Mehdi Rahmati
@fz-juelich.de
Forschungszentrum Jülich gmbh
RESEARCH INTERESTS
Ecohydrology, Environmental Data Science, Soil physics, Soil moisture, Soil infiltration
Scopus Publications
Scopus Publications
Jasper A. Vrugt, Jan W. Hopmans, Yifu Gao, Mehdi Rahmati, Jan Vanderborght, and Harry Vereecken
Wiley
AbstractThe two‐term infiltration equation is commonly used to determine the sorptivity, , and product, , of the dimensionless multiple and saturated soil hydraulic conductivity from cumulative vertical infiltration measurements (L) at times (T). This reduced form of the quasi‐analytical power series solution of Richardson's equation of Philip enjoys a solid physical underpinning but at the expense of a limited time validity. Using simulated infiltration data, Jaiswal et al. have shown this time validity to equal about 2.5 cm of cumulative infiltration. The goals of this work are twofold. First, we investigate the extent to which cumulative infiltration measurements larger than 2.5 cm bias the estimates of and . Second, we investigate the impact of epistemic errors on the inferred time validities and parameters. Partial infiltration curves up to 2.5 cm of cumulative vertical infiltration improve substantially the agreement between actual and least squares estimates of and . But this only holds if the data generating infiltration process follows Richardson's equation and experimental conditions satisfy assumptions of soil homogeneity and a uniform initial water content. Otherwise, autocorrelated cumulative infiltration residuals will bias the least squares estimates of and . Our findings reiterate and reinvigorate earlier conclusions of Haverkamp et al. and show that epistemic errors deteriorate the physical significance of the coefficients of infiltration functions. As a result, the parameters of infiltration functions cannot simply be used in storm water and vadose zone flow models to forecast runoff and recharge at field and landscape scales unless these predictions are accompanied by realistic uncertainty bounds. We conclude that the time validity of Philip's two‐term equation is an elusive theoretical quantity with arbitrary physical meaning.
Arash Rahi, Mehdi Rahmati, Jacopo Dari, Carla Saltalippi, Cosimo Brogi, and Renato Morbidelli
Elsevier BV
Mehdi Rahmati, Alexander Graf, Christian Poppe Terán, Wulf Amelung, Wouter Dorigo, Harrie-Jan Hendricks Franssen, Carsten Montzka, Dani Or, Matthias Sprenger, Jan Vanderborght,et al.
Springer Science and Business Media LLC
AbstractDespite previous reports on European growing seasons lengthening due to global warming, evidence shows that this trend has been reversing in the past decade due to increased transpiration needs. To asses this, we used an innovative method along with space-based observations to determine the timing of greening and dormancy and then to determine existing trends of them and causes. Early greening still occurs, albeit at slower rates than before. However, a recent (2011–2020) shift in the timing of dormancy has caused the season length to decrease back to 1980s levels. This shortening of season length is attributed primarily to higher atmospheric water demand in summer that suppresses transpiration even for soil moisture levels as of previous years. Transpiration suppression implies that vegetation is unable to meet the high transpiration needs. Our results have implications for future management of European ecosystems (e.g., net carbon balance and water and energy exchange with atmosphere) in a warmer world.
Mehdi Rahmati and Mehdi Kousehlou
De Gruyter
Michele Amaddii, Giorgio Rosatti, Daniel Zugliani, Lutz Weihermüller, Cosimo Brogi, Mehdi Rahmati, Pier Lorenzo Fantozzi, and Leonardo Disperati
EDP Sciences
The Alpi Apuane (Italy) are located a few kilometres from the coast of the Ligurian Sea, and they are characterized by peak elevations up to two thousand meters above sea level, as well as narrow, deeply incised valleys and steep slopes. Due to these morphoclimatic conditions, heavy rains are frequent, causing floods, landslides, and debris flows, particularly within the Vezza catchment. In this work we applied two different hydrological-hydraulic models to this catchment, focusing on the catastrophic debris flow event of June 19, 1996. Firstly, recent, well-documented rainfall events were used to validate the engineering geological model of the study area, then we began to analyse the rainfall-runoff and debris flow event of 1996 in the Cardoso sub-catchment. As models, we used the FLO-2D and a novel experimental model, developed by some of the authors and based on TRENT2D, in which the dynamic of a debris flow is fully coupled with the rainfall-runoff response of a basin. Preliminary results show how the used approach allowed us to gain some insight into the hydrological behaviour and debris flows formation, erosion, transport, and deposition in the Cardoso sub-catchment.
