Displays

The land surface is inextricably linked to the atmospheric circulation as it dictates the location and strength of land surface-atmosphere (LA) coupling mechanisms. In this context, soil hydraulic properties are critical to estimate sub-surface processes and fluxes at the surface.  In most numerical weather and climate models, those properties are assigned through maps of soil texture complemented with look-up tables.  Then, the hydraulic properties are used in a large variety of process parameterizations within the models.  In this study, we investigate the sensitivity of the simulated regional climate to changes in the prescribed soil maps in the WRF/CLM4 modeling suite.  Comparison of two widely used soil texture databases, the USGS State Soil Geographic Database (STATSGO) and Beijing Normal University’s soil texture database (GSDE), over the United States and Central America reveals that only 32% of soil texture classifications are in common. Further, the differences are not random but tend to depict small-to-large spatial patterns with a preponderance of either finer or coarser grains. Over North America, the US Great Plains have finer grains in GSDE than in STATSGO, while the opposite is true over Central Mexico.

Seasonal simulations were carried out to assess the changes in the soil-water system that result from changing the soil types (GSDE vs. STATSGO) and their corresponding hydraulic properties. Wherever GSDE has finer grains than STATSGO (e.g., over the US Great Plains), the soil will retain water more strongly as evidenced by smaller latent heat fluxes and larger sensible heat flux. On the other hand, areas of coarser grains in GSDE (e.g., over central Mexico) exhibit an increase in latent heat fluxes and a corresponding decrease in sensible heat flux. Regions with an increase/decrease in latent heat flux have a corresponding increase/decrease in the 2-m moisture content. Similar relations are obtained between sensible heat flux and 2-m temperature. These changes also affect the atmospheric column, which responds with an increase/decrease of temperature and height of the planetary boundary layer. Changes in the vertical structure induce changes in the vertical instability and winds. Interestingly, the chain of modifications resulting from soil texture changes impact the moisture fluxes, and more generally, the atmospheric water budget.

How to cite: Berbery, E. H. and Dennis, E.: The Role of Soil Properties on Regional Climate Simulations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11696, https://doi.org/10.5194/egusphere-egu2020-11696, 2020.

Water transport at the land surface and in the soil – the critical zone - is highly dependent on the soil hydraulic properties. Such properties influence simultaneously the terrestrial water and carbon cycles as they determine the water fluxes in the soil and the soil’s water holding capacity, ultimately affecting runoff production, groundwater recharge, and the amount and temporal variability of plant available water (i.e. plant water stress). Despite their paramount importance, limited global information concerning the spatial distribution of soil hydraulic properties currently exists. Information at the global scale, commonly used in Earth System Models, mostly originates from pedotransfer functions (PTFs). PFTs are empirical relations that express the dependence of soil hydraulic properties on easily measured attributes as soil properties. Several PFTs currently exist, which adopt different formulations, spanning from simple linear regressions to elaborate machine learning, and are trained with different datasets, yielding different soil hydraulic properties for the same soil texture.   

The question we ask in this study is: how does uncertainty in the soil hydraulic parameters propagate in global ecosystem responses? To achieve this, we deploy a numerical experiment covering many different ecosystems. The terrestrial ecosystem model T&C is used to model energy, water, and carbon dynamics at 80 locations worldwide, spanning all climatological regimes, major biomes and soil types. Soil hydraulic properties at each site were estimated using six widely used PTFs starting from local soil textural information. Uncertainty propagation from soil hydraulic properties to modelled ecosystem dynamics was evaluated for all sites and its dependence on soil textural properties and local topography was quantified.

Our results highlight that uncertainty propagation from hydraulic properties to ecosystem dynamics is much stronger for hydrological fluxes (e.g. infiltration, groundwater recharge and runoff production) than carbon dynamics (e.g. gross and net primary productivity and leaf area dynamics) or energy fluxes (net radiation, sensible and latent heat). Uncertainty in hydrological fluxes can be up to 400% using different PTFs, whereas uncertainties in carbon and energy fluxes are typically less than 20%. The largest uncertainties were observed for slow draining soils, containing large fractions of clay, located in regions with intermediate values of wetness (i.e. annual precipitation ≈ annual potential evapotranspiration). Complex topographic features further enhance the role of uncertainty in soil hydraulic properties. Lateral water redistribution affects both runoff production and soil moisture dynamics increasing the effects on both hydrological and carbon dynamics.

How to cite: Paschalis, A., Bonetti, S., Moustakis, Y., and Fatichi, S.: Uncertainty in soil hydraulic properties limits the predictability of global water and carbon dynamics , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7127, https://doi.org/10.5194/egusphere-egu2020-7127, 2020.

The ability of correlation functions to describe structure (Karsanina et al., 2015; Karsanina et al., 2018) and provide means to reconstruct the structure based on correlation functions (Gerke and Karsanina, 2015; Karsanina and Gerke, 2018) alone was proposed as means to effectively compress and store structural information (Gerke et al., 2015). This is especially appealing considering the fact that truly multi-scale digital 3D soil structure model for a single genetic horizon even with the resolution not finer than 1 µm will contain enormous amount (approx., up to 10^15 voxels or even more) of data. Effective management and pore-scale simulations based on such datasets does not seem feasible at the moment. Another approach would be to retrieve only a relevant part of the dataset and operate on it indirectly, in particular based on correlation functions or stochastic reconstructions. The main aim of this work was to investigate the possibility to compress soil structural data, as resulted from X-ray microtomography data and directional correlation functions computation (Gerke et al., 2014), into a very limited number of parameters, potentially with minimal information content loss. We show that with the help of the proposed technique it is possible to compress a 3D image of 900^3-1300^3 voxels into a set of correlation functions, that with the help of fitting of an analytical function in the form of the superposition of three different basis functions may help to map all these correlation functions in a vector of six parameters. We apply the proposed methodology to 16 different soil 3D images and discuss numerous important implications that can help to achieve the ultimate goal of building 3D multi-scale soil structure model from meter to nm. Such model would help in establishing a fully multi-scale hydrological model operating from first principles as opposed to coarse continuum scale models.

This work was supported by Russian Science Foundation grant 19-72-10082 (correlation functions) and Russian Foundation for Basic Research grant 18-34-20131 мол_а_вед (soil data).

References:

Karsanina, M. V., Gerke, K. M., Skvortsova, E. B., Ivanov, A. L., & Mallants, D. (2018). Enhancing image resolution of soils by stochastic multiscale image fusion. Geoderma, 314, 138-145.

Gerke, K. M., Karsanina, M. V., & Mallants, D. (2015). Universal stochastic multiscale image fusion: an example application for shale rock. Scientific reports, 5, 15880.

Karsanina, M. V., & Gerke, K. M. (2018). Hierarchical Optimization: Fast and Robust Multiscale Stochastic Reconstructions with Rescaled Correlation Functions. Physical Review Letters, 121(26), 265501.

Gerke, K. M., & Karsanina, M. V. (2015). Improving stochastic reconstructions by weighting correlation functions in an objective function. EPL (Europhysics Letters), 111(5), 56002.

Gerke, K. M., Karsanina, M. V., Vasilyev, R. V., & Mallants, D. (2014). Improving pattern reconstruction using directional correlation functions. EPL (Europhysics Letters), 106(6), 66002.

Karsanina, M. V., Gerke, K. M., Skvortsova, E. B., & Mallants, D. (2015). Universal spatial correlation functions for describing and reconstructing soil microstructure. PLoS ONE, 10(5), e0126515.

How to cite: Karsanina, M., Lavrukhin, E., Fomin, D., Yudina, A., Abrosimov, K., and Gerke, K.: Compressing soil structural information, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10807, https://doi.org/10.5194/egusphere-egu2020-10807, 2020.

Indirect methods for estimating soil hydraulic properties from particle size distribution have been developed due to the difficulty in accurately determining soil hydraulic properties, and the fact that particle size distribution is one piece of basic soil physical information normally available. The similarity of the functions describing the cumulative distribution of particle size and pore size in the soil has been the basis for relating particle size distribution and the water retention function in the soil. Empirical and semi-physical models have been proposed, but these are based on strong assumptions that are not always valid. For example, soil particles are normally assumed to be spherical, with constant density regardless of their size; and the soil pore space has been described by an assembly of capillary tubes, or the pore space in the soil matrix is assumed to be arranged in a similar way regardless of particle size. However, in a natural soil the geometry of the pores may vary with the size of the particles, leading to a variable relation between particle radius and pore radius.

The current work is based on the hypothesis that the geometry of the pore size and the void ratio depends on the size of the soil particles, and that a physically based model can be generalised to predict the water retention curve from particle size distribution. The rearrangement of the soil particles is considered by introducing a mixing function that modulates the cumulative particle size distribution, while the total porosity is constrained by the saturated water content.

The model performance is evaluated by comparing the soil water retention curve derived from laboratory measurements with a mean Nash–Sutcliffe model efficiency a value of 0.92 and a standard deviation of 0.08. The model is valid for all soil types, not just those with a marginal clay fraction.

How to cite: Pollacco, J., Fernández-Gálvez, J., and Carrick, S.: Predicting water retention curves of fine texture soils from particle size distribution, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6958, https://doi.org/10.5194/egusphere-egu2020-6958, 2020.

