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Measurement and modeling of soil processes in different scales

Water, energy, and solute transport in the vadose zone occur in a variety of scales. How the processes occurring at the small scale control and constrain the large scale responses is a long-standing challenge in vadose zone hydrology. Description of several processes such as evaporation, infiltration, soil-root-water interactions as well as soil characteristics such as conductivity and mechanical impedance rely on small scale measurement which are used to model processes occurring at scales much larger than the measurement scales. The utilization of advanced experimental and modelling tools are required to close the hierarchical gap present in different scales. Within this context, the focus of this session is on measurement or modeling approaches to parametrize or conceptualize soil physical, thermal, hydraulic, and mechanical properties across different spatial and temporal scales and resolutions from the size of a pore to the sample or field scale. We invite contributions related to:
- Measuring soil physical and chemical properties in the lab, field, or watershed utilizing a variety of tools ranging from micro-scale imaging to local measurement by soil sensors, drowns, radars, remote sensing, etc.
- Analytical, empirical, statistical, or numerical modeling approaches that link soil processes across scales, upscaling and downscaling experiences to tackle heterogeneity challenges for the description of vadose zone processes such as evaporation, infiltration, land-atmosphere interactions, and subsurface mass and energy fluxes.
- Modeling or measurement campaigns concerning the spatiotemporal changes of vadose zone properties at different scales induced naturally or by human activities such as freezing-thawing circles, climate change, heavy agricultural machinery, and agricultural practices.

Convener: Mahyar Naseri | Co-conveners: Paolo Nasta, Nima Shokri, Martine van der Ploeg, Wolfgang Durner
| Mon, 23 May, 10:20–11:47 (CEST), 13:20–13:59 (CEST)
Room -2.47/48

Mon, 23 May, 10:20–11:50

Chairpersons: Mahyar Naseri, Martine van der Ploeg, Nima Shokri

Introduction- soil measurement, modeling, and impacts

Tobias Karl David Weber and the ISMC Working Group: Pedotransfer functions

Hydro-pedotransfer functions (hyPTF) are used to relate available knowledge about soil properties to soil hydraulic properties and parameters of interest for applications in process models. At least more than four decades have been invested to derive such relationships. However, while models, methods, data storage capacity, and computational efficiency have advanced, there are fundamental issues related to the scope and adequacy of current hyPTFs, particularly when applied to parameterise models at the field scale and beyond. Much of the hyPTF development process has focussed on refining and advancing the methods, while fundamental questions remain largely unanswered, namely i) how should hyPTFs be built (methods) for maximum prediction confidence, ii) which processes/properties need to be predicted to move beyond the van Genuchten-Mualem based parameterisation of the Richards equation, iii) which new datasets and data coverage are needed, iv) how does the measurement process of soil hydraulic properties determine the construction of hyPTFs and at which scale, iv) what is the implication of diverging scales (lab measurements/field to regional scale of application), v) what scaling/modulation/constraining strategies are required to make hyPTF predictions at field-to-regional scale appropriate and physically meaningful, and vi) what is the spatial representativeness? These questions have been addressed in a joint effort by the members of the International Soil Modelling Consortium (ISMC) Pedotransfer Functions Working Group with the aim to systematise hyPTF research and provide a roadmap guiding both scientists and reviewers.

How to cite: Weber, T. K. D. and the ISMC Working Group: Pedotransfer functions: Hydro-pedotransfer functions: A roadmap for future development       , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-757, https://doi.org/10.5194/egusphere-egu22-757, 2022.

Mats Larsbo et al.

Sub-resolution pore space is increasingly being accounted for in Lattice-Boltzmann models of water flow and solute transport. However, robust methods to estimate the permeability and porosity of sub-resolution voxels in 3D X-ray images, which are needed for model parameterization are lacking. The grey-value of a voxel in a 3D X-ray tomography image is approximately proportional to the density. Since the density in a voxel depends on the volume fractions of solids, air and water, and the densities of these phases, a grey-value cannot be directly translated to a porosity value. The objective of this study was to develop a reliable method for 3D estimation of sub-resolution porosity in undisturbed soil samples using data obtained from standard industrial X-ray tomography images. To achieve this we used the differences in X-ray attenuation between samples saturated with water and saturated with a potassium iodide (KI) solution.

We collected ten intact soil cores (5.5 cm high, 6.5 cm diameter) in aluminium cylinders from the topsoil of an arable field in south-west Sweden. The samples had a large variations both in soil texture and organic carbon content. The samples were scanned using X-ray tomography after being slowly saturated with water from the bottom. The water was then replaced by a KI solution (30 g I L-1) with a larger X-ray attenuation than water, and the samples were scanned a second time. The grey-values of the resulting 3D images were scaled by the known densities of air, water and aluminium and the images were registered (i.e. spatially aligned). Macropores, sand grains and gravel were then removed from the images. The difference in attenuation between the two final images was then used to calculate the sub-resolution porosity (i.e. the degree of saturation) in all voxels in the remaining image of the soil matrix. Average porosities for individual samples, which were in the range 0,34­–0.45, were significantly correlated to matrix porosities estimated from soil water retention measurements.

