ORCID Profile
0000-0002-8625-5455
Current Organisations
Université Laval
,
Ecole Nationale des Travaux publics de l'Etat
,
Université Claude Bernard Lyon 1
,
INSA de Lyon
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Publisher: Wiley
Date: 2020
DOI: 10.1002/VZJ2.20068
Abstract: Many different equations ranging from simple empirical to semi‐analytical solutions of the Richards equation have been proposed for quantitative description of water infiltration into variably saturated soils. The sorptivity, S , and the saturated hydraulic conductivity, K s , in these equations are typically unknown and have to be estimated from measured data. In this paper, we use so‐called characteristic time ( t char ) to design a new method, referred to as the characteristic time method (CTM) that estimates S , and K s , from one‐dimensional (1D) cumulative infiltration data. We demonstrate the usefulness and power of the CTM by comparing it with a suite of existing methods using synthetic cumulative infiltration data simulated by HYDRUS‐1D for 12 synthetic soils reflecting different USDA textural classes, as well as experimental data selected from the Soil Water Infiltration Global (SWIG) database. Results demonstrate that the inferred values of S and K s are in excellent agreement with their theoretical values used in the synthetically simulated infiltration experiments with Nash–Sutcliffe criterion close to unity and RMSE values of 0.04 cm h −1/2 and 0.05 cm h −1 , respectively. The CTM also showed very high accuracy when applied on synthetic data with added measurement noise, as well as robustness when applied to experimental data. Unlike previously published methods, the CTM does not require knowledge of the time validity of the applied semi‐analytical solution for infiltration and, therefore, is applicable to infiltrations with durations from 5 min to several days. A script written in Python of the CTM method is provided in the supplemental material.
Publisher: Elsevier BV
Date: 03-2019
Publisher: Wiley
Date: 05-2021
DOI: 10.1002/VZJ2.20117
Abstract: Recently, a novel approach with excellent performance based on the concept of the characteristic infiltration time, the characteristic time method (CTM), is proposed to infer soil sorptivity ( S ) and saturated hydraulic conductivity ( K s ) from one‐dimensional (1D) cumulative infiltration. The current work provides a simplified version of the CTM, called the SCTM, by eliminating the necessity of the iteration method used in CTM and providing a similar accuracy as the original method when estimating S and K s . We used both synthetic and experimental data to evaluate SCTM in comparison with the original CTM, as well as Sharma (SH) and curve‐fitting methods. In the case of synthetically simulated infiltration experiments, the predicted S and K s values showed an excellent agreement with their theoretical values, with Nash–Sutcliffe ( E ) values higher than 0.9 and RMSE values of 0.11 cm h 1/2 and 0.35 cm h –1 , respectively. In the case of experimental data, the SCTM showed E values larger than 0.73 and RMSE values of 0.64 cm h 1/2 and 0.35 cm h –1 , respectively. The accuracy and the robustness of SCTM was comparable with the original CTM when applied on synthetic infiltration curves as well as on experimental data. Similar to the original CTM, the simplified approach also does not require the knowledge of the time validity, which is needed when using approaches based on Philip's infiltration theory. The method is applicable to infiltrations with durations from 15 min to 24 h. The supplemental material presents the calculation of S and K s using SCTM in an Excel spreadsheet.
Publisher: Copernicus GmbH
Date: 10-07-2018
DOI: 10.5194/ESSD-10-1237-2018
Abstract: Abstract. In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (∼ 76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76 % of the experimental sites with agricultural land use as the dominant type (∼ 40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at 0.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it.