Clay fraction affects soil hydraulic and mechanical properties and dominates specific surface area. Clay fraction is used for soil classification and in pedotransfer functions (PTFs) to estimate soil hydraulic functions from simpler soil properties (texture). Remarkably, despite large variations in composition and properties of clay minerals, PTFs use this attribute in undifferentiated manner, applied similarly to soils in the tropics dominated by Kaolinite and temperate soils with Montmorillonite. The large specific surface area of Montmorillonite compared to Kaolinite reduces both the soil hydraulic conductivity and the residual friction angle. We develop PTFs informed by clay-type via soil specific surface area effects on saturated hydraulic conductivity and residual friction angle. For friction angle, PTFs were fitted to experimental data using information on clay content and clay type. For hydraulic conductivity, analytical models based on surface area and particle size were adapted to capture conductivity data from different climatic regions. Global distributions of clay types are used to map soil specific surface area and related hydro-mechanical properties to improve land-surface models (especially in the tropics) and refine natural hazard risk assessment (landslides and debris flows).

How to cite: Lehmann, P., Leshchinsky, B., Mirus, B., Lu, N., Gupta, S., and Or, D.: Effects of clay type on soil hydraulic and mechanical properties - a global perspective, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8471, https://doi.org/10.5194/egusphere-egu2020-8471, 2020.

Stony soils are soils that contain a high amount of stones and are widespread all over the world.  The effective soil hydraulic properties (SHP), i.e. the water retention curve (WRC) and the hydraulic conductivity curve (HCC) are influenced by the presence of stones in the soil. This influence is normally neglected in vadose zone modeling due to the considerable measurement challenges in stony soils. The available data on the effect of stones on SHP is scarce and there is not a systematic modeling approach to obtain the effective SHP in stony soils. Most of the past studies are limited to the effect of stones on the WRC and saturated hydraulic conductivity and low and medium stone contents (up to 40 % v/v). We investigated the effect of stone content on the effective SHP of stony soils through a series of evaporation experiments. Two soil materials a) sandy loam and b) silt loam as background soils were packed with different volumetric contents (0, 10, 30 and 60 %) of medium stones were in containers with a volume of 5060 cm³. Volumetric stone contents were chosen in a way to present stone-free, moderately stony and highly stony soils. All of the experiments were carried out in two replicate packings with an almost identical bulk density. Packed samples were saturated with water from the bottom and subjected to evaporation in a climate-controlled room. During the evaporation experiments, the pressure head and soil temperature were continuously monitored and the water loss from the soil columns was measured with a balance. The dewpoint method provided additional data on the WRC in the dry soil. The resulting data were evaluated by inverse modeling with the Richards equation to identify effective SHP and to analyze the effect of stone content on the evaporation rate, soil temperature, the effective WRC and the effective HCC. The applied methodology was successful in identifying effective SHP with high precision over the full moisture range. The results reveal a quicker transition from stage I to stage II of evaporation in highly stony soils. Evaporation rate reduces with the increase of the volumetric stone content. The existence of a high amount of stone content shorten stage II of evaporation driven by the vapor diffusion through the restricted soil evaporative surface.

How to cite: Naseri, M., C. Iden, S., and Durner, W.: Effect of stones on soil hydraulic properties: measurement and modeling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-670, https://doi.org/10.5194/egusphere-egu2020-670, 2020.

The integral suspension pressure method (ISP) uses pressure measurements in a soil suspension to derive the particle size distribution (PSD) in the silt range in high resolution. The sedimentation process is mathematically simulated and the simulated suspension pressure at a fixed depth in the sedimentation cylinder is fitted to an observed time series. The PSD is determined by numerically solving the inverse problem. The methodology is implemented in a commercial apparatus named PARIO that is produced by METER AG, Munich.

Practical experiments with PARIO indicated that the accuracy of the method to determine the clay fraction was not as high as expected from theory, which may partly be caused by the error propagation from the independently determined sand fractions. Durner and Iden (2019) thus proposed an extension of the experimental protocol called ISP⁺, which makes the inverse problem better-posed and allows shorter experimental time. After a sedimentation time of few hours, a part of the suspension is drained laterally from the sedimentation cylinder through an outlet, collected and oven-dried. The resulting dry mass of the soil particles is integrated into the objective function of the inverse problem. This markedly reduces the uncertainty of the identified PSD towards the finest particles. We present experimental results from PARIO measurements evaluated by the ISP⁺ method and illustrate the new experimental design and the improvement of accuracy for the clay fraction.

Reference: Durner, W., & Iden, S. C. (2019, January). ISP+: improving the Integral Suspension Pressure method by an independent measurement of clay content. In Geophysical Research Abstracts (Vol. 21).

How to cite: Durner, W., Miller, A., Gisecke, M., and Iden, S. C.: Testing the improved Integral Suspension Pressure method ISP+ with the PARIO™ device, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10906, https://doi.org/10.5194/egusphere-egu2020-10906, 2020.

The International Soil Moisture Network (ISMN, ) is an international cooperation to establish and maintain an open-source global data hosting facility, providing in-situ soil moisture data as well as accompanying soil variables. This database is an essential means for validating and improving global satellite soil moisture products as well as land surface -, climate- , and hydrological models.

For hydrological validation, the quality of used in-situ data is essential. The various independent local and regional in situ networks often do not follow standardized measurement techniques or protocols, collect their data in different units, at different depths and at various sampling rates. Besides, quality control is rarely applied and accessing the data is often not easy or feasible.

The ISMN was created to address the above-mentioned issues. Within the ISMN, in situ soil moisture measurements (surface and sub-surface) are collected, harmonized in terms of units and sampling rates, advanced quality control is applied and the data is then stored in a database and made available online, where users can download it for free.

Since its establishment in 2009 and with continuous financial support through the European Space Agency (ESA), the ISMN evolved into a widely used in situ data source growing continuously (in terms of data volume and users). Historic measurements starting in 1952 up to near–real time are available through the ISMN web portal. Currently, the ISMN consists of 60 networks with more than 2500 stations spread all over the globe. With a steadily growing user community more than 3200 registered users strong the value of the ISMN as a well-established and rich source of in situ soil moisture observations is well recognized. In fact, the ISMN is widely used in variety of scientific fields (e.g. climate, water, agriculture, disasters, ecosystems, weather, biodiversity, etc.).

Our partner networks range from networks with a handful of stations to networks that are composed of over 400 sites, are supported with half yearly provider reports on statistical data about their network (e.g.: data download statistic, flagging statistic, etc.).

About 10’000 datasets are available through the web portal. However, the spatial coverage of in situ observations still needs to be improved. For example, in Africa and South America only sparse data are available. Innovative ideas, such as the inclusion of soil moisture data from low cost sensors (GROW observatory ) collected by citizen scientists, holds the potential of closing this gap, thus providing new information and knowledge.

In this session , we want to give an overview of the ISMN, its unique features and its support of data provider, who are willing to openly share their data, as well as hydrological researcher in need of freely available datasets.

How to cite: Himmelbauer, I., Aberer, D., Schremmer, L., Petrakovic, I., Zappa, L., Xaver, A., Dorigo, W., Goryl, P., and Sabia, R.: The International Soil Moisture Network: an open-source data hosting facility in support of hydrological research , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18547, https://doi.org/10.5194/egusphere-egu2020-18547, 2020.

Land-Atmosphere coupling is a fundamental process of the earth system. From the perspective of atmospheric sciences, a quantitative understanding of the surface energy and mass balances is of vital importance for both numerical weather prediction and climate modeling and needs to be represented adequately in land surface schemes. The partitioning of net radiation into sensible, latent and ground heat fluxes is dependent on the state of the land surface with soil moisture being an important state variable, introducing memory effects of monthly to annual timescales to the coupling. An inadequate representation of the terrestrial water cycle will therefore degrade forecasts and introduce biases in climate simulations. While there exist reasonable estimates for the terrestrial water cycle on subcontinental scales and various observations for evapotranspiration on the point-scale, the validation of land-surface-schemes on the kilometer-scale remains challenging. The fundamental unit on which one can validate all terms of the water balance is the catchment. Here, we present a validation framework based on water balances of mesoscale catchments. The framework incorporates observations of precipitation and streamflow as well as estimates for evapotranspiration from remote sensing data.

The methodology is applied to five mesoscale catchments in Switzerland ranging from 105 km² to 1713 km² for the years 2010-2012. Observations include MeteoSwiss operational analyses, hourly discharge measurements provided by the federal office for the environment and the MODIS MOD16A2 evapotranspiration product. While relying on observations, these datasets are subject to substantial uncertainties. We aim to quantify the major part of this observational uncertainty by using data from FLUXNET sites in the Alpine region and a rain-gauge based precipitation dataset from MeteoSwiss (RhiresM).

As a showcase application, the validation framework is used in order to compare and validate two different parameterizations for soil/ groundwater hydrology in TERRA, the land surface scheme of the COSMO numerical weather prediction and regional climate model. While both versions are based on Richard’s equation, one is implemented with a free drainage boundary condition, while the other one is implemented with a simple parameterization for groundwater. Results from TERRA standalone runs forced with COSMO analysis fields suggest that errors in terrestrial storage change are mostly driven by errors in runoff. In turn, runoff is very sensitive to the parameterization of infiltration and to soil hydraulic parameter. We show that despite large uncertainties in the observations at hand, it is possible to identify respective shortcomings of the two different groundwater formulations and to improve the simulated water balance by introducing a mathematically sound formulation for infiltration and by tuning key parameter associated to ground water discharge.