How to cite: Larsbo, M., Fukumasu, J., and Koestel, J.: A method for 3D mapping of sub-resolution porosity from X-ray tomography images, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11106, https://doi.org/10.5194/egusphere-egu22-11106, 2022.

Rong Qu et al.

Soil aggregates fracture through the coalescence of internal macropores (cracks), forming smaller fragments that change pore structure characteristics. Many studies have measured soil aggregate fracture with laboratory tests, but the impact of internal pore structure has remained elusive in the black box of soil.  This study, which is the first of its kind, uses Xray micro-CT imaging, mechanical measurement experiments and finite element simulations to investigate the relationship between soil pore-scale topology and aggregate mechanical properties including fracture energy. The soil aggregates came from a red soil (Acrisols) experimental field in Jiangxi, China that had been amended with different amounts of manure and lime. From Xray micro-CT, quantitative topology analysis extracted the pore network extraction method. Then the strain-stress relationship and fracture energy of the scanned aggregate were measured using a loading frame. The micro-CT images are used as geometry inputs to perform finite element methods to calculate effective Young’s modulus and detailed strain-stress distribution at micrometers. The experimental results showed that adding manure increased the elastic stiffness and fracture energy of the aggregate. The pore scale strain-stress distribution analysis from finite element simulations found these properties at aggregate scale were weakly correlated to bulk porosity but driven by the stress intensity distribution of the aggregates, agreeing with previous research on model soil structures.

How to cite: Qu, R., Zhou, H., and Hallett, P.: Micron-scale mechanical properties of soil aggregates amended with manure: experimental evidence and image-based finite element simulations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12291, https://doi.org/10.5194/egusphere-egu22-12291, 2022.

Agnieszka Szypłowska et al.

Dielectric properties of soil are often utilized for the purpose of soil moisture measurement. However, the relations between soil complex dielectric permittivity and volumetric water content depend also on other factors, such as the operating frequency of the sensor, soil texture, and temperature. The goal of the presented work is to examine the impact of temperature in the 0.5 – 40°C range on the complex dielectric permittivity spectrum of two soils of silt loam and loamy sand textures. The permittivity spectra were measured in a coaxial transmission-line cell system with the use of a Copper Mountain R60 one-port vector-network-analyzer in the frequency range from 20 MHz to 3 GHz. The relations between the real part of dielectric permittivity and soil volumetric water content were modeled at each examined frequency and the temperature dependence of the applied model parameters was determined. In the future research steps, the obtained relations will be applied and tested with the use of a prototype field soil moisture probe operating in a broadband frequency range.


The research has been supported by the Polish National Agency for Academic Exchange under Grant No. PPI/APM/2018/1/00048/U/001. The soil dielectric spectra have been obtained in the scope of the project No. 2014/15/D/ST10/04000 financed by the Polish National Science Centre (NCN).

How to cite: Szypłowska, A., Lewandowski, A., Kafarski, M., Szerement, J., Wilczek, A., Majcher, J., and Skierucha, W.: The influence of temperature on soil complex dielectric permittivity in the 0.02 – 3 GHz frequency range, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4330, https://doi.org/10.5194/egusphere-egu22-4330, 2022.

Michal Snehota et al.

Magnetic resonance imaging (MRI) of the freezing and thawing process was performed on a series of repacked samples of sand, soil, and sand-soil mixture. The freezing/thawing is performed in the sample container placed inside the vertical bore MRI scanner within the 66 mm inner diameter of the radiofrequency coil. The sample container was vacuum insulated from the sides and bottom to allow for the minimum thickness of the insulation layer. The vacuum was constantly maintained by a vacuum pump. The sample assembly was built from PMMA and other nonmetallic - MRI compatible materials. A porous material in the sample container was cooled at the top by the flow of cold gaseous nitrogen released from the liquid nitrogen stored in the Dewar flask. The cooling took place across the glass plate positioned at the top of the sample in the headspace above the sample. The temperature of the gas that was delivered to the headspace and leaving the headspace was monitored. Additionally, the temperature was monitored in the headspace above the glass disk and directly in the glass disk by fiber optics temperature probes. A 4.7 T magnet at the FZJ was used for MRI. Multiple-Slice Spin-Echo and Zero Echo Time pulse sequences were utilized. The contrast between the frozen and unfrozen water is given by the difference in T1 and T2 relaxation times. The time-lapse 3D imaging was done during the entire course of the experiment. Once the freezing front reached the bottom of the sample, the thawing process was induced. The small changes in sand structure as a consequence of volumetric ice-water changes were studied. The spatiotemporal analysis of the freezing front advancement and frozen water volume has been performed. The data are available for the development of two-phase ice-water simulation models.

