IV. ANALYSIS: SUMMARY
IV-22
SUMMARY: ANALYSIS OF SEEPAGE CONDITIONS
Unit IV described:
• The basis for seepage analysis.
• Information needed for seepage analysis.
• The observational methods of analysis.
• The analytical methods of analysis.
• How to implement methods of seepage analysis.
Basis for Seepage Analysis
The logical analysis of seepage started with the development of Darcy's law in 1856 and the
realization that the Laplace equation governing heat and current flow conduction was also
applicable to the steady-state flow of an incompressible fluid through porous media. Darcy's
law and the Laplace equation are both used in the analysis of seepage conditions today with the
aid of computers.
Information Needed for Seepage Analysis
The information needed to analyze seepage conditions includes:
• The location of various boundaries and flow paths to define the particular porous media
mass considered in the analysis.
• Type of flow (whether the flow is laminar or turbulent).
• Permeability of the various materials through which the seepage flows.
Observational Methods of Seepage Analysis
The observational method of seepage analysis involves visually inspecting the area of seepage,
the surrounding conditions and all potentially related factors. Observations can include taking
readings from instrumentation, such as piezometers. Observations can be used to directly
evaluate a seepage problem and, if necessary, select a remedial action, or to furnish input data
for other methods of seepage analysis.
Analytical Methods of Seepage Analysis
Solutions to steady-state, laminar-flow seepage problems based on the Laplace equation rely on
mathematical solutions, or numerical computer solutions to the finite difference equation for
three or two-dimensional flow. Darcy’s law can be solved directly if the hydraulic gradient and
Darcy permeability are known. Flownets may also be used to solve two-dimensional flow based
on the known geometry of the structure and underlying strata.
Generally, analytical methods are used for design because observational data are not available