How to cite: Regenass, D., Schlemmer, L., Fuhrer, O., Bettems, J.-M., and Schär, C.: Development and application of a catchment-based mass balance validation tool for land surface schemes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10975, https://doi.org/10.5194/egusphere-egu2020-10975, 2020.

Soil moisture content (SMC) is of fundamental importance to many hydrological, biological, biochemical and atmospheric processes. Common soil moisture measurements range from local point measurements to global remote sensing-based SMC datasets. Nevertheless, they always compromise between temporal and spatial resolution. Thus, it is still challenging to quantify spatially and temporally distributed SMC at a regional scale which is extremely relevant for hydrological modeling or agricultural management. The innovative technology Cosmic-Ray Neutron Sensing (CRNS) shows significant potential to fill this gap by quantifying the present hydrogen pools within footprints larger than 0.1 ha.

Owing to the difference in scale between the ground resolution of satellites used to retrieve soil moisture and the common point scale of ground-based soil moisture instruments, the large footprint of the CRNS poses a high potential for the validation of SMC remote sensing products. When linking the CRNS measurements with remote sensing data, the vertical and horizontal characteristics of its footprint need to be considered.

To examine the influence of the CRNS footprint characteristics on the linkage of CRNS and remote sensing data, we couple CRNS measurements with high-resolution UAS-based thermal imagery acquired at two sites in Bavaria and Brandenburg (Germany) using a radiometrically calibrated FLIR Tau 2 336 (FLIR Systems, Inc., Wilsonville, OR, USA) with a focal length of 9 mm. Within this context, we evaluate the added value of applying a horizontal weighting function to the spatially distributed thermal data in comparison to an unweighted mean when statistically representing the corrected neutron counting rates.

The project is part of the DFG-funded research group Cosmic Sense, which aims to provide interdisciplinary new representative insights into hydrological changes at the land surface.

How to cite: Döpper, V., Gränzig, T., Förster, M., and Kleinschmit, B.: Linking thermal UAS-based imagery and Cosmic-Ray Neutron Sensing data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19609, https://doi.org/10.5194/egusphere-egu2020-19609, 2020.

The dynamics of soil organic matter is strongly controlled by the hydrophysical environmental factors, including motility, aqueous diffusivity of substrates, gaseous diffusivity, and energetic constraints on microbial physiology. The relationships among these physical factors depend on soil moisture and the architecture of the soil pores. In this regard, the soil water retention curve can serve as a macroscopic signature of pore-size distribution. Therefore, the sensitivity of aerobic and anaerobic microbial activity must be closely associated with the shape of the soil water retention curve. The soil water retention curve is, in turn, strongly dependent on soil texture and structure. Here, we present a physically-based model of aerobic and anaerobic microbial respiration rates. We also present a novel experimental technique for the characterization of the soil-moisture sensitivity of soil microbial activity. The proposed experimental and modeling approaches allow direct coupling of the fate soil organic matter with the nature of soil structure.

How to cite: Ghezzehei, T., Alvarez, J., Villa, Y., and Ryals, R.: Relating soil structure and hydrophysical characteristics to aerobic and anaerobic soil respiration, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21234, https://doi.org/10.5194/egusphere-egu2020-21234, 2020.

Infiltration is strongly affected by soil structure. The measurement technique and the land use are two soil structure-related attributes that are typically available in descriptions of infiltration experiments. We hypothesized that these attributes may be good predictors of the performance of different infiltration models, and of the parameter values in those models. The international soil infiltration database SWIG assembled in the Institute of Agrosphere in Jülich, Germany, was used as the data source. The database encompasses about 5000 experiments all over the world, Texture, measurement method and land use were known for all experiments, availability of organic carbon content, bulk density, saturated hydraulic conductivity (Ksat), pH, the electrical conductivity of saturated paste, and initial water content varied. Comparison of the performance of eight infiltration models showed that Horton and Mezencev models outperformed all others and that one of these two models could be preferred based on the infiltration measurement method. The machine learning method – regression trees – was applied to find the most influential predictors of parameters of Horton and Mezencev models. The measurement method, the textural class, and the land use were the most influential predictors in 80% of cases for both models. The measurement method was the most influential input in 40% of cases. The accuracy of parameter estimates increased when only the subset of measurements with the same method was used to estimate infiltration parameters. Land use, textural class, and organic carbon content dominated as the most influential predictors for the parameters of the Mezencev model, whereas land use, textural class, Ksat, and bulk density became most important in the case of the Horton model. Overall, estimates of the infiltration equation parameters can be more accurate if they have been developed for the same measurement method as in the task in hand. Land use category and the infiltration measurement method provide useful surrogate information about the soil structure effect on infiltration. 

How to cite: Karahan, G., Kim, S., and Pachepsky, Y.: Parameters of infiltration models as affected by the measurement technique and land use, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11633, https://doi.org/10.5194/egusphere-egu2020-11633, 2020.

The near-saturated hydraulic conductivity is an important parameter in relation to the analysis of heterogeneous transport in the soil macropore system. To a high degree, leaching of phosphorus out of the root zone takes place in the macropores either in a dissolved form or as phosphorus bound to colloids. In this work, a newly constructed and improved drip infiltrometer (DIM) is presented being able to measure the unsaturated hydraulic conductivity in the near-saturated range (i.e. in the range of matric potentials between -0.1 and 3 -kPa) on undisturbed soil columns (20 cm by 20 cm). The DIM is a modified version of the classical multistep system establishing gravity flow at decreasing flow rates. The procedure is that the soil column is placed on top of a ceramic plate. Five tensiometers measure the change in the matric potential a different flow rates applied by a drip-irrigation device mounted on the top of the column. By applying a certain inflow at the top and suction at the bottom of the sample, a steady state flow is established based on tensiometer readings showing a constant gradient along the soil sample. This allows the determination of the near-saturated hydraulic conductivity by applying Darcy’s equation. Compared to an earlier version of the infiltrometer, the instrument has been improved in several ways. This involves a high level of automation of the computer program controlling the analysis making it possible to setup a number of settings and constrains in order to optimize the analysis. Examples are given for newly developed pedotransfer functions predicting the saturated and near-saturated hydraulic conductivity. Results were used to model water transport in the vadose zone spatially distributed over Denmark using variation in the hydraulic properties as well as spatially distributed metrological data. Models results ended up with a map pointing out risk areas of macropore transport in relation to the leaching of phosphorus.

How to cite: Iversen, B. V., Koppelgaard, M., and Kotlar, A. M.: An improved drip infiltrometer measuring the near-saturated hydraulic conductivity: Pedotransfer development and macropore transport, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22667, https://doi.org/10.5194/egusphere-egu2020-22667, 2020.

The representation of the thermal and hydrological state in the land model component of Earth System Models is crucial to have a realistic simulation of subsurface processes and the coupling between the atmo-, lito- and biosphere. There is evidence suggesting an inaccurate simulation of subsurface thermodynamics in current-generation Earth System Models, which have Land Surface Models that are too shallow. In simulations with a bottom boundary too close to the surface, the energy propagation and spatio-temporal variability of subsurface temperatures are affected. This potentially restrains the simulation of land-air interactions and subsurface phenomena, e.g. energy/moisture balance and storage capacity, freeze/thaw cycles and permafrost evolution. We introduce modifications for a deeper soil into the JSBACH soil model component of the MPI-ESM for climate projections of the 21st century. Subsurface layers are added progressively to increase the bottom boundary depth from 10m to 1400m. This leads to near-surface cooling of the soil and encourages regional terrestrial energy uptake by one order of magnitude and more.
The depth-changes in the soil also have implications for the hydrological regime, in which the moisture between the surface and the bedrock is sensitive to variations in the thermal regime. Additionally, we compare two different global soil parameter datasets that have major implications for the vertical distribution and availability of soil moisture and its exchange with the land surface. The implementation of supercool water and water phase changes in the soil creates a coupling between the soil thermal and hydrological regimes. In both cases of bottom boundary and water depth changes, we explore the sensitivity of JSBACH from the perspective of changes in the soil thermodynamics, energy balance and storage, as well as the effect of including freezing and thawing processes and their influence on the simulation of permafrost areas in the Northern Hemisphere high latitudes. The latter is of particular interest due to their vulnerability to long-term climate change.

How to cite: Steinert, N., González-Rouco, F., Hagemann, S., de Vrese, P., García-Bustamante, E., Jungclaus, J., Lorenz, S., Melo-Aguilar, C., and Navarro, J.: Impact of improved land model depth and hydrology on climate change projections , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19277, https://doi.org/10.5194/egusphere-egu2020-19277, 2020.

This study utilises in-situ and reanalysis soil moisture data inputs from various sources to evaluate the effect of soil water stress on Gross Primary Productivity (GPP) of different Plant Functional Types (PFTs) using Terrestrial Ecosystem Model in R (TEMIR), which is under development by Tai Group of Atmosphere-Biosphere Interactions (Tai et al. in prep.). An empirical soil water stress function with reference to Community Land Model (CLM) Version 4.5 is employed to quantify water stress experienced by vegetation which hinders stomatal conductance and thus carboxylation rate. The model results are compared against observations at FLUXNET sites in semi-arid regions across the globe at daily timescale where in-situ GPP data is available and water stress inhibits plant functions to some extent. By dividing the soil into two layers (topsoil and root zone), GPP simulation improves significantly comparing with using single layer bulk soil (Modified Nash-Sutcliffe Model Efficiency Coefficient N increases from -0.686 to -0.586). Such upgrade is particularly substantial for vegetation with shallow roots such as grass PFTs. Despite this improvement, the model is characterised by an overall overestimation of GPP when water stress occurs, and inconsistency of accuracy subject to PFTs and degree of water stress experienced. This study informs responses of various PFTs to soil water stress, capacity of TEMIR in simulating the responses, and possible drawbacks of empirical soil water stress functions, and highlights the importance of topsoil moisture data input for vegetation drought monitoring.