How to cite: Snehota, M., Koestel, J., Pohlmeier, A., Princ, T., Sobotkova, M., Cislerova, M., and Sklenar, J.: Dynamics of freezing and thawing of water in saturated sand and soil: Magnetic resonance imaging study, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13065, https://doi.org/10.5194/egusphere-egu22-13065, 2022.

Scott B. Jones et al.

Electromagnetic (EM)-based sensors used for water content determination are now being widely used across the globe in research, environmental monitoring networks, weather stations, irrigation management, feed and grain quality control in addition to a host of other applications. The multi-million-dollar EM sensor market continues to expand and yet lacks test standards and is generally lacking in information about sensor quality and performance. Decades of past sensor assessments have presented mixed testing approaches and a commensurate measure of mixed results. Confusion regarding EM sensor-function, -failure rate and -value, stems from testing results that often use non-standard targets including inhomogeneous (variable density and water content) and complex materials (e.g., soils) that may not be widely available for subsequent testing and verification by others. Electromagnetic sensors employ time- or frequency-domain measurements to estimate real (and sometimes including imaginary) permittivity and electrical conductivity, with different sensors measuring at varied and often unknown frequencies. Sensor output is affected by environmental impacts on circuitry (temperature) combined with effects of porous medium temperature, electrical conductivity, interfacial polarization and dielectric relaxation, all of which often combine to alter the apparent permittivity and resulting water content. Although a few attempts have been made to standardize testing, more work and research is required before an international standard can be recognized and adopted. Here we point to standardizing 1) granular porous test media, 2) media packing approaches and 3) permittivity-water content calibration functions with examples and comparison of different EM sensors.  

How to cite: Jones, S. B., Chang, C.-Y., González-Teruel, J. D., Robinson, D. A., Friedman, S. P., Szyplowska, A., and Skierucha, W.: A Framework for Standardizing Electromagnetic Water Content Sensor Assessment using Granular Porous Media, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6597, https://doi.org/10.5194/egusphere-egu22-6597, 2022.

Juan D. González-Teruel et al.

Soil moisture is of major relevance in agricultural and environmental monitoring, having a direct impact in crop growth and yield, and playing an important role in soil conservation and landscape management. Several well-known techniques are widely used to determine soil moisture, but dielectric methods are notable for their automation potential and integration in monitoring and irrigation control systems. Measurement of dielectric properties in moist porous substances, such as soils, has been shown to provide reliable estimation of water content. However, frequency domain dielectric spectroscopy seems to reveal information about other useful physicochemical properties of soils. Dielectric spectroscopy measurements are normally restricted to laboratory setups and limited for low budgets due to the high cost, bulk and weight of the equipment. We evaluated the performance of a low-cost, handheld, open-source VNA (Vector Network Analyzer) for the measurement of the complex permittivity of soils in the 1 MHz to 900 MHz frequency range. The tested device was compared with a commercial model using a low-cost, self-manufactured, open-ended coaxial probe to measure the broadband dielectric properties of organic liquids. An empirical method based on known dielectric properties of standard fluids was used to calibrate the probe. The tested low-cost VNA paired with the experimental probe was found to provide accurate and reliable measurements of the broadband complex permittivity from 50 to 700 MHz. The broadband complex permittivity of mineral soils of varied textures was obtained for a range of bulk densities and water contents from dry to water-saturated conditions.

How to cite: González-Teruel, J. D., Jones, S. B., Robinson, D. A., Giménez-Gallego, J., Zornoza, R., and Torres-Sánchez, R.: Assessment of a low-cost Handheld Vector Network Analyzer to Measure the Broadband Complex Permittivity of Soils, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2914, https://doi.org/10.5194/egusphere-egu22-2914, 2022.

Andrzej Wilczek et al.

The study of water transport in the vadose zone is difficult to describe because of the variety of phenomena determining changes in soil moisture. A profile probe can be a tool that can help in the analysis of topsoil moisture. However, in order to analyse phenomena at different scales, it is necessary to integrate many probes in one system.

The aim of this work was to develop a solution to collect soil moisture and temperature data and visualise them in a user-friendly way. The use of cloud technologies and the Internet of Things IoT provided easy integration to enable further scaling of similar solutions. The developed solution based on TDR probes and the PTDT profile probe allowed the collection of data for analysis for over a year. Tests indicate that the system can be used to study water transport (dynamic moisture changes) associated with precipitation, evaporation or capillary rise. Additional temperature analysis allows the determination of soil frost depth. The current deepening water deficit and intensifying climate change indicate the need to accelerate work related to the implementation of such soil moisture monitoring systems.

