Comparison of three methods to develop pedotransfer functions for the saturated water content and field water capacity in permafrost region

Yi, Xiangsheng; Li, Guosheng; Yin, Yanyu

doi:10.1016/j.coldregions.2012.12.005

Cited by 25 publications

(12 citation statements)

References 41 publications

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“…The total porosity (Pt, %), capillary porosity (Pc, %) and noncapillary porosity (Pn, %) of the soil were calculated according to Equations (6)- (8), respectively. The equations used [37,38] are given below. …”

Section: Methodsmentioning

confidence: 99%

“…Soil water content (S, %), saturated water content (SW, %), capillary moisture capacity (CW, %) that is quantified in the field by the capacity of the unsaturated aggregates to absorb water by capillarity [37], field water capacity (FW, %) that is defined as water in the soil retained against gravity [38], and bulk density (D, g/cm 3 ) were calculated according to Equations (1), (2), (3), (4) and (5), respectively. The total porosity (Pt, %), capillary porosity (Pc, %) and noncapillary porosity (Pn, %) of the soil were calculated according to Equations (6)- (8), respectively.…”

Section: Methodsmentioning

confidence: 99%

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Effects of a Wildfire on Selected Physical, Chemical and Biochemical Soil Properties in a Pinus massoniana Forest in South China

Xue

QiuJing

Chen

2014

Forests

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Abstract:Pinus massoniana forests bordering South China are often affected by wildfires. Fires cause major changes in soil properties in many forest types but little is known about the effects of fire on soil properties in these P. massoniana forests. Such knowledge is important for providing a comprehensive understanding of wildfire effects on soil patterns and for planning appropriate long-term forest management in these forests. Changes in soil physical properties, carbon, nutrients, and enzymes were investigated in a P. massoniana forest along a wildfire-induced time span consisting of an unburned soil, and soils 0, one, four, and seven years post-fire. Soil (0-10 cm) was collected from burned and unburned sites immediately and one, four, and seven years after a wildfire. The wildfire effects on soil physical and chemical properties and enzyme activities were significantly different among treatment variation, time variation, and treatment-by-time interaction. Significant short-term effects on soil physical, chemical, and biological properties were found, which resulted in a deterioration of soil physical properties by increasing soil bulk density and decreasing macropores and capillary moisture. Soil pH increased significantly in the soil one-year post-fire. Carbon, total nitrogen (N) and phosphorus (P), and available N and P increased significantly immediately and one year after the wildfire and decreased progressively to concentrations lower than in the unburned soil. Total potassium (K) and exchangeable K increased immediately after the wildfire and then continuously decreased along the burned time-span. Urease, acid phosphatase, and catalase activities significantly decreased OPEN ACCESSForests 2014, 5 2948 compared to those in the unburned soil. In fire-prone P. massoniana forests, wildfires may significantly influence soil physical properties, carbon, nutrients, and enzyme activity.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Effects of a Wildfire on Selected Physical, Chemical and Biochemical Soil Properties in a Pinus massoniana Forest in South China

Xue

QiuJing

Chen

2014

Forests

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“…This is ascribed to the accuracy of the PTFs for these Ψm values, which had R 2 values near 0.60 (Table 3). Other soil attributes not considered for the PTFs developed here, such as organic carbon, influence the water retention for large pore sizes and, if considered, can increase R 2 for -1 and -3 kPa Ψm (Yi et al, 2013). Yi et al (2013) observed that soil organic carbon exhibits a higher correlation (0.82, p < 0.01) with the saturation water content.…”

Section: Resultsmentioning

confidence: 80%

Influence of physical attributes and pedotransfer function for predicting water retention in management systems

Auler

Pires

Pineda

2017

Rev. bras. eng. agríc. ambient.

