could be that a suitable pump is not available or is beyond the budget for the project. Or it could be that the aquifer is not very productive, and the available wells are not capable of pumping long enough at sufficient rates to collect adequate data for analysis. It could also be that the aquifer is highly contaminated, in which case running a pumping test would result in the production of large volumes of contaminated water that require treatment and disposal that is too expensive for the project budget. For such cases there are alternative methods called slug tests. These tests involve displacing a known quantity—that is, a “slug”—of water to or from a well or piezometer and monitoring water levels in the well as the water level recovers to the initial static water level. Water can be added to or removed from the well, or the water level can be displaced using a slug made of a cylinder (usually a sealed length of pipe that is filled with sand or cement) that is lowered into the well below the water table. The basic theory behind slug testing is that the well is in hydraulic equilibrium with the aquifer at the start of the test, then the slug displaces the water level and essentially creates a hydraulic gradient between the water level in the well and the hydraulic head in the aquifer. This gradient then drives the water level in the well back to hydraulic equilibrium, which manifests as a recovery of water levels in the well over time.
Test Procedure
The general procedure for slug tests involves measuring the static water level in the well, then introducing or removing a slug or a volume water, taking an initial measurement at the start of recovery ([latex]h_{0}[/latex]), then measuring the heads ([latex]h[/latex]) at various times during the recovery period. The quantities of [latex]\frac{h}{h_{0}}[/latex] at each measurement time, called the residual drawdown, are generally the key values used to analyze the slug testing results.
There are many methods for analyzing slug test data, including manually matching to type curves as well as sophisticated numerical computer methods. A detailed overview of slug test analysis is presented in section 14 of An Introduction to Hydraulic Testing in Hydrogeology: Basic Pumping, Slug, and Packer Methods↗ by Woessner and others (2023) and in Analysis and Evaluation of Pumping Test Data (2nd edition) ↗ by Kruseman and others (2000). Both books are available as free downloads from The Groundwater Project. Students and working hydrogeologists who would like more information about conducting and analyzing slug tests should download and review those books. An exercise related to slug tests is provided as Exercise 7 in the in the book by Woessner and others (2023).
Potential Problems with Slug Tests
One limitation of slug tests is that they are generally not capable of determining storage parameters—that is, storativity, specific yield—for the aquifer. There are complex numerical methods that can derive reasonable estimates; however, these are difficult to use and generally not widely available. This can be a major limitation for aquifer studies that require prediction of the impacts of future pumping, as those predictions require reliable storage parameters.
A second limitation of slug tests, and single well tests in general, is related to the scale of the volume of aquifer measured. For multi‑well aquifer tests with a pumping well and a single observation well, the drawdown response in the observation well reflects a somewhat integrated “average”, or representative, transmissivity and storativity for the part of the aquifer between the two wells. For any single well test, the test is at best measuring a very small volume of the aquifer around the well. Aquifers always have some amount of heterogeneity, or spatial variability in the permeability and storage parameters, and multi‑well tests generally integrate this variability better than single well tests. On the other hand, slug tests can help investigate heterogeneity when multiple wells are available for testing on a study site.
Finally, for slug tests and single well tests in general, the well loss and influence of the filter pack have a significant impact on test results. Care must be taken when performing slug tests to ensure that a sufficient stress—that is, water level displacement—is applied to the well to adequately stress the aquifer outside of the well. Most piezometers and wells have a gravel pack or filter pack (Figure 34 and Figure 35), which is a zone of high‑permeability sand and gravel emplaced in the annulus between the well screen and the intact aquifer formation. When performing a slug test, the displacement of the water level and resulting re‑equilibration of the well with the aquifer will be affected by the filter pack in the well, and if an insufficient stress is applied to the well, then the test will measure the permeability of the filter pack rather than the aquifer. Since a properly designed filter pack is intended to be more permeable than the aquifer, the results of the test will likely over‑state the permeability of the aquifer and make the test results unreliable.