Determining hydraulic properties of concrete and mortar by inverse modelling

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.

Download Full-text

Comparison of different estimation procedures for the hydraulic properties of horticultural substrates by One-Step technique

Journal of Agricultural Engineering ◽

10.4081/jae.2013.289 ◽

2013 ◽

Vol 44 (2s) ◽

Author(s):

Carlo Bibbiani ◽

Carlo A. Campiotti ◽

Luca Incrocci ◽

Alberto Pardossi

Keyword(s):

Hydraulic Conductivity ◽

Hydraulic Properties ◽

Water Retention ◽

Water Retention Curve ◽

Step Method ◽

Retention Curve ◽

Van Genuchten Model ◽

One Step ◽

Conductivity Function ◽

The One

The improved iterative method for the simultaneous determination of the hydraulic properties of growing media from One-Step experiment by Bibbiani, is performed and compared with simplified equations by Valiantzas and Londra. Brooks and Corey equation for water retention, and Kozeny power equation for hydraulic conductivity characterized the hydraulic properties of the porous media. The iterative procedure is applied on pure peat, pumice, and their mixes. The One- Step method has been previously optimized: processing the mean cumulative outflow curves recorded versus time, an estimation of diffusivity, and therefore of the hydraulic functions, is derived. Estimated water retention curve is compared with nine experimental data, and with the estimation of the Van Genuchten model, via the RETC code. Bibbiani’s and Van Genuchten’s models overlap except for the “very wet” range near saturation, whereas the Valiantzas and Londra’s procedure didn’t get satisfactory results. In regard to diffusivity, a good similarity between Bibbiani’s and Van Genuchten-Mualem’s curves can be assessed, while Valiantzas and Londra’s procedure generally results in higher values. Due to the lack of estimation of the water retention curve, Valiantzas and Londra’s procedure fails to estimate the hydraulic conductivity function, whereas Bibbiani’s and Van Genuchten-Mualem’s curves match together in most cases.

Download Full-text

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

Engenharia Agrícola ◽

10.1590/s0100-69162013000200008 ◽

2013 ◽

Vol 33 (2) ◽

pp. 291-302 ◽

Cited By ~ 10

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.

Download Full-text

Further tests of the HYPROP evaporation method for estimating the unsaturated soil hydraulic properties

Journal of Hydrology and Hydromechanics ◽

10.1515/johh-2017-0046 ◽

2018 ◽

Vol 66 (2) ◽

pp. 161-169 ◽

Cited By ~ 14

Author(s):

Camila R. Bezerra-Coelho ◽

Luwen Zhuang ◽

Maria C. Barbosa ◽

Miguel Alfaro Soto ◽

Martinus Th. van Genuchten

Keyword(s):

Hydraulic Conductivity ◽

Unsaturated Soil ◽

Hydraulic Properties ◽

Water Retention ◽

Measurement Techniques ◽

Richards Equation ◽

Water Retention Curve ◽

Soil Hydraulic Properties ◽

Evaporation Method ◽

Soil Hydraulic

AbstractMany soil, hydrologic and environmental applications require information about the unsaturated soil hydraulic properties. The evaporation method has long been used for estimating the drying branches of the soil hydraulic functions. An increasingly popular version of the evaporation method is the semi-automated HYPROP©measurement system (HMS) commercialized by Decagon Devices (Pullman, WA) and UMS AG (München, Germany). Several studies were previously carried out to test the HMS methodology by using the Richards equation and the van-Genuchten-Mualem (VG) or Kosugi-Mualem soil hydraulic functions to obtain synthetic data for use in the HMS analysis, and then to compare results against the original hydraulic properties. Using HYDRUS-1D, we carried out independent tests of the HYPROP system as applied to the VG functions for a broad range of soil textures. Our results closely agreed with previous findings. Accurate estimates were especially obtained for the soil water retention curve and its parameters, at least over the range of available retention measurements. We also successfully tested a dual-porosity soil, as well as an extremely coarse medium with a very high van Genuchtennvalue. The latter case gave excellent results for water retention, but failed for the hydraulic conductivity. In many cases, especially for soils with intermediate and highnvalues, an independent estimate of the saturated hydraulic conductivity should be obtained. Overall, the HMS methodology performed extremely well and as such constitutes a much-needed addition to current soil hydraulic measurement techniques.

