scholarly journals Studying Unimodal, Bimodal, PDI and Bimodal-PDI Variants of Multiple Soil Water Retention Models: II. Evaluation of Parametric Pedotransfer Functions Against Direct Fits

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 896 ◽  
Author(s):  
Amir Haghverdi ◽  
Hasan Sabri Öztürk ◽  
Wolfgang Durner
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Water Retention ◽  
Organic Matter Content ◽  
Pedotransfer Functions ◽  
Model Parameters ◽  
Retention Data ◽  
Soil Water Retention ◽  
Data Set ◽  
Free Parameters

A high-resolution soil water retention data set (81 repacked soil samples with 7729 observations) measured by the HYPROP system was used to develop and evaluate the performance of regression parametric pedotransfer functions (PTFs). A total of sixteen soil hydraulic models were evaluated including five unimodal water retention expressions of Brooks and Corey (BC model), Fredlund and Xing (FX model), Kosugi (K model), van Genuchten with four free parameters (VG model) and van Genuchten with five free parameters (VGm model). In addition, eleven bimodal, Peters–Durner–Iden (PDI) and bimodal-PDI variants of the original expressions were studied. Six modeling scenarios (S1 to S6) were examined with different combinations of the following input predictors: soil texture (percentages of sand, silt and clay), soil bulk density, organic matter content, percent of stable aggregates and saturated water content (θs). Although a majority of the model parameters showed low correlations with basic soil properties, most of the parametric PTFs provided reasonable water content estimations. The VGm parametric PTF with an RMSE of 0.034 cm3 cm−3 was the best PTF when all input predictors were considered. When averaged across modeling scenarios, the PDI variant of the K model with an RMSE of 0.045 cm3 cm−3 showed the highest performance. The best performance of all models occurred at S6 when θs was considered as an additional input predictor. The second-best performance for 11 out of the 16 models belonged to S1 with soil textural components as the only inputs. Our results do not recommend the development of parametric PTFs using bimodal variants because of their poor performance, which is attributed to their high number of free parameters.

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

2009 ◽  
Vol 6 (3) ◽  
pp. 4265-4306 ◽  
Author(s):  
K. Verbist ◽  
W. M. Cornelis ◽  
D. Gabriels ◽  
K. Alaerts ◽  
G. Soto
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Water Retention ◽  
Measurement Techniques ◽  
Inverse Modelling ◽  
Model Parameters ◽  
Arid Zones ◽  
Water Harvesting ◽  
Data Set

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 (Ksat) independently. Tension infiltrometer measurements proved a good estimator of the Ksat 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 observed soil water content and simulated values was as high as R2=0.93 for ten selected observation points used in the model calibration phase, with overall correlation for the 22 observation points equal to 0.85. Model results indicate that the infiltration trench has a significant effect on soil water storage, especially at the base of the trench.

scholarly journals Investigation into water retention behaviour of deformable soils

2013 ◽  
Vol 50 (2) ◽  
pp. 200-208 ◽  
Author(s):  
Simon Salager ◽  
Mathieu Nuth ◽  
Alessio Ferrari ◽  
Lyesse Laloui
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Water Retention ◽  
Void Ratio ◽  
Degree Of Saturation ◽  
Retention Data ◽  
Soil Water Retention ◽  
Retention Behaviour ◽  
Wide Range ◽  
Water Retention Behaviour

The paper presents an experimental and modelling approach for the soil-water retention behaviour of two deformable soils. The objective is to investigate the physical mechanisms that govern the soil-water retention properties and to propose a constitutive framework for the soil-water retention curve accounting for the initial state of compaction and deformability of soils. A granular soil and a clayey soil were subjected to drying over a wide range of suctions so that the residual state of saturation could be attained. Different initial densities were tested for each material. The soil-water retention curves (SWRCs) obtained are synthesized and compared in terms of water content, void ratio, and degree of saturation, and are expressed as a function of the total suction. The studies enable assessment of the effect of the past and present soil deformation on the shape of the curves. The void ratio exerts a clear influence on the air-entry value, revealing that the breakthrough of air into the pores of the soil is more arduous in denser states. In the plane of water content versus suction, the experimental results highlight the fact that from a certain value of suction, the retention curves corresponding to different densities of the same soil are convergent. The observed features of behaviour are conceptualized into a modelling framework expressing the evolution of the degree of saturation as a function of suction. The proposed retention model makes use of the theory of elastoplasticity and can thus be generalized into a hysteretic model applicable to drying–wetting cycles. The calibration of the model requires the experimental retention data for two initial void ratios. The prediction of tests for further ranges of void ratios proves to be accurate, which supports the adequacy of formulated concepts.

scholarly journals Modelling of soil-water retention curve considering the effects of existing salt solution in the pore fluid