Acknowledgments: The research was supported by the Polish National Agency for Academic Exchange under Grant no. PPI/APM/2018/1/00048/U/001.

How to cite: Wilczek, A., Kafarski, M., Majcher, J., Szypłowska, A., Lewandowski, A., and Skierucha, W.: Validation of profile probe for measurement of soil moisture in an Internet of Things system, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5693, https://doi.org/10.5194/egusphere-egu22-5693, 2022.

Marcin Kafarski et al.

The necessity of saving water is a very important issue in precision agriculture. It requires soil moisture monitoring of very large field areas. Soil moisture maps obtained in real time are very useful for proper and economic irrigation.

The soil moisture sensor market is very large. Sensors differ in accuracy, price, measurement speed, etc. However, typical soil moisture sensors are designed for fixed installation or manual insertion. The aim of this work was to present sensors which have high accuracy, high speed of measurement and high mechanical strength required for field mapping performed by an automated platform, which makes hundreds or thousands measurements at a given field. In addition to the aforementioned properties, the sensors should have a big sensitivity zone, which would minimize the impact of air gaps, stones, roots and soil local heterogeneity on moisture measurement results. The presented results involve the design of the sensors and laboratory verification of their performance.

Acknowledgments: The research was supported by the Polish National Agency for Academic Exchange under Grant no. PPI/APM/2018/1/00048/U/001.

How to cite: Kafarski, M., Jacek, M., Andrzej, W., Agnieszka, S., Arkadiusz, L., and Wojciech, S.: Soil moisture probes for mobile irrigation machines, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8405, https://doi.org/10.5194/egusphere-egu22-8405, 2022.

Leonardo Inforsato et al.

Equations for soil hydraulic properties are used to numerically solve the Richards equation. Uncertainties in the parameters that compose these mathematical models propagate into simulation results and their quantification is important. Parameter fitting is usually done using measured data of conductivity (K), matric potential (h), and/or water content (q). Solvers that use derivatives in the fitting process estimate the parameter uncertainties based on the Hessian matrix and the covariance matrix. This procedure considers the uncertainties of the parameters have a normal distribution, and the precision of the parameter predictions are expressed as standard deviations and correlated by a correlation matrix. This approximation is acceptable when reliable data is available, but it is not true for scenarios with higher uncertainties in the original data. We developed a new method to fit the most commonly used models for the q, h, K relationships with a sigmoidal function for the q – h retention function. To approach the parameter uncertainty distribution to a normal distribution, a transformation is applied to the parameters and bootstrapping is used to generate the parameter uncertainty distribution. The transformation shows a better performance according to Shapiro‑Wilk and D'Agostino's test. Another improvement was obtained by using two arbitrary points instead of qs and qr to anchor the retention function. When the two anchoring points are selected within the range of the measured data used for the regression, a lower uncertainty for the fitted parameters resulted. The choice of the anchoring points also impacted the correlation matrix.

How to cite: Inforsato, L., de Jong van Lier, Q., and Durner, W.: A novel fitting procedure for soil hydraulic properties with improved parameter uncertainty assessment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8760, https://doi.org/10.5194/egusphere-egu22-8760, 2022.

Nicolás Riveras Muñoz et al.

Bearing capacity (BC) can explain mechanical soil quality, but its alteration generally comes accompanied by changes in other soil functions. One way to determine BC is by compression tests on undisturbed soil samples, where increasing normal loads are applied at the surface of confined soil core cylinders. Nevertheless, in natural conditions soils are semi-confined, allowing the soil particles to move upward to release the applied forces. Furthermore, in agricultural soils, the loads are primarily dynamic, such as the traffic of machinery or cattle. In this study, we hypothesized that the application of dynamic loads on unconfined soils is more detrimental than static loads, reflected as a decrease in the functionality of two agricultural soils under conventional tillage management. For this purpose, static and dynamic pre-compression tests to determine BC were evaluated in 2 soils, 2 depth levels, and 2 levels of mechanical resistance (8 treatments in total), using semi-confined cylinders, complemented with measurements of saturated hydraulic conductivity (Ks) as an indicator of pore functionality before and after loading. When comparing the dynamic with the static test, it showed no changes in BCwhich was reflected in a homogenization under the studied conditions.. Nevertheless, an increase in Ks from 66 cm h-1 in the initial condition, to 186 cm h-1 in static condition, and 295 cm h-1 in the dynamic test could be shown. The increase in the dynamic test contradicted our initial assumption and could be attributed to cracking of the soils, boosted by the partial confinement of the samples, which allowed sideways movement of the soil against the loads creating zones of preferential flow.