Download Full-text

Testing an infiltrometer methodology to investigate water impact effects on both soil sealing and hydraulic properties of a loam soil under conventional tillage and no-tillage

10.5194/egusphere-egu2020-22632 ◽

2020 ◽

Author(s):

Mirko Castellini ◽

Simone Di Prima ◽

Anna Maria Stellacci ◽

Massimo Iovino ◽

Vincenzo Bagarello

Keyword(s):

Hydraulic Conductivity ◽

Hydraulic Properties ◽

Water Retention ◽

Soil Management ◽

Water Retention Curve ◽

Soil Hydraulic Properties ◽

Retention Curve ◽

Soil Sealing ◽

Loam Soil ◽

Soil Hydraulic

Testing new experimental procedures to assess the effects of the drops impact on the soil sealing formation is a main topic in soil hydrology.In this field investigation, the methodological approach proposed first by Bagarello et al. (2014) was extended to account for a greater soil infiltration surface (i.e., about 3.5 times higher), a higher range and number of heights of water pouring and to evaluate the different impact on soil management. For this purpose, the effects of three water pouring heights (low, L=3 cm; medium, M=100 cm; high, H=200 cm) on both no-tilled (NT) and conventionally tilled (CT) loam soil were investigated by Beerkan infiltration runs and using the BEST-procedure of data analysis to estimate the soil hydraulic properties.Final infiltration rate decreased when perturbing runs (i.e., M and H) were carried out as compared with the non-perturbing (L) ones (by a factor of 1.5-3.1 under NT and 3.4-4.4 under CT). Similarly, the water retention scale parameter, hg, increased (i.e., higher in absolute terms) by a factor 1.6-1.8 under NT and by a factor 1.7 under CT. Saturated hydraulic conductivity, Ks, changed significantly as a function of the increase of water pouring height; regardless of the soil management, perturbing runs caused a reduction in soil permeability by a factor 5 or 6. Effects on hydraulic functions (i.e., soil water retention curve and hydraulic conductivity function), obtained with the BEST-Steady algorithm, were also highlighted. For instance, differences in water retention curve at fixed soil pressure head values (i.e., field capacity, FC, and permanent wilting point, PWP) due to perturbing and non-perturbing runs, were estimated as higher under NT (3.8%) than CT (3.4%) for FC, and equal to 2.1% or 1.6% for PWP.Main results of this investigation confirm that a recently tilled loamy soil, without vegetation cover, can be less resilient as compared to a no-tilled one, and that tested water pouring heights methodology looks promising to mimic effects of high energy rainfall events and to quantify the soil sealing effects under alternative management of the soil.AcknowledgmentsThe work was supported by the project &#8220;STRATEGA, Sperimentazione e TRAsferimento di TEcniche innovative di aGricoltura conservativA&#8221;, funded by Regione Puglia&#8211;Dipartimento Agricoltura, Sviluppo Rurale ed Ambientale, CUP: B36J14001230007.&#160;ReferencesBagarello, V., Castellini, M., Di Prima, S., Iovino, M. 2014. Soil hydraulic properties determined by infiltration experiments and different heights of water pouring. Geoderma, 213, 492&#8211;501. https://doi.org/10.1016/j.geoderma.2013.08.032

Download Full-text

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

Water ◽

10.3390/w10101431 ◽

2018 ◽

Vol 10 (10) ◽

pp. 1431 ◽

Cited By ~ 10

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.

Download Full-text

Estimation of tropical soils’ hydraulic properties with inverse method and tension infiltrometer field data

Ambiente e Agua - An Interdisciplinary Journal of Applied Science ◽

10.4136/ambi-agua.2503 ◽

2020 ◽

Vol 15 (3) ◽

pp. 1

Author(s):

João José da Silva Junior ◽

Alberto Colombo ◽

Geraldo Cézar Oliveira ◽

Bruno Montoani Silva ◽

José Eduardo Juliaci Eugênio

Keyword(s):

Hydraulic Conductivity ◽

Inverse Method ◽

Hydraulic Properties ◽

Water Retention ◽

Tropical Soils ◽

Laboratory Method ◽

Water Retention Curve ◽

Soil Conditions ◽

Tension Infiltrometer ◽

Conductivity Curve

In the last few years, many studies have been published by authors from several countries offering approximations and use of the inverse method. However, the unique environmental conditions and distinct properties of the tropical soils in Brazil require extra considerations and the need to adjust these methods to tropical soil conditions. Considering the above, this determined the parameters of the van Genuchten (1980) model (θs, θr, α, n) of the water retention curve in the soils. It also determined the parameter (Ks) of the soil’s hydraulic conductivity curve by solving an inverse problem using the HYDRUS-2D model, considering cumulative infiltration data collected in the field by means of an infiltration test using the tension infiltrometer. It then compared the hydraulic properties determined by these methods in relation to the standard laboratory method. The inverse method was able to efficiently determine the water retention curves in the soils here studied; however, it was not possible to reliably determine the unsaturated hydraulic conductivity curve.

