Estimating Characteristic Grain Sizes and Effective Porosity from Hydraulic Conductivity Data.

Abstract

In groundwater applications, knowledge about a range of hydraulically relevant parameters is beneficial to counteract data scarcity and enhance parameter robustness. The present study provides a novel procedure to reverse engineer representative grain diameters and effective porosity from values of hydraulic conductivity. A large data set comprising more than 500 sieve curves and more than 1000 values of hydraulic conductivity was analyzed for interparameter dependencies between characteristic grain sizes, hydraulic conductivity and effective porosity. Based on that analysis, a mathematical model consisting of a set of empirical and physically based equations was developed. The procedure was applied on another large data set and its accuracy, deviations and error propagation were quantified. The method works best for well-sorted sediments. Practical examples are given in order to demonstrate the range of applicability of the procedure. The input is interchangeable, such that different input data enable calculating characteristic grain sizes, hydraulic conductivity and effective porosity. A free, open-source stand-alone GUI of the procedure is available for download.