2021 ◽  
Vol 337 ◽  
pp. 02001
Author(s):  
Hamed Sadeghi ◽  
Ali Golaghaei Darzi
Keyword(s):  
Soil Water ◽  
Osmotic Potential ◽  
Water Retention ◽  
Pore Fluid ◽  
Water Retention Curve ◽  
Model Parameters ◽  
Retention Data ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Retention Curve

Soil-water retention curve (SWRC) has a wide application in geoenvironmental engineering from the predication of unsaturated shear strength to transient two-phase flow and stability analyses. Although various SWRC models have been proposed to take into account some influencing factors, less attention has been given to consider the effects of pore fluid osmotic potential. Therefore, the key objective of this study is to extend van Genchten’s model so that osmotic potential is considered as an independent factor governing the SWRC behavior. The new model comprises only six variables, which can be calibrated through minimal experimental measurements. More importantly, most of the model parameters have physical meaning by correlating macroscopic volumetric behavior and general trends of SWRC to osmotic potential. The results of validation tests revealed that the new osmotic-dependent SWRC model can predict the retention data in terms of both total and matric suction for two different soils and various molar concentrations very good. The proposed modeling approach does not require any advanced mercury intrusion porosimetry (MIP) tests, yet it can deliver excellent predictions by calibrating only six parameters which are far less than those incorporated into similar models for saline water permeating through the pore structure.

Global mapping of volumetric water content at 10, 33 and 1500 kPa using the WoSIS global database

2021 ◽  
Author(s):  
Maria Eliza Turek ◽  
Gerard Heuvelink ◽  
Niels Batjes ◽  
Laura Poggio
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Water Retention ◽  
Spatial Prediction ◽  
Volumetric Water Content ◽  
Data Availability ◽  
Pedotransfer Functions ◽  
Soil Water Retention ◽  
Direct Mapping

<p>Soil water content is a key property for modelling the water balance in hydrological, eco-hydrological and agro-hydrological models. Currently available global maps of soil water retention are mostly based on pedotransfer functions applied to maps of other basic soil properties. We developed global maps of the volumetric water content at 10, 33 and 1500 kPa by direct mapping based on soil water content data derived from the WoSIS Soil Profile Database and covariates describing vegetation, terrain morphology, climate, geology and hydrology using the SoilGrids workflow. The preparation of the input soil data consisted of the verification of available volumetric water content data and conversion of gravimetric to volumetric data using measured and estimated bulk density. In total we had 9609, 41082 and 49224 soil water content observations at 10, 33 and 1500 kPa, respectively, and prepared around 200 covariates as candidate predictors. After covariates selection, model tuning and cross-validation and final model fitting for 3D spatial prediction, results were presented for the globe with uncertainty estimation. The results were also compared to other available global maps of water retention to evaluate differences between direct mapping against other types of approaches. Directly developing global maps of soil water content, with associated uncertainty, is a novel approach for this type of properties, and contributes to improving global soil data availability and quality.</p>

scholarly journals Studying Unimodal, Bimodal, PDI and Bimodal-PDI Variants of Multiple Soil Water Retention Models: I. Direct Model Fit Using the Extended Evaporation and Dewpoint Methods

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 900 ◽  
Author(s):  
Amir Haghverdi ◽  
Mohsen Najarchi ◽  
Hasan Sabri Öztürk ◽  
Wolfgang Durner
Keyword(s):  
High Resolution ◽  
Soil Water ◽  
Water Retention ◽  
The United States ◽  
Retention Data ◽  
Soil Water Retention ◽  
Retention Models ◽  
Direct Model ◽  
Free Parameters ◽  
Measured Water

This study focuses on the reliable parametrization of the full Soil Water Retention Curve (SWRC) from saturation to oven-dryness using high resolution but limited range measured water retention data by the Hydraulic Property Analyzer (HYPROP) system. We studied the performance of five unimodal water retention models including the Brooks and Corey model (BC model), the Fredlund and Xing model (FX model), the Kosugi model (K model), the van Genuchten constrained model with four free parameters (VG model), and the van Genuchten unconstrained model with five free parameters (VGm model). In addition, eleven alternative expressions including Peters–Durner–Iden (PDI), bimodal, and bimodal-PDI variants of the original models were evaluated. We used a data set consisting of 94 soil samples from Turkey and the United States with high-resolution measured data (a total of 9264 measured water retention data pairs) mainly via the HYPROP system and supplemented for some samples with measured dry-end data using the WP4C instrument. Among unimodal expressions, the FX and the K models with the Mean Absolute Error (MAE) values equal to 0.005 cm3 cm−3 and 0.015 cm3 cm−3 have the highest and the lowest accuracy, respectively. Overall, the alternative variants provided a better fit than the unimodal expressions. The unimodal models, except for the FX model, fail to provide reliable dry-end estimations using HYPROP data (average MAE: 0.041 cm3 cm−3, average r: 0.52). Our results suggested that only models that account for the zero water content at the oven dryness and properly shift from the middle range to dry-end (i.e., the FX model and PDI variants) can adequately represent the full SWRC using typical data obtained via the HYPROP system.

