Identification of hydraulic parameters in layered soils based on a quasi-Newton method

Zijlstra, Jan J; Dane, J. H.

doi:10.1016/0022-1694(95)02909-5

Cited by 33 publications

(21 citation statements)

References 17 publications

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“…Agreement between in situ and predicted hydraulic functions was generally satisfactory, even though the K function was highly variable. The K function variability was attributed not only to spatial variability but also to the computational and convergence efficiency of the model in which many parameters are simultaneously optimised (Zijlstra and Dane, 1996). Consequently, lack of parameter uniqueness and lower boundary conditions limitations are common deficiencies in inverse modelling of soils with contrasting horizons (Romano, 1993).…”

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

confidence: 99%

“…Consequently, lack of parameter uniqueness and lower boundary conditions limitations are common deficiencies in inverse modelling of soils with contrasting horizons (Romano, 1993). Narrow SWC range depicted by internal drainage experiments especially from poorly drained soils can result in ill-posed inverse solution and parameter estimation of soil hydraulic properties (Zijlstra and Dane, 1996;Simunek et al, 1998;Hopmans and Simunek, 1999).…”

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

confidence: 99%

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Estimating hydraulic conductivity of internal drainage for layered soils in situ

Mavimbela

Rensburg

2013

Hydrol. Earth Syst. Sci.

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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.

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

confidence: 99%

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.

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“…In recent years, inverse methods of parameter optimization applied to field experiments have became popular and appear promising [3][4][5][6]. Various optimization methods such as Simplex [4], quasi-Newton [7], Levenberg-Marquardt [6,8], Ant Colony [9] and Adjoint method [10] have been used for parameter estimation of unsaturated parameters. In particular, the estimation of the saturated hydraulic conductivity k is rather critical because the groundwater flow is highly sensitive to this parameter [11].…”

Section: Introductionmentioning

confidence: 99%

Hydraulic conductivity estimation in partially saturated soils using a full‐Newton method

Guarracino

Santos

2007

Commun. Numer. Meth. Engng.

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SUMMARYAn iterative algorithm based on a full-Newton method for the estimation of the saturated hydraulic conductivity k from drainage experiments is presented. The water flow in the unsaturated zone is assumed to be described by Richards equation and the well-known van Genuchten constitutive model. The cost functional used for the parameter optimization is defined as the L 2 -error between the calculated pressure head values and the observed data at discrete points in the soil profile during the drainage process. The derivative of pressure head with respect to the parameter k is obtained as the solution of a differential equation with appropriate boundary and initial conditions. A Galerkin finite element procedure is used to obtain approximated solutions of the two differential problems involved in each iteration: the direct problem and the derivative of the functional. The algorithm was implemented in one-dimensional domains and used to estimate k in layered soils using both synthetically generated data and observed data from an experimental plot in the Azul River basin (Buenos Aires, Argentina). Numerical examples show that the proposed algorithm yields very good estimations of the saturated hydraulic conductivity and becomes a promising method for in situ estimation of this parameter.

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“…Van Dam et al, 1994;Hopmans et al, 2002), and later used in field scale applications (e.g. Zijlstra and Dane, 1996;Mertens et al, 2006), with the early field application by Dane and Hruska (1983) as an exception. An important advantage of inverse procedures, if formulated within the context of a parameter optimization problem, is that a detailed error analysis of the estimated parameter can be obtained.…”

Section: Introductionmentioning

confidence: 99%

“…An important advantage of inverse procedures, if formulated within the context of a parameter optimization problem, is that a detailed error analysis of the estimated parameter can be obtained. However, while parameter optimization methods provide several advantages, a number of problems related to computational efficiency, convergence, and parameter uniqueness remain to be solved, especially when many hydraulic parameters should be estimated simultaneously (Van Genuchten and Leji, 1992;Zijlstra and Dane, 1996).…”

Section: Introductionmentioning

confidence: 99%

Using an inverse modelling approach to evaluate the water retention in a simple water harvesting technique

Verbist

Cornelis

Gabriëls

et al. 2009

Hydrol. Earth Syst. Sci.

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Abstract. In arid and semi-arid zones, runoff harvesting techniques are often applied to increase the water retention and infiltration on steep slopes. Additionally, they act as an erosion control measure to reduce land degradation hazards. Nevertheless, few efforts were observed to quantify the water harvesting processes of these techniques and to evaluate their efficiency. In this study, a combination of detailed field measurements and modelling with the HYDRUS-2D software package was used to visualize the effect of an infiltration trench on the soil water content of a bare slope in northern Chile. Rainfall simulations were combined with high spatial and temporal resolution water content monitoring in order to construct a useful dataset for inverse modelling purposes. Initial estimates of model parameters were provided by detailed infiltration and soil water retention measurements. Four different measurement techniques were used to determine the saturated hydraulic conductivity (K sat ) independently. The tension infiltrometer measurements proved a good estimator of the K sat value and a proxy for those measured under simulated rainfall, whereas the pressure and constant head well infiltrometer measurements showed larger variability. Six different parameter optimization functions were tested as a combination of soil-water content, water retention and cumulative infiltration data. Infiltration data alone proved insufficient to obtain high model accuracy, due to large scatter on the data set, and water content data were needed to obtain optimized effective parameter sets with small confidence intervals. Correlation between the observed soil water content and the simulated values was as high as R 2 =0.93 for ten selected observation points used in the model calibration phase, with overall correlation for Correspondence to: K. Verbist (koen.verbist@ugent.be) the 22 observation points equal to 0.85. The model results indicate that the infiltration trench has a significant effect on soil-water storage, especially at the base of the trench.

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Identification of hydraulic parameters in layered soils based on a quasi-Newton method

Cited by 33 publications

References 17 publications

Estimating hydraulic conductivity of internal drainage for layered soils in situ

Estimating hydraulic conductivity of internal drainage for layered soils in situ

Hydraulic conductivity estimation in partially saturated soils using a full‐Newton method

Using an inverse modelling approach to evaluate the water retention in a simple water harvesting technique

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