Keywords: Soil water stress, Terrestrial model representation, Photosynthesis, In-situ data, Reanalysis data, FLUXNET

How to cite: Lam, T. and Tai, A. P. K.: Simulating Gross Primary Productivity of vegetation under soil water stress using in-situ and reanalysis soil moisture data inputs, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21397, https://doi.org/10.5194/egusphere-egu2020-21397, 2020.

The PARIO system is a novel technique for the measurement of soil particle-size distribution. It is a computerized sedimentation-based system that will yield a quasi-continuous particle-size distribution curve. Given that it is semi-automated, continuous and sedimentation-based, this system promises to become a good and compatible alternative to the traditional pipette or hydrometer techniques. Through hundreds of measurements we have acquired practical operational knowledge that this poster will share with potential future users. We will also present quantitative information on the technique’s sensitivity to e.g. temperature shift or intermittent vibration during measurement. We also used a set of 45 soil samples of various texture from Norway to compare particle-size distribution measured by the PARIO system, the traditional pipette technique and laser diffractometry. We discuss measurement results as well as related sample-preparation aspects.

How to cite: Nemes, A., Angyal, A., Mako, A., Jacobsen, J. E., and Herczeg, E.: Measurement of soil particle-size distribution by the PARIO measurement system: lessons learned and comparison with two other measurement techniques, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9832, https://doi.org/10.5194/egusphere-egu2020-9832, 2020.

Typical information in soil databases is the soil texture and particle size distribution. These properties are used for soil description or predicting other soil properties such as bulk density or hydraulic conductivity. Measuring particle size distribution with standards methods such as the pipette or hydrometer is time-consuming because of the sample pre-treatment used to remove organic matter or iron and the sample post-treatment. Nowadays, there are new methodologies for determining soil particle size distribution, such as the Integral Suspension Pressure (ISP) method, which measures the silt content in a semi-automatized process. Thus, the main objective of this study was to evaluate the suitability of the ISP method compared to standard techniques used in soil analysis and evaluate the effect of organic matter content in the ISP measurements. The main results showed that the ISP method is equivalent in accuracy to the pipette, especially for soils rich in silt or sand content. Also, the results demonstrate the convenience of removing the soil organic matter when using the ISP for soils with more than 1.5% organic matter.

How to cite: Contreras, C., Acevedo, S., Martínez, S., and Bonilla, C.: Evaluating the Integral Suspension Pressure method for measuring the particle size distribution in soils with high organic matter content, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12380, https://doi.org/10.5194/egusphere-egu2020-12380, 2020.

REQUASUD network (based in Wallonia, Belgium) consists of laboratories working directly with farmers, giving them soil fertility diagnostics and advice for a good management of soils and cultures. Therefore, the laboratories analyze, among others, available nutrients. But they need more information to correctly interpret the results and give fertility advice, like the cationic exchange capacity (CEC) and the clay content. However, analyzing CEC and clay content is expensive, time-consuming and requires the use of chemicals. To overpass this problem, the near-infrared reflectance spectroscopy (NIRS) has been developed and is now used routinely in the laboratories. This method is rapid, non-destructive and allows the simultaneous estimation of soil characteristics. Nowadays, the REQUASUD NIR database performances for clay content are the followings : RPD = 2,22% for cultures and RPD = 1,72% for grasslands. This method of analysis can be used for other purposes than fertility advice.

How to cite: Mariage, C., Colinet, G., and Genot, V.: Using the NIRS for analyzes of soil clay content, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21865, https://doi.org/10.5194/egusphere-egu2020-21865, 2020.

As the basic unit of soil, aggregates are considered as a stable soil organic ( SOC ) pool. Changes in organic subtract due to straw addition induce variations in soil microbial community or activity, which may effect the C sequestration in aggregates. Most of the previous studies on soil microorganisms assessment was done at large scale i.e. larger quantities of soil, however, few studies on SOC is known in aggregate size fractions. This study investigated the effects of soil aggregate size on the distribution of microorganism and SOC, and the relationship of microorganism and C sequestration inside aggregate size fractions with ¹³C-labelled straw addition. Soil samples were collected from 0-15 cm and classified into 5 aggregates sizes classes ( ＞5 mm, 2-5 mm, 1-2 mm, 0.25-1 mm and ＜0.25 mm ), and the graded aggregates were incubated for 180 days at 20 °C, with or without ¹³C-labelled straw residue. The incorporation of ¹³C into the five aggregate size fractions was analyzed.

After incubation, the SOC, DOC and ROC contents were increased more rapidly and significantly in aggregate ( ＞5 mm ) than that in aggregate ( ＜5 mm ) under straw addition, with the same trend of new carbon derived from straw. The total PLFAs was increased most significantly in aggregate ( ＞5 mm ), especially fungi and negative bacteria ( G- ), while the positive bacteria ( G+ ) increased slightly in aggregate ( ＜0.25 mm ), with no significant change in total PLFAs. The proportion of bacteria in total microorganism increased gradually, as the aggregate size increased in straw treatment. The results imply that aggregate ( ＞5 mm ) have more space for C sequestration and greater contribution to new carbon turnovering in soil than other small aggregates, and it gradually tended to be bacterial with the enrichment of carbon. In addition, the SOC contents were strongly related to the amount of fungi and G- in aggregate ( ＜5 mm ), while related to G+ in aggregate ( ＜0.25 mm ) under straw addition.

How to cite: Lu, J., Li, S. P., Wu, X., and Degre, A.: Soil aggregate size affects C sequestration and microorganisms inside aggregate under straw addition, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20840, https://doi.org/10.5194/egusphere-egu2020-20840, 2020.

Lime and animal manure can have major impacts on soil physical properties, particularly in degraded and highly weathered soils that are naturally acidic. Here we evaluate how treatment of a regular till Acrisol in southeast China with different amounts of lime and/or pig manure, and planted with maize, affects pore scale properties down to micron size using synchrotron microtomography (SR–mCT). Soil macroaggregates (2 - 5 mm) from 4 treatments were measured: 1) Control, no manure amendment; 2) low manure (150 kg N ha^-1 y^-1); 3) high manure (600 kg N ha^-1 y^-1); and 4) high manure (600 kg N ha^-1 y^-1)+ lime (3000 kg Ca(OH)₂ ha^-1 every 3 years). Pore structure at a resolution of 3.7 µm was reconstructed in 3D and the Multi- Relaxation- Time (MRT) Scheme for Multi- Phase Lattice Boltzmann Method (LBM) was used to simulate water flow and retention. Topological analysis was performed based on the extracted pore network by using the maximal ball-based pore network extraction. A quasi-static pore network solver was applied to compute the capillary pressure based on the extracted pore networks. The application of a high amount of pig manure increased the fraction of macropores (>100 µm) to 38.61% compared to the controlled level (18.15%). A high amount of pig manure also decreased total porosity to 8.08% compared to 11.35% for the control, suggesting less micropores caused by high pig manure treatment. The application of high amount of pig manure and lime also caused more uniform water flow. Control samples had a velocity frequency at around e¹¹ of the normalized velocity (respect to the mean), while the samples from the other treatments had more evenly distributed peaks. Water flows most quickly due to least impediment by pores in the samples with high manure amendment. The slope between permeability and porosity increased from 8.10 Darcy (controlled) to 174.47 Darcy (high amount of manure treatment). The amendment of 600 kg N ha^-1 y^-1 pig manure increased water retention ability calculated by the simulations. For the capillary pressure > -50 kPa, control samples had the greatest water saturation level compared with the samples from the other treatments, while there were no significant differences of water saturation of samples from all the treatments for the capillary pressure < -1000 kPa . The simulated water retention results had the same trend with the measured results.

How to cite: Qu, R., Zhou, H., and Hallet, P.: Quantification of micron-scale structural and hydraulic properties of long-term pig manure and lime amended red soil aggregates using the lattice Boltzmann method and pore network modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19170, https://doi.org/10.5194/egusphere-egu2020-19170, 2020.

Soil moisture predictions are increasingly important in hydrological, ecological and agricultural applications. In recent years the availability of wide-area assessments of current and future soil-moisture states has grown, yet few studies have combined model-based assessments with observations beyond the point scale. Here we use the JULES land surface model together with COSMOS-UK data to evaluate the extent to which data assimilation can improve predictions of soil moisture across the United Kingdom.

COSMOS-UK is a network of soil moisture sensors run by UKCEH. The network provides soil moisture measurements at around 50 sites throughout the UK using innovative Cosmic Ray Neutron Sensors (CRNS). Half hourly measurements of the meteorological variables that the Joint UK Land Environment Simulator (JULES) requires as driving data are also recorded at COSMOS-UK sites, allowing us to run JULES at observation locations. This provides a unique opportunity to compare soil moisture outputs from JULES with CRNS observations; these measurements have a footprint of up to 12 ha (approx 30 acres) and are therefore better scale matched with JULES outputs than those from point sensors.

