A general BEST method predicting soil hydraulic parameters for any type of water retention and hydraulic conductivity curves

2020 ◽  
Author(s):  
Jesús Fernández-Gálvez ◽  
Joseph Pollacco ◽  
Laurent Lassabatere ◽  
Rafael Angulo-Jaramillo ◽  
Sam Carrick
Keyword(s):  
Hydraulic Conductivity ◽  
Water Retention ◽  
Pedotransfer Functions ◽  
Distribution Data ◽  
Hydraulic Parameters ◽  
Pore Size Distributions ◽  
Soil Transfer ◽  
Soil Hydraulic Parameters ◽  
Transfer Parameters ◽  
Soil Hydraulic

<p>Soil hydraulic characterization is crucial to describe the retention and transport of water in soil, but current methodologies limit its spatial applicability. This work presents a cost-effective general Beerkan Estimation of Soil Transfer parameters (BEST) methodology using single ring infiltration experiments to derive soil hydraulic parameters for any type of unimodal water retention and hydraulic conductivity functions. The proposed method relies on the BEST approach. The novelty lies in the use of Kosugi hydraulic parameters without need for textural information. Kosugi functions were chosen because they are based on physical principles (log-normal distribution for pore size distributions). A link between the Kosugi parameters (i.e., relationship between <em>σ</em> and <em>h</em><sub>kg</sub>) was introduced to reduce the number of parameters estimated and to avoid the need for information on the soil texture. This simplifies the procedures and avoids sources of errors related to the use of pedotransfer functions as for the previous BEST methods. Lastly, the method uses a quasi-exact formulation that is valid for all times, instead of the approximate expansions previously used, avoiding related inaccuracy and allowing the use of any infiltration data encompassing or not both transient and steady states. The new BEST methods were tested against numerically generated data for several contrasting synthetic soils, and the results show that these methods provide consistent hydraulic functions close to the target functions. The new BEST method is accurate and can use any type of water retention and hydraulic conductivity functions (Fernández-Gálvez et al., 2019).</p><p> </p><p> </p><p><strong>Reference</strong></p><p>Fernández-Gálvez, J., Pollacco, J.A.P., Lassabatere, L., Angulo-Jaramillo, R., Carrick, S., 2019. A general Beerkan Estimation of Soil Transfer parameters method predicting hydraulic parameters of any unimodal water retention and hydraulic conductivity curves: Application to the Kosugi soil hydraulic model without using particle size distribution data. Adv. Water Resour. 129, 118–130. https://doi.org/10.1016/j.advwatres.2019.05.005</p>

Estimating soil hydraulic properties from saturation to complete dryness

2021 ◽  
Author(s):  
Budiman Minasny ◽  
Rudiyanto Rudiyanto ◽  
Federico Maggi
Keyword(s):  
Soil Moisture ◽  
Hydraulic Conductivity ◽  
Soil Water ◽  
Hydraulic Properties ◽  
Water Retention ◽  
Pedotransfer Functions ◽  
Soil Hydraulic Properties ◽  
Soil Moisture Dynamics ◽  
Soil Hydraulic ◽  
Moisture Dynamics

<p>To study the effect of drought on soil water dynamics, we need an accurate description of water retention and hydraulic conductivity from saturation to complete dryness. Recent studies have demonstrated the inaccuracy of conventional soil hydraulic models, especially in the dry end. Likewise, current pedotransfer functions (PTFs) for soil hydraulic properties are based on the classical Mualem-van Genuchten functions.</p><p>This study will evaluate models that estimate soil water retention and unsaturated hydraulic conductivity curves in full soil moisture ranges. An example is the Fredlund-Xing scaling model coupled with the hydraulic conductivity model of Wang et al. We will develop pedotransfer functions that can estimate parameters of the model. We will compare it with existing PTFs in predicting water retention and hydraulic conductivity.</p><p>The results show that a new suite of PTFs that used sand, silt, clay, and bulk density can be used successfully to predict water retention and hydraulic conductivity over a range of moisture content. The prediction of hydraulic properties is used in a soil water flow model to simulate soil moisture dynamics under drought. This study demonstrates the importance of accurate hydraulic model prediction for a better description of soil moisture dynamics.</p><p> </p>

