A Comprehensive Model for Single Ring Infiltration I: Initial Water Content and Soil Hydraulic Properties

2018 ◽  
Vol 82 (3) ◽  
pp. 548-557 ◽  
Author(s):  
Ryan D. Stewart ◽  
Majdi R. Abou Najm
Keyword(s):  
Water Content ◽  
Hydraulic Properties ◽  
Initial Water Content ◽  
Comprehensive Model ◽  
Soil Hydraulic Properties ◽  
Initial Water ◽  
Single Ring ◽  
Soil Hydraulic

Hyphal colonization of Rhizophagus irregularis increases unsaturated hydraulic conductivity of a loamy sand distant from roots

2021 ◽  
Author(s):  
Michael Bitterlich ◽  
Richard Pauwels
Keyword(s):  
Hydraulic Conductivity ◽  
Water Content ◽  
Hydraulic Properties ◽  
Volumetric Water Content ◽  
Rhizophagus Irregularis ◽  
Loamy Sand ◽  
Soil Hydraulic Properties ◽  
Unsaturated Hydraulic Conductivity ◽  
Soil Hydraulic ◽  
Root Exclusion

<p>Hydraulic properties of mycorrhizal soils have rarely been reported and difficulties in directly assigning potential effects to hyphae of arbuscular mycorrhizal fungi (AMF) arise from other consequences of AMF being present, i.e. their influence on growth and water consumption rates of their host plants that both also influence soil hydraulic properties.</p><p>We assumed that the typical nylon meshes used for root-exclusion experiments in mycorrhizal research can provide a dynamic hydraulic barrier. It is expected that the uniform pore size of the rigid meshes causes a sudden hydraulic decoupling of the enmeshed inner volume from the surrounding soil as soon as the mesh pores become air-filled. Growing plants below the soil moisture threshold for hydraulic decoupling would minimize plant-size effects on root-exclusion compartments and allow for a more direct assignment of hyphal presence to modulations in soil hydraulic properties.</p><p>We carried out water retention and hydraulic conductivity measurements with two tensiometers introduced in two different heights in a cylindrical compartment (250 cm³) containing a loamy sand, either with or without the introduction of a 20 µm nylon mesh equidistantly between the tensiometers. Introduction of a mesh reduced hydraulic conductivity across the soil volumes by two orders of magnitude from 471 to 6 µm d<sup>-1</sup> at 20% volumetric water content.</p><p>We grew maize plants inoculated or not with Rhizophagus irregularis in the same soil in pots that contained root-exclusion compartments while maintaining 20% volumetric water content. When hyphae were present in the compartments, water potential and unsaturated hydraulic conductivity increased for a given water content compared to compartments free of hyphae. These differences increased with progressive soil drying.</p><p>We conclude that water extractability from soils distant to roots can be facilitated under dry conditions when AMF hyphae are present.</p><p> </p>

Root effects on soil water and hydraulic properties

Biologia ◽  
2007 ◽  
Vol 62 (5) ◽  
Author(s):  
Horst Gerke ◽  
Rolf Kuchenbuch
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Water Content ◽  
Bulk Density ◽  
Soil Water ◽  
Soil Water Content ◽  
Hydraulic Properties ◽  
Soil Hydraulic Properties ◽  
Soil Hydraulic ◽  
Root Effects

AbstractPlants can affect soil moisture and the soil hydraulic properties both directly by root water uptake and indirectly by modifying the soil structure. Furthermore, water in plant roots is mostly neglected when studying soil hydraulic properties. In this contribution, we analyze effects of the moisture content inside roots as compared to bulk soil moisture contents and speculate on implications of non-capillary-bound root water for determination of soil moisture and calibration of soil hydraulic properties.In a field crop of maize (Zea mays) of 75 cm row spacing, we sampled the total soil volumes of 0.7 m × 0.4 m and 0.3 m deep plots at the time of tasseling. For each of the 84 soil cubes of 10 cm edge length, root mass and length as well as moisture content and soil bulk density were determined. Roots were separated in 3 size classes for which a mean root porosity of 0.82 was obtained from the relation between root dry mass density and root bulk density using pycnometers. The spatially distributed fractions of root water contents were compared with those of the water in capillary pores of the soil matrix.Water inside roots was mostly below 2–5% of total soil water content; however, locally near the plant rows it was up to 20%. The results suggest that soil moisture in roots should be separately considered. Upon drying, the relation between the soil and root water may change towards water remaining in roots. Relations depend especially on soil water retention properties, growth stages, and root distributions. Gravimetric soil water content measurement could be misleading and TDR probes providing an integrated signal are difficult to interpret. Root effects should be more intensively studied for improved field soil water balance calculations.

