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11 results on '"Rahmati, Mehdi"'

1. On Infiltration and Infiltration Characteristic Times

Author

Rahmati, Mehdi, Latorre, Borja, Moret‐Fernández, David, Lassabatere, Laurent, Talebian, Nima, Miller, Dane, Morbidelli, Renato, Iovino, Massimo, Bagarello, Vincenzo, Neyshabouri, Mohammad Reza, Zhao, Ying, Vanderborght, Jan, Weihermüller, Lutz, Jaramillo, Rafael Angulo, Or, Dani, Genuchten, Martinus van, Vereecken, Harry, Hydrogeology, Environmental hydrogeology, Hydrogeology, Environmental hydrogeology, Latorre Garcés, Borja, Moret-Fernández, David, Department of Soil Science and Engineering, Faculty of Agriculture, University of Maragheh, Institute of Bio- and Geosciences [Jülich] (IBG), Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association, Consejo Superior de Investigaciones Científicas [Spain] (CSIC), Departamento de Suelo y Agua, Pomology Department, Estación Experimental de Aula Dei, Équipe 5 - Impact des Aménagements et des Polluants sur les HYdrosystèmes (IAPHY), Laboratoire d'Ecologie des Hydrosystèmes Naturels et Anthropisés (LEHNA), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Centre National de la Recherche Scientifique (CNRS), Bond University [Gold Coast], Department of Civil and Environmental Engineering of the University of Perugia, Italy, Università degli Studi di Perugia = University of Perugia (UNIPG), Università degli studi di Palermo - University of Palermo, University of Tabriz [Tabriz], College of Resources and Environmental Engineering [Yantai], Ludong University, Desert Research Institute (DRI), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Department of Earth Sciences, Utrecht University, Center for Environmental Studies, CEA, São Paulo State University, Latorre Garcés, Borja [0000-0002-6720-3326], Moret-Fernández, David [0000-0002-6674-0453], Rahmati M., Latorre B., Moret-Fernandez D., Lassabatere L., Talebian N., Miller D., Morbidelli R., Iovino M., Bagarello V., Neyshabouri M.R., Zhao Y., Vanderborght J., Weihermuller L., Jaramillo R.A., Or D., Th. van Genuchten M., and Vereecken H.

Subjects
Science & Technology, EROSION, sorptivity, HYDRAULIC CONDUCTIVITY, INFILTROMETER, Infiltration, Environmental Sciences & Ecology, PARAMETERS, SOIL, MODEL, Physical Sciences, Limnology, [SDE]Environmental Sciences, ddc:550, Water Resources, EQUATION, Settore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-Forestali, WATER, steady state, time domain validity, Marine & Freshwater Biology, Life Sciences & Biomedicine, hydraulic conductivity, Environmental Sciences, Water Science and Technology
Abstract

In his seminal paper on the solution of the infiltration equation, Philip (1969), https://doi.org/10.1016/b978-1-4831-9936-8.50010-6 proposed a gravity time, tgrav, to estimate practical convergence time and the time domain validity of his infinite time series expansion, TSE, for describing the transient state. The parameter tgrav refers to a point in time where infiltration is dominated equally by capillarity and gravity as derived from the first two (dominant) terms of the TSE. Evidence suggests that applicability of the truncated two-term equation of Philip has a time limit requiring higher-order TSE terms to better describe the infiltration process for times exceeding that limit. Since the conceptual definition of tgrav is valid regardless of the infiltration model used, we opted to reformulate tgrav using the analytic implicit model proposed by Parlange et al. (1982), https://doi.org/10.1097/00010694-198206000-00001 valid for all times and related TSE. Our derived gravity times ensure a given accuracy of the approximations describing transient states, while also providing insight about the times needed to reach steady state. In addition to the roles of soil sorptivity (S) and the saturated (Ks) and initial (Ki) hydraulic conductivities, we explored the effects of a soil specific shape parameter β, involved in Parlange's model and related to the type of soil, on the behavior of tgrav. We show that the reformulated tgrav (notably (Formula presented.) where F(β) is a β-dependent function) is about three times larger than the classical tgrav given by (Formula presented.). The differences between the classical tgrav,Philip and the reformulated tgrav increase for fine-textured soils, attributed to the time needed to attain steady-state infiltration and thus i + nfiltration for inferring soil hydraulic properties. Results show that the proposed tgrav is a better indicator of time domain validity than tgrav,Philip. For the attainment of steady-state infiltration, the reformulated tgrav is suitable for coarse-textured soils. Still neither the reformulated tgrav nor the classical tgrav,Philip are suitable for fine-textured soils for which tgrav is too conservative and tgrav,Philip too short. Using tgrav will improve predictions of the soil hydraulic parameters (particularly Ks) from infiltration data compared to tgrav,Philip., Water Resources Research, 58 (5), ISSN:0043-1397, ISSN:1944-7973

Published
2022

2. Parasite inversion for determining the coefficients and time-validity of Philip's two-term infiltration equation

Author

Jaiswal, Parakh, Gao, Yifu, Rahmati, Mehdi, Vanderborght, Jan, Simunek, Jirka, Vereecken, Harry, and Vrugt, Jasper A

Subjects
Science & Technology, HYDRAULIC CONDUCTIVITY, Soil Science, DISC INFILTROMETER, Environmental Sciences & Ecology, Agriculture, PONDED CONDITIONS, PARAMETER, WATER-RETENTION, SOILS, MODEL, VERTICAL INFILTRATION, Physical Sciences, STEADY INFILTRATION, Water Resources, MONTE-CARLO-SIMULATION, Life Sciences & Biomedicine, Environmental Sciences
Abstract

ispartof: VADOSE ZONE JOURNAL vol:21 issue:1 status: published

Published
2022

3. Mixed formulation for an easy and robust numerical computation of sorptivity.

Author

Lassabatere, Laurent, Peyneau, Pierre-Emmanuel, Yilmaz, Deniz, Pollacco, Joseph, Fernández-Gálvez, Jesús, Latorre, Borja, Moret-Fernández, David, Di Prima, Simone, Rahmati, Mehdi, Stewart, Ryan D., Abou Najm, Majdi, Hammecker, Claude, and Angulo-Jaramillo, Rafael

Subjects
SOIL moisture, WATER pressure, HYDRAULIC conductivity
Abstract

Sorptivity is one of the most important parameters for the quantification of water infiltration into soils. 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. [ABSTRACT FROM AUTHOR]

Published
2023
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4. A scaling procedure for straightforward computation of sorptivity.