We have used the Land Variational Ensemble Data Assimilation Framework (LaVEnDAR) to combine soil moisture estimates from JULES with daily CRNS observations from one year at a number of COSMOS-UK sites. We show that this results in improved soil moisture predictions from JULES over several years. This has been achieved by optimising parameters in the pedo-transfer function used to derive JULES soil physics parameters from soil texture information. Using data assimilation with LaVEnDAR in this way allows us to explore the relationships between soil moisture estimates, soil physics parameters and soil texture, as well as improving the agreement between JULES model outputs and observations.

How to cite: Cooper, E., Pinnington, E., Ellis, R., Blyth, E., Dadson, S., and Cooper, H.: Improving estimates of UK soil moisture using the JULES land surface model with COSMOS-UK measurements in the LaVEnDAR data assimilation framework, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11566, https://doi.org/10.5194/egusphere-egu2020-11566, 2020.

Time Domain Reflectometry (TDR) is an accurate and widely used technique for real time estimation of soil volumetric water content (θ), and the bulk electrical conductivity (σ). Although there are multiple software that allow monitoring θ and σ by connecting the TDR device to a PC, this system used under field conditions can be in many cases awkward. This paper presents a wireless, portable, unexpansive, simple, and versatile system to measure θ and the σ by connecting the TDR device to a smart phone. The system consists on a M5Stack processing unit that integrates a Wifi connectivity. The UART port of the M5Stack is connected to the TDR device through RS232-ttl adapter. The hardware is programmed in micropython language that allows the M5Stack acts as a server between the user and the TDR device through a web page read with a smart phone. The software, which is compatible with Campbell TDR100 and 1502C Tektronix devices, allows creating different project where the TDR waveforms are stored. A simple θ and the σ measurement is also allowed. Since the objective of the portable system is to ease and makes θ and σ samplings faster, a complementary web page for subsequent and more accurate estimates of θ and σ was also developed.

How to cite: Villoro, A., Latorre, B., Jiménez, J., López, M. V., Nicolau, J. M., Tormo, J., and Moret-Fernández, D.: A wireless system for volumetric water content measurement by TDR, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4507, https://doi.org/10.5194/egusphere-egu2020-4507, 2020.

Continuous soil moisture content monitoring is key to understand the soil and water flow and transport processes and their impact on a wide range of environmental change and quality processes. Nowadays, there are a wide variety of electromagnetic sensors for estimating soil volumetric content. These include those from established manufacturers (>50€) and low-cost (<50€) amateur electronics enthusiasts with open-source projects. For each sensor, the manufacturer typically provides both a calibration function and an estimation of the sensing volume of the device. The objective of this work is to evaluate the performance –regarding the accuracy and effective sensing volume– of a wide variety of soil water sensors and to compare these results with those provided originally by the respective manufacturer. Twenty-five different electromagnetic sensors representative of the current best-known commercial (19) and the low-cost brands (6) were tested in the laboratory using 3 soils of contrasting texture. Benchmark values for comparison were obtained by the gravimetric method. The sensing volume for each probe was characterized by recording readings while the probes approached a water surface. The Root Mean Square Errors of the sensors ranged from 0.02 to 0.10 cm³/cm³, and the sensing volume of the different probes exhibited a large variability, ranging from 0.5 to 1500 cm³. Importantly, the probes evaluated in laboratory conditions showed different errors for each soil type. The loamy soil readings presented the smallest errors, followed by sandy and clayey soils. No statistically significant differences were found in measurement accuracy between low-cost and higher-priced probes. From the study of the sensing volume explored, with the exception of one case, it can be concluded that the low-cost probes generally explore a smaller volume than the established probes. The selection of the appropriate probe based on its sensing value could be important for different types of risk analysis and management applications.

How to cite: Campo-Bescós, M. A., Iturria, I., Gomez, U., Gimenez, R., Casali, J., and Muñoz-Carpena, R.: Study of accuracy and sensing volume of a wide range of established and low-cost soil water content probes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19015, https://doi.org/10.5194/egusphere-egu2020-19015, 2020.

Soil water repellency (SWR) has significant consequences for crop yield, carbon sequestration, aggregate stability, soil erosion, and water movement. It is known to be linked to hydrophobic substances and pore structure. Conservation agriculture could affect SWR through both aspects. However, most of the studies have only focused on hydrophobic substances due to the complexity of soil pore structure measurement and quantification. In this study, X-ray computed tomography at a resolution of 27.27 μm was used to calculate the shape, porosity, and connectivity of the pore network and reveal the impact of hydrophobic substances and pore structure on SWR. All samples were collected from two long-term experimental fields. The treatments were conventional tillage with residue removal (CT), reduced tillage with residue incorporated (RT), and no-tillage with residue mulch (NT) in both of the fields. The water repellency index was determined using the intrinsic sorptivity method by measuring the water and ethanol sorptivity. The results showed that RT and NT treatment increased the porosity of pores of 55-165 μm in diameter that had a positive relationship with ethanol sorptivity and water repellency index, respectively. However, the total porosity and the porosity of >165 μm in diameter had no significant link with SWR properties. RT and NT treatments could enhance ethanol sorptivity by increasing pore connectivity. However, pore connectivity had no effect on water sorptivity because of the hydrophobic substances. NT treatment also reduced water sorptivity by increasing pore surface area and hydrophobic substances. Soil organic carbon and microbial biomass carbon, both of them as hydrophobic substances, were higher under RT and NT treatment than CT. Microbial biomass carbon was more positively correlated to SWR than soil organic carbon, which indicates that microbial biomass carbon is a better indicator explaining tillage effects on SWR. Overall, RT and NT treatment could increase the water repellency index, which was a result of the interactions between pore structure and hydrophobic substances. In order to unravel the mechanisms underlying conservation tillage impacts on SWR more accurately, it is essential to determine both pore structure and hydrophobic substances at the same time.

How to cite: Li, S., Lu, J., and Degré, A.: Factors governing soil water repellency under tillage management: the role of pore structure and hydrophobic substances, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20719, https://doi.org/10.5194/egusphere-egu2020-20719, 2020.

Soil moisture plays an important role for the understanding of hydrological processes due to its influence on water and energy fluxes between the soil surface and the atmosphere. Knowledge of soil water dynamics is especially critical in water-scarce areas. In agroforestry systems, for instance, excessive competition for water between the trees and crops might outweigh the benefits of the system, thus preventing a successful implementation.
Several techniques exist for measuring soil moisture and commercial devices vary widely in cost, reliability and efficiency. An alternative approach could be to estimate soil moisture dynamics from soil thermal dependencies. Similar approaches are already being used in remote sensing, as soil moisture influences the soil thermal properties and thus the surface energy balance and soil heat transfer. However, few studies have tested the feasibility of estimating in-situ soil moisture dynamics from soil temperature dynamics within a soil profile. Temperature sensors are cheaper, smaller and technically robust and could thus provide an interesting alternative to available commercial soil moisture sensors.
In this study, we quantify the effect of soil moisture on phase shift and amplitude attenuation of soil temperature to estimate soil moisture content. We investigate these relationships from two different angles. Firstly, we use virtual measurements in coupled model simulations of soil water and soil heat dynamics to infer the general feasibility and precision of the method in an idealized error-free world. A sensitivity analysis can give insights on how the parametrization of the thermal diffusivity affects the precision and feasibility. Secondly, we compare findings from these simulations to results from analyzing time series of both soil moisture and soil temperature measured in an agroforestry field site in South Africa. A tentative analysis of these time series reveals that the amplitude attenuation and phase shift in the daily temperature signal is clearly sensitivity to changes in soil moisture. Finally, we aim to setup a coupled model for the study site based on the available soil hydraulic and textural data and compare simulated with observed phase shifts and attenuations at different depths.

How to cite: Hoffmeister, S., Haßler, S., Mälicke, M., and Zehe, E.: Estimating in-situ soil moisture dynamics from soil thermal dependencies, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13852, https://doi.org/10.5194/egusphere-egu2020-13852, 2020.

