Optimization of Hydraulic Functions from Transient Outflow and Soil Water Pressure Data

Abstract

Inverse solution techniques currently used for estimating unsaturated soil hydraulic functions from laboratory outflow experiments use cumulative outflow only in combination with initial and final soil water pressure head values. Additional soil water information is needed to improve the estimation procedure and to minimize uniqueness problems. It was the objective of this study to experimentally explore the feasibility of using both cumulative outflow and soil water pressure head data in the inverse solution for laboratory determination of soil hydraulic functions using both one-step and multistep outflow experiments. Soil water pressure head was measured with a microtensiometer and pressure transducer. Desorption experiments were performed under both pressure and suction for the following soils: Yolo silt loam (flne-silty, mixed, nonacid, thermic Typic Xerorthent), Panoche loam (fine-loamy, mixed [calcareous], thermic TypicTorriorthent), Hanford sandy loam (coarse-loamy, mixed, nonacid, thermic Typic Xerorthent), and Oso-Flaco fine sand (coarse-loamy, mixed Typic Cryorthod-fine-loamy, mixed, raesic Ustollic Haplargid). Water retention curves optimized from cumulative outflow alone were compared with those obtained from outflow and soil water pressure head measurements for both one-step and multistep outflow experiments. Computer optimization of the retention curve by the inverse solution technique using transient outflow experiments was greatly improved when cumulative transient outflow data were combined with simultaneously measured soil water pressure bead data. Pressure and suction experiments yielded equally good results for one-step and multistep desorption. Moreover, the addition of soil water pressure head data resulted in unique parameter values for the optimized soil hydraulic functions under our experimental conditions. P REDICTION OF WATER MOVEMENT in soil as well as the fate of salts and contaminants under different combinations of soil, climatic, and management conditions is dependent on availability of representative Hydrologic Science, Dep.

Centrifuge modeling of one-step outflow tests for unsaturated parameter estimations

“…Their results showed that multi-step tests can contain sufficient information for unique estimates while one-step tests show poorer estimations. On the other hand, Eching and Hopmans (1993) conducted both one-step and multi-step outflow experiments, and with the inclusion of pore water pressure data in the inverse methods, both onestep and multi-step methods gave excellent results with the optimized parameters agreeing well with the independently measured p-θ data. Since the multi-step tests took twice as long to perform as the one-step tests, it was concluded that the one-step test is still an attractive option if pore water pressure measurements are available.…”

“…Multi-step tests, in which applied pneumatic pressure or suction is changed stepwise with small increments, have also been conducted (Eching and Hopmans, 1993;Eching et al, 1994;van Dam et al, 1994). van Dam et al (1994) carried out both one-step and multi-step experiments and compared the optimized parameters using only cumulative outflow as the input data.…”

Combined effect of heterogeneity, anisotropy and saturation on steady state flow and transport: Structure recognition and numerical simulation

“…[15] A series of multistep out-and inflow experiments [e.g., Eching and Hopmans, 1993] was performed to estimate the hydraulic properties of the three sands. Plexiglas columns with an inner diameter of 5.4 cm and a filter plate at the bottom were carefully filled with sand to a height of about 34 cm using the same filling tube as for preparing the layers of the heterogeneous tank.…”

Inverse estimation of soil hydraulic properties under oil palm trees

“…Inverse solutions based on the Richards equation are now increasingly used for estimating the unsaturated soil hydraulic properties. An advantage of this approach is that the retention and hydraulic conductivity functions can be estimated simultaneously from transient flow data, as shown by many past and recent studies (Abbasi et al, 2003;Abbaspour et al, 1999;Dane and Hruska, 1983;Eching and Hopmans, 1993;Kool and Parker, 1987;Lazarovitch et al, 2007;Minasny and Field, 2005;Ritter et al, 2003;Russo et al, 1991;Schwarzel et al, 2006;Sonnleitner et al, 2003;Zachmann et al, 1981). The soil hydraulic parameters are then obtained by minimizing an objective function, usually defined as the sum of squared deviations between observed and predicted transient water flow variables (Hopmans et al, 2002).…”