scholarly journals Spatial variability of the parameters of soil-water characteristic curves in gravel-mulched fields

2019 ◽  
Vol 20 (1) ◽  
pp. 231-239
Author(s):  
Wenju Zhao ◽  
Taohong Cao ◽  
Zongli Li ◽  
Yu Su ◽  
Zhiwei Bao
Keyword(s):  
Spatial Variability ◽  
Soil Water ◽  
Water Retention ◽  
Characteristic Curve ◽  
Model Parameters ◽  
Soil Hydraulic Properties ◽  
Geostatistical Methods ◽  
Classical Statistics ◽  
Van Genuchten Model ◽  
Soil Water Characteristic Curves

Abstract Knowledge of the soil-water characteristic curve (SWCC) and its spatial variability is essential for many agricultural, environmental, and engineering applications. We analyzed the spatial variability of the parameters of SWCC in gravel-mulched fields using classical statistics and geostatistical methods. Soil samples were collected from the layer in 64 evenly distributed 1 × 1 m quadrats 4 m apart, center to center. SWCC in the gravel-mulched fields could be fitted well by both the van Genuchten and Brooks–Corey models, but the fit was better with the van Genuchten model. The type of fitting three parameters was tested. The model parameters θs and n of each type of soil were weakly variable, and α was moderately variable. The results indicate that the gravel-mulched field has better water retention, and the water retention effect of the new gravel-mulched fields is most obvious. The spatial variation of the parameters in SWCC can therefore be used to infer soil hydraulic properties, which is important for simplifying the calculation of SWCC and quantitatively determining the retention of soil water and for managing the capacity of soil to retain water in gravel-mulched fields in arid regions.

The Development of a One-Parameter Model for the Soil-Water Characteristic Curve in Loess Gully Regions

2012 ◽  
Vol 256-259 ◽  
pp. 488-493
Author(s):  
Xiao Yu Song ◽  
Huai You Li ◽  
Wen Juan Shi
Keyword(s):  
Soil Water ◽  
Hydraulic Properties ◽  
Characteristic Curve ◽  
Soil Samples ◽  
Soil Hydraulic Properties ◽  
Logarithmic Model ◽  
Soil Water Characteristic Curve ◽  
Soil Water Characteristic Curves ◽  
Best Fit ◽  
Gardner Model

It is important to understand soil hydraulic properties in order to predict the movement of water and solutes such as pollutants. To this end, 55 soil samples were collected from different areas of the Nanxiaohegou basin and used to generate soil-water characteristic curves. These were then fitted using the power-, exponential-, and logarithmic versions of the Gardner model; the logarithmic model yielded the best fit overall. The logarithmic model was further simplified to yield a one-parameter model for estimating the soil-water characteristic curve within the basin, and it was demonstrated that the value of the single parameter is dependent on the topography and usage of the land.

Multifractal analysis of soil hydraulic properties in arid areas

Soil Research ◽  
2016 ◽  
Vol 54 (8) ◽  
pp. 914 ◽  
Author(s):  
N. Pahlevan ◽  
M. R. Yazdani ◽  
A. A. Zolfaghari ◽  
M. Ghodrati
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Soil Water ◽  
Multifractal Analysis ◽  
Hydraulic Properties ◽  
Water Retention ◽  
Scaling Analysis ◽  
Soil Hydraulic Properties ◽  
Soil Water Retention ◽  
Soil Hydraulic

Physical and hydraulic properties of soil are variable at different spatial scales. This indicates the necessity of understanding spatial patterns of soil properties. Scaling analysis, such as multifractal analysis, has been used to determine the spatial variability of soil properties. There are however limited numbers of studies concerning the applications of multifractal techniques applied to characterise spatial variability of soil properties in arid lands. The objective of this study was to quantify the scaling patterns of soil properties measured across a transect and to apply multifractal analysis in arid land areas. A transect with a length of 4.80km was selected, and soil properties were measured at 0–20cm depth every 145m along the transect. The soil properties analysed were: texture (sand, silt, clay), pH, electrical conductivity (EC), bulk density (BD), soil hydraulic properties (saturated hydraulic conductivity Ks and the van Genuchten soil water-retention equation’s parameters nv and αv), saturated water content (θs), and the slope of the soil water-retention curve at its inflection point (S). Results showed that the variability of pH and BD was characterised by quasi-monofractal behaviour. Results showed that soil hydraulic properties such as Ks, αn, nv, S, and θs were characterised by higher multifractal indices in the transects. EC showed the highest tendency to a multifractal type of scaling or the higher degree of multifractality.

