scholarly journals Bimodal pore distribution on soils under conservation management system for coffee crop

2013 ◽  
Vol 33 (2) ◽  
pp. 291-302 ◽  
Author(s):  
Carla E. Carducci ◽  
Geraldo C. de Oliveira ◽  
Walmes M. Zeviani ◽  
Vico M. P. Lima ◽  
Milson E. Serafim
Keyword(s):  
Management System ◽  
Soil Structure ◽  
Water Retention ◽  
Conservation Management ◽  
Pore Distribution ◽  
Water Retention Curve ◽  
Residual Water ◽  
Retention Data ◽  
Retention Curve ◽  
Van Genuchten Model

This study aims at detailing bimodal pore distribution by means of water retention curve in an oxidic-gibbsitic Latosol and in a kaolinitic cambisol Latossol under conservation management system of coffee crop. Samples were collected at depths of 20; 40; 80; 120 and 160 cm on coffee trees rows and between rows under oxidic-gibbsitic Latosol (LVd) and kaolinitic cambisol Latossol (LVAd). Water retention curve was determined at matrix potentials (Ψm) -1; -2; -4; -6; -10 kPa obtained from the suction unit; the Ψm of -33; -100; -500; -1,500 kPa were obtained by the Richards extractor, and WP4-T psychrometer was used to determine Ψm -1,500 to -300,000 kPa. The water retention data were adjusted to the double van Genuchten model by nonlinear model procedures of the R 2.12.1 software. Was estimated the model parameter and inflection point slope. The system promoted changes in soil structure and water retention for the conditions evaluated, and both showed bimodal pores distribution, which were stronger in LVd. There was a strong influence of mineralogy gibbsitic in the water retention more negative than Ψm -1500 kPa, reflected in the values of the residual water content.

scholarly journals Determining hydraulic properties of concrete and mortar by inverse modelling

2012 ◽  
Vol 1475 ◽  
Author(s):  
Sébastien Schneider ◽  
Dirk Mallants ◽  
Diederik Jacques
Keyword(s):  
Hydraulic Conductivity ◽  
Hydraulic Properties ◽  
Water Retention ◽  
Inverse Modelling ◽  
Degree Of Saturation ◽  
Water Retention Curve ◽  
Retention Data ◽  
Capillary Suction ◽  
Near Surface ◽  
Van Genuchten Model

ABSTRACTThis paper presents a methodology and results on estimating hydraulic properties of the concrete and mortar considered for the near surface disposal facility in Dessel, Belgium, currently in development by ONDRAF/NIRAS. In a first part, we estimated the van parameters for the water retention curve for concrete and mortar obtained by calibration (i.e. inverse modelling) of the van Genuchten model [1] to experimental water retention data [2]. Data consisted of the degree of saturation measured at different values of relative humidity. In the second part, water retention data and data from a capillary suction experiment on concrete and mortar cores was used jointly to successfully determine the van Genuchten retention parameters and the Mualem hydraulic conductivity parameters (including saturated hydraulic conductivity) by inverse modelling.

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.

scholarly journals Filter Paper Method for the Determination of the Soil Water Retention Curve

2015 ◽  
Vol 39 (5) ◽  
pp. 1344-1352 ◽  
Author(s):  
Eurileny Lucas de Almeida ◽  
Adunias dos Santos Teixeira ◽  
Francisco Chagas da Silva Filho ◽  
Raimundo Nonato de Assis Júnior ◽  
Raimundo Alípio de Oliveira Leão
Keyword(s):  
Filter Paper ◽  
Water Retention ◽  
Water Retention Curve ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Matric Potential ◽  
Retention Curve ◽  
Filter Paper Method ◽  
Van Genuchten Model ◽  
Paper Method

ABSTRACT High cost and long time required to determine a retention curve by the conventional methods of the Richards Chamber and Haines Funnel limit its use; therefore, alternative methods to facilitate this routine are needed. The filter paper method to determine the soil water retention curve was evaluated and compared to the conventional method. Undisturbed samples were collected from five different soils. Using a Haines Funnel and Richards Chamber, moisture content was obtained for tensions of 2; 4; 6; 8; 10; 33; 100; 300; 700; and 1,500 kPa. In the filter paper test, the soil matric potential was obtained from the filter-paper calibration equation, and the moisture subsequently determined based on the gravimetric difference. The van Genuchten model was fitted to the observed data of soil matric potential versus moisture. Moisture values of the conventional and the filter paper methods, estimated by the van Genuchten model, were compared. The filter paper method, with R2 of 0.99, can be used to determine water retention curves of agricultural soils as an alternative to the conventional method.