Publisher: Elsevier BV
Date: 09-2018
Publisher: Copernicus GmbH
Date: 06-03-2018
Publisher: Elsevier BV
Date: 08-2021
Publisher: MDPI AG
Date: 28-02-2021
DOI: 10.3390/MIN11030257
Abstract: Pyrite and calcite are mineral phases that play a major role in acid and neutral mine drainage processes. However, the prediction of acid mine drainage (AMD) or contaminated neutral drainage (CND) requires knowledge of the mineral composition of mining waste and the related potential for element release. This paper studies the combination of acid–base neutralizing capacity (ANC–BNC) with geochemical modeling for the characterization of mining waste and prediction of AMD and CND. The proposed approach is validated with three synthetic mineral assemblages: (1) siliceous sand with pyrite only, representing mining waste responsible for AMD, (2) siliceous sand with calcite and pyrite, representing calcareous waste responsible for CND, and (3) siliceous sand with calcite only, simulating calcareous matrices without any pyrite. The geochemical modeling approach using PHREEQC software was used to model pH evolution and main element release as a function of the added amount of acid or base over the entire pH range: 1 pH 13. For calcareous matrices (sand with calcite), the results are typical of a carbonated environment, the geochemistry of which is well known. For matrices containing pyrite, the results identify different pH values favoring the dissolution of pyrite: pH = 2 in a pyrite-only environment and pH = 6 where pyrite coexists with calcite. The neutral conditions can be explained by the buffering capacity of calcite, which allows iron oxyhydroxide precipitation. Major element release is then related to the dissolution and precipitation of the mineral assemblages. The geochemical modeling allows the prediction of element speciation in the solid and liquid phases. Our findings clearly prove the potential of combined ANC–BNC experiments along with geochemical modeling for the characterization of mining waste and the assessment of risk of AMD and CND.
Publisher: MDPI AG
Date: 05-06-2021
DOI: 10.3390/MIN11060606
Abstract: Mining produces significant amounts of solid mineral waste. Mine waste storage facilities are often challenging to manage and may cause environmental problems. Mining waste is often linked to contaminated mine drainage, including acidic waters with more or less elevated concentrations of trace metals such as lead. This work presents a study on the mobilization of lead from waste from two typical mining sites: Zeida and Mibladen, two now-closed former Pb–Zn mines in the Moulouya region of Morocco. Our research investigates the mobilization potential of Pb from the waste of these mines. The study involved acid–base neutralization capacity tests (ANC–BNC) combined with geochemical modeling. Experimental data allowed for the quantification of the buffering capacity of the s les and the mobilization rates of lead as a function of pH. The geochemical model was fitted to experimental results with thermodynamic considerations. The geochemical model allowed for the identification of the mineral phases involved in providing the buffering capacity of carbonated mining waste (Mibladen) and the meager buffering capacity of the silicate mining waste (Zeida). These cases are representative of contaminated neutral drainage (CND) and acid mine drainage (AMD), respectively. The results highlight the consistency between the ANC–BNC experimental data and the associated modeling in terms of geochemical behavior, validating the approach and identifying the main mechanisms involved. The modeling approach identifies the dissolution of the main solid phases, which impact the pH and the speciation of lead as a function of the pH. This innovative approach, combining ANC–BNC experiments and geochemical modeling, allowed for the accurate identification of mineral phases and surface complexation phenomena, which control the release of lead and its speciation in drainage solutions, as well as within solid phases, as a function of pH.
Publisher: Copernicus GmbH
Date: 24-03-2021
Abstract: Abstract. Sorptivity is a parameter of primary importance in the study of unsaturated flow in soils. This integral parameter is often considered for modeling the computation of water infiltration into vertical soil profiles (1D or 3D axisymmetric geometry). Sorptivity can be directly estimated from the knowledge of the soil hydraulic functions (water retention of hydraulic conductivity), using the integral formulation of Parlange (Parlange, 1975). However, it requires the prior determination of the soil hydraulic diffusivity and its numerical integration between the initial and the final saturation degrees, which may be tricky for some instances (e.g., coarse soil with diffusivity functions quasi-infinite close to saturation). In this paper, we present a specific scaling procedure for the computation of sorptivity considering slightly positive water pressure heads at the soil surface and initial dry conditions (corresponding to most water infiltration on the field). The square sorptivity is related to the square dimensionless sorptivity (referred to as cp parameter) corresponding to a unit soil (i.e., unit values of all the scaled parameters and zero residual water content) utterly dry at the initial state and saturated at the final state. The cp parameter was computed numerically and analytically for five current models: delta functions (Green and Ampt model), Brooks and Corey, van Genuchten-Mualem, van Genuchten-Burdine, and Kosugi models as a function of the shape parameters. The values are tabulated and can be easily used to determine any dimensional sorptivity value for any case. We propose brand-new analytical expressions for some of the models and validate previous formulations for the other models. Our numerical results also showed that the relation between the cp parameters and shape parameters strongly depends on the chosen model, with either increasing or decreasing trends when moving from coarse to fine soils. These results highlight the need for carefully selecting the proper model for the description of the water retention and hydraulic conductivity functions for the rigorous estimation of sorptivity. Present results show the need to understand better the hydraulic model's mathematical properties, including the links between their parameters, and, secondly, to better relate these properties to the physical processes of water infiltration into soils.