Author

Lassabatere, Laurent, Peyneau, Pierre-Emmanuel, Yilmaz, Deniz, Pollacco, Joseph, Fernández-Gálvez, Jesús, Latorre, Borja, Moret-Fernández, David, Di Prima, Simone, Rahmati, Mehdi, Stewart, Ryan D., Abou Najm, Majdi, Hammecker, Claude, and Angulo-Jaramillo, Rafael

Subjects
SOIL profiles, HYDRAULIC conductivity, NUMERICAL integration, SOLIFLUCTION, HYDRAULIC models, SEEPAGE, SOIL permeability
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. 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. [ABSTRACT FROM AUTHOR]

Published
2021
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5. Simplified characteristic time method for accurate estimation of the soil hydraulic parameters from one‐dimensional infiltration experiments.

Author

Rahmati, Mehdi, Rezaei, Meisam, Lassabatere, Laurent, Morbidelli, Renato, and Vereecken, Harry

Subjects
SOIL infiltration, HYDRAULIC conductivity, SOIL absorption & adsorption, ITERATIVE methods (Mathematics), MATHEMATICAL models
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 (Ks) 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 Ks. 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 Ks 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 h1/2 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 h1/2 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 Ks using SCTM in an Excel spreadsheet. Core Ideas: A simplified version of the CTM is proposed to estimate the S and Ks from a 1D infiltration curve.The SCTM is nearly as accurate as the original CTM in prediction of S and Ks.The SCTM eliminates the necessity of the iteration method used in original CTM. [ABSTRACT FROM AUTHOR]

Published
2021
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6. Three‐ and four‐term approximate expansions of the Haverkamp formulation to estimate soil hydraulic properties from disc infiltrometer measurements.

Author

Moret‐Fernández, David, Latorre, Borja, López, Maria V., Pueyo, Yolanda, Lassabatere, Laurent, Angulo‐Jaramilo, Rafael, Rahmati, Mehdi, Tormo, Jaume, and Nicolau, José M.

Subjects
LOAM soils, INFILTROMETERS, SILT loam, HYDRAULIC conductivity, SOIL infiltration, SOILS
Abstract

Soil sorptivity, S, and saturated hydraulic conductivity, Ks, can be estimated from the inverse analysis of a disc infiltrometer cumulative infiltration curve using the quasi‐exact implicit (QEI) analytical Haverkamp et al. (1994) equation, which is a function of Ks, S, the parameters β and γ, the disc radius, rd, and the water content increase, ∆θ. Given the complexity of solving QEI, this paper presents three‐term, 3T, and four‐term, 4T, QEI expansions to estimate S and Ks. The interplays between β, γ, Ks and S employing S‐Ks, γ‐Ks, γ‐S, γ‐β, S‐β and Ks‐β error maps generated for a loam soil synthetic infiltration were analyzed with QEI. To reduce the number of variables, Δθ, rd and γ were packed into the A=γrd∆θ term. Five different QEI expansion analyses were evaluated: (i and ii) optimization of 3T using A, 3TA, or β, 3Tβ, as fixed variables; (iii and iv) optimization of 3T, 3TAβ, and 4T, 4TAβ, using constant β and A values; and (v) optimization of 4T leaving all coefficients free, 4TF. The different methods were evaluated with synthetic infiltrations for homogeneous sand, loam and silt soils, and for an uniform loam soil with a contact sand layer. The QEI expansions were applied to experimental infiltrations, and the results were compared to those obtained with QEI, using β = 0.6 and γ = 0.75. Infiltrations were performed at zero cm of soil tension. Global optimization with QEI demonstrates that γ and β are extremely linked. This makes it difficult to estimate these two parameters. All procedures applied to synthetic homogeneous soils resulted in good Ks and S approaches. However, only 3TA, 3TAβ and 4TAβ obtained accurate estimates of Ks and S when applied to a synthetic homogeneous soil with a contact sand layer. Application of the different methods to the experimental infiltrations showed that 3TAβ and 4TAβ gave the most accurate and robust estimates of S and Ks. [ABSTRACT FROM AUTHOR]

Published
2020
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7. The relevance of Philip theory to Haverkamp quasi-exact implicit analytical formulation and its uses to predict soil hydraulic properties.

Author

Rahmati, Mehdi, Latorre, Borja, Lassabatere, Laurent, Angulo-Jaramillo, Rafael, and Moret-Fernández, David

Subjects
*SENSITIVITY analysis, *HYDRAULIC conductivity, *WATER seepage, *SOILS, *SAND
Abstract

