Simulation of Water-Table Aquifers Using Specified Saturated Thickness

• Published in: Ground water 2015-01, Vol.53 (1), p.151-157
• Main Authors: Sheets, Rodney A., Hill, Mary C., Haitjema, Henk M., Provost, Alden M., Masterson, John P.
• Format: Article
• Language: English
• Subjects: Approximation; Aquifers; Calibration; Computation; Computer simulation; Error analysis; Errors; Groundwater; Hydrodynamics; Mathematical analysis; Mathematical models; Models, Theoretical; Simulation; Thickness measurement; Water Movements
• ISSN: 0017-467X; 1745-6584
• DOI: 10.1111/gwat.12164

Simulating groundwater flow in a water‐table (unconfined) aquifer can be difficult because the saturated thickness available for flow depends on model‐calculated hydraulic heads. It is often possible to realize substantial time savings and still obtain accurate head and flow solutions by specifying an approximate saturated thickness a priori, thus linearizing this aspect of the model. This specified‐thickness approximation often relies on the use of the “confined” option in numerical models, which has led to confusion and criticism of the method. This article reviews the theoretical basis for the specified‐thickness approximation, derives an error analysis for relatively ideal problems, and illustrates the utility of the approximation with a complex test problem. In the transient version of our complex test problem, the specified‐thickness approximation produced maximum errors in computed drawdown of about 4% of initial aquifer saturated thickness even when maximum drawdowns were nearly 20% of initial saturated thickness. In the final steady‐state version, the approximation produced maximum errors in computed drawdown of about 20% of initial aquifer saturated thickness (mean errors of about 5%) when maximum drawdowns were about 35% of initial saturated thickness. In early phases of model development, such as during initial model calibration efforts, the specified‐thickness approximation can be a very effective tool to facilitate convergence. The reduced execution time and increased stability obtained through the approximation can be especially useful when many model runs are required, such as during inverse model calibration, sensitivity and uncertainty analyses, multimodel analysis, and development of optimal resource management scenarios.