scholarly journals A new framework to determine general multimodal soil water characteristic curves

2021 ◽  
Author(s):  
Wei Yan ◽  
Emanuel Birle ◽  
Roberto Cudmani
Keyword(s):  
Soil Water ◽  
Characteristic Curve ◽  
Calibration Method ◽  
Soil Suction ◽  
Proposed Model ◽  
Van Genuchten Model ◽  
Soil Water Characteristic Curves ◽  
The Relationship ◽  
New Framework ◽  
Different Soils

AbstractA soil water characteristic curve (SWCC) model named as discrete-continuous multimodal van Genuchten model with a convenient parameter calibration method is developed to describe the relationship between soil suction and the water content of a soil with complex pore structure. The modality number N of the SWCC in the proposed model can be any positive integer (the so-called multimodal or N-modal SWCC). A unique set of parameters is determined by combining curve fitting and a graphical method based on the shape features of the SWCC in the log s–log Se plane. In addition, a modality number reduction method is proposed to minimize the number of parameters and simplify the form of SWCC function. The proposed model is validated using a set of bimodal and trimodal SWCC measurements from different soils, which yield a strong consistency between the fitted curves and the measured SWCC data. The uniqueness in the set of parameters provides the possibility to further improve the proposed model by correlating the parameters to soil properties and state parameters.

scholarly journals Temporal stability of electrical conductivity in a sandy soil

2016 ◽  
Vol 30 (3) ◽  
pp. 349-357 ◽  
Author(s):  
Aura Pedrera-Parrilla ◽  
Eric C. Brevik ◽  
Juan V. Giráldez ◽  
Karl Vanderlinden
Keyword(s):  
Electrical Conductivity ◽  
Spatial Variability ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Precision Agriculture ◽  
Temporal Stability ◽  
Principal Component ◽  
Model Parameters ◽  
Soil Spatial Variability

Abstract Understanding of soil spatial variability is needed to delimit areas for precision agriculture. Electromagnetic induction sensors which measure the soil apparent electrical conductivity reflect soil spatial variability. The objectives of this work were to see if a temporally stable component could be found in electrical conductivity, and to see if temporal stability information acquired from several electrical conductivity surveys could be used to better interpret the results of concurrent surveys of electrical conductivity and soil water content. The experimental work was performed in a commercial rainfed olive grove of 6.7 ha in the ‘La Manga’ catchment in SW Spain. Several soil surveys provided gravimetric soil water content and electrical conductivity data. Soil electrical conductivity values were used to spatially delimit three areas in the grove, based on the first principal component, which represented the time-stable dominant spatial electrical conductivity pattern and explained 86% of the total electrical conductivity variance. Significant differences in clay, stone and soil water contents were detected between the three areas. Relationships between electrical conductivity and soil water content were modelled with an exponential model. Parameters from the model showed a strong effect of the first principal component on the relationship between soil water content and electrical conductivity. Overall temporal stability of electrical conductivity reflects soil properties and manifests itself in spatial patterns of soil water content.

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.

