M. H. Zhang, X. Feng, M. Bano, C. Liu, Q. Liu, X. Wang
Soil water content (SWC) estimation is important for many areas including hydrology, agriculture, soil science, and environmental science. Ground penetrating radar (GPR) is a promising geophysical method for SWC estimation. However, at present, most of the studies are based on partial information of GPR, like travel time or amplitude information, to invert the SWC. Full waveform inversion (FWI) can use the information of the entire waveform, which can improve the accuracy of parameter estimation. This study proposes a novel SWC estimation scheme by using the FWI of GPR, optimized by the grey wolf optimizer (GWO) algorithm. The proposed scheme includes a petrophysical relationship to link the SWC with the relative dielectric permittivity, 1D GPR forward modeling, and a GWO optimization algorithm. First, numerical modeling was carried out, and the proposed scheme was applied to both noise‐free and noisy data to verify its applicability. Then, the proposed method was applied to data collected from a field experimental site. These results, derived from both synthetic and real datasets, show that the proposed inversion scheme resulted in a good match between the observed and calculated GPR data. In the numerical modeling, it was observed that the SWC could be inverted accurately, even when noise was present in the data. These demonstrate that the GWO method can be applied for the quantitative interpretation of GPR data. The proposed scheme shows potential for SWC estimation by using GPR full waveform data.
{"title":"Soil water content estimation by using ground penetrating radar data full waveform inversion with grey wolf optimizer algorithm","authors":"M. H. Zhang, X. Feng, M. Bano, C. Liu, Q. Liu, X. Wang","doi":"10.1002/vzj2.20379","DOIUrl":"https://doi.org/10.1002/vzj2.20379","url":null,"abstract":"Soil water content (SWC) estimation is important for many areas including hydrology, agriculture, soil science, and environmental science. Ground penetrating radar (GPR) is a promising geophysical method for SWC estimation. However, at present, most of the studies are based on partial information of GPR, like travel time or amplitude information, to invert the SWC. Full waveform inversion (FWI) can use the information of the entire waveform, which can improve the accuracy of parameter estimation. This study proposes a novel SWC estimation scheme by using the FWI of GPR, optimized by the grey wolf optimizer (GWO) algorithm. The proposed scheme includes a petrophysical relationship to link the SWC with the relative dielectric permittivity, 1D GPR forward modeling, and a GWO optimization algorithm. First, numerical modeling was carried out, and the proposed scheme was applied to both noise‐free and noisy data to verify its applicability. Then, the proposed method was applied to data collected from a field experimental site. These results, derived from both synthetic and real datasets, show that the proposed inversion scheme resulted in a good match between the observed and calculated GPR data. In the numerical modeling, it was observed that the SWC could be inverted accurately, even when noise was present in the data. These demonstrate that the GWO method can be applied for the quantitative interpretation of GPR data. The proposed scheme shows potential for SWC estimation by using GPR full waveform data.","PeriodicalId":23594,"journal":{"name":"Vadose Zone Journal","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ernesto Sanz, Andrés F. Almeida‐Ñaulay, Carlos G. H. Díaz‐Ambrona, Sergio Zubelzu Mínguez, Ana M. Tarquis
Understanding the dynamics of the soil–vegetation–atmosphere (SVA) system, particularly in arid and semiarid regions, remains challenging due to its intricate and interdependent nature. This system creates problems for rangeland administration, such as insurance and risk management. This paper focuses on the complex interactions within the SVA system, particularly on rangeland ecosystems in Spain's semiarid and arid regions. By employing multifractal detrended cross‐correlation analysis (MFCCA), we explore the joint behavior of key variables, including precipitation (PCP), evapotranspiration (ETP), aridity index (Arid. I.), soil water availability (SWA), biomass (Bio), and normalized difference vegetation index (NDVI). Analyzing a 20‐year data series from Madrid and Almeria provinces, we reveal distinct patterns in the studied variables’ persistence, multifractality, and asymmetry. Notably, the differences in the generalized Hurst exponents ((q)) between Madrid and Almeria for SWA with NDVI, SWA with Bio, and NDVI with Bio underscore distinct interactions in these regions. Moreover, multifractal analyses unveil differences in the complexity of joint variables’ behaviors in the two regions. Almeria exhibits higher multifractality across variables, indicating more complex and variable environmental interactions, likely due to its more arid conditions. These findings suggest that Almeria has more sensitivity to changes, requiring adaptive management strategies, while in Madrid, water availability and related variables play a more dominant role in driving vegetation dynamics. These findings shed light through MFCCA on the nuanced dynamics of rangeland ecosystems in semiarid and arid regions, emphasizing the importance of considering complexity‐based approaches to understand the intricate interplay among key variables in the SVA system.