Thermal diffusivity (κ) of soils is highly dependent on soil moisture (θ), and so it is a common practice to measure the thermal diffusivity across a range of water contents. Thermal diffusivity of sandy soils, which occupy about 10% of land surface, was investigated. The results of this research may be used in various studies for sandy soils energy and water balance calculation.This study aims at the regression model of the sandy soils κ(θ) curves introduction. To achieve this goal, 9 more samples of sandy soils of the East European Plain were taken. Undisturbed soil cores were sampled from the 0–1.75 m layer with thin-walled steel cylinders 70 mm in height and 50 mm in diameter and were studied using the unsteady-state method. Additional sampling was carried out to provide soil material necessary to investigate basic properties of soils. Statistic analysis was performed for the dataset of 23 samples including the newly studied Lammelic Arenosols from Voronezh region and earlier investigated Anthrosols, Brunic Arenosols, and Albic Retisols from Moscow region. The ranges of sand, silt, and clay within the data set were 87–97, 0–8, and 1–6%; organic carbon content ranged from 0.1 to 0.9%; bulk density was rather high: from 1510 to 1660 kg m^-3. Thermal diffusivity of capillary moistened soils was (6.2–7.6)×10^-7 m²s^-1; that of air-dry soils was about 2×10^-7 m²s^-1, and the peak values were almost 10×10^-7 m²s^-1 for soils with organic carbon content less than 0.3%, and did not exceed 8.5×10^-7 m²s^-1 for soils with organic carbon content from 0.5 to 0.9%. To compare different κ(θ) curves, we used a four-parameter approximation:

where κ₀ is the thermal diffusivity of dry soil, а is the difference between the highest thermal diffusivity and the thermal diffusivity of dry soil, θ₀ and b are shape parameters. The Willmott index of agreement between the model-predicted and observed values (d_r), which approaches 1.0 when the predictions approach the observations, was used for evaluating the approximation quality. The efficiency of grouping soils was confirmed. The average curves for two groups differing in organic carbon ranges (C ≥ 0.5%, d_r = 0.877; C < 0.5%, d_r = 0.819) turned out to be more precise than the average curve obtained for the whole dataset (d_r = 0.796). The linear correlation analysis of soil properties and the parameters of κ(θ) curves revealed a correlation between organic carbon content and а (-0.623) and between bulk density and κ₀ (0.574). Curve parameters and basic soil properties of samples were used in order to carry out the forward stepwise multiple regression. The quality of obtained regression functions was evaluated using the R² coefficient. The higher R² values of κ₀ and a were 0.776 and 0.637, respectively; the lower R² values of θ₀and b were 0.485 and 0.451, respectively. The obtained regression functions allow estimating apparent thermal diffusivity of sandy soils basing on available data on basic soil properties and soil water contents.

How to cite: Lebedev, A., Arkhangelskaya, T., and Milichenkova, V.: Modelling thermal diffusivity of sandy soils, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1052, https://doi.org/10.5194/egusphere-egu2020-1052, 2020.

Frozen soil thermal conductivity (FSTC), which describes frozen soils’ ability to conduct heat under a unit temperature gradient, is a critical parameter of the partial differential heat conduction equation required for numerical studies of coupled heat and mass transport processes and engineering applications in cold and arid regions. FSTC is complicated because it is affected by factors such as temperature, unfrozen water and ice content, and soil texture. Although many FSTC models are available in literature, many of these models were developed using steady-state method that are subject to errors associated with phase change and water redistribution or not even tested with experiments. In addition, no studies have assessed their applicability and reliability. We conducted an extensive literature review and collated over 30 FSTC models. Their performance was evaluated with a large compiled dataset measured with transient method (e.g., heat pulse method), which is less likely to be affected by phase change and water redistribution at unfrozen or low subfreezing temperatures. In addition, a new FSTC model that is capable of accurately estimating FSTC at both unfrozen and frozen conditions is proposed.

How to cite: He, H., He, D., Kojima, Y., Flerchinger, G., and Dyck, M.: Modelling of frozen soil thermal conductivity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1753, https://doi.org/10.5194/egusphere-egu2020-1753, 2020.

Evaporation from real soils is a rather complex process, where atmospheric processes and internal water-transport and phase-transfer processes interfere each other, often nonlinearly. Coupled surface flow and diffusion from interfering neighboring pores through viscous or turbulent boundary layer determine the upper (atmospheric) boundary condition for the capillary and viscous water flow through the pore network of the porous media.

Recent research studied the influence of corner flow and thin-film flow on the evaporation or drying process. At pore scale these studies use microfluidic setups (Eijkel et al., 2005; Zhao et al., 2016) or micro-models (Zhang et al., 2011; Prat, 2011; Vorhauer et al., 2015; Geistlinger et al., 2019). At REV-scale the studies are based on packed glass beads and sands (Hoogland et al., 2016). Parametrizations of the soil hydraulic functions for the very dry region include corner- and film flow contributions (e.g. Peters et al., 2015).

To the best of our knowledge there is no study of the impact of thick-film flow caused by the roughness of the pore-solid interface on the evaporation (drying) process.

The objective of this paper is to present a comparative study of the two relevant water transport mechanisms corner- and thick-film flow at pore scale using micro-model experiments. The micro-models exhibit the same pore structure, but are different in their surface roughness. This is achieved by producing them based on silicon (smooth surface) and glass ceramics (rough surface). This allows to reduce the complexity of the evaporation process and control the relevant process parameter.

[1] Geistlinger, H., Ding, Y., Apelt, B., Schlüter, S., Küchler, M., Reuter, D., et al. (2019). Evaporation study based on micromodel experiments: Comparison of theory and experiment. Water Resources Research, 55, 6653–6672. https://doi.org/10.1029/2018WR024647

[2] Geistlinger, H., & Leuther, F. (2018). Evaporation study for real soils based on HYPROP‐hydraulic functions and micro‐CT‐measured pore‐ size distribution. Vadose Zone Journal, 17(1). https://doi.org/10.2136/vzj2018.02.0041 180041

How to cite: Ding, Y. and Geistlinger, H.: The Impact of Corner- and Thick-Film flow on Evaporation: A Micromodel Study, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2058, https://doi.org/10.5194/egusphere-egu2020-2058, 2020.

The pressure plate method has been widely used for describing the soil water retention curve (SWRC). However, the simplified evaporation method (SEM) appears as an alternative because of its high resolution and automatization. On the other hand, the unimodal and bimodal van Genuchten models (VGM) have been used for describing the SWRC by computing the shape parameters. However, parametric pedotransfer functions (PTFs) have been developed based on the pressure plates method, focusing on the unimodal VGM. Therefore, the objectives of this study were: (1) to measure the SWRC with the simplified evaporation method (SEM) coupled to the dewpoint potentiometer (DP) in soils with different land use and soil texture, (2) to adjust and compare the VG unimodal and bimodal parameters, and (3) to estimate the VG unimodal and bimodal parameters through regression techniques including a linear approach and random forest. Thirty topsoils (disturbed and undisturbed cores) were sampled across a climate gradient and measured by duplicated. Preliminary results showed that the high resolution of the SWRC data obtained with the SEM + DP leads to a better fit when using the bimodal VGM.

How to cite: Acevedo, S., Contreras, C., Martinez, S., and Bonilla, C.: Estimating the unimodal and bimodal van Genuchten model parameters using the simplified evaporation and dewpoint methods, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15082, https://doi.org/10.5194/egusphere-egu2020-15082, 2020.

Crack formation and development have been a general concern in agricultural science. Cracks contribute to soil aeration, aggregate formation, and easy root penetration. However, cracks facilitated water evaporation, accelerated soil desiccation, allowed deep infiltration of pesticides/pollutants through preferential flow, and polluted the shallow water-table in Belgium.  From many years, farmers reported the presence of cracks in their field; however, few studies investigated cracks formation from agricultural soil under different cultural practices. This research investigated the effect of cultural practices (conventional and reduced tillage) on crack formation and on soil hydraulic properties.

Soils were collected right from the agricultural field and processed (in laboratory) under evaporation experiment on a small drying chamber. Ceramic-IR-emitter heated the chamber while sensors (PT1000, DHT22) measured the temperature and relative humidity. Digital camera took photos of the soil surface at 30min interval. Balance and tensiometer commanded by a datalogger (CR800), recorded the soil hydraulic properties (water suction, water retention, evaporation rate etc.). Cracks were monitored and extracted using image analysis performed by ImageJ and PCAS software. The soil water retention curve (SWRC) was fitted with the bimodal models of Durner (1994) and Seki (2007). The output data were analysed statistically using appropriate software. Three treatments were considered including: disturbed soil, conventional tillage and reduced tillage.  

The results showed higher cracks formation on disturbed soil > reduced-tillage > conventional-tillage due to loose of soil cohesion, soil organic content, soil aggregation, biological activities, and soil porosity. Crack formed at low matrix suction for reduce tillage, but higher tension for conventional tillage and disturbed soil. The soil evaporation rate was also greater in reduced-tillage > conventional tillage > disturbed soil. The effect of cracks affected the SWRC for reduced tillage and disturbed soil. The result suspected the presence of pre-installing (or micro)cracks in the reduced-tillage samples. Future study is needed to assess the presence of pre-(micro)-cracks in soil using X-ray microtomography. 

How to cite: Ralaizafisoloarivony, N. A.: Assessing the effect of soil crack dynamics on hydraulic properties of agricultural soil from reduced tillage and conventional tillage fields, Wallonia-Belgium, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20194, https://doi.org/10.5194/egusphere-egu2020-20194, 2020.

Estimating the depth of the restrictive layer of soil in a cranberry field based on CT scan images

Cranberry production is a dominant culture in Québec, Canada. In cranberry production, there is a substantial need for water whether for irrigation, harvesting, or frost control. Some farms are implementing subirrigation procedures in order to reduce water use and increase fruit yields. However, this irrigation method may impose hydraulic stresses on soil particles which results in the movement of fine particles. The accumulation of the soil particles in narrow pore throats leads to the formation of restrictive layers in soil.  In this respect, we are going to study the changes in soil media and its porosity based on X-ray computed tomography (CT) which is a non-destructive imaging method. Consequently, X-ray CT has become a great asset to analyze soil physical properties. With the analysis of the images captured by the use of X-ray computed tomography, it is possible to visualize and analyze the pore network structure in the soil media.