A New Approach to Estimate Soil Hydraulic Parameters Using Only Soil Water Retention Data

2008 ◽  
Vol 72 (2) ◽  
pp. 471-479 ◽  
Author(s):  
Navin K. C. Twarakavi ◽  
Hirotaka Saito ◽  
Jirka Šimunek ◽  
M. Th. van Genuchten
Keyword(s):  
Soil Water ◽  
Water Retention ◽  
Retention Data ◽  
Hydraulic Parameters ◽  
Soil Water Retention ◽  
New Approach ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

scholarly journals Uncertainty in the determination of soil hydraulic parameters and its influence on the performance of two hydrological models of different complexity

2010 ◽  
Vol 14 (2) ◽  
pp. 251-270 ◽  
Author(s):  
G. Baroni ◽  
A. Facchi ◽  
C. Gandolfi ◽  
B. Ortuani ◽  
D. Horeschi ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Hydraulic Conductivity ◽  
Water Content ◽  
Root Zone ◽  
Hydraulic Parameters ◽  
Hydrological Models ◽  
Conductivity Data ◽  
Hydraulic Parameter ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

Abstract. Data of soil hydraulic properties forms often a limiting factor in unsaturated zone modelling, especially at the larger scales. Investigations for the hydraulic characterization of soils are time-consuming and costly, and the accuracy of the results obtained by the different methodologies is still debated. However, we may wonder how the uncertainty in soil hydraulic parameters relates to the uncertainty of the selected modelling approach. We performed an intensive monitoring study during the cropping season of a 10 ha maize field in Northern Italy. The data were used to: i) compare different methods for determining soil hydraulic parameters and ii) evaluate the effect of the uncertainty in these parameters on different variables (i.e. evapotranspiration, average water content in the root zone, flux at the bottom boundary of the root zone) simulated by two hydrological models of different complexity: SWAP, a widely used model of soil moisture dynamics in unsaturated soils based on Richards equation, and ALHyMUS, a conceptual model of the same dynamics based on a reservoir cascade scheme. We employed five direct and indirect methods to determine soil hydraulic parameters for each horizon of the experimental profile. Two methods were based on a parameter optimization of: a) laboratory measured retention and hydraulic conductivity data and b) field measured retention and hydraulic conductivity data. The remaining three methods were based on the application of widely used Pedo-Transfer Functions: c) Rawls and Brakensiek, d) HYPRES, and e) ROSETTA. Simulations were performed using meteorological, irrigation and crop data measured at the experimental site during the period June – October 2006. Results showed a wide range of soil hydraulic parameter values generated with the different methods, especially for the saturated hydraulic conductivity Ksat and the shape parameter α of the van Genuchten curve. This is reflected in a variability of the modeling results which is, as expected, different for each model and each variable analysed. The variability of the simulated water content in the root zone and of the bottom flux for different soil hydraulic parameter sets is found to be often larger than the difference between modeling results of the two models using the same soil hydraulic parameter set. Also we found that a good agreement in simulated soil moisture patterns may occur even if evapotranspiration and percolation fluxes are significantly different. Therefore multiple output variables should be considered to test the performances of methods and models.

scholarly journals Uncertainty in the determination of soil hydraulic parameters and its influence on the performance of two hydrological models of different complexity

2009 ◽  
Vol 6 (3) ◽  
pp. 4065-4105 ◽  
Author(s):  
G. Baroni ◽  
A. Facchi ◽  
C. Gandolfi ◽  
B. Ortuani ◽  
D. Horeschi ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Hydraulic Conductivity ◽  
Water Content ◽  
Root Zone ◽  
Hydraulic Parameters ◽  
Hydrological Models ◽  
Conductivity Data ◽  
Hydraulic Parameter ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