由于土壤-植被-大气（SVA）系统错综复杂且相互依存，因此了解该系统的动态（尤其是在干旱和半干旱地区）仍然具有挑战性。该系统给牧场管理（如保险和风险管理）带来了问题。本文重点研究 SVA 系统内部复杂的相互作用，尤其是西班牙半干旱和干旱地区的牧场生态系统。通过采用多分形去趋势交叉相关分析 (MFCCA)，我们探讨了降水量 (PCP)、蒸散量 (ETP)、干旱指数 (Arid.I.)、土壤水分可用性 (SWA)、生物量 (Bio) 和归一化差异植被指数 (NDVI) 等关键变量的联合行为。通过分析马德里省和阿尔梅里亚省 20 年的数据序列，我们揭示了所研究变量的持续性、多重性和非对称性的独特模式。值得注意的是，马德里和阿尔梅里亚两地在 SWA 与 NDVI、SWA 与 Bio 以及 NDVI 与 Bio 的广义赫斯特指数（(q)）上的差异突出表明了这两个地区不同的相互作用。此外，多分形分析揭示了两个地区联合变量行为复杂性的差异。阿尔梅里亚各变量的多分形程度较高，表明环境相互作用更为复杂多变，这可能是由于该地区更为干旱所致。这些研究结果表明，阿尔梅里亚对变化的敏感度更高，需要采取适应性管理策略，而在马德里，水供应和相关变量在植被动态中起着更主要的驱动作用。这些研究结果通过多变量协同增效模式揭示了半干旱和干旱地区牧场生态系统的微妙动态，强调了考虑基于复杂性的方法以了解 SVA 系统中关键变量之间错综复杂的相互作用的重要性。
{"title":"Joint multiscale dynamics in soil–vegetation–atmosphere systems: Multifractal cross‐correlation analysis of arid and semiarid rangelands","authors":"Ernesto Sanz, Andrés F. Almeida‐Ñaulay, Carlos G. H. Díaz‐Ambrona, Sergio Zubelzu Mínguez, Ana M. Tarquis","doi":"10.1002/vzj2.20374","DOIUrl":"https://doi.org/10.1002/vzj2.20374","url":null,"abstract":"Understanding the dynamics of the soil–vegetation–atmosphere (SVA) system, particularly in arid and semiarid regions, remains challenging due to its intricate and interdependent nature. This system creates problems for rangeland administration, such as insurance and risk management. This paper focuses on the complex interactions within the SVA system, particularly on rangeland ecosystems in Spain's semiarid and arid regions. By employing multifractal detrended cross‐correlation analysis (MFCCA), we explore the joint behavior of key variables, including precipitation (PCP), evapotranspiration (ETP), aridity index (Arid. I.), soil water availability (SWA), biomass (Bio), and normalized difference vegetation index (NDVI). Analyzing a 20‐year data series from Madrid and Almeria provinces, we reveal distinct patterns in the studied variables’ persistence, multifractality, and asymmetry. Notably, the differences in the generalized Hurst exponents ((<jats:italic>q</jats:italic>)) between Madrid and Almeria for SWA with NDVI, SWA with Bio, and NDVI with Bio underscore distinct interactions in these regions. Moreover, multifractal analyses unveil differences in the complexity of joint variables’ behaviors in the two regions. Almeria exhibits higher multifractality across variables, indicating more complex and variable environmental interactions, likely due to its more arid conditions. These findings suggest that Almeria has more sensitivity to changes, requiring adaptive management strategies, while in Madrid, water availability and related variables play a more dominant role in driving vegetation dynamics. These findings shed light through MFCCA on the nuanced dynamics of rangeland ecosystems in semiarid and arid regions, emphasizing the importance of considering complexity‐based approaches to understand the intricate interplay among key variables in the SVA system.","PeriodicalId":23594,"journal":{"name":"Vadose Zone Journal","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Estimates of the van Genuchten (1980, abbreviated as VG) parameters and saturated hydraulic conductivity (Ks) were made for the contiguous United States at a resolution of 100 m and seven soil depths by combining the SoilGrids+ (SG+) soil property maps of Ramcharan et al. with the R3H3 member of the Rosetta3 hierarchical pedotransfer functions (PTFs) of Zhang et al. To this end, we developed multi‐threaded code that significantly speeds up computation (up to a factor 25) depending on the level of parallelism. We verified estimates first by calculating simple summary statistics of estimated basic properties of SG+ with actual measured soil properties for 14,113 pedons in the National Cooperative Soil Survey (NCSS) (2023) labsample database. Next, we computed summary statistics of PTF‐estimated moisture contents for NCSS and SG+ data. The results show estimation errors are dominated by intrinsic errors of the PTF, and that (potentially correctable) systematic errors are present in SG+ soil properties and PTF estimates. The resulting hydraulic property maps contain well over 750 million points for each of the seven layers and show considerable horizontal and depth variation for each VG parameter and Ks, except the VG “n” parameter, which is dominated by values between 1.25 and 1.6. The hydraulic property maps are 99.9% complete, and we demonstrate that plausible profiles and uncertainty information can be generated for virtually each point. The maps are available as two multi‐channel GeoTIFF maps per SG+ layer: one with the five hydraulic parameters and one with the corresponding covariances.