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

2009 ◽  
Vol 13 (10) ◽  
pp. 1979-1992 ◽  
Author(s):  
K. Verbist ◽  
W. M. Cornelis ◽  
D. Gabriels ◽  
K. Alaerts ◽  
G. Soto
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Water Retention ◽  
Measurement Techniques ◽  
Inverse Modelling ◽  
Model Parameters ◽  
Arid Zones ◽  
Water Harvesting ◽  
Data Set

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 (Ksat) independently. The tension infiltrometer measurements proved a good estimator of the Ksat 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 R2=0.93 for ten selected observation points used in the model calibration phase, with overall correlation for 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.

scholarly journals Developing Pseudo Continuous Pedotransfer Functions for International Soils Measured with the Evaporation Method and the HYPROP System: I. The Soil Water Retention Curve

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3425
Author(s):  
Amninder Singh ◽  
Amir Haghverdi ◽  
Hasan Sabri Öztürk ◽  
Wolfgang Durner
Keyword(s):  
Soil Water ◽  
Water Retention ◽  
Soil Samples ◽  
Pedotransfer Functions ◽  
Water Retention Curve ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Data Set ◽  
Retention Curve ◽  
Evaporation Method

Direct measurements of soil hydraulic properties are time-consuming, challenging, and often expensive. Therefore, their indirect estimation via pedotransfer functions (PTFs) based on easily collected properties like soil texture, bulk density, and organic matter content is desirable. This study was carried out to assess the accuracy of the pseudo continuous neural network PTF (PCNN-PTF) approach for estimating the soil water retention curve of 153 international soils (a total of 12,654 measured water retention pairs) measured via the evaporation method. In addition, an independent data set from Turkey (79 soil samples with 7729 measured data pairs) was used to evaluate the reliability of the PCNN-PTF. The best PCNN-PTF showed high accuracy (root mean square error (RMSE) = 0.043 cm3 cm−3) and reliability (RMSE = 0.061 cm3 cm−3). When Turkish soil samples were incorporated into the training data set, the performance of the PCNN-PTF was enhanced by 33%. Therefore, to further improve the performance of the PCNN-PTF for new regions, we recommend the incorporation of local soils, when available, into the international data sets and developing new sets of PCNN-PTFs.

A NOTE ON THE PHYSICS OF SOIL WATER RETENTION THROUGH FRACTAL PARAMETERS

Fractals ◽  
2006 ◽  
Vol 14 (02) ◽  
pp. 143-148 ◽  
Author(s):  
H. MILLÁN ◽  
M. AGUILAR ◽  
J. DOMÌNGUEZ ◽  
L. CÈSPEDES ◽  
E. VELASCO ◽  
...  
Keyword(s):  
Soil Water ◽  
Water Retention ◽  
Goodness Of Fit ◽  
Fractal Model ◽  
Data Sets ◽  
Retention Data ◽  
Soil Water Retention ◽  
Data Set ◽  
Mass Fractal ◽  
Fractal Parameters

Fractals are important for studying the physics of water transport in soils. Many authors have assumed a mass fractal structure while others consider a fractal surface approach. Each model needs comparisons on the same data set in terms of goodness-of-fit and physical interpretation of parameters. In this note, it is shown, with some representative data sets, that a pore-solid interface fractal model could fit soil water retention data better than a mass fractal model. In addition to the interfacial fractal dimension, this model predicts the tension at dryness. This value is very close to 106 kPa as theoretically predicted.

scholarly journals Effects of various input levels and different soil water retention curve models on water content estimation using different statistical methods

2015 ◽  
Vol 47 (2) ◽  
pp. 312-332 ◽  
Author(s):  
Hossein Bayat ◽  
Eisa Ebrahimi
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Water Retention ◽  
Water Retention Curve ◽  
Model Parameters ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Retention Curve ◽  
Input Variables ◽  
Gardner Model

This study investigated the impact of different input variables on the predictability of the water content using soil water retention curve (SWRC) models. The particle and aggregate size distribution model parameters were calculated by fitting the Perrier model to the related distributions for 75 soil samples. Nine SWRC models were fitted to the experimental data and their coefficients were obtained. The regression method was used to estimate the coefficients for nine SWRC models at three input levels. Cluster analysis classified the SWRC models into more homogeneous groups according to the accuracy of their predictions. The SWRC estimated using the Gardner model had the highest accuracy, but it was not an appropriate model for the soils because of its low fitting accuracy. Boltzman, Campbell, and Fermi models obtained the highest accuracy after the Gardner model. The Durner model yielded the lowest prediction accuracy due to the lack of correlation between the input variables and coefficients in this model. Thus, the water content predictions obtained using different SWRC models varied because different input variables were employed.

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