Determination of hydraulic conductivity as a function of depth and water content for soil in situ

Rose, C. W.; Stern, WR; Drummond, JE

doi:10.1071/sr9650001

Cited by 132 publications

(49 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The water content data for the unsteady drainage-flux experiment at the McGee Ranch are listed in Appendix A, Table A Hydraulic conductivities were calculated by a time-averaging approach (Rose, Stern, and Drummond 1965), using actual head gradients rather than an assumed unit gradient. These data are listed in Appendix A, Table A Figure 4.16 it appears as though the gradients are relatively constant in time.…”

Section: Unsteady Drainage-flux Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Characterization of unsaturated hydraulic conductivity at the Hanford Site

Rockhold¹,

Fayler²,

Gee³

1988

View full text Add to dashboard Cite

Section: Unsteady Drainage-flux Methodsmentioning

confidence: 99%

“…Further developments in the method were made by Nielsen et. al (1964); Rose, Stern, and Drummond (1965);and Watson (1966). The actual computations of hydraulic conductivity used in this study are based on the timeaveraging method used by Rose, Stern, and Drummond (1965), and the instantaneous profile method (after Watson 1966).…”

Section: Unsteady Drainage-fluxmentioning

confidence: 99%

Characterization of unsaturated hydraulic conductivity at the Hanford Site

Rockhold¹,

Fayler²,

Gee³

1988

View full text Add to dashboard Cite

“…For in situ conditions, possible methods are the plane of zero flux (Rose et al, 1965), constant flux vertical time domain reflectometry (Parkin et al, 1995) and the instantaneous profile method (Rose et al, 1965). The instantaneous profile method of Rose et al (1965) is also considered the reference method (Vichuad and Dane, 2002).…”

Section: S S W Mavimbela and L D Van Rensburg: Estimating Hydraumentioning

confidence: 99%

Estimating hydraulic conductivity of internal drainage for layered soils in situ

Mavimbela

Rensburg

2013

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. The soil hydraulic conductivity (K function) of three layered soils cultivated at Paradys Experimental Farm, near Bloemfontein (South Africa), was determined from in situ drainage experiments and analytical models. Pre-ponded monoliths, isolated from weather and lateral drainage, were prepared in triplicate on representative sites of the Tukulu, Sepane and Swartland soil forms. The first two soils are also referred to as Cutanic Luvisols and the third as Cutanic Cambisol. Soil water content (SWC) was measured during a 1200 h drainage experiment. In addition soil physical and textural data as well as saturated hydraulic conductivity (K s ) were derived. Undisturbed soil core samples of 105 mm with a height of 77 mm from soil horizons were used to measure soil water retention curves (SWRCs). Parameterization of SWRC was through the Brooks and Corey model. Kosugi and van Genuchten models were used to determine SWRC parameters and fitted with a RMSE of less 2 %. The SWRC was also used to estimate matric suctions for in situ drainage SWC following observations that laboratory and in situ SWRCs were similar at near saturation. In situ K function for horizons and the equivalent homogeneous profiles were determined. Model predictions based on SWRC overestimated horizons K function by more than three orders of magnitude. The van Genuchten-Mualem model was an exception for certain soil horizons. Overestimates were reduced by one or more orders of magnitude when inverse parameter estimation was applied directly to drainage SWC with HYDRUS-1D code. Best fits (R 2 ≥ 0.90) were from Brooks and Corey, and van Genuchten-Mualem models. The latter also predicted the profiles' effective K function for the three soils, and the in situ based function was fitted with R 2 ≥ 0.98 irrespective of soil type. It was concluded that the inverse parameter estimation with HYDRUS-1D improved models' K function estimates for the studied layered soils.

show abstract

“…For instance, if the VG model with three unknown parameters (Ks, a, and n) is used, at least three different discharge rates and pressure head profiles at three times are needed to create three independent equations. This scenario actually forms the basis of the well -known instantaneous profile method (Rose et al, 1965;Watson, 1966).…”

Section: Introductionmentioning

confidence: 99%

Stochastic Fusion of Information for Characterizing and Monitoring the Vadose Zone

Yeh

Šimůnek

2002

Vadose Zone Journal

View full text Add to dashboard Cite

Inverse problems for vadose zone hydrological processes are often being perceived as illposed and intractable. Consequently, solutions to inverse problems are often subject to skepticism. In this paper, using examples, we elucidate difficulties associated with inverse problems and the prerequisites for such problems to be well -posed so that a unique solution exists. We subsequently explain the need of a stochastic conceptualization of the inverse problem and, in turn, the conditional-effective -parameter concept. This concept aims to resolve the ill -posed nature of inverse problems for the vadose zone, for which generally only sparse data are available. Next, the development of inverse methods for the vadose zone, based on a conditional -effective -parameter concept, is explored, including cokriging, the use of a successive linear estimator, and a sequential estimator. Their applications to the vadose zone inverse problems are subsequently examined, which include hydraulic /pneumatic and electrical resistivity tomography surveys, and hydraulic conductivity estimation using observed pressure heads, concentrations, and arrival times. Finally, a stochastic information fusion technology is presented that assimilates information from unsaturated hydraulic tomography and electrical resistivity tomography. This technology offers great promise to effectively characterize heterogeneity, to monitor processes in the vadose zone, and to quantify uncertainty associated with vadose zone characterization and monitoring.

show abstract

Determination of hydraulic conductivity as a function of depth and water content for soil in situ

Cited by 132 publications

References 6 publications

Characterization of unsaturated hydraulic conductivity at the Hanford Site

Characterization of unsaturated hydraulic conductivity at the Hanford Site

Estimating hydraulic conductivity of internal drainage for layered soils in situ

Stochastic Fusion of Information for Characterizing and Monitoring the Vadose Zone

Contact Info

Product

Resources

About