Publisher: Copernicus GmbH
Date: 24-02-2023
Abstract: Abstract. Sorptivity is one of the most important parameters for the quantification of water infiltration into soils. Parlange (1975) proposed a specific formulation to derive sorptivity as a function of the soil water retention and hydraulic conductivity functions, as well as initial and final soil water contents. However, this formulation requires the integration of a function involving hydraulic diffusivity, which may be undefined or present numerical difficulties that cause numerical misestimations. In this study, we propose a mixed formulation that scales sorptivity and splits the integrals into two parts: the first term involves the scaled degree of saturation, while the second involves the scaled water pressure head. The new mixed formulation is shown to be robust and well-suited to any type of hydraulic function – even with infinite hydraulic diffusivity or positive air-entry water pressure heads – and any boundary condition, including infinite initial water pressure head, h→-∞. Lastly, we show the benefits of using the proposed formulation for modeling water into soil with analytical models that use sorptivity.
Publisher: Authorea, Inc.
Date: 18-01-2023
DOI: 10.22541/AU.167403072.23915930/V1
Abstract: Estimating of soil sorptivity ( S ) and saturated hydraulic conductivity ( K s ) parameters by field infiltration tests are widespread due to the ease of the experimental protocol and data treatment. The analytical equation proposed by Haverk et al. (1994) allows the modeling of the cumulative infiltration process, from which the hydraulic parameters can be estimated. This model depends on both initial and final values of the soil hydraulic conductivity, initial soil sorptivity, the volumetric water content increase ( ∆ θ ), and two infiltration constants, the so-called β and γ parameters. However, to reduce the number of unknown variables when inverting experimental data, constant parameters such as β and γ are usually prefixed to 0.6 and 0.75, respectively. In this study, the values of these constants are investigated using numerical infiltration curves for different soil types and initial soil water contents for the van Genuchten-Mualem (vGM) soil hydraulic model. Our approach considers the long-time expansions of the Haverk model, the exact soil properties such as S , K s , and initial soil moisture to derive the value of the β and γ parameters for each specific case. We then generated numerically cumulative infiltration curves using Hydrus 3-D software and fitted the long-time expansions to derive the value of the β and γ parameters. The results show that these parameters are influenced by the initial soil water content and the soil type. However, for initially dry soil conditions, some prefixed values can be proposed instead of the currently used values. If an accurate estimate of S and K s is the case, then for coarse-textured soils such as sand and loamy sand, we propose the use of 0.9 for both constants. For the remaining soils, the value of 0.75 can be retained for γ . For β constant, 0.75 and 1.5 values can be considered for, intermediate permeable soils (sandy loam and loam) and low permeable soils (silty loam and silt), respectively. We clarify that the results are based on using the vGM model to describe the hydraulic functions of the soil and that the results may differ, and the assumptions may change for other models.