How to cite: Riveras Muñoz, N., Salazar, O., Seitz, S., Scholten, T., and Seguel, O.: The effect of dynamic-unconfined loads on soil bearing capacity and hydraulic conductivity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5548, https://doi.org/10.5194/egusphere-egu22-5548, 2022.

Anna Schneider et al.

Soil physical properties can show high heterogeneity in forest soils, implying a high spatial variability of soil moisture and plant water availability. Legacy effects of past land use, resulting in a small-scale mosaic of anthropogenically modified and unmodified soils in forest areas, further increase this spatial heterogeneity. The soils associated with relict charcoal hearths (RCH), most prominently characterized by a technogenic layer rich in charcoal fragments, are a widespread example for such land use legacy soils in forest areas. 

The objective of our study was to characterize the soil moisture regime of forest soils and RCH soils on sandy substrates in the northeastern German lowlands; and in particular to assess the long-term effect of the prolonged summer drought period in 2018 on spatial and temporal variability of soil moisture. We monitored matric potentials, soil water contents and soil temperature from June 2018 in forest soils in the Tauersche Forst (Brandenburg, Germany). Three soil profiles (one reference forest soil profile and two characteristic RCH soil profiles) were instrumented, sampled for laboratory analyses of bulk density, pore size distribution, saturated hydraulic conductivity, and persistence of water repellency; and root density distribution in the profiles was recorded. 

The soils in all profiles show low porosity and plant available water contents. On RCH soils, overall porosity is clearly higher compared with the reference soils, mainly related to larger volumes of coarse and fine pores. Soil moisture monitoring shows very high spatial and temporal variability of the recorded data after the prolonged dry period in 2018, with gradual rewetting over the winter periods and only short-term fluctuations of soil moisture in reaction to high-intensity precipitation events in the summer periods. The comparison of in-situ and laboratory-based water retention data shows strong hysteresis effects during the rewetting, with increasingly clear reactions of soil water contents to precipitation events over the years following the dry period, especially in the charcoal-rich substrates. The differences in soil moisture between the dry and the wetter periods were clearly higher in the RCH soils, which, compared with the reference soils, showed higher water contents under wet conditions and lower water contents under dry conditions. The results affirm that land use legacies can clearly increase the spatial and temporal variations of soil moisture in forest areas.

How to cite: Schneider, A., Bonhage, A., Raab, A., and Raab, T.: Spatial and temporal variability of soil moisture in land-use legacy forest soils in Brandenburg, Germany, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2182, https://doi.org/10.5194/egusphere-egu22-2182, 2022.

Utibe Utin et al.

Agricultural soil structure can vary markedly over a growing season, whether it be from the slumping of seedbeds in cultivated soils or the action of plants and weather under zero-tillage.  Water retention and transport properties therefore also vary over the growing season, with implications to hydrological processes, crop water availability and ecosystem processes such as carbon cycling. Collecting water retention data is time-consuming and expensive, with most studies relying on one time point.  To overcome this constraint, we explored whether the simpler to obtain measurements of bulk density or macroporosity could predict the temporal dynamics of the soil water retention curve (SWRC) in field soils. Using soil samples compacted in the laboratory, Assouline (2006) developed a model to predict the soil water retention curves of compacted soils using only bulk density of the compacted soil and the parameters of the SWRC of a previous compacted state. In this work, we tested the workability of Assouline (2006) model for field conditions using data obtained from two tillage experiments on contrasting soil textures (loamy sand and clay loam) in the UK. We also developed a new model using macroporosity to predict the temporal dynamics of the SWRC. Data obtained for the sandy loam (SL) soils were for the following tillage treatments:  Zero Tillage (ZT-SL), non-inversion Shallow Tillage (ST-SL), Plough (P-SL) and Compacted (C-L) while those of the clay loam soils were non-inversion Shallow Tillage (ST-CL) and Deep Tillage (DT-CL), and Plough (P-CL) with 9 replications for each treatment. For the sandy loam soils, SWRCs at Timepoint 2 (August - post harvest) were predicted from the parameters of SWRCs at Timepoint 1 (May – 1 month post cultivation). SWRCs predictions for the clay loam soils at Timepoints 2 (August – post harvest) and 3 (September – post cultivation) were achieved using the parameters of Timepoint 1 (April – post winter) while those of Timepoint 3 were obtained with the parameters of Timepoint 2. For the sandy loam soils, very good fits of the SWRC were obtained with either the bulk density or macroposity model. The bulk density model had R2 ranging from 0.907 to 0.950 and RMSE ranging from 0.052 and 0.092.  The macroporosity model performed slightly better, with R2 ranging from 0.914 to 0.953 and RMSE ranging from 0.049 to 0.054.  For the clay loam soil, the bulk density model had R2 ranging from 0.824 to 0.876 and RMSE ranging from 0.105 to 0.077, while the macroporosity model had R2 ranging from 0.821 to 0.881 and RMSE ranging from 0.086 to 0.065. Both models worked better for sandy loam than clay loam soil. The macroporsity based model provided a more accurate prediction than the bulk density model, particularly at predicting time-dependency at the wet end of the SWRC.  This is very early research that will continue to explore whether simple parameters that are practical to collect in the field can aid predictions of the SWRC over time.