Highlights • This work approximates the quasi-exact implicit formulation of Haverkamp model up to three-term expansion. • The accuracy of the proposed approximation is evaluated based on the quasi-exact implicit model. • A sensitivity analysis is conducted to define the infiltration time for which this expansion remains valid. • The proposed approximation is compared with Philip (1957) one- and two-term approximate expansions. Abstract The quasi-exact implicit (QEI) analytical formulation of Haverkamp equation, which might be also known as Parlange model, and its one- and two-term approximate expansions are among the mostly used equations for in situ determination of soil sorptivity, S , and saturated hydraulic conductivity, K s , from unsaturated one-dimensional (1D) cumulative infiltration into soils. However, from practical point of view, the approximate expansions are only valid from short to intermediate times and the QEI analytical formulation has a complex resolution, which makes its use complicated in inverting procedures. Therefore, alternative functions are needed to compute cumulative infiltration for longer times and improve inverting procedures for easier, more robust and accurate predictions of S and K s. In this regard, current work presents and evaluates a new three-term approximation of the QEI analytical formulation. As a first step, we checked the accuracy of the proposed three-term approximate expansion with respect to the QEI formulation for three different soils (sand, loam and silt) in order to define its time domain validity. Next, the accuracy of the three-term approximate expansion to estimate S , K s and the β parameter was compared to those obtained with one- and two-term approximate expansions. Lastly, a large dataset of field experimental data was inverted using the proposed three approximate expansions and the QEI analytical formulation, and goodness of fits predicted and measured cumulative infiltration curves and accuracy of the parameters (S , K s and the β) estimates were compared. The results revealed that the three-term approximate has a larger validity time interval compared to one- and two-term approximate expansions, which allows its use for larger infiltration times durations resulting in more accurate estimates of K s. Its capability of estimating S is also improved. The accurate prediction of β parameter is not still guaranteed for none of the approximate expansions. Compared to the one- and two-term approximate expansions, the experimental infiltration data usage revealed that the three-term approximate expansion resulted in higher performance and better prediction of hydraulic parameters. [ABSTRACT FROM AUTHOR]

Published
2019
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8. Soil Air Permeability Modeling and Its Use for Predicting Unsaturated Soil Hydraulic Conductivity.

Author

Rahmati, Mehdi and Neyshaboury, Mohammad Reza

Subjects
*PERMEABILITY, *HYDRAULIC conductivity
Abstract

Since the direct measurement of soil hydraulic conductivity [Kw(θ)] is time consuming and difficult, several methods have been suggested for its prediction. However, their application still reθuires some kind of direct or experimental measurement, even after calibration. Considering much easier measurement of the air permeability [Ka(θ)] and the water and air flows in the soil medium, several attempts have been made to link Kw(θ) and Ka(θ), most of which have used Ka(θ) to predict the saturated hydraulic conductivity (Ks). The current research was aimed to model the air permeability and evaluate its application for Kw(θ) prediction. In this regard, laboratory measurements were conducted for Kw(θ) and Ka(θ) at different soil moisture contents (θ). Then, we introduced a semitheoretical model and evaluated it using measured data. Results showed that the proposed model can predict Kw(θ), with an average evaluation error of 3.69% and average R2 of 0.88. Regarding the fast and nondestructive measurement of Ka(θ) compared with Kw(θ), the proposed model seems to be more practical to characterize unsaturated soil hydraulic conductivity and can improve the accuracy and efficiency of Kw(θ) estimation. [ABSTRACT FROM AUTHOR]

Published
2016
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9. Influence of the β parameter of the Haverkamp model on the transient soil water infiltration curve

Author

Borja Latorre, Laurent Lassabatere, Juan J. Jiménez, M.V. López, Ricardo Sorando, Mehdi Rahmati, Rafael Angulo-Jaramillo, Francisco A. Comín, David Moret-Fernández, Ministerio de Economía, Industria y Competitividad (España), Latorre Garcés, Borja, Moret-Fernández, David, Lassabatere, Laurent, Rahmati, Mehdi, López Sánchez, María Victoria, Comín, Francisco A., Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Laboratoire d'Ecologie des Hydrosystèmes Naturels et Anthropisés (LEHNA), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Centre National de la Recherche Scientifique (CNRS), Instituto Pirenaico de Ecologia (IPE), ARAID Researcher, Spanish National Research Council (IPE-CSIC), Instituto Pirenaico de Ecología-CSIC (IPE-CSIC), Consejo Superior de Investigaciones Científicas [Spain] (CSIC), Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Instituto Pirenaico de Ecologia, CSIC (Spanish Research Council), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE), Latorre Garcés, Borja [0000-0002-6720-3326], Moret-Fernández, David [0000-0002-6674-0453], Lassabatere, Laurent [0000-0002-8625-5455], Rahmati, Mehdi [0000-0001-5547-6442], López Sánchez, María Victoria [0000-0003-4113-0381], and Comín, Francisco A. [0000-0003-4328-3023]

Subjects
Sorptivity Hydraulic conductivity Water retention curve Methods, Materials science, Water retention curve, Sorptivity, Hydraulic conductivity, 0208 environmental biotechnology, Soil science, 02 engineering and technology, Methods, Infiltrometer, Simultaneous optimization, Water Science and Technology, 04 agricultural and veterinary sciences, 6. Clean water, 020801 environmental engineering, Infiltration (hydrology), Loam, Soil water, [SDE]Environmental Sciences, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Abstract

28 Pags.- 5 Figs.- 3 Tabls. The definitive version is available at: https://www.sciencedirect.com/science/journal/00221694, Soil water infiltration can be described with the quasi-analytical Haverkamp et al. (1994) equation, defined by the hydraulic conductivity (Ks), sorptivity (S) and the β parameter. Ks and S are commonly estimated from the transient cumulative infiltration curve, using a constant β value. The objective of this work was to study the influence of β on the estimation of Ks and S. The study was first performed on synthetic 1-D infiltration curves generated at different infiltration times for loam sandy, loamy and silty soils, and next extrapolated to a 3-D loam synthetic soil and on 10 infiltrations curves measured on the field with a disc infiltrometer on different types of soils. The infiltration measurements lasted between 600 and 900 s. The results showed that, while early infiltration times (i.e. 100 s) promoted good estimations for S, longer infiltrations (i.e. 1.000 s) were required to estimate accurately Ks. Only very long infiltration (i.e. 10.000 s) allowed defining the actual β value. A similar behaviour was observed for the 3-D infiltration measurements. Except for β, significant relationships (R2 = 0.99) were obtained between the Ks and S of the three theoretical soils and the corresponding values calculated by optimizing the three hydraulic parameters on 2.000 s 1-D infiltration curves. The large confidence interval observed in β (between 0.3 and 2.0) resulted from the fact that β had a small effect on the infiltration curve. A significant relationship (R2 = 0.99) was also obtained between the Ks and S optimized from the experimental curves using a β = 1.1 and the corresponding values obtained by simultaneous optimization of the three hydraulic parameters. These results demonstrated that S and Ks can be accurately estimated using a constant β and that downward infiltration is not an appropriate procedure to estimate β., This research was supported by Ministry of Economy, Industry and Innovation (CGL2014-53017-C2-1-R and CGL2016-80783-R).