Publisher: Copernicus GmbH
Date: 06-03-2018
DOI: 10.5194/ESSD-2018-11
Abstract: Abstract. In this paper, we present and analyze a global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database, for the first time. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and USA. In addition to its global spatial coverage, the collected infiltration curves cover a time span of research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use were gathered along with the infiltration data, which makes the database valuable for the development of pedo-transfer functions for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (~76 %) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on the land use is available for 76 % of experimental sites with agricultural land use as the dominant type (~40 %). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for use by public domain only and can be copied freely by referencing it. Supplementary data are available at doi:10.1594/PANGAEA.885492. Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend/update the SWIG by uploading new data to it.
Publisher: MDPI AG
Date: 20-07-2021
Abstract: Background: A set of four case-control (n = 109), randomized-controlled (n = 7), cross-sectional (n = 78), and intervention (n = 47) studies was conducted across three countries to investigate the effects of sun exposure on worker physiology and cognition. Methods: Physiological, subjective, and cognitive performance data were collected from people working in ambient conditions characterized by the same thermal stress but different solar radiation levels. Results: People working under the sun were more likely to experience dizziness, weakness, and other symptoms of heat strain. These clinical impacts of sun exposure were not accompanied by changes in core body temperature but, instead, were linked with changes in skin temperature. Other physiological responses (heart rate, skin blood flow, and sweat rate) were also increased during sun exposure, while attention and vigilance were reduced by 45% and 67%, respectively, compared to exposure to a similar thermal stress without sunlight. Light-colored clothes reduced workers’ skin temperature by 12–13% compared to darker-colored clothes. Conclusions: Working under the sun worsens the physiological heat strain experienced and compromises cognitive function, even when the level of heat stress is thought to be the same as being in the shade. Wearing light-colored clothes can limit the physiological heat strain experienced by the body.
Publisher: Wiley
Date: 11-11-2021
Publisher: Copernicus GmbH
Date: 23-12-2021
Abstract: Abstract. Sorptivity is one of the most important parameters for the quantification of water infiltration into soils. Parlange (1975) proposed a specific formulation to derive sorptivity as a function of the soil water retention and hydraulic conductivity functions, as well as initial and final soil water contents. However, this formulation requires the integration of a function involving the hydraulic diffusivity, which may be undefined or present numerical difficulties that cause numerical misestimations. In this study, we propose a mixed formulation that scales sorptivity and splits the integrals into two parts: the first term involves the scaled degree of saturation while the second involves the scaled water pressure head. The new mixed formulation is shown to be robust and well-suited to any type of hydraulic functions - even with infinite hydraulic diffusivity or positive air-entry water pressure heads - and any boundary condition, including infinite initial water pressure head, h → −∞.
Publisher: Copernicus GmbH
Date: 22-09-2021
DOI: 10.5194/HESS-25-5083-2021
Abstract: Abstract. Sorptivity is a parameter of primary importance in the study of unsaturated flow in soils. This hydraulic parameter is required to model water infiltration into vertical soil profiles. Sorptivity can be directly estimated from the soil hydraulic functions (water retention and hydraulic conductivity curves), using the integral formulation of Parlange (1975). However, calculating sorptivity in this manner requires the prior determination of the soil hydraulic diffusivity and its numerical integration between initial and final saturation degrees, which may be difficult in some situations (e.g., coarse soil with diffusivity functions that are quasi-infinite close to saturation). In this paper, we present a procedure to compute sorptivity using a scaling parameter, cp, that corresponds to the sorptivity of a unit soil (i.e., unit values for all parameters and zero residual water content) that is utterly dry at the initial state and saturated at the final state. The cp parameter was computed numerically and analytically for five hydraulic models: delta (i.e., Green and Ampt), Brooks and Corey, van Genuchten–Mualem, van Genuchten–Burdine, and Kosugi. Based on the results, we proposed brand new analytical expressions for some of the models and validated previous formulations for the other models. We also tabulated the output values so that they can easily be used to determine the actual sorptivity value for any case. At the same time, our numerical results showed that the relation between cp and the hydraulic shape parameters strongly depends on the chosen model. These results highlight the need for careful selection of the proper model for the description of the water retention and hydraulic conductivity functions when estimating sorptivity.
Location: France
No related grants have been discovered for Laurent Lassabatere.