{"title":"Soil hydraulic property maps for the contiguous United States at 100‐m resolution and seven depths: Code design and preliminary results","authors":"Marcel G. Schaap, Yonggen Zhang, Craig Rasmussen","doi":"10.1002/vzj2.20377","DOIUrl":"https://doi.org/10.1002/vzj2.20377","url":null,"abstract":"Estimates of the van Genuchten (1980, abbreviated as VG) parameters and saturated hydraulic conductivity (<jats:italic>K</jats:italic><jats:sub>s</jats:sub>) were made for the contiguous United States at a resolution of 100 m and seven soil depths by combining the SoilGrids+ (SG+) soil property maps of Ramcharan et al. with the R3H3 member of the Rosetta3 hierarchical pedotransfer functions (PTFs) of Zhang et al. To this end, we developed multi‐threaded code that significantly speeds up computation (up to a factor 25) depending on the level of parallelism. We verified estimates first by calculating simple summary statistics of estimated basic properties of SG+ with actual measured soil properties for 14,113 pedons in the National Cooperative Soil Survey (NCSS) (2023) labsample database. Next, we computed summary statistics of PTF‐estimated moisture contents for NCSS and SG+ data. The results show estimation errors are dominated by intrinsic errors of the PTF, and that (potentially correctable) systematic errors are present in SG+ soil properties and PTF estimates. The resulting hydraulic property maps contain well over 750 million points for each of the seven layers and show considerable horizontal and depth variation for each VG parameter and <jats:italic>K</jats:italic><jats:sub>s</jats:sub>, except the VG “<jats:italic>n</jats:italic>” parameter, which is dominated by values between 1.25 and 1.6. The hydraulic property maps are 99.9% complete, and we demonstrate that plausible profiles and uncertainty information can be generated for virtually each point. The maps are available as two multi‐channel GeoTIFF maps per SG+ layer: one with the five hydraulic parameters and one with the corresponding covariances.","PeriodicalId":23594,"journal":{"name":"Vadose Zone Journal","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Information about the spatial distribution of soil hydraulic parameters is necessary for the accurate prediction of soil water flow and the coupled movement of chemicals and heat at the field scale using a process‐based model. Physics‐informed neural networks (PINNs), which can provide physical constraints in deep learning to obtain a mesh‐free solution, can be used to inversely estimate soil hydraulic parameters from less and noisy training data. Previous studies using PINNs have successfully estimated soil hydraulic parameters for homogeneous soil but estimating such parameters of layered soil profiles where the interface depth and the parameters are unknown still has some difficulties. The objective of this study was to develop PINNs to inversely estimate the distribution of soil hydraulic parameters, such as saturated hydraulic conductivity and α and n of the Mualem–van Genuchten model directly within layered soil profiles by predicting changes in the pressure head from training data based on simulation results at given depths during infiltration. The impact of factors affecting PINNs performance, such as the weights assigned to each component of the loss function, time range used in error computations, and number of samples used to assess the physical constraint, was investigated. By assigning a larger weight to the physical constraint and excluding the earlier stage of infiltration in the loss function, the changes in the pressure head and the three soil hydraulic parameter distributions within the layered soil were successfully estimated. The developed PINNs can be further applied to more complex soils and can be improved.