How to cite: Utin, U., Hallett, P., Geris, J., and Smith, J.: Can the temporal dynamics of soil water retention on agricultural land be predicted from the simple time-dependent parameters bulk density or macroporosity?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12709, https://doi.org/10.5194/egusphere-egu22-12709, 2022.

Albara Almawazreh et al.

Over the last decades the rapid expansion of the city of Bangalore and the associated population growth led to changes in agricultural management practices, which resulted in an increase in irrigated areas compared to rain-fed areas and enhanced use of mineral fertilizers.

To analyse the long-term impact of this transformation on soil properties and the water cycle, two sets of plot trials (rainfed and irrigated) were established at the University of Agricultural Sciences Bangalore (UASB) GKVK campus. Lablab (Lablab purpureus L. Sweet), finger millet (Eleusine coracana L.Gaertn.) , and maize (Zea mays L.) three crops common to the region were sown and treated with three species-specefic levels of N fertilizer (high, medium, low). A soil moisture network consisting of 216 sensors was installed at the rainfed and irrigated sites at three depths (15, 40 and 70 cm). Soil moisture data has been collected since 2017 and is used to calibrate and validate a 1D Richards-based model HYDRUS-1D. The results of the analysis of variance (ANOVA) of the moisture data indicate significant differences in the water uptake of maize and millet crops in the wet seasons, but smaller differences over dry seasons. The initial modeling results confirm the statisticals findings, with millet plots under higher N treatments having higher water uptake and less evaporation than the low N treatment plots, while the differences in lablab plots are negligable.The modelling will, however, continue over both wet and dry seasons to assess how limited amounts of water would affect the differences between N treatments.

How to cite: Almawazreh, A., Uteau, D., Buerkert, A., and Peth, S.: Modelling effects of land use intensification and soil management practices on field water cycles and water use efficiency in Bangalore, India, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12687, https://doi.org/10.5194/egusphere-egu22-12687, 2022.

Mon, 23 May, 13:20–14:50

Chairpersons: Paolo Nasta, Mahyar Naseri, Wolfgang Durner

Introduction- Towards soil measurement, modeling in larger scales

Quirijn de Jong van Lier et al.

Vadose zone hydrological models employing finite difference numerical solutions of the Richards equation allow simulating the movement and predicting the state of soil water and associated quantities in the vadose zone. Robust algorithms are available to perform such simulations and most numerical issues with these have been solved. Parameters describing the relation between hydraulic conductivity K, pressure head h, and water content θ determine the quality of model output. We performed two case studies, one with maize in the southeast of Brazil (São Paulo State) evaluating a wet-year and a dry-year scenario, and one with soybean in the northeast of Brazil (Maranhão State). Parameters of the Van Genuchten-Mualem (VGM) relations were obtained from laboratory evaporation experiments with undisturbed soil samples. The parameter uncertainty was expressed as standard error and correlations between parameters were expressed in a correlation matrix. A previously developed stochastic framework was used to evaluate the outputs of the SWAP hydrological model according to the uncertainty and correlations in the VGM parameters. Performing runs with 105 stochastic realizations per scenario, we evaluated the predictions of evaporation, transpiration, bottom flux, and runoff and their frequency distribution with respective crops at both locations. Results will be discussed and show that no general conclusion can be drawn about the frequency distributions of soil water balance components as a result of the uncertainty of and correlation between VGM parameters. Skewed or multimodal distributions of output parameters are common, and the most commonly performed prediction using the average VGM parameter values does not always agree to the mean or median of stochastic realizations. Users of hydrological models should be aware of this propagation of uncertainty and correlation into the model outputs. The investigation of the representativeness of average VGM parameters in specific scenarios adds to the interpretation of the predictive power of hydrological models.

How to cite: de Jong van Lier, Q., Dos Santos, A. K. B., and Looms, M. C.: Are average hydraulic parameters representative? A stochastic analysis of water balance components predicted by a hydrological model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2688, https://doi.org/10.5194/egusphere-egu22-2688, 2022.

Nima Shokri et al.