Download Full-text

Effect of Chia Seed Mucilage on the Rhizosphere Hydraulic Characteristics

Sustainability ◽

10.3390/su13063303 ◽

2021 ◽

Vol 13 (6) ◽

pp. 3303

Author(s):

Faisal Hayat ◽

Mohanned Abdalla ◽

Muhammad Usman Munir

Keyword(s):

Hydraulic Conductivity ◽

Hydraulic Properties ◽

Water Retention ◽

Numerical Models ◽

Chemical Properties ◽

Water Retention Curve ◽

Soil Drying ◽

Retention Curve ◽

Unsaturated Hydraulic Conductivity ◽

Chia Seed

The rhizosphere is one of the major components in the soil–plant–atmosphere continuum which controls the flow of water from the soil into roots. Plant roots release mucilage in the rhizosphere which is capable of altering the physio-chemical properties of this region. Here, we showed how mucilage impacted on rhizosphere hydraulic properties, using simple experiments. An artificial rhizosphere, treated or not with mucilage, was placed in a soil sample and suction was applied to mimic the negative pressure in plant xylem. The measured water contents and matric potential were coupled with numerical models to estimate the water retention curve and hydraulic conductivity. A slower loss of water was observed in the treated scenario which resulted in an increase in water retention. Moreover, a slightly lower hydraulic conductivity was initially observed in the treated scenario (8.44 × 10−4 cm s−1) compared to the controlled one in saturated soil. Over soil drying, a relatively higher unsaturated hydraulic conductivity was observed. In summary, we demonstrated that mucilage altered the rhizosphere hydraulic properties and enhanced the unsaturated hydraulic conductivity. These findings improve our understanding of how plants capture more water, and postulate that mucilage secretion could be an optimal trait for plant survival during soil drying.

Download Full-text

The influence of microplastic on soil hydraulic properties

10.5194/egusphere-egu2020-9337 ◽

2020 ◽

Author(s):

Patrizia Hangele ◽

Katharina Luise Müller ◽

Hannes Laermanns ◽

Christina Bogner

Keyword(s):

Hydraulic Conductivity ◽

Soil Water ◽

Hydraulic Properties ◽

Water Retention ◽

Pore Space ◽

Water Retention Curve ◽

Soil Hydraulic Properties ◽

Soil Water Retention ◽

Soil Hydraulic Conductivity ◽

Soil Hydraulic

The need to study the occurrence and effects of microplastic (MP) in different ecosystems has become apparent by a variety of studies in the past years. Until recently, research regarding MP in the environment has mainly focused on marine systems. Within terrestrial systems, studies suggest soils to be the biggest sink for MP. Some studies now started to explore the presence of MP in soils. However, there is a substantial lack of the basic mechanistic understanding of the behaviour of MP particles within soils.This study investigates how the presence of MP in soils affects their hydraulic properties. In order to understand these processes, experiments are set up under controlled laboratory conditions as to set unknown influencing variables to a minimum. Different substrates, from simple sands to undisturbed soils, are investigated in soil cylinders. MP particles of different sizes and forms of the most common plastic types are applied to the surface of the soil cylinders and undergo an irrigation for the MP particles to infiltrate. Soil-water retention curves and soil hydraulic conductivity are measured before and after the application of MP particles. It is hypothesised that the infiltrated MP particles clog a part of the pore space and should thus reduce soil hydraulic conductivity and change the soil-water retention curve of the sample. Knowledge about the influence of MP on soil hydraulic properties are crucial to understand transport and retention of MP in soils.

Download Full-text

How does PTF Interpret Soil Heterogeneity? A Stochastic Approach Applied to a Case Study on Maize in Northern Italy

Water ◽

10.3390/w11020275 ◽

2019 ◽

Vol 11 (2) ◽

pp. 275 ◽

Cited By ~ 2

Author(s):

Angelo Basile ◽

Antonello Bonfante ◽

Antonio Coppola ◽

Roberto De Mascellis ◽

Salvatore Falanga Bolognesi ◽

...