Published
2018

10. Development and analysis of the Soil Water Infiltration Global database

Author

M. Rahmati, L. Weihermüller, J. Vanderborght, Y. A. Pachepsky, L. Mao, S. H. Sadeghi, N. Moosavi, H. Kheirfam, C. Montzka, K. Van Looy, B. Toth, Z. Hazbavi, W. Al Yamani, A. A. Albalasmeh, M. Z. Alghzawi, R. Angulo-Jaramillo, A. C. D. Antonino, G. Arampatzis, R. A. Armindo, H. Asadi, Y. Bamutaze, J. Batlle-Aguilar, B. Béchet, F. Becker, G. Blöschl, K. Bohne, I. Braud, C. Castellano, A. Cerdà, M. Chalhoub, R. Cichota, M. Císlerová, B. Clothier, Y. Coquet, W. Cornelis, C. Corradini, A. P. Coutinho, M. B. de Oliveira, J. R. de Macedo, M. F. Durães, H. Emami, I. Eskandari, A. Farajnia, A. Flammini, N. Fodor, M. Gharaibeh, M. H. Ghavimipanah, T. A. Ghezzehei, S. Giertz, E. G. Hatzigiannakis, R. Horn, J. J. Jiménez, D. Jacques, S. D. Keesstra, H. Kelishadi, M. Kiani-Harchegani, M. Kouselou, M. Kumar Jha, L. Lassabatere, X. Li, M. A. Liebig, L. Lichner, M. V. López, D. Machiwal, D. Mallants, M. S. Mallmann, J. D. de Oliveira Marques, M. R. Marshall, J. Mertens, F. Meunier, M. H. Mohammadi, B. P. Mohanty, M. Pulido-Moncada, S. Montenegro, R. Morbidelli, D. Moret-Fernández, A. A. Moosavi, M. R. Mosaddeghi, S. B. Mousavi, H. Mozaffari, K. Nabiollahi, M. R. Neyshabouri, M. V. Ottoni, T. B. Ottoni Filho, M. R. Pahlavan-Rad, A. Panagopoulos, S. Peth, P.-E. Peyneau, T. Picciafuoco, J. Poesen, M. Pulido, D. J. Reinert, S. Reinsch, M. Rezaei, F. P. Roberts, D. Robinson, J. Rodrigo-Comino, O. C. Rotunno Filho, T. Saito, H. Suganuma, C. Saltalippi, R. Sándor, B. Schütt, M. Seeger, N. Sepehrnia, E. Sharifi Moghaddam, M. Shukla, S. Shutaro, R. Sorando, A. A. Stanley, P. Strauss, Z. Su, R. Taghizadeh-Mehrjardi, E. Taguas, W. G. Teixeira, A. R. Vaezi, M. Vafakhah, T. Vogel, I. Vogeler, J. Votrubova, S. Werner, T. Winarski, D. Yilmaz, M. H. Young, S. Zacharias, Y. Zeng, Y. Zhao, H. Zhao, H. Vereecken, Institute of Bio- and Geosciences [Jülich] (IBG), Forschungszentrum Jülich GmbH, Department of Soil Science and Engineering, Faculty of Agriculture, University of Maragheh, ISMC International Soil Modeling Consortium, Institute of Bio and Geosciences Forschungszentrum Jülich, USDA-ARS : Agricultural Research Service, Chinese Academy of Agricultural Sciences (CAAS), Tarbiat Modares University [Tehran], Urmia University, Hungarian Academy of Sciences (MTA), University of Pannonia, UAE University, Jordan University of Science and Technology [Irbid, Jordan], Laboratoire d'Ecologie des Hydrosystèmes Naturels et Anthropisés (LEHNA), Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Centre National de la Recherche Scientifique (CNRS), Centro Acadêmico do Agreste (CAA), Universidade Federal de Pernambuco [Recife] (UFPE), Hellenic Agricultural Organization, Soil and Water Resources Institute, Department of Physics (DFI), Federal University of Lavras (UFLA), University of Tehran, Makerere University (MAK), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Innovative Groundwater Solutions, Interactions et dynamique des environnements de surface (IDES), Université Paris-Sud - Paris 11 (UP11)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay, Eau et Environnement (IFSTTAR/GERS/EE), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-PRES Université Nantes Angers Le Mans (UNAM), Department of Earth Sciences, Institute of Geographical Sciences, Freie Universität Berlin, Centre for Water Resource Systems, Institute of Hydraulic Engineering and Water Resources Management, University of Technology, University of Rostock [Germany], Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Pyrenean Institute of Ecology (CSIC), Universitat de València (UV), Mount Albert Research Station, New Zealand Institute for Plant and Food Research Limited, Czech Technical University in Prague (CTU), The New Zealand Institute for Plant & Food Research (NEW ZEALAND), Institut des Sciences de la Terre d'Orléans - UMR7327 (ISTO), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS), Biogéosystèmes Continentaux - UMR7327, PSL Research University (PSL)-PSL Research University (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Ghent University [Belgium] (UGENT), Department of Civil and Environmental Engineering of the University of Perugia, Italy, Università degli Studi di Perugia (UNIPG), UniRedentor University Center, Embrapa Solos, Ministério da Agricultura, Department of Soil Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Agricultural Research, Education and Extension Organization Maragheh, Dryland Agricultural Research Institute, East Azerbaijan Agricultural and Natural Resources Research and Education center, Scientific Member of Soil and Water Research Department, Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, Centre for Agricultural Research [Budapest] (ATK), Department of Natural Resources and Environment, Faculty of Agriculture, Jordan University of Science and Technology, Department of Watershed Management Engineering, Faculty of Natural Resources, Life and Environmental Sciences, University of California, Geographisches Institut, Rheinische Friedrich-Wilhelms-Universität Bonn, Institute of Plant Nutrition and Soil Science, Christian-Albrechts-Universität zu Kiel (CAU), ARAID Researcher, Spanish National Research Council (IPE-CSIC), Instituto Pirenaico de Ecología-CSIC (IPE-CSIC), Enginereed and Geosystems Analysis Unit, Belgian Nuclear Research Centre, Soil, Water and Land Use Team, Wageningen Environmental Researc, Civil, Surveying and Environmental Engineering, University of Newcastle [Australia] (UoN), Department of Soil Science, College of Agriculture, Isfahan University of Technology, Agricultural and Food Engineering Department, Indian Institute of Technology Kharagpur (IIT Kharagpur), State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Research Soil Scientist, United States Department of Agriculture - Agricultural Research Service, Slovak Academy of Sciences, Slovak Academy of Science [Bratislava] (SAS), Departamento de Suelo y Agua, Consejo Superior de Investigaciones Científicas (CSIC), Pomology Department, Estación Experimental de Aula Dei, Regional Research Station, ICAR-Central Arid Zone Research Institute, CSIRO Land and Water, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Soil Science Graduate Program (ufsm.br/ppgcs), Federal University of Santa Maria, Science and Technology of the Amazonas – IFAM, Federal Institute of Education, Environment Centre Wales, Bangor University, ENGIE, Earth and Life Institute - Environmental Sciences (ELIE), Université Catholique de Louvain (UCL), Department of Environmental Sciences, Urmia Lake Research Institute, Department of Biological and Agricultural Engineering, 2117 TAMU, College Station, Texas A&M University System, Department of Agroecology, Research Centre Foulum, Aarhus University, Shiraz University (Shiraz University ), University of Kurdistan, University of Tabriz, Department of Hydrology, Geological Survey of Brazil (CPRM), Department of Water Resources and Environment, Soil and Water Research Department, Agricultural Research, Education and Extension Organization (AREEO), Sistan Agricultural and Natural Resources Research and