Soil moisture has a direct impact on ecosystem functioning, vegetation and crop production, environmental health and affects the stability of rural communities. Soil moisture plays a crucial role in all aspects of land-atmosphere interactions including extreme events such as heatwaves, droughts and floods. The highly localized and complex nature of soil moisture present a major challenge to its accurate estimation. Notwithstanding recent advances in satellite-based monitoring, the temporal and spatial resolution and shallow observation impede their application to mechanistic modeling and to highly resolved applications. Motivated by the importance of soil moisture on many hydrologic processes, the objective of the present study is to develop a predictive tool capable of describing the relationship between soil moisture and a wide range of climatic and soil related parameters. Within this context, we report a dense in-situ measurement networks that offer valuable ground truthing supplemented by physics informed machine learning (ML) techniques. We conducted a detailed observational campaign covering 100,000 m2 in Falkenberg in Germany by deploying a dense network of sensors to measure soil moisture (at 29 locations), ambient temperature and relative humidity, wind speed, near-surface radiation fluxes and soil temperature. We also determined soil characteristics and important properties (e.g., particle size distribution). We used static and dynamic climatic and soil-related predictors (covariates) for training the ML models to capture the complex relationship between the soil moisture and predictor covariates. Following Hassani et al. [2020], we employ different ML algorithms for model training to evaluate their performance in forecasting soil moisture dynamics in space and time using rigorous cross-validation. This work will shed new lights on the interaction and relationship between soil moisture dynamics and a variety of climatic and soil parameters.



Hassani, A., Azapagic, A., Shokri, N. (2020). Predicting Long-term Dynamics of Soil Salinity and Sodicity on a Global Scale, Proc. Nat. Acad. Sci., 117(52), 33017-33027, doi.org/10.1073/pnas.2013771117

How to cite: Shokri, N., Bakhshian, S., Zarepakzad, N., Nevermann, H., Hohenegger, C., and Or, D.: Predicting regional soil moisture dynamics using machine learning techniques and a dense observational network , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5682, https://doi.org/10.5194/egusphere-egu22-5682, 2022.

Vilim Filipović et al.

Soil degradation processes, such as erosion, has been reported as one of the main concerns in agricultural areas. The resulting erosion-affected soils are characterized by modified soil hydraulic and other properties, strongly affecting the agricultural productivity. The study objective was to identify hydropedological factors controlling soil water dynamics in erosion-affected hillslope vineyard soils and to test uni- and bimodal porosity models. The hydropedological study was conducted at three locations: Jastrebarsko (location I), and Jazbina (II) and (III). The selected sites had same agricultural management practices and similar slope with identified Stagnosol soil type. Soil Hydraulic Properties (SHP) were estimated using Evaporation and WP4C methods on intact soil cores while the soil hydraulic functions were fitted using uni- and bimodal porosity models in HYPROP-FIT software. The study illustrated that erosion-affected soil structural properties governing hillslope hydrology in the arable landscape, in this case, vineyards, were evident and had a significant impact on SHP and, consequently, soil water dynamics. Both unimodal and bimodal soil hydraulic models fitted the data agreeably; although, it can be clearly noticed that the bimodal model performed better in particular cases where data showed non-uniform pore size distributions. HYDRUS-1D simulations showed, in general, that both models provided a similar distribution of flux components between infiltration, surface runoff, and drainage (bottom flux) in most cases. Overall, the differences generated when using the bimodal hydraulic functions can lead to a large discrepancy in water flow quantification. It is evident that the SHP and water dynamics in highly erosion-affected heterogeneous soils with developed structure and pore space (e.g., compacted soil with cracks and biopores) cannot be adequately explained using the unimodal porosity functions or by applying single porosity models. However, the validity of more complex approaches should be further tested, and parametrization should be performed with extra care, as using the non-appropriate model can lead to errors in the water balance.

How to cite: Filipović, V., Defterdarović, J., Krevh, V., Filipović, L., Magdić, I., He, H., Haghverdi, A., and Gerke, H. H.: Soil Hydraulic Properties and Water Flow Estimation Using Uni- and Bimodal Porosity Models in Erosion-Affected Hillslope , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8062, https://doi.org/10.5194/egusphere-egu22-8062, 2022.

Annelie Ehrhardt et al.

Preferential and lateral subsurface flow may be responsible for the accelerated transport of water and solutes in sloping agricultural landscapes; however, the process is difficult to observe. One idea is to compare time series of soil moisture observations in the field with those in lysimeters, where flow is vertically oriented. This study aims at identifying periods of deviations in soil water contents and pressure heads measured in the field and in a weighing lysimeter with the same soil profile. Wavelet Coherency Analysis (WCA) was applied to time series of hourly soil water content and pressure head data (15, 32, 60, 80, and 140 cm depths) from Colluvic Regosol soil profiles in summer 2017. The phase shifts and periodicities indicated by the WCA plots reflected the response times to rain events in the same depth of lysimeter and field soil. For many rain events and depths, sensors installed in the field soil showed a faster response than those in the lysimeters soil. This could be explained by either vertical preferential flow or lateral subsurface flow from upper hillslope positions. Vice versa, a faster sensor response in the lysimeter soil could be indicative for vertical preferential effects. The WCA plots comprise all temporal patterns of time shifts and correlations between larger data time series’ in a condensed form to identify potentially relevant periods for more detailed analyses of subsurface flow dynamics.