Abstract. Data of soil hydraulic properties forms often a limiting factor in unsaturated zone modelling, especially at the larger scales. Investigations for the hydraulic characterization of soils are time-consuming and costly, and the accuracy of the results obtained by the different methodologies is still debated. However, we may wonder how the uncertainty in soil hydraulic parameters relates to the uncertainty of the selected modelling approach. We performed an intensive monitoring study during the cropping season of a 10 ha maize field in Northern Italy. These data were used to: i) compare different methods for determining soil hydraulic parameters and ii) evaluate the effect of the uncertainty in these parameters on different outputs (i.e. evapotranspiration, water content in the root zone, fluxes through the bottom boundary of the root zone) of two hydrological models with different complexity: SWAP, a widely used model of soil moisture dynamics in unsaturated soils based on Richards equation, and ALHyMUS, a conceptual model of the same dynamics based on a reservoir cascade scheme. We employed five direct and indirect methods to determine soil hydraulic parameters for each horizon of the experimental field. Two methods were based on a parameter optimization of: a) laboratory measured retention and hydraulic conductivity data and b) field measured retention and hydraulic conductivity data. Three methods were based on the application of widely used Pedo-Transfer Functions: c) Rawls and Brakensiek; d) HYPRES; and e) ROSETTA. Simulations were performed using meteorological, irrigation and crop data measured at the experimental site during the period June–October 2006. Results showed a wide range of soil hydraulic parameter values evaluated with the different methods, especially for the saturated hydraulic conductivity Ksat and the shape parameter α of the Van Genuchten curve. This is reflected in a variability of the modeling results which is, as expected, different for each model. The variability of the simulated water content in the root zone and of the fluxes at the root zone bottom for different soil hydraulic parameter sets is found to be often larger than the difference between modeling results of the two models using the same soil hydraulic parameter set. Also we found that a good agreement in simulated soil moisture patterns may occur even if evapotranspiration and percolation fluxes are significantly different. Therefore multiple output variables should be considered to test the performances of methods and models.

Assessment of Empirical and Semi-Empirical Models for Estimating a Soil Infiltration Function

2020 ◽  
Vol 63 (4) ◽  
pp. 833-845
Author(s):  
Mohamed Khaled Salahou ◽  
Xiyun Jiao ◽  
Haishen Lü
Keyword(s):  
Pedotransfer Functions ◽  
Observation Data ◽  
Hydraulic Parameters ◽  
Soil Infiltration ◽  
Infiltration Model ◽  
Infiltration Models ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic ◽  
Semi Empirical ◽  
Kostiakov Model

HighlightsThe hydraulic performance computed with the KE or GA model is nearly the same, as long the models are calibrated using the same observation data.The GA model with the soil hydraulic parameters obtained from the pedotransfer functions adequately represented the soil infiltration function.The particle size distribution or the soil texture are recommended to estimate soil hydraulic parameters with the VG-ROSETTA model. Abstract. Field-scale estimation of a soil infiltration function is important for the design, simulation, and/or evaluation of surface irrigation systems. Semi-empirical and empirical infiltration models are used to estimate the infiltration function. Semi-empirical infiltration models have substantial computational and parameterization complexities, e.g., soil hydraulic parameters are needed to estimate the infiltration function. In contrast, empirical infiltration models are generally not considered to have specific initial and boundary conditions. The objectives of this study were to compare a semi-empirical infiltration model and an empirical infiltration model. The Green-Ampt model (GA) and the Kostiakov model (KE) were used as semi-empirical and empirical infiltration models, respectively. The soil hydraulic parameters for the GA model were estimated using various pedotransfer functions (PTFs), and in an additional assessment, the measured water content data were used to calibrate and validate the soil hydraulic parameters using the HYDRUS-1D model. The results show that the hydraulic performance computed with the KE or GA model is nearly the same, as long as they are calibrated using the same observation data. Additionally, the results indicate that the GA model with the soil hydraulic parameters obtained from the PTFs adequately represented the soil infiltration function in the borders. Keywords: Empirical infiltration model, Green-Ampt model, Infiltration model, Kostiakov model, Semi-empirical infiltration model, Soil hydraulic properties.