Education Center, Department of Soil Science, University of Saskatchewan, Department of Earth and Environmental Sciences [Leuven-Heverlee], Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), GeoEnvironmental Research Group, Faculty of Philosophy and Letters, University of Extremadura, Soil Science Department, University of Panonia, Department of Soil Management, UNESCO Chair on Eremology, Ghent University, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran, Soil and Water Research Institute, Instituto de Geomorfología y Suelos, Department of Geography, Universidad de Málaga [Málaga], Department of Physical Geography, Trier University, Civil Engineering Program, Alberto Luiz Coimbra Institute for Postgraduate Studies and Research in Engineering (COPPE), Federal University of Rio de Janeiro, Faculty of Agriculture, United Graduate School of Agricultural Science, Department of Materials and Life Science, Seikei University, Plant and Environmental Sciences, University of Gothenburg (GU), Rural Development Division, Japan International Research Center for Agricultural Sciences (JIRCAS), RiverLy (UR Riverly), Department of Agricultural and Bio-Resources Engineering, Faculty of Engineering, Ahmadu Bello University Zaria, Federal Agency for Water Management, Institute for land and water management research, Department of Water Resources, ITC Faculty of Geo-Information Science and Earth Observation, Twente University, Faculty of Agriculture and Natural Resources, Ardakan University, Department of Rural Engineering, University of Córdoba, Soil Physics, Embrapa Soils, Department of Soil Science, Agriculture Faculty, University of Zanja, Faculty of Civil Engineering, Department of Geography, Escuela Militar de Ingeniería (EMI), Engineering Faculty, Civil Engineering Department, Munzur University, Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, University Station, University of Texas at Austin [Austin], Monitoring and Exploration Technologies, Helmholtz Centre for Environmental Research (UFZ), College of Resources and Environmental Engineering, Ludong University, ANR-11-BS56-0027,FLOODSCALE,Observation et modélisation multi-échelles pour la compréhension et la simulation des crues éclair(2011), ANR-07-VULN-0001,AVUPUR,Assessing the Vulnerability of Peri-Urban-Rivers.(2007), MEHDI RAHMATI, University of Maragheh, Maragheh, Iran/Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany, LUTZ WEIHERMÜLLER, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany, SEYED HAMIDREZA SADEGHI, Tarbiat Modares University, Iran, LILI MAO, Chinese Academy of Agricultural Sciences, Beijing, YAKOV A. PACHEPSKY, USDA-ARS Environmental Microbial and Food Safety Laboratory, Beltsville, MD, JAN VANDERBORGHT, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany, NILOOFAR MOOSAVI, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany, HOSSEIN KHEIRFAM, Urmia University, Urmia, Iran, CARSTEN MONTZKA, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany, KRIS VAN LOOY, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany, ZEINAB HAZBAVI, Tarbiat Modares University, Iran, BRIGITTA TOTH, Hungarian Academy of Sciences, Budapest, Hungary/University of Pannonia, Keszthely, Hungary, WAFA AL YAMANI, Environment Agency, Abu Dhabi, UAE, AMMAR A. ALBALASMEH, Jordan University of Science and Technology, RAFAEL ANGULO-JARAMILLO, Univ Lyon, Université Claude Bernard Lyon, ANTÔNIO CELSO DANTAS ANTONINO, UFPE, GEORGE ARAMPATZIS, Hellenic Agricultural Organization, Soil and Water Resources Institute, Greece, ROBSON ANDRÉ ARMINDO, UFLA, HOSSEIN ASADI, University of Tehran, Karaj, Iran, YAZIDHI BAMUTAZE, Makerere University, Kampala, Uganda, JORDI BATLLE-AGUILAR, INRA, AgroParisTech Thiverval-Grignon, France/IDES CNRS/Université Paris-Sud, Orsay CEDEX/Innovative Groundwater Solutions (IGS), South Australia, Australia, BÉATRICE BÉCHET, IFSTTAR, GERS, France, MA'IN Z. ALGHZAWI, Jordan University of Science and Technology, FABIAN BECKER, Freie Universität Berlin, BRENT CLOTHIER, Plant and Food Research, Palmerston North, New Zealand, WIM CORNELIS, Ghent University, Ghent, Belgium, CORRADO CORRADINI, University of Perugia, Perugia, Italy, ARTUR PAIVA COUTINHO, UFPE, MURIEL BASTISTA DE OLIVEIRA, UniRedentor, Itaperuna, JOSE RONALDO DE MACEDO, CNPS, MATHEUS FONSECA DURÃES, UFLA, NÁNDOR FODOR, Agricultural Institute, Centre for Agricultural Research, Hungarian Academy of Sciences, GÜNTER BLÖSCHL, Centre for Water Resource Systems, TU Wien, Karlsplatz/Institute of Hydraulic Engineering and Water Resources Management, ALESSIA FLAMMINI, Ghent University, Ghent, Belgium, ASGHAR FARAJNIA, East Azerbaijan Agricultural and Natural Resources Research and Education Center, Iran, IRAJ ESKANDARI, Dryland Agricultural Research Institute, Agricultural Research, Education and Extension Organization Maragheh, East Azerbaijan, Iran, HOJAT EMAMI, Ferdowsi University of Mashhad, Mashhad, Iran, KLAUS BOHNE, University of Rostock, Germany, ISABELLE BRAUD, Irstea, UE RiverLy, Lyon-Villeurbanne Center, France, CLARA CASTELLANO, Pyrenean Institute of Ecology-CSIC, ARTEMI CERDÀ, University of Valencia, Spain, MAHA CHALHOUB, INRA AgroParisTech Functional Ecology and Ecotoxicology of Agroecosystems, ROGERIO CICHOTA, Plant and Food Research, Mount Albert Research Station, Auckland, New Zealand, MILENA CÍSLEROVÁ, Czech Technical University in Prague, Faculty of Civil Engineering, YVES COQUET, INRA AgroParisTech Functional Ecology and Ecotoxicology of Agroecosystems/Université d'Orléans, CNRS, Orléans, France, HAMID KELISHADI, Isfahan University of Technology, Iran, RAINER HORN, Christian-Albrechts-Universität zu Kiel, Germany, EVANGELOS G. HATZIGIANNAKIS, Hellenic Agricultural Organization, Soil and Water Resources Institute, Greece, SIMONE GIERTZ, Universität Bonn, Bonn, Germany, TEAMRAT A. GHEZZEHEI, University of California, Merced, USA, MOHAMAD HOSSEIN GHAVIMIPANAH, Tarbiat Modares University, Iran, MAMOUN GHARAIBEH, Jordan University of Science and Technology, JUAN JOSÉ JIMÉNEZ, ARAID Researcher, Instituto Pirenaico de Ecología, Spanish National Research Council, SASKIA DEBORAH KEESSTRA, Soil, Water and Land Use Team, Wageningen Environmental Research/the University of Newcastle, Australia, DIEDERIK JACQUES, Enginereed and Geosystems Analysis Unit, Belgian Nuclear Research Centre, Mol, Belgium, MAHBOOBEH KIANI-HARCHEGANI, Faculty of Natural Resources, Tarbiat Modares University, Iran, MEHDI KOUSELOU, Faculty of Agriculture, University of Maragheh, Maragheh, Iran, MADAN KUMAR JHA, Indian Institute of Technology Kharagpur, India, LAURENT LASSABATERE, Univ Lyon, Université Claude Bernard Lyon 1, CNRS, ENTPE, Vaulx-en-Velin, France, XIAOYAN LI, Beijing Normal University, Beijing, China, MARK A. LIEBIG, USDA Agricultural Research Service, Mandan, ND, USA, DENIZ YILMAZ, Munzur University, Tunceli, Turkey, MICHAEL H. YOUNG, University of Texas at Austin, University Station, USA, HONG ZHAO, University of Twente, Enschede, the Netherlands, HARRY VEREECKEN, Forschungszentrum Jülich GmbH, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany/ISMC International Soil Modeling Consortium, Institute of Bio and Geosciences