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A B S T R A C TThe aims of this study were to evaluate the effects of the soil structural physical attributes on the water retention and to develop pedotransfer functions (PTFs) for the estimation of the soil water content (θ) at different matric potentials of a Dystrophic Red Latosol (Hapludox) under conventional tillage (CT) and no-tillage (NT) soil management systems. The effects of long-term CT and NT (over 25 years) management on the soil bulk density (BD), total porosity (TP), macroporosity (Ma), microporosity (Mi) and water retention were investigated. The PTFs were developed to predict θ and used to evaluate the soil water retention curve only for the NT system. The NT system was characterized by smaller values of the soil BD and higher values of the soil TP and Mi than the CT system. The NT system exhibited a higher θ retained than the CT system for the pore-size interval of 0.2-30 µm. However, the CT system exhibited a large amount of water retention for pores smaller than 0.2 µm. The PTFs were utilized to estimate θ at matric potentials of -1, -3, -6, -10, -33, -100, -400, -800, and -1,500 kPa with adequate accuracy. The soil BD, Ma, Mi and sand content were the main variables considered to estimate θ for the different matric potentials evaluated.Atributos físicos e funções de pedotransferência para estimativa da retenção de água em sistemas de manejo R E S U M OOs objetivos deste estudo foram avaliar os efeitos de atributos físicos estruturais do solo sobre a retenção de água e desenvolver funções de pedotransferência (FPT) para a estimativa de conteúdos de água (θ) em diferentes potenciais mátricos de um Latossolo Vermelho distrófico em sistema convencional (SC) e sistema plantio direto (SPD). Os efeitos de longo prazo dos manejos SC e SPD (mais de 25 anos) sobre a densidade do solo (DS), porosidade total (PT), macroporosidade (Ma), microporosidade (Mi) e retenção de água foram investigados. As FPT foram desenvolvidas para predizer os θs utilizados na determinação da curva de retenção de água apenas para o SPD. O SPD apresentou menor DS e maior PT e Mi que o SC. O SPD aumentou o conteúdo de água retido em poros de tamanho entre 0,2 e 30 µm, em relação ao SC. No entanto, o SC apresentou maior conteúdo de água retido em poros com raio menor que 0,2 µm. As FPTs utilizadas para estimar θ para os potenciais mátricos de -1, -3, -6, -10, -33, -100, -400, -800 e -1500 kPa tiveram acurácia adequada. A DS, Ma, Mi e teor de areia foram as principais variáveis consideradas para estimar o conteúdo de água nesses potenciais mátricos. Key words:no-tillage conventional tillage soil porosity Palavras-chave: sistema plantio direto sistema plantio convencional porosidade do solo

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“…Also, due to the occurring of nonlinear equations between dependent variables and predicting variables, the neural network have the better efficiency compared with the basic regression equations. Yi et al (2013) investigated the accuracy of ANN and analyzed the regression method using correlation coefficient and the RMSE. They reported that the neural network is able to predict the easily measurable soil parameters with more accuracy and less error.…”

Section: Discussionmentioning

confidence: 99%

“…As a result, ANN method can typically extract the maximum amount of information from the data. For these reasons, the ANN method had a wide application (Merdun et al, 2006;Yi et al, 2013), and many scholars implicate that the general prediction of ANN is better than the MLR method (Moghimi et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Selection of a suitable model for the prediction of soil water content in north of Iran

Esmaeelnejad

Ramezanpour

Seyedmohammadi

et al. 2015

Span. j. agric. res.

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Multiple Linear Regression (MLR), Artificial Neural Network (ANN) and Rosetta model were employed to develop pedotransfers functions (PTFs) for soil moisture prediction using available soil properties for northern soils of Iran. The Rosetta model is based on ANN works in a hierarchical approach to predict water retention curves. For this purpose, 240 soil samples were selected from the south of Guilan province, Gilevan region, northern Iran. The data set was divided into two subsets for calibration and testing of the models. The general performance of PTFs was evaluated using coefficient of determination (R 2 ), root mean square error (RMSE) and mean biased error between the observed and predicted values. Results showed that ANN with two hidden layers, Tan-sigmoid and linear functions for hidden and output layers respectively, performed better than the others in predicting soil moisture. In the other hand, ANN can model non-linear functions and showed to perform better than MLR. After ANN, MLR had better accuracy than Rosetta. The developed PTFs resulted in more accurate estimation at matric potentials of 100, 300, 500, 1000, 1500 kPa. Whereas, Rosetta model resulted in slightly better estimation than derived PTFs at matric potentials of 33 kPa. This research can provide the scientific basis for the study of soil hydraulic properties and be helpful for the estimation of soil water retention in other places with similar conditions, too. Additional keywords: multiple linear regression; neural networks; pedotransfer function; Rosetta; soil moisture curve.

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Comparison of three methods to develop pedotransfer functions for the saturated water content and field water capacity in permafrost region

Cited by 25 publications

References 41 publications

Effects of a Wildfire on Selected Physical, Chemical and Biochemical Soil Properties in a Pinus massoniana Forest in South China

Effects of a Wildfire on Selected Physical, Chemical and Biochemical Soil Properties in a Pinus massoniana Forest in South China

Influence of physical attributes and pedotransfer function for predicting water retention in management systems

Selection of a suitable model for the prediction of soil water content in north of Iran

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