How to cite: Ehrhardt, A., Groh, J., and Gerke, H. H.: Wavelet Analysis of Soil Water State Variables for Identification of Lateral Subsurface Flow: Lysimeter versus Field Data , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2256, https://doi.org/10.5194/egusphere-egu22-2256, 2022.

Julian Krause and Birgit Terhorst

The study is part of the European Development Fund-Project “BigData@Geo - Advanced Environmental Technology Using AI in the Web” which aims to develop a high-resolution regional earth system model for the region of Lower Franconia. The present work provides ground-truth data in order to calibrate the modelling approaches with the regional climate model REMO and the regional soil moisture model WaSiM-ETH.

Lower Franconia belongs to those regions in Germany which are expected to be strongly affected by climate change. Regional climate models show that average temperatures will rise and dry periods as well as extreme precipitation events occur more frequently. However, the consequences of changing climate conditions on soils, landscapes as well as on land use are not sufficiently known for Lower Franconia.

Yields of forestry and agriculture depend very much on the availability of soil water. During the growing season the water retention capacity of soils is therefore highly relevant. Up to present, datasets as well as modelling results of future scenarios on soil moisture are only scarcely available on local as well as on regional scale. In order to generate future scenarios, calculation of the soil moisture regime forms the base in order to evaluate present day conditions as well as to develop prognostic studies. As we intend to obtain most realistic parameters, generation of real-time soil moisture data with high temporal resolution at selected sites is crucial. Our monitoring sites are characteristic for Lower Franconia and serve to calibrate regions for modelling approaches.

In order to obtain data on dynamics and causes of soil moisture fluctuations as well as to understand process flows, soil geographical surveys form an essential component of our research design for selected sites related to the monitoring stations. Furthermore, relevant sedimentological and pedological parameters such as grain size distribution, permeability, and bulk density are analyzed in the laboratory. Thus, our representative test sites combine detailed ground-truth data with soil moisture and thus, form consecutive modules as parts of soil moisture models. These modules drive and control the modelling procedures of the sub-projects and they further serve for assessments and calibration of the area-wide hydrological and climate modelling in the “BigData@Geo” ERDF-project.

Based on our data we can provide qualitative soil moisture information to the public, such as precipitation and infiltration thresholds and seasonal patterns. Combined with the real-time availability of the monitoring data via our online platform “Klimaatlas Unterfranken”, we provide valuable information for the shareholders decision making process – regarding for instance plant health, risk assessment during extreme weather events or adapting their businesses to the future climate and soil moisture conditions.

How to cite: Krause, J. and Terhorst, B.: Monitoring and Modelling of Soil Moisture at Characteristic Sites in Lower Franconia (Germany), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2621, https://doi.org/10.5194/egusphere-egu22-2621, 2022.

Robert Mietrach and Thomas Wöhling

Efficient 1.5-D hillslope model using 1D Richards' and 1D Boussinesq equations coupled by the Method Of Lines


Robert Mietrach, Thomas Wöhling




Modeling lateral subsurface flow at the hill slope scale by considering the full 2D or 3D spacial domain can be quite complex from a computational point of view. To reduce simulation times a new prototype model consisting of a set of 1D Richards' equations linked with the Boussinesq equation is presented.


The Method Of Lines approach to solving the Richards' equation has already been shown to be an efficient and stable alternative to established solution methods, such as low-order finite difference and finite element methods applied to the mixed form of Richards' equation. Besides its beneficial properties in numerical challenging scenarios, the Method Of Lines approach allows for easier integration of additional differential equations which proves advantageous here, when integrating the Boussinesq equation into the combined model. In the combined model it is assumed that lateral flow primarily happens at soil layer interfaces. The Boussinesq equation is than used to link the 1D columns at these soil layer interface nodes in the lateral direction. Thus enabling water transport between adjacent columns and therefor along the hillslope. In an analog procedure it would be possible to extend the presented model to also simulate for surface runoff.


Simulations for several synthetic setups have been carried out and compared to solutions to the full 2D problem from the software Hydrus. The results show good agreement between the two approaches, with the benefit of reduced simulation times and increased numerical stability of the presented model.

How to cite: Mietrach, R. and Wöhling, T.: Efficient 1.5-D hillslope model using 1D Richards' and 1D Boussinesq equations coupled by the Method Of Lines, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10017, https://doi.org/10.5194/egusphere-egu22-10017, 2022.