scholarly journals Artificial Neural Networks for Predicting the Water Retention Curve of Sicilian Agricultural Soils

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1431 ◽  
Author(s):  
Alessandro D’Emilio ◽  
Rosa Aiello ◽  
Simona Consoli ◽  
Daniela Vanella ◽  
Massimo Iovino
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Soil Water ◽  
Hydraulic Properties ◽  
Water Retention ◽  
Water Retention Curve ◽  
Retention Data ◽  
Soil Hydraulic Properties ◽  
Retention Curve ◽  
Artificial Neural

Modeling soil-water regime and solute transport in the vadose zone is strategic for estimating agricultural productivity and optimizing irrigation water management. Direct measurements of soil hydraulic properties, i.e., the water retention curve and the hydraulic conductivity function, are often expensive and time-consuming, and represent a major obstacle to the application of simulation models. As a result, there is a great interest in developing pedotransfer functions (PTFs) that predict the soil hydraulic properties from more easily measured and/or routinely surveyed soil data, such as particle size distribution, bulk density (ρb), and soil organic carbon content (OC). In this study, application of PTFs was carried out for 359 Sicilian soils by implementing five different artificial neural networks (ANNs) to estimate the parameter of the van Genuchten (vG) model for water retention curves. The raw data used to train the ANNs were soil texture, ρb, OC, and porosity. The ANNs were evaluated in their ability to predict both the vG parameters, on the basis of the normalized root-mean-square errors (NRMSE) and normalized mean absolute errors (NMAE), and the water retention data. The Akaike’s information criterion (AIC) test was also used to assess the most efficient network. Results confirmed the high predictive performance of ANNs with four input parameters (clay, sand, and silt fractions, and OC) in simulating soil water retention data, with a prediction accuracy characterized by MAE = 0.026 and RMSE = 0.069. The AIC efficiency criterion indicated that the most efficient ANN model was trained with a relatively low number of input nodes.

scholarly journals Water retention curve to analyze soil structure changes due to liming

2019 ◽  
Vol 91 (3) ◽  
Author(s):  
TALITA R. FERREIRA ◽  
LUIZ F. PIRES ◽  
ANDRÉ C. AULER ◽  
ANDRÉ M. BRINATTI ◽  
JOSHUA O. OGUNWOLE
Keyword(s):  
Soil Structure ◽  
Water Retention ◽  
Water Retention Curve ◽  
Retention Curve ◽  
Structure Changes

scholarly journals Parametric soil water retention models: a critical evaluation of expressions for the full moisture range

2018 ◽  
Vol 22 (2) ◽  
pp. 1193-1219 ◽  
Author(s):  
Raneem Madi ◽  
Gerrit Huibert de Rooij ◽  
Henrike Mielenz ◽  
Juliane Mai
Keyword(s):  
Hydraulic Conductivity ◽  
Soil Water ◽  
Water Retention ◽  
Minor Effect ◽  
Residual Water ◽  
Retention Data ◽  
General Criterion ◽  
Soil Water Retention ◽  
Retention Curve ◽  
Soil Hydraulic

Abstract. Few parametric expressions for the soil water retention curve are suitable for dry conditions. Furthermore, expressions for the soil hydraulic conductivity curves associated with parametric retention functions can behave unrealistically near saturation. We developed a general criterion for water retention parameterizations that ensures physically plausible conductivity curves. Only 3 of the 18 tested parameterizations met this criterion without restrictions on the parameters of a popular conductivity curve parameterization. A fourth required one parameter to be fixed. We estimated parameters by shuffled complex evolution (SCE) with the objective function tailored to various observation methods used to obtain retention curve data. We fitted the four parameterizations with physically plausible conductivities as well as the most widely used parameterization. The performance of the resulting 12 combinations of retention and conductivity curves was assessed in a numerical study with 751 days of semiarid atmospheric forcing applied to unvegetated, uniform, 1 m freely draining columns for four textures. Choosing different parameterizations had a minor effect on evaporation, but cumulative bottom fluxes varied by up to an order of magnitude between them. This highlights the need for a careful selection of the soil hydraulic parameterization that ideally does not only rely on goodness of fit to static soil water retention data but also on hydraulic conductivity measurements. Parameter fits for 21 soils showed that extrapolations into the dry range of the retention curve often became physically more realistic when the parameterization had a logarithmic dry branch, particularly in fine-textured soils where high residual water contents would otherwise be fitted.