{"title":"Inverse analysis of soil hydraulic parameters of layered soil profiles using physics‐informed neural networks with unsaturated water flow models","authors":"Koki Oikawa, Hirotaka Saito","doi":"10.1002/vzj2.20375","DOIUrl":"https://doi.org/10.1002/vzj2.20375","url":null,"abstract":"Information about the spatial distribution of soil hydraulic parameters is necessary for the accurate prediction of soil water flow and the coupled movement of chemicals and heat at the field scale using a process‐based model. Physics‐informed neural networks (PINNs), which can provide physical constraints in deep learning to obtain a mesh‐free solution, can be used to inversely estimate soil hydraulic parameters from less and noisy training data. Previous studies using PINNs have successfully estimated soil hydraulic parameters for homogeneous soil but estimating such parameters of layered soil profiles where the interface depth and the parameters are unknown still has some difficulties. The objective of this study was to develop PINNs to inversely estimate the distribution of soil hydraulic parameters, such as saturated hydraulic conductivity and <jats:italic>α</jats:italic> and <jats:italic>n</jats:italic> of the Mualem–van Genuchten model directly within layered soil profiles by predicting changes in the pressure head from training data based on simulation results at given depths during infiltration. The impact of factors affecting PINNs performance, such as the weights assigned to each component of the loss function, time range used in error computations, and number of samples used to assess the physical constraint, was investigated. By assigning a larger weight to the physical constraint and excluding the earlier stage of infiltration in the loss function, the changes in the pressure head and the three soil hydraulic parameter distributions within the layered soil were successfully estimated. The developed PINNs can be further applied to more complex soils and can be improved.","PeriodicalId":23594,"journal":{"name":"Vadose Zone Journal","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advancing and receding water contact angles, often denoted as the maximum and minimum apparent water contact angles, are crucial parameters reflecting a soil's water holding capacity. These parameters play an important role in establishing theoretical soil–water characteristic curves (SWCCs) for unsaturated soils. However, pre‐assuming constant advancing and receding contact angles during soil wetting and drying processes may be erroneous due to their close correlations with the water content and void ratio. To address this research gap, systematic laboratory measurements were conducted on a loess with different void ratios and water contents. Apparent water contact angles were acquired using an axisymmetric drop shape analyzer, enabling a comprehensive dataset. Analysis of variance was employed to assess the statistically significant differences between void ratios and water contents. The results reveal a significant increase in the observed water contact angle as the void ratio decreases and a decrease with increasing water content. Although both the void ratio and water content influence the water contact angle, the latter has a more pronounced effect. The relationship between the receding water contact angle and water content/void ratio is observed to be linear. The identification of this linear relationship offers insights into the fitting of the SWCC for loess across varying void ratios. This study serves to enhance theoretical methodologies, particularly in the adaptation of contact angles, thus facilitating the development of more precise SWCC models.
{"title":"Quantitative experimental study on the apparent contact angle of unsaturated loess and its application in soil–water characteristics curve modeling","authors":"Yingpeng Fu, Ling Xu, Hongjian Liao","doi":"10.1002/vzj2.20376","DOIUrl":"https://doi.org/10.1002/vzj2.20376","url":null,"abstract":"Advancing and receding water contact angles, often denoted as the maximum and minimum apparent water contact angles, are crucial parameters reflecting a soil's water holding capacity. These parameters play an important role in establishing theoretical soil–water characteristic curves (SWCCs) for unsaturated soils. However, pre‐assuming constant advancing and receding contact angles during soil wetting and drying processes may be erroneous due to their close correlations with the water content and void ratio. To address this research gap, systematic laboratory measurements were conducted on a loess with different void ratios and water contents. Apparent water contact angles were acquired using an axisymmetric drop shape analyzer, enabling a comprehensive dataset. Analysis of variance was employed to assess the statistically significant differences between void ratios and water contents. The results reveal a significant increase in the observed water contact angle as the void ratio decreases and a decrease with increasing water content. Although both the void ratio and water content influence the water contact angle, the latter has a more pronounced effect. The relationship between the receding water contact angle and water content/void ratio is observed to be linear. The identification of this linear relationship offers insights into the fitting of the SWCC for loess across varying void ratios. This study serves to enhance theoretical methodologies, particularly in the adaptation of contact angles, thus facilitating the development of more precise SWCC models.","PeriodicalId":23594,"journal":{"name":"Vadose Zone Journal","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Solutions of the linearized Richardson–Richards Equation (RRE) for one‐dimensional soil water flow in layered soils with sinusoidal flux in the frequency domain are derived. We evaluate the accuracy of our analytical and other analytical solutions by comparing them with results from a standard numerical model. Our analytical solution agrees with the numerical solution under multi‐layered heterogeneous soil, while others disagree. We also demonstrate the capability of the proposed solution to simulate soil moisture dynamics under a realistic, multi‐frequency flux case. The procedure described in the paper is valid for any series of arbitrary periodic flux superpositions for layered heterogeneous . Moreover, our solution is efficient in the calculation compared with numerical solutions, especially when dealing with long‐time series soil moisture, which can provide a validation of numerical models.