Diana Hofmann, Björn Thiele, Meike Siebers, Mehdi Rahmati, Vadim Schütz, Seungwoo Jeong, Jiaxin Cui, Laurent Bigler, Federico Held, Bei Wu,et al.
MDPI AG
Toxic breakdown products of young Camelina sativa (L.) Crantz, glucosinolates can eliminate microorganisms in the soil. Since microorganisms are essential for phosphate cycling, only insensitive microorganisms with phosphate-solubilizing activity can improve C. sativa’s phosphate supply. In this study, 33P-labeled phosphate, inductively coupled plasma mass spectrometry and pot experiments unveiled that not only Trichoderma viride and Pseudomonas laurentiana used as phosphate-solubilizing inoculants, but also intrinsic soil microorganisms, including Penicillium aurantiogriseum, and the assemblies of root-colonizing microorganisms solubilized as well phosphate from apatite, trigger off competitive behavior between the organisms. Driving factors in the competitiveness are plant and microbial secondary metabolites, while glucosinolates of Camelina and their breakdown products are regarded as key compounds that inhibit the pathogen P. aurantiogriseum, but also seem to impede root colonization of T. viride. On the other hand, fungal diketopiperazine combined with glucosinolates is fatal to Camelina. The results may contribute to explain the contradictory effects of phosphate-solubilizing microorganisms when used as biofertilizers. Further studies will elucidate impacts of released secondary metabolites on coexisting microorganisms and plants under different environmental conditions.
Mehdi Rahmati, Dani Or, Wulf Amelung, Sara L. Bauke, Roland Bol, Harrie-Jan Hendricks Franssen, Carsten Montzka, Jan Vanderborght, and Harry Vereecken
Springer Science and Business Media LLC
D. Yilmaz, L. Lassabatere, D. Moret‐Fernandez, M. Rahmati, R. Angulo‐Jaramillo, and B. Latorre
Wiley
Estimating of soil sorptivity ( S ) and saturated hydraulic conductivity ( Ks ) parameters by field infiltration tests are widespread due to the ease of the experimental protocol and data treatment. The analytical equation proposed by Haverkamp et al. (1994) allows the modelling 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 new approach considers the long‐time expansions of the Haverkamp model, the exact soil properties such as S , Ks 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‐3D 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 Ks 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.
Meisam Rezaei, Seyed Rohollah Mousavi, Asghar Rahmani, Mojtaba Zeraatpisheh, Mehdi Rahmati, Mojtaba Pakparvar, Vahid Alah Jahandideh Mahjenabadi, Piet Seuntjens, and Wim Cornelis
Elsevier BV
Laurent Lassabatere, Pierre-Emmanuel Peyneau, Deniz Yilmaz, Joseph Pollacco, Jesús Fernández-Gálvez, Borja Latorre, David Moret-Fernández, Simone Di Prima, Mehdi Rahmati, Ryan D. Stewart,et al.
Copernicus GmbH
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.
Mirko Castellini, Simone Di Prima, Ryan Stewart, Marcella Biddoccu, Mehdi Rahmati, and Vincenzo Alagna
MDPI AG
Conserving water resources is a current challenge that will become increasingly urgent in future due to climate change. The arid and semi-arid areas of the globe are expected to be particularly affected by changes in water availability. Consequently, advances in ecohydrology sciences, i.e., the interplay between ecological and hydrological processes, are necessary to enhance the understanding of the critical zone, optimize water resources’ usage in arid and semi-arid areas, and mitigate climate change. This Special Issue (SI) collected 10 original contributions on sustainable land management and the optimization of water resources in fragile environments that are at elevated risk due to climate change. In this context, the topics mainly concern transpiration, evapotranspiration, groundwater recharge, deep percolation, and related issues. The collection of manuscripts presented in this SI represents knowledge of ecohydrology. It is expected that ecohydrology will have increasing applications in the future. Therefore, it is realistic to assume that efforts to increase environmental sustainability and socio-economic development, with water as a central theme, will have a greater chance of success.