Method for Quick Prediction of Hydraulic Conductivity and Soil-Water Retention of Unsaturated Soils

2018 ◽  
Vol 2672 (52) ◽  
pp. 108-117 ◽  
Author(s):  
Shaoyang Dong ◽  
Yuan Guo ◽  
Xiong (Bill) Yu
Keyword(s):  
Finite Element ◽  
Hydraulic Conductivity ◽  
Soil Properties ◽  
Soil Water ◽  
Unsaturated Soil ◽  
Unsaturated Soils ◽  
Hydraulic Properties ◽  
Water Retention ◽  
Characteristic Curve ◽  
Soil Water Retention

Hydraulic conductivity and soil-water retention are two critical soil properties describing the fluid flow in unsaturated soils. Existing experimental procedures tend to be time consuming and labor intensive. This paper describes a heuristic approach that combines a limited number of experimental measurements with a computational model with random finite element to significantly accelerate the process. A microstructure-based model is established to describe unsaturated soils with distribution of phases based on their respective volumetric contents. The model is converted into a finite element model, in which the intrinsic hydraulic properties of each phase (soil particle, water, and air) are applied based on the microscopic structures. The bulk hydraulic properties are then determined based on discharge rate using Darcy’s law. The intrinsic permeability of each phase of soil is first calibrated from soil measured under dry and saturated conditions, which is then used to predict the hydraulic conductivities at different extents of saturation. The results match the experimental data closely. Mualem’s equation is applied to fit the pore size parameter based on the hydraulic conductivity. From these, the soil-water characteristic curve is predicted from van Genuchten’s equation. The simulation results are compared with the experimental results from documented studies, and excellent agreements were observed. Overall, this study provides a new modeling-based approach to predict the hydraulic conductivity function and soil-water characteristic curve of unsaturated soils based on measurement at complete dry or completely saturated conditions. An efficient way to measure these critical unsaturated soil properties will be of benefit in introducing unsaturated soil mechanics into engineering practice.

Bayesian Estimation of Soil-Water Characteristic Curves

2021 ◽  
Author(s):  
Jie Zhang ◽  
Shuai Yang ◽  
Lulu Zhang ◽  
Mingliang Zhou
Keyword(s):  
Soil Water ◽  
Bayesian Model ◽  
Characteristic Curve ◽  
Measurement Data ◽  
Bayes Theorem ◽  
Empirical Method ◽  
Measured Data ◽  
Suggested Method ◽  
Empirical Methods ◽  
Soil Water Characteristic Curves

The soil-water characteristic curve (SWCC) is a significant prerequisite for studying the mechanical properties of unsaturated soil. As experimental measurement of the SWCC is time-consuming, empirical methods have been suggested to estimate the SWCC. However, the uncertainty associated with SWCC can be substantial. In this paper, a hybrid method based on Bayes’ theorem is suggested to estimate the SWCC, where an empirical method can be used to provide prior knowledge about the SWCC, and a limited quantity of measured data is used to update the SWCC. The Bayesian model is then solved with a Markov Chain Monte Carlo simulation. Through the suggested method, the valuable information provided by the empirical method can be combined with the measurement data. The suggested method can not only provide the best estimate about the SWCC, but also account for the associated uncertainty. Also, the effect of more measured points on the estimation of SWCC can be quantified. The suggested method provides a practical means to estimate the SWCC using a limited amount of data.

The Trial Research of Soil-Water Characteristic Curves of Unsaturated Soil and its Engineering Application

2012 ◽  
Vol 170-173 ◽  
pp. 3050-3053
Author(s):  
Cui Ran Liu ◽  
Jin Jun Guo
Keyword(s):  
Soil Water ◽  
Unsaturated Soil ◽  
Permeability Coefficient ◽  
Characteristic Curve ◽  
Engineering Application ◽  
Engineering Properties ◽  
Confining Pressures ◽  
Soil Water Characteristic Curves ◽  
Matrix Suction ◽  
Water Contents

With the improved triaxial equipment, the tests of research of the relationships between matrix suction and water content are performed And based on the test data, the curves between matrix suction and water contents under different confining pressures are drawn and the change rule between them are analyzed. And then the function between them is simulated out. Through the soil-water characteristic curve, the permeability coefficient of unsaturated soil can be calculated and the shear strength of unsaturated soil can be predicted. These results are important to research the engineering properties of unsaturated soil.

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