{"title":"Frequency domain‐based analytical solutions for one‐dimensional soil water flow in layered soils","authors":"Jiong Zhu, Yuanyuan Zha, Tian‐Chyi Jim Yeh","doi":"10.1002/vzj2.20372","DOIUrl":"https://doi.org/10.1002/vzj2.20372","url":null,"abstract":"Solutions of the linearized Richardson–Richards Equation (RRE) for one‐dimensional soil water flow in layered soils with sinusoidal flux in the frequency domain are derived. We evaluate the accuracy of our analytical and other analytical solutions by comparing them with results from a standard numerical model. Our analytical solution agrees with the numerical solution under multi‐layered heterogeneous soil, while others disagree. We also demonstrate the capability of the proposed solution to simulate soil moisture dynamics under a realistic, multi‐frequency flux case. The procedure described in the paper is valid for any series of arbitrary periodic flux superpositions for layered heterogeneous . Moreover, our solution is efficient in the calculation compared with numerical solutions, especially when dealing with long‐time series soil moisture, which can provide a validation of numerical models.","PeriodicalId":23594,"journal":{"name":"Vadose Zone Journal","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Asghar Ghorbani, Morteza Sadeghi, Markus Tuller, Wolfgang Durner, Scott B. Jones
The hydrodynamics of variably saturated soils or porous media in general are described via nonlinear functions of water retention and hydraulic conductivity, which facilitate the simulation of various mass and energy transport processes (e.g., water, heat, contaminants, colloids) within the porous medium. We set out to derive improved functions for more accurate estimations of soil hydraulic functions to advance the simulation of porous medium hydrodynamics. A new model is proposed for estimating the unsaturated hydraulic conductivity (UHC) from a soil water retention (SWR) function that is parameterized via nonlinear regression of measured data. The function can be viewed as a generalized van Genuchten (1980) model (GVG). We tested the new SWR and UHC expressions for numerous data sets from literature that cover a wide range of soil textures. Our comparisons reveal more accurate estimations using the GVG model by comparison with the original van Genuchten model.
可变饱和土壤或一般多孔介质的流体力学是通过保水性和导水率的非线性函数来描述的，这有助于模拟多孔介质中的各种质量和能量传输过程（如水、热、污染物、胶体）。我们着手推导改进的函数，以便更准确地估算土壤水力函数，从而推动多孔介质流体力学的模拟。我们提出了一个新模型，用于根据土壤水分滞留（SWR）函数估算非饱和水力传导率（UHC），该函数通过对测量数据的非线性回归进行参数化。该函数可视为广义的 van Genuchten（1980 年）模型（GVG）。我们对文献中的大量数据集测试了新的 SWR 和 UHC 表达式，这些数据集涵盖了广泛的土壤质地。比较结果表明，使用 GVG 模型与原始范-格努赫腾模型相比，估算结果更为准确。
{"title":"A generalized van Genuchten model for unsaturated soil hydraulic conductivity","authors":"Asghar Ghorbani, Morteza Sadeghi, Markus Tuller, Wolfgang Durner, Scott B. Jones","doi":"10.1002/vzj2.20369","DOIUrl":"https://doi.org/10.1002/vzj2.20369","url":null,"abstract":"The hydrodynamics of variably saturated soils or porous media in general are described via nonlinear functions of water retention and hydraulic conductivity, which facilitate the simulation of various mass and energy transport processes (e.g., water, heat, contaminants, colloids) within the porous medium. We set out to derive improved functions for more accurate estimations of soil hydraulic functions to advance the simulation of porous medium hydrodynamics. A new model is proposed for estimating the unsaturated hydraulic conductivity (UHC) from a soil water retention (SWR) function that is parameterized via nonlinear regression of measured data. The function can be viewed as a generalized van Genuchten (1980) model (GVG). We tested the new SWR and UHC expressions for numerous data sets from literature that cover a wide range of soil textures. Our comparisons reveal more accurate estimations using the GVG model by comparison with the original van Genuchten model.","PeriodicalId":23594,"journal":{"name":"Vadose Zone Journal","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jana Schneider, Stefanie Kiemle, K. Heck, Y. Rothfuss, I. Braud, Rainer Helmig, J. Vanderborght