Forschungszentrum, Germany., MARÍA VICTORIA LÓPEZ, Departamento de Suelo y Agua, Estación Experimental de Aula Dei (EEAD), Consejo Superior de Investigaciones Científicas, Spain, DEEPESH MACHIWAL, ICAR-Central Arid Zone Research Institute, Regional Research Station, Gujarat, India, DIRK MALLANTS, CSIRO Land and Water, Glen Osmond, South Australia, Australia, MICAEL STOLBEN MALLMANN, UFSM, JEAN DALMO DE OLIVEIRA MARQUES, IFAM, MILES R. MARSHALL, Centre for Ecology & Hydrology, Environment Centre Wales, Deiniol Road, Bangor, UK, JAN MERTENS, ENGIE Research and Technologies, Brussels, Belgium, FÉLICIEN MEUNIER, Université catholique de Louvain, Earth and Life Institute-Environmental Sciences, Louvain-la Neuve, Belgium, MOHAMMAD HOSSEIN MOHAMMADI, University of Tehran, Karaj, Iran, BINAYAK P. MOHANTY, Department of Biological and Agricultural Engineering, Texas A&M Univ., College Station, USA, MANSONIA PULIDO-MONCADA, Aarhus University, Department of Agroecology, Research Centre Foulum, Tjele, Denmark, SUZANA MONTENEGRO, UFPE, RENATO MORBIDELLI, University of Perugia, Perugia, Italy, DAVID MORET-FERNÁNDEZ, Departamento de Suelo y Agua, Estación Experimental de Aula Dei (EEAD), Consejo Superior de Investigaciones Científicas (CSIC), Spain, ALI AKBAR MOOSAVI, Department of Soil Science, College of Agriculture, Shiraz University, Shiraz, Iran, MOHAMMAD REZA MOSADDEGHI, Department of Soil Science, College of Agriculture, Isfahan University of Technology, Iran, SEYED BAHMAN MOUSAVI, Department of Soil Science and Engineering, Faculty of Agriculture, University of Maragheh, Maragheh, Iran, HASAN MOZAFFARI, Department of Soil Science, College of Agriculture, Shiraz University, Shiraz, Iran, KAMAL NABIOLLAHI, Department of Soil Science and Engineering, Faculty of Agriculture, University of Kurdistan, Iran, MOHAMMAD REZA NEYSHABOURI, Department of Soil Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran, MARTA VASCONCELOS OTTONI, CPRM, THEOPHILO BENEDICTO OTTONI FILHO, UFRJ, MOHAMMAD REZA PAHLAVAN-RAD, Soil and Water Research Department, Sistan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Zabol, Iran, ANDREAS PANAGOPOULOS, Hellenic Agricultural Organization, Soil and Water Resources Institute, Greece, STEPHAN PETH, Department of Soil Science, University of Kassel, Germany, PIERRE-EMMANUEL PEYNEAU, IFSTTAR, Bouguenais, France, TOMMASO PICCIAFUOCO, Centre for Water Resource Systems, Vienna, Austria/University of Perugia, Perugia, Italy, JEAN POESEN, Catholic University of Leuven, Geo-Institute, Belgium, MANUEL PULIDO, GeoEnvironmental Research Group, University of Extremadura, Cáceres, Spain, DALVAN JOSÉ REINERT, UFSM, SABINE REINSCH, Centre for Ecology & Hydrology, Environment Centre Wales, UK, MEISAM REZAEI, Department of Soil Management, UNESCO Chair on Eremology, Ghent University, Ghent, Belgium/Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran, FRANCIS PARRY ROBERTS, Centre for Ecology & Hydrology, Environment Centre Wales, UK, DAVID ROBINSON, Centre for Ecology & Hydrology, Environment Centre Wales, Deiniol Road, UK, JESÚS RODRIGO-COMINO, University of Málaga, Spain/Trier University, Trier, Germany, OTTO CORRÊA ROTUNNO FILHO, UFRJ, TADAOMI SAITO, Faculty of Agriculture, Tottori University, Japan, HIDEKI SUGANUMA, Seikei University, Tokyo, Japan, CARLA SALTALIPPI, Department of Civil and Environmental Engineering, University of Perugia, Perugia, Italy, RENÁTA SÁNDOR, Agricultural Institute, Centre for Agricultural Research, Hungarian Academy of Sciences, Hungary, BRIGITTA SCHÜTT, Freie Universität Berlin, Department of Earth Sciences, Institute of Geographical Sciences, Berlin, Germany, MANUEL SEEGER, Department of Physical Geography, Trier University, Germany, NASROLLAH SEPEHRNIA, Department of Soil Science, College of Agriculture, Isfahan University of Technology, Isfahan, Iran, EHSAN SHARIFI MOGHADDAM, Department of Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modares University, Iran, MANOJ SHUKLA, Plant and Environmental Sciences, New Mexico State University, Las Cruces, New Mexico, USA, SHIRAKI SHUTARO, Japan International Research Center for Agricultural Science, Rural Development Division, Tsukuba, Japan, RICARDO SORANDO, Irstea, UE RiverLy, Lyon-Villeurbanne Center, France, AJAYI ASISHANA STANLEY, Ahmadu Bello University Zaria, Nigeria, PETER STRAUSS, Institute for Land and Water Management Research, Federal Agency for Water Management, Austria, ZHONGBO SU, University of Twente, Enschede, the Netherlands, RUHOLLAH TAGHIZADEH-MEHRJARDI, Ardakan University, Ardakan, Yazd Province, Iran, ENCARNACIÓN TAGUAS, University of Córdoba, Spain, WENCESLAU GERALDES TEIXEIRA, CNPS, ALI REZA VAEZI, University of Zanjan, Zanjan, Iran, MEHDI VAFAKHAH, Tarbiat Modares University, Iran, YING ZHAO, Ludong University, China, YIJIAN ZENG, University of Twente, Enschede, the Netherlands, STEFFEN ZACHARIAS, UFZ Helmholtz Centre for Environment Research, Monitoring and Exploration Technologies, Leipzig, Germany, LUBOMÍR LICHNER, Institute of Hydrology, Slovak Academy of Sciences, Bratislava, Slovakia, TOMAS VOGEL, Czech Technical University in Prague, Faculty of Civil Engineering, Czech Republic, IRIS VOGELER, Plant and Food Research, Mount Albert Research Station, Auckland, New Zealand, JANA VOTRUBOVA, Czech Technical University in Prague, Faculty of Civil Engineering, Czech Republic, STEFFEN WERNER, Department of Geography, Ruhr University Bochum, Germany, THIERRY WINARSKI, Univ Lyon, Université Claude Bernard Lyon 1, CNRS, ENTPE, Vaulx-en-Velin, France, Jülich Research Centre, European Commission, Ministerio de Economía y Competitividad (España), Czech Science Foundation, Slovak Research and Development Agency, Rahmati, Mehdi, López Sánchez, María Victoria, Moret-Fernández, David, Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS), PSL Research University (PSL)-PSL Research University (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Rahmati, Mehdi [0000-0001-5547-6442], López Sánchez, María Victoria [0000-0003-4113-0381], Moret-Fernández, David [0000-0002-6674-0453], Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association, Université Claude Bernard Lyon 1 (UCBL), Hellenic Agricultural Organization Demeter (HAO Demeter), Makerere University [Kampala, Ouganda] (MAK), University of Rostock, Plant & Food Research, Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Universiteit Gent = Ghent University [Belgium] (UGENT), Virginia Polytechnic Institute and State University [Blacksburg], Beijing Normal University (BNU), Slovak Academy of Sciences (SAS), Université Catholique de Louvain = Catholic University of Louvain (UCL), Aarhus University [Aarhus], Universidad de Málaga [Málaga] = University of Málaga [Málaga], Programa de Engenharia Civil (COC/COPPE-UFRJ), Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia (COPPE-UFRJ), Universidade Federal do Rio de Janeiro (UFRJ)-Universidade Federal do Rio de Janeiro (UFRJ), Ahmadu Bello University, Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), College of Resources and Environmental Engineering [Yantai], Department of Water Resources, UT-I-ITC-WCC, and Faculty of Geo-Information Science and Earth Observation

