scholarly journals Capability of Diffuse Reflectance Spectroscopy to Predict Soil Water Retention and Related Soil Properties in an Irrigated Lowland District of Southern Italy

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1712
Author(s):  
Antonio Leone ◽  
Guido Leone ◽  
Natalia Leone ◽  
Ciro Galeone ◽  
Eleonora Grilli ◽  
...  
Keyword(s):  
Soil Properties ◽  
Soil Water ◽  
Water Retention ◽  
Southern Italy ◽  
Multivariate Calibration ◽  
Diffuse Reflectance Spectroscopy ◽  
Soil Analysis ◽  
Reflectance Spectroscopy ◽  
Reflectance Spectra ◽  
Soil Water Retention

In this study, we examined the potential of vis-NIR reflectance spectroscopy, coupled with partial least squares regression (PLSR) analysis, for the evaluation and prediction of soil water retention at field capacity (FC) and permanent wilting point (PWP) and related basic soil properties [organic carbon (OC), sand, silt, and clay contents] in an agricultural irrigated land of southern Italy. Soil properties were determined in the laboratory with reference to the Italian Official Methods for Soil Analysis. Vis-NIR reflectance spectra were measured in the laboratory, using a high-resolution spectroradiometer. All soil variables, with the exception of silt, evidently affected some specific spectral features. Multivariate calibrations were performed to predict the soil properties from reflectance spectra. PLSR was used to calibrate the spectral data using two-thirds of samples for calibration and one-third for validation. Spectroscopic data were pre-processed [multiplicative scatter correction (MSC), standard normal variance (SNV), wavelet detrending (WD), first and second derivative transformation, and filtering] prior to multivariate calibration. The results revealed very good models (2.0 < RPD < 2.5) for the prediction of FC, PWP and sand, and excellent (RPD > 2.5) models for the prediction of clay and OC, whereas a poor (RPD < 1.4) prediction model was obtained for silt.

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.

Uncertainty analysis for large-scale prediction of the van Genuchten soil-water retention parameters with pedotransfer functions

Soil Research ◽  
2014 ◽  
Vol 52 (5) ◽  
pp. 431 ◽  
Author(s):  
K. Liao ◽  
S. Xu ◽  
J. Wu ◽  
Q. Zhu
Keyword(s):  
Soil Properties ◽  
Soil Water ◽  
Water Retention ◽  
Pedotransfer Functions ◽  
Soil Water Retention ◽  
Input Uncertainty ◽  
Spatial Estimation ◽  
Uncertainty Measurement ◽  
Error Bars ◽  
Retention Parameters

Hydrological, environmental and ecological modellers require van Genuchten soil-water retention parameters that are difficult to measure. Pedotransfer functions (PTFs) are thus routinely applied to predict hydraulic parameters (θs, ln(α) and n) from basic soil properties (e.g. bulk density, soil texture and organic matter content). This study investigated the spatial variations of van Genuchten parameters via geostatistical methods (e.g. kriging and co-kriging with remote-sensing data) and multiple-stepwise-regression-based PTFs with a limited number of samples (58) collected in Pingdu City, Shandong Province, China. The uncertainties in the spatial estimation of van Genuchten parameters were evaluated using bootstrap and Latin hypercube sampling methods. Results show that PTF-estimated parameters are less varied than observed parameters. The uncertainty in the parameter estimation is mainly due to the limited number of samples used for deriving PTFs (intrinsic uncertainty) and spatial interpolations of basic soil properties by (co)kriging (input uncertainty). When considering the intrinsic uncertainty, 36%, 29% and 47% of measurements are within the corresponding error bars (95% confidence intervals of the predictions) for the θs, ln(α) and n, respectively. When considering both intrinsic and input uncertainties, 86%, 66% and 88% of observations are within the corresponding error bars for the θs, ln(α) and n, respectively. Therefore, the input uncertainty is more important in the spatial estimation of van Genuchten parameters than the intrinsic uncertainty. Measurement of basic soil properties at high resolution and properly use of powerful spatial interpolation approach are both critical in the accurate spatial estimation of van Genuchten parameters.

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 Verification on PTF (Pedo-Transfer Function) estimating soil water retention based on soil properties

2014 ◽  
Vol 41 (4) ◽  
pp. 391-398
Author(s):  
Seung-Oh Hur ◽  
Yeon-Gyu Sonn ◽  
Byung-Kewn Hyun ◽  
Kook-Sik Shin ◽  
Taek-Keun Oh ◽  
...  
Keyword(s):  
Transfer Function ◽  
Soil Properties ◽  
Soil Water ◽  
Water Retention ◽  
Soil Water Retention

Estimation of the water retention curve for unsaturated clay

2011 ◽  
Vol 91 (4) ◽  
pp. 543-549 ◽  
Author(s):  
Seid Majdeddin Mir Mohammad Hosseini ◽  
Navid Ganjian ◽  
Yadolah Pashang Pisheh
Keyword(s):  
Soil Properties ◽  
Soil Water ◽  
Unsaturated Soil ◽  
Laboratory Tests ◽  
Water Retention ◽  
Water Retention Curve ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Retention Curve ◽  
Unsaturated Clay

Mir Mohammad Hosseini, S. M., Ganjian, N. and Pashang Pisheh, Y. 2011. Estimation of the water retention curve for unsaturated clay. Can. J. Soil Sci. 91: 543–549. Extensive laboratory tests are essential in order to determine the soil water retention curve, defined as the relationship between water content and suction, in an unsaturated soil. These laboratory tests are usually costly and time consuming. Moreover, for most practical problems, it has been found that approximate unsaturated soil properties are adequate for analysis. Thus, empirical procedures for predicting unsaturated soil parameters would be invaluable. The water retention curve can be estimated using soil properties to avoid the costs of experimental methods. Estimation of the water retention curve based on index properties is highly desirable due to its simplicity and low cost. Here, a model for the estimation of the soil water retention curve for fine soils is introduced, which takes the plasticity index and fine content into account, and is based on the Van Genuchten and Fredlund-Xing equations. The proposed equations are validated by comparing measured and simulated results. The curves predicted with these models were found to be in good agreement with the experimental results.

INFLUENCE OF SOIL MATRIX ON SOIL-WATER RETENTION CURVE AND HYDRAULIC CHARACTERISTICS

2017 ◽  
Vol 16 (4) ◽  
pp. 869-877
Author(s):  
Vasile Lucian Pavel ◽  
Florian Statescu ◽  
Dorin Cotiu.ca-Zauca ◽  
Gabriela Biali ◽  
Paula Cojocaru
Keyword(s):  
Soil Water ◽  
Water Retention ◽  
Water Retention Curve ◽  
Hydraulic Characteristics ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Soil Matrix ◽  
Retention Curve
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