Keyword(s):

Hydraulic Conductivity ◽

Spatial Variability ◽

Soil Water ◽

Hydraulic Properties ◽

Water Retention ◽

Pedotransfer Functions ◽

Water Retention Curve ◽

Real Field ◽

Retention Curve

Soil water balance on a local scale is generally achieved by applying the classical nonlinear Richards equation that requires hydraulic properties, namely, water retention and hydraulic conductivity functions, to be known. Its application in agricultural systems on field or larger scales involves three major problems being solved, related to (i) the assessment of spatial variability of soil hydraulic properties, (ii) accounting for this spatial variability in modelling large-scale soil water flow, and (iii) measuring the effects of such variability on real field variables (e.g., soil water storage, biomass, etc.). To deal with the first issue, soil hydraulic characterization is frequently performed by using the so-called pedotransfer functions (PTFs), whose effectiveness in providing the actual information on spatial variability has been questioned. With regard to the second problem, the variability of hydraulic properties at the field scale has often been dealt with using a relatively simple approach of considering soils in the field as an ensemble of parallel and statistically independent tubes, assuming only vertical flow. This approach in dealing with spatial variability has been popular in the framework of a Monte Carlo technique. As for the last issue, remote sensing seems to be the only viable solution to verify the pattern of variability, going by several modelling outputs which have considered the soil spatial variability. Based on these premises, the goals of this work concerning the issues discussed above are the following: (1) analyzing the sensitivity of a Richards-based model to the measured variability of θ(h) and k(θ) parameters; (2) establishing the predictive capability of PTF in terms of a simple comparison with measured data; and (3) establishing the effectiveness of use of PTF by employing as data quality control an independent and spatially distributed estimation of the Above Ground Biomass (AGB). The study area of approximately 2000 hectares mainly devoted to maize forage cultivation is located in the Po plain (Lodi), in northern Italy. Sample sites throughout the study area were identified for hydropedological analysis (texture, bulk density, organic matter content, and other chemical properties on all the samples, and water retention curve and saturated hydraulic conductivity on a sub-set). Several pedotransfer functions were tested; the PTF‒Vereckeen proved to be the best one to derive hydraulic properties of the entire soil database. The Monte Carlo approach was used to analyze model sensitivity to two measured input parameters: the slope of water retention curve (n) and the saturated hydraulic conductivity (k0). The analysis showed sensitivity of the simulated process to the parameter n being significantly higher than to k0, although the former was much less variable. The PTFs showed a smoothing effect of the output variability, even though they were previously validated on a set of measured data. Interesting positive and significant correlations were found between the n parameter, from measured water retention curves, and the NDVI (Normalized Difference Vegetation Index), when using multi-temporal (2004–2018) high resolution remotely sensed data on maize cultivation. No correlation was detected when the n parameter derived from PTF was used. These results from our case study mainly suggest that: (i) despite the good performance of PTFs calculated via error indexes, their use in the simulation of hydrological processes should be carefully evaluated for real field-scale applications; and (ii) the NDVI index may be used successfully as a proxy to evaluate PTF reliability in the field.

Download Full-text

Implementation of a physically based water percolation routine in the Crocus (V7) snowpack model

10.5194/gmd-2017-56 ◽

2017 ◽

Cited By ~ 1

Author(s):

Christopher J. L. D'Amboise ◽

Karsten Müller ◽

Laurent Oxarango ◽

Samuel Morin ◽

Thomas V. Schuler

Keyword(s):

Hydraulic Conductivity ◽

Water Retention ◽

Synthetic Data ◽

Richards Equation ◽

Water Retention Curve ◽

Parameter Uncertainties ◽

Time Step ◽

Data Set ◽

Capillary Suction ◽

Water Percolation

Abstract. Abstract. We present a new water percolation routine added to the 1D snowpack model Crocus as an alternative to the empirical bucket routine. This routine is based on Richards equation, and describes flow in an unsaturated porous medium governed by capillary suction and hydraulic conductivity of snow layers. We tested the Richards routine on two data sets, one recorded from an automatic weather station over the winter of 2013–2014 at Filefjell, Norway, and a simple synthetic data set. Model results using the Richards routine generally lead to thinner and denser simulated crust layers compared to the bucket routine. Wet snow layers often reach the transition between the pendular and funicular regimes, with 17 % of snow layers obtaining saturation of > 10 % and 4.3 % of layers had saturation of > 15 % for the synthetic data set. The Richards routine had a maximum liquid water content of 167.3 kg m-3 where the bucket routine had a maximum of 42.1 kg m-3. To express the water retention curve and the hydraulic conductivity of snow layers, the Richards routine heavily relies on accurate density and grain size estimations. We found the Richards routine was sensitive to the chosen modelling time step. The time step dependency is a result of feedback between the water percolation routine and the snows compaction and metamorphism routines. We show that the new routine has been implemented in the Crocus model, but due to amplification of parameter uncertainties through a number of feedbacks, meaningful applicability is limited until new and better parameterizations of water retention is developed for different snow types.

Download Full-text