Subjects
Condutividade Hidráulica, [SDV]Life Sciences [q-bio], 0208 environmental biotechnology, 02 engineering and technology, Silt, computer.software_genre, Soil, RING INFILTROMETERS, 900 Geschichte und Geografie::910 Geografie, Reisen::910 Geografie, Reisen, Hydraulic conductivity, ELECTRICAL-CONDUCTIVITY, Agricultural land, ddc:550, Meteorology & Atmospheric Sciences, SATURATED HYDRAULIC CONDUCTIVITY, Geosciences, Multidisciplinary, database, lcsh:Environmental sciences, 2. Zero hunger, lcsh:GE1-350, Database, IN-SITU, lcsh:QE1-996.5, Geology, 04 agricultural and veterinary sciences, PE&RC, Pedo-transfer functions, 6. Clean water, Infiltration (hydrology), HYDROPHYSICAL PARAMETERS, [SDE]Environmental Sciences, Physical Sciences, INFILTRATION GLOBAL DATABASE, Hidrologia, PHYSICAL-PROPERTIES, SANDY SOIL, TENSION INFILTROMETER, Ecology and Environment, Pedotransfer function, PEDOTRANSFER FUNCTIONS, Life Science, SOIL INFILTRATION MEASUREMENTS, Land surface models, Soil Water Infiltration Global database, ANALYSIS OF THE SOIL WATER, Science & Technology, Land use, Infiltration, 15. Life on land, 020801 environmental engineering, Infiltração, lcsh:Geology, Solo, Infiltration, Land surface models, Land use, Pedo-transfer functions, SWIG, Agriculture and Soil Science, Data quality, ITC-ISI-JOURNAL-ARTICLE, Earth and Environmental Sciences, INFILTROMETER MEASUREMENTS, Soil water, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, General Earth and Planetary Sciences, Environmental science, Hydrology, ITC-GOLD, computer
Abstract