scholarly journals MODELOS DE CURVA DE RETENÇÃO DE ÁGUA NO SOLO

Irriga ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 115 ◽  
Author(s):  
Roberto Filgueiras ◽  
Vinicius Mendes Rodrigues de Oliveira ◽  
Fernando França da Cunha ◽  
Everardo Chartuni Mantovani ◽  
Epitácio Jose de Souza
Keyword(s):  
Potential Field ◽  
Water Retention ◽  
Field Capacity ◽  
Water Retention Curve ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Retention Curve ◽  
Permanent Wilting Point ◽  
Van Genuchten Model ◽  
Wilting Point

MODELOS DE CURVA DE RETENÇÃO DE ÁGUA NO SOLO  ROBERTO FILGUEIRAS¹; VINICIUS MENDES RODRIGUES DE OLIVEIRA²; FERNANDO FRANÇA DA CUNHA³; EVERARDO CHARTUNI MANTOVANI³ E EPITÁCIO JOSE DE SOUZA4 1 Doutorando em Engenharia Agrícola, Universidade Federal de Viçosa. Viçosa, MG. Email: [email protected]²    Doutorando em Engenharia Agrícola, Universidade Federal de Viçosa. Viçosa, MG³    Prof. Dr. Departamento de Engenharia Agrícola, Universidade Federal de Viçosa. Viçosa, MG4      Doutorando em Agronomia (Ciência do Solo), UNESP. Ilha Solteira, SP.  1 RESUMO  O objetivo deste trabalho foi comparar a umidade na capacidade de campo e ponto de murcha permanente obtida com os modelos de obtenção da curva de retenção de água no solo de van Genuchten e potencial e ainda comparar os valores de capacidade de campo obtidos com a tensão de 6 e 33 kPa. Para isto ajustaram-se os modelos van Genuchten e potencial para as tensões de 10, 30, 50, 100, 500 e 1500 kPa, através da câmara de Richards. Posteriormente, encontrou-se os valores de umidade para as tensões na capacidade de campo (6 e 33 kPa) e ponto de murcha permanente (1500 kPa). Ambos os modelos predisseram a umidade na capacidade de campo a 33 kPa e o ponto de murcha permanente com alta precisão, exatidão e concordância, quando comparado os dois métodos. Palavras-chave: van Genuchten, potencial, capacidade de campo.  FILGUEIRAS R.; DE OLIVEIRA V. M. R.; CUNHA F. F. DA; MANTOVANI E. C.; E. J. DE SOUZA.WATER RETENTION CURVE MODELS IN THE SOIL       2 ABSTRACT The objective of this study was to compare the moisture at field capacity and permanent wilting point obtained by the models and potential for obtaining the soil water retention curve by van Genuchten, also comparing the field capacity values with the tension of 6 and 33 kPa. Thus, it adjusted the van Genuchten model and potential for voltages of 10, 30, 50, 100, 500 and 1500 kPa through Richards chamber, subsequently finding the moisture values for the voltages at field capacity (6 and 33 kPa) and permanent wilting point (1500 kPa). Both models predicted moisture at field capacity at 33 kPa and the permanent wilting point with high precision, accuracy and harmony, when the two methods are compared. Keywords: van Genuchten , potential, field capacity. 

Relating soil structure and hydrophysical characteristics to aerobic and anaerobic soil respiration

2020 ◽  
Author(s):  
Teamrat Ghezzehei ◽  
Jennifer Alvarez ◽  
Yocelyn Villa ◽  
Rebecca Ryals
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Soil Water ◽  
Soil Structure ◽  
Water Retention ◽  
Water Retention Curve ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Retention Curve ◽  
Aerobic And Anaerobic

<p>The dynamics of soil organic matter is strongly controlled by the hydrophysical environmental factors, including motility, aqueous diffusivity of substrates, gaseous diffusivity, and energetic constraints on microbial physiology. The relationships among these physical factors depend on soil moisture and the architecture of the soil pores. In this regard, the soil water retention curve can serve as a macroscopic signature of pore-size distribution. Therefore, the sensitivity of aerobic and anaerobic microbial activity must be closely associated with the shape of the soil water retention curve. The soil water retention curve is, in turn, strongly dependent on soil texture and structure. Here, we present a physically-based model of aerobic and anaerobic microbial respiration rates. We also present a novel experimental technique for the characterization of the soil-moisture sensitivity of soil microbial activity. The proposed experimental and modeling approaches allow direct coupling of the fate soil organic matter with the nature of soil structure.</p>

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