Stable water isotopologs can add valuable information to the understanding of evaporation processes. The identification of the evaporation front from isotopolog concentration depth profiles under very dry soil conditions is of particular interest. We compared two different models that describe isotopolog transport in a drying unsaturated porous medium: SiSPAT‐Isotope and DuMux. In DuMux, the medium can dry out completely whereas in SiSPAT‐Isotope, drying is limited to the residual water saturation. We evaluated the impact of residual water saturation on simulated isotopic concentration. For a low residual water saturation, both models simulated similar isotopolog concentrations. For high residual water saturation, SiSPAT‐Isotope simulated considerably lower concentrations than DuMux. This is attributed to the buffering of changes in isotopolog concentrations by the residual water in SiSPAT‐Isotope and an additional enrichment due to evaporation of residual water in DuMux. Additionally, we present a comparison between high‐frequency experimental data and model simulations. We found that diffusive transport processes in the laminar boundary layer and in the dried‐out surface soil layer need to be represented correctly to reproduce the observed downward movement of the evaporation front and the associated peak of isotopolog enrichment. Artificially increasing the boundary layer thickness to reproduce a decrease in evaporation rate leads to incorrect simulation of the location of the evaporation front and isotopolog concentration profile.
{"title":"Analysis of experimental and simulation data of evaporation‐driven isotopic fractionation in unsaturated porous media","authors":"Jana Schneider, Stefanie Kiemle, K. Heck, Y. Rothfuss, I. Braud, Rainer Helmig, J. Vanderborght","doi":"10.1002/vzj2.20363","DOIUrl":"https://doi.org/10.1002/vzj2.20363","url":null,"abstract":"Stable water isotopologs can add valuable information to the understanding of evaporation processes. The identification of the evaporation front from isotopolog concentration depth profiles under very dry soil conditions is of particular interest. We compared two different models that describe isotopolog transport in a drying unsaturated porous medium: SiSPAT‐Isotope and DuMux. In DuMux, the medium can dry out completely whereas in SiSPAT‐Isotope, drying is limited to the residual water saturation. We evaluated the impact of residual water saturation on simulated isotopic concentration. For a low residual water saturation, both models simulated similar isotopolog concentrations. For high residual water saturation, SiSPAT‐Isotope simulated considerably lower concentrations than DuMux. This is attributed to the buffering of changes in isotopolog concentrations by the residual water in SiSPAT‐Isotope and an additional enrichment due to evaporation of residual water in DuMux. Additionally, we present a comparison between high‐frequency experimental data and model simulations. We found that diffusive transport processes in the laminar boundary layer and in the dried‐out surface soil layer need to be represented correctly to reproduce the observed downward movement of the evaporation front and the associated peak of isotopolog enrichment. Artificially increasing the boundary layer thickness to reproduce a decrease in evaporation rate leads to incorrect simulation of the location of the evaporation front and isotopolog concentration profile.","PeriodicalId":23594,"journal":{"name":"Vadose Zone Journal","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141648962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Special Issue: Tribute to Rien van Genuchten, recipient of the 2023 Wolf Prize for Agriculture","authors":"Jan W. Hopmans, Jiří Šimůnek, Binayak P. Mohanty","doi":"10.1002/vzj2.20327","DOIUrl":"https://doi.org/10.1002/vzj2.20327","url":null,"abstract":"","PeriodicalId":23594,"journal":{"name":"Vadose Zone Journal","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141719937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Thanks to Reviewers, Vadose Zone Journal, 2023","authors":"","doi":"10.1002/vzj2.20370","DOIUrl":"https://doi.org/10.1002/vzj2.20370","url":null,"abstract":"","PeriodicalId":23594,"journal":{"name":"Vadose Zone Journal","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141613063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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