Estimating soil hydraulic properties and their uncertainty: the use of stochastic simulation in the inverse modelling of the evaporation method

Geoderma ◽  
2005 ◽  
Vol 126 (3-4) ◽  
pp. 277-290 ◽  
Author(s):  
Budiman Minasny ◽  
Damien J. Field
Keyword(s):  
Stochastic Simulation ◽  
Hydraulic Properties ◽  
Inverse Modelling ◽  
Soil Hydraulic Properties ◽  
Evaporation Method ◽  
Soil Hydraulic

scholarly journals Upward infiltration–evaporation method to estimate soil hydraulic properties

2017 ◽  
Vol 62 (10) ◽  
pp. 1683-1693 ◽  
Author(s):  
C. Peña-Sancho ◽  
T.A. Ghezzehei ◽  
B. Latorre ◽  
C. González-Cebollada ◽  
D. Moret-Fernández
Keyword(s):  
Hydraulic Properties ◽  
Soil Hydraulic Properties ◽  
Evaporation Method ◽  
Soil Hydraulic

scholarly journals Assessing the cover crop effect on soil hydraulic properties by inverse modelling in a 10-year field trial

2019 ◽  
Vol 222 ◽  
pp. 62-71
Author(s):  
Jose Luis Gabriel ◽  
Miguel Quemada ◽  
Diana Martín-Lammerding ◽  
Marnik Vanclooster
Keyword(s):  
Cover Crop ◽  
Field Trial ◽  
Hydraulic Properties ◽  
Inverse Modelling ◽  
Soil Hydraulic Properties ◽  
Soil Hydraulic

scholarly journals Further tests of the HYPROP evaporation method for estimating the unsaturated soil hydraulic properties

2018 ◽  
Vol 66 (2) ◽  
pp. 161-169 ◽  
Author(s):  
Camila R. Bezerra-Coelho ◽  
Luwen Zhuang ◽  
Maria C. Barbosa ◽  
Miguel Alfaro Soto ◽  
Martinus Th. van Genuchten
Keyword(s):  
Hydraulic Conductivity ◽  
Unsaturated Soil ◽  
Hydraulic Properties ◽  
Water Retention ◽  
Measurement Techniques ◽  
Richards Equation ◽  
Water Retention Curve ◽  
Soil Hydraulic Properties ◽  
Evaporation Method ◽  
Soil Hydraulic

AbstractMany soil, hydrologic and environmental applications require information about the unsaturated soil hydraulic properties. The evaporation method has long been used for estimating the drying branches of the soil hydraulic functions. An increasingly popular version of the evaporation method is the semi-automated HYPROP©measurement system (HMS) commercialized by Decagon Devices (Pullman, WA) and UMS AG (München, Germany). Several studies were previously carried out to test the HMS methodology by using the Richards equation and the van-Genuchten-Mualem (VG) or Kosugi-Mualem soil hydraulic functions to obtain synthetic data for use in the HMS analysis, and then to compare results against the original hydraulic properties. Using HYDRUS-1D, we carried out independent tests of the HYPROP system as applied to the VG functions for a broad range of soil textures. Our results closely agreed with previous findings. Accurate estimates were especially obtained for the soil water retention curve and its parameters, at least over the range of available retention measurements. We also successfully tested a dual-porosity soil, as well as an extremely coarse medium with a very high van Genuchtennvalue. The latter case gave excellent results for water retention, but failed for the hydraulic conductivity. In many cases, especially for soils with intermediate and highnvalues, an independent estimate of the saturated hydraulic conductivity should be obtained. Overall, the HMS methodology performed extremely well and as such constitutes a much-needed addition to current soil hydraulic measurement techniques.

scholarly journals Inverse modelling of in situ soil water dynamics: accounting for heteroscedastic, autocorrelated, and non-Gaussian distributed residuals

2015 ◽  
Vol 12 (2) ◽  
pp. 2155-2199 ◽  
Author(s):  
B. Scharnagl ◽  
S. C. Iden ◽  
W. Durner ◽  
H. Vereecken ◽  
M. Herbst
Keyword(s):  
Least Squares ◽  
Soil Water ◽  
Hydraulic Properties ◽  
Ordinary Least Squares ◽  
Water Dynamics ◽  
Inverse Modelling ◽  
Parameter Estimates ◽  
Soil Hydraulic Properties ◽  
Likelihood Model ◽  
Soil Hydraulic

Abstract. Inverse modelling of in situ soil water dynamics is a powerful tool to test process understanding and determine soil hydraulic properties at the scale of interest. The observations of soil water state variables are typically evaluated using the ordinary least squares approach. However, the underlying assumptions of this classical statistical approach of independent, homoscedastic, and Gaussian distributed residuals are rarely tested in practice. In this case study, we estimated the soil hydraulic properties of a homogeneous, bare soil profile from field observations of soil water contents. We used a formal Bayesian approach to estimate the posterior distribution of the parameters in the van Genuchten–Mualem (VGM) model of the soil hydraulic properties. Three likelihood models that differ with respect to assumptions about the statistical features of the time series of residuals were used. Our results show that the assumptions of the ordinary least squares did not hold, because the residuals were strongly autocorrelated, heteroscedastic and non-Gaussian distributed. From a statistical point of view, the parameter estimates obtained with this classical statistical approach are therefore invalid. Since a test of the classic first-order autoregressive (AR(1)) model led to strongly biased model predictions, we introduced an modified AR(1) model which eliminates this critical deficit of the classic AR(1) scheme. The resulting improved likelihood model, which additionally accounts for heteroscedasticity and nonnormality, lead to a correct statistical characterization of the residuals and thus outperformed the other two likelihood models. We consider the corresponding parameter estimates as statistically correct and showed that they differ systematically from those obtained under ordinary least squares assumptions. Moreover, the uncertainty in the parameter estimates was increased by accounting for autocorrelation in the observations. Our results suggest that formal Bayesian inference using a likelihood model that correctly formalizes the statistical properties of the residuals may also prove useful in other inverse modelling applications in soil hydrology.

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