27 Pags.- 11 Tabls.- 8 Figs. © Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License., 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 https://doi.org/10.1594/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., First author thanks the International and Scientific Cooperation Office of the University of Maragheh, Iran, as well as the research committee and board members of the university for their assistance in conducting the current work. The financial support received from the Forschungszentrum Jülich GmbH is gratefully acknowledged by the first author. Parts of the database were made available through research work carried out in the framework of LIFE+ projects funded by the EC. The support of the Spanish Ministry of Economy through project CGL2014-53017-C2-1-R is acknowledged. The support of the Czech Science Foundation through project no. 16-05665S is acknowledged. The support of the Slovak Research and Development Agency through project no. APVV-15-0160 is acknowledged.

Published
2018

11. Incorporating machine learning models and remote sensing to assess the spatial distribution of saturated hydraulic conductivity in a light-textured soil.

Author

Rezaei, Meisam, Mousavi, Seyed Rohollah, Rahmani, Asghar, Zeraatpisheh, Mojtaba, Rahmati, Mehdi, Pakparvar, Mojtaba, Jahandideh Mahjenabadi, Vahid Alah, Seuntjens, Piet, and Cornelis, Wim

Subjects
*SOIL permeability, *MACHINE learning, *REMOTE sensing, *SOIL sampling, *HYDRAULIC conductivity, *SPECTRAL reflectance
Abstract

• Saturated soil hydraulic conductivity was predicted reasonably using easily accessible environmental data and limited soil observations. • Random Forest outperformed best, resulting in high-resolution hydraulic conductivity which can be used in the hydrological model at a large scale. • Silt content, Bands 7, 6, 4, 2, NDPI, and NDVI covariates explained most of the soil hydraulic conductivity variations. Saturated soil hydraulic conductivity (K sat) is a key component in hydrogeology and water management. This study aimed at evaluating popular tree-based machine learning algorithms (Random forest (RF), Quantile random forest (QRF), Cubist (Cu), and Decision tree regression (DTr)) to assess the spatial distribution of K sat in a sandy agricultural field. Soil surface reflectance derived from Landsat-8 (OLI/TIRS) (several remotely sensed data including original surface reflectances of spectral bands and 22 remote sensing indices) as well as limited ground measured soil data were used as predictor covariates. Using collected disturbed and undisturbed soil samples, physicochemical properties (K sat , porosity, organic matter, and texture contents) were determined. Based on novel supervised feature selection, covariates including Landsat-8 spectral Band2, Band4, Band6, and Band7, normalized difference pond index (NDPI), normalized difference vegetation index (NDVI), and silt content were identified as the most important factors in K sat prediction. Variable importance analysis showed Band7 and Band6 were explaining 54% of the total K sat variation. The model evaluation, using five statistics cretria, Taylor diagram and the Kruskal–Wallis (KW) test, demonstrates the outperformance of RF being followed by QRF, Cu, and DTr models. Accordingly, the RF method combined with an optimized sampling approach provides the most accurate digital soil K sat map. The uncertainty analysis showed no significant different trend in K sat predictions by applying more dense datasets confirming original-limited data (n = 28) was efficient and sufficient to derive a reliable K sat -map. The developed approach, which can be scaled up at a large scale, seems to be useful in modelling water flow and solute transport for water and nutrient management purposes toward precision agriculture. [ABSTRACT FROM AUTHOR]

Published
2023
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