Habib Khodaverdiloo, Amir Bahrami, Mehdi Rahmati, Harry Vereecken, Mirhassan Miryaghoubzadeh, and Sally Thompson
Wiley
Soil bulk density (ρb) is an important indicator of soil quality, productivity, compaction and porosity. Despite its importance, ρb is often omitted from global datasets due to the costs of making many direct ρb measurements and the difficulty of direct measurement on rocky, sandy, very dry, or very wet soils. Pedotransfer functions (PTFs) are deployed to address these limitations. Using readily available soil properties, PTFs employ estimator equations to fit existing datasets to estimate properties like ρb. However, PTF performance often declines when applied to soils outside those in the training dataset. Potentially, recalibrating existing PTFs using new observations would leverage the power of large datasets used in the original PTF derivation, while updating information based on new soil observations. Here, we evaluate such a recalibration approach for ρb estimation, benchmarking its performance against two alternatives: the original, uncalibrated PTFs, and novel, local PTFs derived solely from new soil observations. Using a ρb dataset of N = 360 total observations obtained in West Azerbaijan, Iran, we varied the local dataset size (with N = 15, 30, 60, and 360) and recalibrated four existing PTFs with these data. Local PTFs were generated based on stepwise multiple linear regression for the same datasets. The same PTFs (original, recalibrated, and local) were also applied to the study area, and the resulting ρb estimates were compared with the global SoilGrids dataset. Recalibration of PTFs reduced errors relative to the original uncalibrated PTFs; for instance, the NSE increased from −22.07 to 0.30 (uncalibrated) to 0.20–0.41 (recalibrated), and RMSE decreased from 0.12 to 0.60 Mg m−3 (uncalibrated) to 0.10–0.13 Mg m−3 (recalibrated). The recalibrated PTFs performance was comparable to or better than local PTFs applied to the same data. Recalibration of existing PTFs with local/regional uses provides a viable alternative to the use of global datasets or the development of local PTFs in data‐scarce regions.
Mehdi Rahmati, Borja Latorre, David Moret‐Fernández, Laurent Lassabatere, Nima Talebian, Dane Miller, Renato Morbidelli, Massimo Iovino, Vincenzo Bagarello, Mohammad Reza Neyshabouri,et al.
American Geophysical Union (AGU)
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 tgrav=F(β)S2/Ks−Ki2, ${t}_{\\text{grav}}=\\,F(\\beta ){S}^{2}/{\\left({K}_{s}-{K}_{i}\\right)}^{2},$ where F(β) is a β‐dependent function) is about three times larger than the classical tgrav given by tgrav,Philip=S2/Ks−Ki2 $\\,{t}_{\\text{grav},\\text{Philip}}={S}^{2}/{\\left({K}_{s}-{K}_{i}\\right)}^{2}$ . 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.
Parakh Jaiswal, Yifu Gao, Mehdi Rahmati, Jan Vanderborght, Jirka Šimůnek, Harry Vereecken, and Jasper A. Vrugt
Wiley
Many different equations have been proposed to describe quantitatively one‐dimensional soil water infiltration. The unknown coefficients of these equations characterize soil hydraulic properties and may be estimated from a n record, {t∼i,I∼i}i=1n$\\{ {\\tilde t_i},{\\tilde I_i}\\} _{i = 1}^n$ , of cumulative infiltration measurements using curve fitting techniques. The two‐term infiltration equation, I(t)=St+cKst$I(t) = S\\sqrt t + c{K_{\\rm{s}}}t$ , of Philip has been widely used to describe measured infiltration data. This function enjoys a solid mathematical–physical underpinning and admits a closed‐form solution for the soil sorptivity, S [L T−1/2], and multiple, c [−], of the saturated hydraulic conductivity, Ks [L T−1]. However, Philip's two‐term equation has a limited time validity, tvalid [T], and thus cumulative infiltration data, I∼(t∼)$\\tilde I(\\tilde t)$ , beyond t=tvalid$t = {t_{{\\rm{valid}}}}$ will corrupt the estimates of S and Ks. This paper introduces a novel method for estimating S, c, Ks, and tvalid of Philip's two‐term infiltration equation. This method, coined parasite inversion, use as vehicle Parlange's three‐parameter infiltration equation. As prerequisite to our method, we present as secondary contribution an exact, robust and efficient numerical solution of Parlange's infiltration equation. This solution admits Bayesian parameter estimation with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm and yields as byproduct the marginal distribution of Parlange's β parameter. We evaluate our method for 12 USDA soil types using synthetic infiltration data simulated with HYDRUS‐1D. An excellent match is observed between the inferred values of S and Ks and their “true” values known beforehand. Furthermore, our estimates of c and tvalid correlate well with soil texture, corroborate linearity of the c(β)$c({{\\beta}})$ relationship for 0≤t≤tvalid$0 \\le t \\le {t_{{\\rm{valid}}}}$ , and fall within reported ranges. A cumulative vertical infiltration of about 2.5 cm may serve as guideline for the time‐validity of Philip's two‐term infiltration equation.