Development of a China Dataset of Soil Hydraulic Parameters Using Pedotransfer Functions for Land Surface Modeling

2013 ◽  
Vol 14 (3) ◽  
pp. 869-887 ◽  
Author(s):  
Yongjiu Dai ◽  
Wei Shangguan ◽  
Qingyun Duan ◽  
Baoyuan Liu ◽  
Suhua Fu ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Land Surface ◽  
Soil Characteristics ◽  
Surface Modeling ◽  
Pedotransfer Functions ◽  
Water Retention Curve ◽  
Hydraulic Parameters ◽  
Land Surface Modeling ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

Abstract The objective of this study is to develop a dataset of the soil hydraulic parameters associated with two empirical soil functions (i.e., a water retention curve and hydraulic conductivity) using multiple pedotransfer functions (PTFs). The dataset is designed specifically for regional land surface modeling for China. The authors selected 5 PTFs to derive the parameters in the Clapp and Hornberger functions and the van Genuchten and Mualem functions and 10 PTFs for soil water contents at capillary pressures of 33 and 1500 kPa. The inputs into the PTFs include soil particle size distribution, bulk density, and soil organic matter. The dataset provides 12 estimated parameters and their associated statistical values. The dataset is available at a 30 × 30 arc second geographical spatial resolution and with seven vertical layers to the depth of 1.38 m. The dataset has several distinct advantages even though the accuracy is unknown for lack of in situ and regional measurements. First, this dataset utilizes the best available soil characteristics dataset for China. The Chinese soil characteristics dataset was derived by using the 1:1 000 000 Soil Map of China and 8595 representative soil profiles. Second, this dataset represents the first attempt to estimate soil hydraulic parameters using PTFs directly for continental China at a high spatial resolution. Therefore, this dataset should capture spatial heterogeneity better than existing estimates based on lookup tables according to soil texture classes. Third, the authors derived soil hydraulic parameters using multiple PTFs to allow flexibility for data users to use the soil hydraulic parameters most preferable to or suitable for their applications.

Effective Hydraulic Parameters in Horizontally and Vertically Heterogeneous Soils for Steady-State Land–Atmosphere Interaction

2007 ◽  
Vol 8 (4) ◽  
pp. 715-729 ◽  
Author(s):  
Binayak P. Mohanty ◽  
Jianting Zhu
Keyword(s):  
Fractal Dimension ◽  
Steady State ◽  
Hydraulic Conductivity ◽  
Surface Boundary ◽  
Hydraulic Parameters ◽  
Effective Parameters ◽  
Hydraulic Parameter ◽  
Soil Hydraulic Parameters ◽  
Atmosphere Interaction ◽  
Soil Hydraulic

Abstract In this study, the authors investigate effective soil hydraulic parameter averaging schemes for steady-state flow in heterogeneous shallow subsurfaces useful to land–atmosphere interaction modeling. “Effective” soil hydraulic parameters of the heterogeneous shallow subsurface are obtained by conceptualizing the soil as an equivalent homogeneous medium. It requires that the effective homogeneous soil discharges the same mean surface moisture flux (evaporation or infiltration) as the heterogeneous media. Using the simple Gardner unsaturated hydraulic conductivity function, the authors derive the effective value for the saturated hydraulic conductivity Ks or the shape factor α under various hydrologic scenarios and input hydraulic parameter statistics. Assuming one-dimensional vertical moisture movement in the shallow unsaturated soils, both scenarios of horizontal (across the surface landscape) and vertical (across the soil profile) heterogeneities are investigated. The effects of hydraulic parameter statistics, surface boundary conditions, domain scales, and fractal dimensions in case of nested soil hydraulic property structure are addressed. Results show that the effective parameters are dictated more by the α heterogeneity for the evaporation scenario and mainly by Ks variability for the infiltration scenario. Also, heterogeneity orientation (horizontal or vertical) of soil hydraulic parameters impacts the effective parameters. In general, an increase in both the fractal dimension and the domain scale enhances the heterogeneous effects of the parameter fields on the effective parameters. The impact of the domain scale on the effective hydraulic parameters is more significant as the fractal dimension increases.

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