This study reports the results of subirrigation experiments for four different sandy soils. These column experiments aimed to reproduce the effects of subirrigation in cranberry fields for 40 years. Seven different time steps were taken with a medical CT scanner SOMATOM Definition AS+ 128 (Siemens, Germany). The 2-D horizontal 16-bit gray-scale images were captured by an X-ray energy level of 140 KeV. For each column, we got 1677 images of 512  512 pixels with a voxel size of 0.1 × 0.1 × 0.6 mm (x, y, z). Studying our images for further analysis, we used several global and local methods to find the most reliable and efficient one to binarize our images. Results show that the methods and the image analysis neighborhood have a great impact on the accuracy of the image segmentation. We were able to reconstruct a 3-D visualization of the soil pore network for each column. We used this reconstruction to demonstrate that the variation of porosity and soil pore characteristics can be studied over time. We find that the transport of soil particles tends to be highest when there are fine sandy soil particles on top of a layer of coarse soil. These finer particles have sufficient energy to be remobilized within the pore network while coarser particles remain in place. Our results show that soil particle transport can be assessed using time-lapse imagery and thus makes it possible to approximate the depth and amount of time that will be required for these restrictive layers to form in different soil profiles. Finally, it would be possible to find the best structure of soil in construction of a cranberry field in the future.

How to cite: Shahriarinia, E., Gumiere, S. J., and Dupuis, C.: Estimating the depth of the restrictive layer of soil in a cranberry field based on CT scan images, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11917, https://doi.org/10.5194/egusphere-egu2020-11917, 2020.

Due to the current expansion of arid regions, the pressure on available water resources is increasing. A suitable measure for water availability and dynamics in dry soil is the relative humidity (RH) of the soil air as shown in Goss and Madliger (2007). Due to the heterogeneity of soil, water inputs, and root water uptake, the humidity of soil air will vary in space. Therefore, area-representative measurement methods are needed to find a representative measure of the soil water status. Existing sensors for the direct determination of relative humidity only represent a single location with a spatial extent of up to several cm.

We introduce a new measuring principle that averages over a spatially heterogeneously distributed relative humidity (Lazik et al., 2019). It is based on the selective steady-state diffusion of water vapor through closed semipermeable membrane tubes. The resulting pressure changes within the tubes are sensitive to the respective vapor pressures. One tube is exposed to the environment while two further tubes enable observing reference states of vapor pressure for same (p,T)-conditions. The relative humidity of interest follows immediately from the comparison of the measured pressure changes.

We show that the new type of membrane-based relative humidity sensor (MHS) is able to work without any external calibration. An important conclusion from our theory is that RH measurement using an MHS does not depend on temperature. This independence could be confirmed experimentally for laboratory conditions (temperature 22 to 28 °C, air pressure 993 to 1015 hPa). The comparison of our first laboratory prototype with calibrated RH reference sensors in a range of 4 to 100% RH proves the linearity of the measuring method and its accuracy.

A potential application is the improvement of water use efficiency in irrigated agriculture. As demonstrated in Goss and Madliger (2007) the RH readings can be converted to a water potential. If the sensor is buried in/above the root zone of an irrigated agricultural field, it can help schedule irrigation to maintain the water potential in the root zone within a range that maximizes the crop yield per volume of irrigation water. If the sensor is buried in dry soils, it may contribute to improved estimates of vapor-based water transport and groundwater recharge. In case large-scale data are needed that can realistically only be acquired by remote sensing, such data will probably require calibration with ground-truth data. Our technology can deliver such data with a much larger footprint than typical mm to cm -scale humidity sensors that measure the humidity within a measurement chamber with a volume below 1 cm³ that is in contact with a poorly defined but tiny soil volume.

Goss, K.-U., Madliger, M. (2007) Water Resources Research 43(5): W05433. doi: 10.1029/2006WR005197

Lazik, D., de Rooij, G.H., Lazik, D., Meissner, R. (2019) Sensors 19(23): 5073. doi: 10.3390/s19235073

How to cite: Lazik, D., de Rooij, G. H., Lazik, W., and Meissner, R.: Sensor for measuring the average of a spatial distribution of the relative air humidity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6852, https://doi.org/10.5194/egusphere-egu2020-6852, 2020.

Micro-nano-bubbles (MNBs) are tiny bubbles with diameters ranging from tens of nanometers to several tens of micrometers. Owing to their small diameter, MNBs have some characteristics. Compared with normal bubbles, MNBs have lower rising velocity and persist for long periods in the liquid phase. MNBs technology is proposed to use for various areas such as groundwater remediation, aquaculture, mass transfer. Although MNB generation methods and applied to problems are attracted, the continuous in-situ measurement technique has not researched well. An easy, continuous, and inexpensive method is desired for more efficiently using MNBs. In previous research, the dielectric constant of MNBs water was different from that of water. Therefore we hypothesized that continuous measurement of dielectric constant could be used to estimate MNBs in the water. The purpose of this study is to investigate the attempt to continuous measurement for MNBs. To measure dielectric constant, we used time domain reflectometry (TDR). A TDR probe (0.15 m long) was used with a cable tester (Model 1502C, Tektronix Inc.) in this study. We also used GS3 sensor (METER Group, Inc.) for water temperature measurement because the dielectric constant changed with temperature. Dielectric constant and water temperature were measured every 1 min during before and after MNBs generation. We conducted experiments with several MNBs generators. Measured dielectric constant changed before and after MNBs generation. Although estimated dielectric constant from water temperature differed from measured dielectric constant, both agreed about half day. It was suggested that simultaneous measurement of temperature and dielectric constant can estimate the amount of MNB in water.

How to cite: Aoki, S., Tamaki, M., and Noborio, K.: Trial of continuous measurement of micro-nano bubbles in water, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13879, https://doi.org/10.5194/egusphere-egu2020-13879, 2020.

How to cite: Zhou, Z., Shi, L., and Zha, Y.: Seeing Macro-dispersivity from Hydraulic Conductivity Field with Convolutional Neural Network, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3212, https://doi.org/10.5194/egusphere-egu2020-3212, 2020.

There is a long-lasting interest in obtaining the effective hydraulic conductivity functions of soil mixtures. The few available models to obtain hydraulic conductivity of mixtures are mostly empirical and applicable for saturated conditions. We propose a simple physical model based on the effective medium theory to calculate the effective hydraulic conductivity of soil mixtures with two or more components. The model incorporates the volumetric content of each mixture component and their hydraulic conductivity to calculate the effective conductivity of the mixture. The results of the model were compared with the measured hydraulic conductivity data obtained from the simplified evaporation method using the Hyprop device. Samples were prepared by packing homogeneous mixtures of different soil textures in cylinders with a volume of 250 cm³. Packed soil mixtures were saturated and exposed to evaporation in a climate controlled laboratory with constant air temperature and humidity. The results show an acceptable match between the measured and modeled hydraulic conductivity of the tested soil mixtures. The model can be used as a physical way to describe the effective hydraulic conductivity of mixtures in a wide range of moisture.

How to cite: Joshi, D. C., Naseri, M., and Durner, W.: A physical based model to describe effective hydraulic conductivity of the soil mixtures, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21173, https://doi.org/10.5194/egusphere-egu2020-21173, 2020.

Splash, which is the first stage of the water erosion, is a dynamic and complex phenomenon. The ejection of soil particles occurs within fractions of a second after the impact of a drop. The diameter of the deformation formed on the surface can be measured in millimeters. The complicated nature of the phenomenon necessitates the use of advanced equipment (high-speed cameras or surface scanners) and models for simplification of the subject of the study to analyze selected aspects of the splash.

The work presents the results of research in which glass beads were used as a soil model. The aim of the experiments was to determine the influence of the initial position of the deposit elements on their displacement as a result of a droplet impact.

A water drop with a diameter of 4.2 mm falling freely from a height of 1.5 m was used in the study. The beds were placed in aluminum rings with a diameter of 40 mm. The measurements were based on the initial and final position of the beads used as markers; these beads differed in color from the rest of the deposit. The source of data included pictures taken with a digital camera before and after the impact and control recordings made with high-speed cameras to correct possible errors. Additionally, some of the samples were scanned with a microtomograph, which allowed characterizing the surface deformation. Taking into account their structure, the beds used in the measurements were divided into two groups. The first one was used to analyze the influence of drops on individual elements - symmetrical patterns from colored beads were prepared on the sample surface; the second group was used to analyze the influence of drops on groups of elements - layers of beads with the same color were prepared on the surface of these samples.

Based on the experiment results, the movement of the deposit elements was divided into three types: displacement inside the area wetted by a drop, ejection, and placement on the crater rim. The initial location of the beads displaced over the greatest distances was a narrow ring covering the area from 4 to 8 mm from the point of the drop impact. It is worth noting that this area was associated with strong surface deformation. The use of "monolayers" helped to indicate that 97% of the beads ejected outside the ring with the deposit originated from the bed surface layer.

References

Mazur R., Ryżak M., Sochan A., Marciszuk K., Beczek M., Lamorski K., Bieganowski A., 2020. Surface deformation and displacement of bed elements during splash – Model tests. Catena 185, 104277

The study was partially funded from the National Science Centre, Poland in the frame of project no. 2014/14/E/ST10/00851.

How to cite: Mazur, R., Ryżak, M., Sochan, A., Marciszuk, K., Beczek, M., Lamorski, K., and Bieganowski, A.: Particle displacement due to splash - analysis based on glass bead deposits, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20742, https://doi.org/10.5194/egusphere-egu2020-20742, 2020.