Laurent Lassabatere, Pierre-Emmanuel Peyneau, Deniz Yilmaz, Joseph Pollacco, Jesús Fernández-Gálvez, Borja Latorre, David Moret-Fernández, Simone Di Prima, Mehdi Rahmati, Ryan D. Stewart,et al.
Copernicus GmbH
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.
Naser Miran, Mir Hassan Rasouli Sadaghiani, Vali Feiziasl, Ebrahim Sepehr, Mehdi Rahmati, and Salman Mirzaee
Springer Science and Business Media LLC
Mehdi Rahmati, Meisam Rezaei, Laurent Lassabatere, Renato Morbidelli, and Harry Vereecken
Wiley
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.
Panah Mohamadi, Abbas Ahmadi, Bakhtiar Fezizadeh, Ali Asghar Jafarzadeh, and Mehdi Rahmati
Springer Science and Business Media LLC
Lutz Weihermüller, Peter Lehmann, Michael Herbst, Mehdi Rahmati, Anne Verhoef, Dani Or, Diederick Jacques, and Harry Vereecken
American Geophysical Union (AGU)
Modeling of the land surface water‐, energy‐, and carbon balance provides insight into the behavior of the Earth System, under current and future conditions. Currently, there exists a substantial variability between model outputs, for a range of model types, whereby differences between model input parameters could be an important reason. For large‐scale land surface, hydrological, and crop models, soil hydraulic properties (SHP) are required as inputs, which are estimated from pedotransfer functions (PTFs). To analyze the functional sensitivity of widely used PTFs, the water fluxes for different scenarios using HYDRUS‐1D were simulated and predictions compared. The results showed that using different PTFs causes substantial variability in predicted fluxes. In addition, an in‐depth analysis of the soil SHPs and derived soil characteristics was performed to analyze why the SHPs estimated from the different PTFs cause the model to behave differently.
Raúl Roberto Poppiel, José Alexandre Melo Demattê, Nícolas Augusto Rosin, Lucas Rabelo Campos, Mahboobeh Tayebi, Benito Roberto Bonfatti, Shamsollah Ayoubi, Samaneh Tajik, Farideh Abbaszadeh Afshar, Azam Jafari,et al.
Geoderma Elsevier BV
David Moret‐Fernández, Borja Latorre, Maria V. López, Yolanda Pueyo, Laurent Lassabatere, Rafael Angulo‐Jaramilo, Mehdi Rahmati, Jaume Tormo, and José M. Nicolau
Wiley
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.
Fereshteh Alizadeh Motaghi, Nikou Hamzehpour, Sara Mola Ali Abasiyan, and Mehdi Rahmati
Elsevier BV
Reza Hassanpour, Davoud Zarehaghi, Mohammad Reza Neyshabouri, Bakhtiar Feizizadeh, and Mehdi Rahmati
SPIE-Intl Soc Optical Eng
Abstract. Optical trapezoid model (OPTRAM) as a method has been proposed to retrieve soil moisture from remote sensing data. It is based on the assumption that a trapezoidal shape would be derived from plotting of vegetation index (VI) versus shortwave-infrared transformed reflectance (STR) data assuming a linear relationship between VI and STR. A literature review and the present study indicate that the relationship between VI and STR under both dry and wet conditions, especially in the wide range of vegetation cover, is nonlinear. Therefore, we modified the OPTRAM model by introducing nonlinear edges to the VI-STR space and then employed the modified OPTRAM (denoted as MOPTRAM) using Sentinel-2 observations to predict surface (θsurf) and root zone (θrz) soil moistures. Soil moisture predicted by MOPTRAM and OPTRAM methods were compared with ground truth volumetric soil moisture data of a maize field. Accuracy of the predictions from the MOPTRAM increased as compared to that from the OPTRAM for both θsurf and θrz with a wide range of vegetation cover. The root-mean-square error and R2 for the θsurf estimates from MOPTRAM were 0.036 cm3 / cm3 and 0.748, respectively, with corresponding figures of 0.047 and 0.692 from OPTRAM, implying greater prediction accuracy for the modified model in the studied area.
Bijan Abadi, Arash Yadollahi, Ahmad Bybordi, and Mehdi Rahmati
Elsevier BV
Bijan Abadi, Arash Yadollahi, Ahmad Bybordi, and Mehdi Rahmati
Elsevier BV