scholarly journals Bayesian inverse modelling of in situ soil water dynamics: using prior information about the soil hydraulic properties

2011 ◽  
Vol 8 (1) ◽  
pp. 2019-2063 ◽  
Author(s):  
B. Scharnagl ◽  
J. A. Vrugt ◽  
H. Vereecken ◽  
M. Herbst
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Vadose Zone ◽  
Hydraulic Properties ◽  
Prior Information ◽  
Hydraulic Parameters ◽  
Soil Hydraulic Properties ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

Abstract. In situ observations of soil water state variables under natural boundary conditions are often used to estimate field-scale soil hydraulic properties. However, many contributions to the soil hydrological literature have demonstrated that the information content of such data is insufficient to reliably estimate all the soil hydraulic parameters. In this case study, we tested whether prior information about the soil hydraulic properties could help improve the identifiability of the van Genuchten-Mualem (VGM) parameters. Three different prior distributions with increasing complexity were formulated using the ROSETTA pedotransfer function (PTF) with input data that constitutes basic soil information and is readily available in most vadose zone studies. The inverse problem was posed in a formal Bayesian framework and solved using Markov chain Monte Carlo (MCMC) simulation with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. Synthetic and real-world soil water content data were used to illustrate our approach. The results of this study corroborate and explicate findings previously reported in the literature. Indeed, soil water content data alone contained insufficient information to reasonably constrain all VGM parameters. The identifiability of these soil hydraulic parameters was substantially improved when an informative prior distribution was used with detailed knowledge of the correlation structure among the respective VGM parameters. A biased prior did not distort the results, which inspires confidence in the robustness and effectiveness of the presented method. The Bayesian framework presented in this study can be applied to a wide range of vadose zone studies and provides a blueprint for the use of prior information in inverse modelling of soil hydraulic properties at various spatial scales.

euptfv2: updated hydraulic pedotransfer functions for Europe

2021 ◽  
Author(s):  
Brigitta Szabó ◽  
Melanie Weynants ◽  
Tobias Weber
Keyword(s):  
Hydraulic Conductivity ◽  
Soil Properties ◽  
Water Content ◽  
Hydraulic Properties ◽  
Field Capacity ◽  
Pedotransfer Functions ◽  
Predictor Variables ◽  
Soil Hydraulic Properties ◽  
Matric Potential ◽  
Soil Hydraulic

<p>We present improved European hydraulic pedotransfer functions (PTFs) which now use the machine learning algorithm random forest and include prediction uncertainties. The new PTFs (euptfv2) are an update of the previously published euptfv1 (Tóth et al., 2015). With the derived hydraulic PTFs soil hydraulic properties and van Genuchten-Mualem model parameters can be predicted from easily available soil properties. The updated PTFs perform significantly better than euptfv1 and are applicable for 32 predictor variables combinations. The uncertainties reflect uncertainties from the considered input data, predictors and the applied algorithm. The euptfv2 includes transfer functions to compute soil water content at saturation (0 cm matric potential head), field capacity (both -100 and -330 cm matric potential head) and wilting point (-15,000 cm matric potential head), plant available water content computed with field capacity at -100 and -330 cm matric potential head, saturated hydraulic conductivity, and Mualem-van Genuchten parameters of the moisture retention and hydraulic conductivity curves. The influence of predictor variables on predicted soil hydraulic properties is explored and suggestions to best predictor variables given.</p><p>The algorithms have been implemented in a web interface (https://ptfinterface.rissac.hu) and an R package (https://doi.org/10.5281/ZENODO.3759442) to facilitate the use of the PTFs, where the PTFs’ selection is automated based on soil properties available for the predictions and required soil hydraulic property.</p><p>The new PTFs will be applied to derive soil hydraulic properties for field- and catchment- scale hydrological modelling in European case studies of the OPTAIN project (https://www.optain.eu/). Functional evaluation of the PTFs is performed under the iAqueduct research project.</p><p> </p><p>This research has been supported by the Hungarian National Research, Development and Innovation Office (grant no. KH124765), the János Bolyai Research Scholarship of the Hungarian Academy of Sciences (grant no. BO/00088/18/4), and the German Research Foundation (grant no. SFB 1253/12017). OPTAIN is funded by the European Union’s Horizon 2020 Program for research and innovation under Grant Agreement No. 862756.</p>

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