Pedotransfer functions (PTFs) are widely used tools to predict soil properties across different spatial scales and are commonly built using regression-based techniques (e.g., multiple linear regression or regression trees) and, more recently, machine learning methods (e.g., artificial neural networks). In these techniques, soil material arising from different soil horizons are treated as independent samples despite the depth dependency that exists for horizons within individual pedons. Here we propose a new approach to build PTFs that takes into account the depth dependency of saturated hydraulic conductivity (K_sat) and refer to this type of depth-dependent PTFs as a “pedontranfer” function (PnTF). Slope (β₁) and intercept (β₀) parameters describing the relationship of log-scale K_sat with soil horizon depth were fit to pedons selected from the Pedogenic and Environmental DataSet (PEDS). The intercept parameter can be interpreted as the K_sat at a 0 cm depth (i.e., K_sat at the soil surface) and β₁ as the rate of change of K_sat with respect to depth. In order to build the PnTF, we used field-based pedon information from PEDS, encompassing approximately 2,000 pedons and >13,000 soil horizons across the United States and estimated K_sat using a generalized Kozeny-Carman equation. Our results show a strong negative linear relationship between β₁ and β₀ (r² = 0.80; P < 0.01). When we predicted the fitted line of the linear relationship between β₁ and β₀ using a multiple linear regression with different soil and climatological variables we found a significant (P < 0.01) and direct relationship, with relatively good agreement (R² = 0.38). Our results suggest that the PnTF approach represents a step forward in the development of the next generation of PTFs, although further research is needed to improve its precision and accuracy. We believe that PnTFs, in principle, have significant advantages over PTFs that should be of interest to the community of developers and users of Earth system and community land models. For example, soil K_sat at depth may be predicted from knowledge only of the surface K_sat since β₁ can be predicted from β₀. Future work should incorporate other soil databases in order to account for systematic biases of the different methods to measure or estimate K_sat.

How to cite: Cueva, A., Hirmas, D. R., Nemes, A., and Sullivan, P. L.: From Pedo to Pedon: Towards the next generation of transfer functions to estimate saturated hydraulic conductivity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12699, https://doi.org/10.5194/egusphere-egu2020-12699, 2020.

As they mostly deal with undisturbed samples, soil hydrophysics analyses often present variability in their results. No one can deny that soil, and particularly structured soil, is a very complex and challenging media to describe. But it remains that the lab measurements themselves deserve attention. To what extent are they reproducible? To what extent different labs following the same protocol do they provide the same results for a given soil sample? Is this uncertainty quantifiable? Is there a way to standardize or harmonize the analyses? And of course, to what extent does it really matter when it comes to produce reliable information about i.e. drought consequences?

When most of the labs related to chemical analyses can rely on ring tests to improve their capacity, soil physics labs can’t. Building reference samples that could fit into classical measurement devices is one of the options that could allow to run ring tests in soil physics measurements.

The poster will present an attempt to develop reference samples in view to measure the wet end of the retention curve.

How to cite: Degré, A., Pomes-Bordedebat, A., and Belazereg, I.: Test of possible standard samples for soil physical analyses, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9463, https://doi.org/10.5194/egusphere-egu2020-9463, 2020.

The EFRE-Project BigData@Geo, founded by the European Union, aims to create highly resolved climate projections for the model region of Lower Franconia in Bavaria, Germany. These projections are analyzed and made available to local stakeholders of agriculture, forestry, and viniculture as well as the public. As recent regional climate models are not dealing with the necessary spatiotemporal resolution the model REMO will be developed in the project‘s frame in cooperation with the Climate Service Center Germany (GERICS).

For these very high resolutions, besides improvements like the non-hydrostatic atmosphere, higher resolved static land surface parameters, and land use land cover changes, etc., realistic modeling of the soil hydrology becomes absolutely necessary. Therefore, REMO is extended by a 5-layer soil scheme which is a first step to overcome restrictions of the recently used soil hydrology scheme due to the included vertical water flow. Furthermore, the current work also aims to implement lateral water flows between grid cells because this is the only way to model the soil hydrology appropriate to the project‘s question.

The current model version of REMO includes a bucket scheme that treats the soil hydrology as a single layer. The soil depth is equal to the rooting depth and, thus, depends on the overlying vegetation class. Consequently, the whole soil moisture of the soil is available for transpiration. Evaporation only occurs if the soil moisture reaches at least 90 % of the field capacity.

The 5-layer scheme has 5 layers with increasing thicknesses for deeper layers. The maximum depth of the soil is at approximately 10 m or the depth of the bedrock. Due to the existence of water below the rooting zone and the processes of capillary rise and percolation more water becomes available for transpiration compared to the bucket scheme. Furthermore, evaporation only occurs if the uppermost layer contains soil moisture which is a more realistic process representation as well.

First results of the comparison of the two schemes and with observation data in the EURO-CORDEX region and a german subregion are presented. We also show some sensitivity studies of the current improvements to the parameterizations of the 5-layer scheme which are necessary for the goal of incorporation of the lateral flow.

How to cite: Abel, D., Pollinger, F., Ziegler, K., and Paeth, H.: Extension of the regional climate model REMO by a 5-layer soil scheme, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2964, https://doi.org/10.5194/egusphere-egu2020-2964, 2020.

A robust solution to Richards' equation for complex soil hydraulic models using the Method Of Lines

Robust numerical solutions are required for automatic parameter estimation, uncertainty analysis of soil hydraulic models, but also to quantify and legitimate model complexity.
The Method Of Lines approach to solve Richards' equation has already be shown to be an efficient and stable alternative to established methods, namely 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 where further processes should be included in the modeling.

In this work a slightly modified Method Of Lines approach is used to solve the pressure based Richards' equation. A finite differencing scheme is applied to the spatial derivative and the resulting system of ordinary differential equations is reformulated as differential-algebraic system of equations (DAE). The open-source code IDAS from the Sundials suite is used to solve the DAE system. This solution has been extended to include hydraulic models that can account for hysteresis, dual-permeability and non-equilibrium effects. The different hydraulic model implementations have been verified against results from the software Hydrus and show good agreement with those.
Bayesian model selection techniques and the concept of the model confusion matrix can be used to examine the legitimacy of a given model's complexity with regards to available input data.
To generate the necessary data a Monte Carlo Sampling over a range of soil parameters was carried out for the models of different complexity. The computations were performed at the high-performance computing facilities at TU Dresden using the developed code.

The results of the analysis show the identifiability of the models, i.e. how well a model recognizes itself through Bayesian model selection when it was the one that has generated the data. This is a useful technique when building model ensembles for diagnostic or predictive purposes.

How to cite: Mietrach, R., Wöhling, T., and Schütze, N.: A robust solution to Richards' equation for complex soil hydraulic models using the Method Of Lines, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7663, https://doi.org/10.5194/egusphere-egu2020-7663, 2020.

     Understanding the rules of soil water movement under drip irrigation can provide data support and theoretical basis for developing precise drip irrigation strategies. In this study, a two-years-old Populus tomentosa plantation under surface drip irrigation on sandy loam soil was selected to measure the dynamics of soil water potential (ψ_s), wetting front and soil water content (θ) during irrigation and water redistribution periods were investigated in field experiments. Then, the observed data in the field were used to evaluate the accuracy and feasibility of the HYDRUS-2D/3D model for simulating the short-term soil water movement. Besides, the validated model was used to simulate the dynamics of wetting front under different initial soil water content (θ_i). During irrigation, the variation of ψ_s, horizontal and vertical movement distances of the wetting front, and θ within the wetting volume with irrigation duration could be described by the logistic function (R² = 0.99), the logarithm function (R² = 0.99), the power function (R² = 0.82), and the polynomial function (R² = 0.99), respectively. At the end of irrigation, the horizontal and vertical movement distances of the wetting front reached 22.9 cm and 37.3 cm, respectively. The ψ_s and θ within the soil wetting volume were 61.6% and 30.9% higher than those at the start of the irrigation, respectively, but the ψ_s decreased to its initial level about 120 hours later after the stop of irrigation. The average deviations of the horizontal and vertical wetting radius between the simulated and measured values were 1.3 and 4.5 cm, respectively. The mean RMSE and RMAE of HYDRUS-2D/3D for simulating θ at the end of irrigation and during water redistribution were 0.021 cm³∙cm^-3 and 9.7%, respectively. The movement distances of wetting front in the experimental plantation under various soil drought degrees (soil water availabilities were 40%, 60%, 73% and 80%) were obtained through scenarios simulations using HYDRUS-2D/3D. And it was found that the wetting front could move further under higher θ_i, and the movement distance of the wetting front was always smaller in the horizontal direction than in the vertical direction under different θ_i conditions. Consequently, HYDRUS-2D/3D can be used to well simulate the short-term soil water movement in drip-irrigated young P. tomentosa plantations on sandy loam soil. In addition, the constructed figure (describes the variations of the horizontal and vertical soil wetting distances with the irrigation duration) can be used to determine the reasonable irrigation duration for the plantations of P. tomentosa and other tree species on sandy loam soil.

How to cite: Li, D., Xi, B., and Jia, L.: Using HYDRUS 2D/3D to Evaluate Soil Water Movement in Drip-irrigated Young Populus tomentosa Plantations on Sandy Loam Soil, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11286, https://doi.org/10.5194/egusphere-egu2020-11286, 2020.