Modelling water dynamics in the rhizosphere
Introduction
The rhizosphere is defined as the region of soil over which plants have influence (Hartmann et al., 2008, Hiltner, 1904). The size of this region varies depending on the precise definition used. Typical sizes range from a fraction of a millimeter, when considering microbial interactions, to tens of millimeters when considering volatile root exudates (Gregory, 2006). The structural, chemical, biological and hydraulic properties of the rhizosphere are known to be significantly different to those in the surrounding bulk soil (Carminati et al., 2017, Dexter, 1987, Whalley et al., 2005).
Both plants and microbes engineer the rhizosphere in response to soil structure, water content and the availability of nutrients (Gregory, 2006). Growing roots compact the soil around them resulting in a reduced porosity adjacent to the roots (Dexter, 1987, Whalley et al., 2005). As they take up water plants drive wetting and drying in the soil, a process that increases soil structure formation (Grant and Dexter, 1989). Roots also excrete a range of organic compounds and shed root cap cells. These rhizodeposits inhibit competition (Czarnes et al., 2000, Walker et al., 2003), and promote or inhibit microorganisms (Baetz and Martinoia, 2014). Of the plant exudates, one of the most pertinent to rhizosphere water dynamics is mucilage. Secreted mucilage can form a layer that may diffuse into the rhizosphere to form a “rhizosheath” containing aggregated soil particles (Knee et al., 2001). The influence of mucilage can significantly alter the hydraulic properties of the rhizosphere (Carminati et al., 2010). Mucilage increases the area of root soil contact and thus increases the moisture supply to the plant (Yang et al., 2010). In addition, the high water-holding capacity of mucilage allows it to store up to 27 times its own mass in water (Capitani et al., 2013, Edmond Ghanem et al., 2010). As a result, mucilage can protect plant roots against diurnal soil water fluctuations, acute and osmotic stress, and the influence of saline environments (Morse, 1990, Yang et al., 2010).
The role of the rhizosphere in terms of water dynamics is difficult to quantify and has been the subject of many studies (Daly et al., 2015, Downie et al., 2014, Mooney et al., 2012) and recent reviews (Carminati et al., 2016, Oburger and Schmidt, 2016, Roose et al., 2016). Some studies suggest rhizosphere soil may be wetter than bulk soil (Young, 1995), whilst others suggest the opposite (Daly et al., 2015). This contradiction could be due to the hydration state of the soil, i.e., in dry conditions it has been found that the rhizosphere is wetter than the surrounding soil, whilst in saturated conditions the rhizosphere has been found to be drier (Carminati, 2012, Moradi et al., 2011). However, at least part of the difficulty associated with these measurements is that, from a physical perspective, it is difficult to disentangle rhizosphere soil from bulk soil.
There are a range of different dynamic processes that occur in the rhizosphere on different spatial and temporal scales. These range from fast equilibration of air-water menisci on the pore-scale, slower variations in saturation on the macro-scale, and modification of the soil structural properties on the pore scale. As all these processes influence water dynamics, it is natural to ask the question: how do processes occurring on multiple temporal and spatial scales influence water dynamics in the rhizosphere and, hence, root water uptake? In this review we focus on several key aspects of water movement in the rhizosphere and how these dynamics can be understood using image based modelling and upscaling to link different spatial and temporal scales.
Image based modelling refers to the technique of extracting geometries from, and solving equations on a series of images to predict properties. In discussing the application of these methods to the rhizosphere, we must first consider the scale on which we are working. Typically, image based models can be classified as being on the pore scale or the root scale, depending on the precise features which they resolve. On the pore scale, image based modelling can be further classified into network based modelling or direct modelling (Blunt, 2001, Blunt et al., 2013). Pore network models are predicated on the idea that a representative pore network, consisting of pores with fixed but not necessarily cylindrical shape (Blunt, 2001), can be extracted from the image instead of explicitly considering the pore scale geometry (Fatt, 1956). The governing equations for fluid flow in an individual pore can then be solved in this idealized geometry, and the overall network behavior can be calculated without taking the precise details of the geometry into account. For a review see Cnudde and Boone (2013).
The alternative approach of direct modelling refers to a direct implementation of equations on geometries obtained from the images. Specifically relating to soils, image based modelling studies include, but are not limited to, flow modelling (Dal Ferro et al., 2015, Daly et al., 2015, Scheibe et al., 2015, Tracy et al., 2015), transport modelling (Daly et al., 2016, Keyes et al., 2013, Masum et al., 2016) and modelling the effects of soil compaction on Darcy flow (Aravena et al., 2010, Aravena et al., 2014). On the plant-root scale there are numerous models for water uptake, detailed in reviews by Roose and Schnepf (2008) and Vereecken et al. (2016). Spatially explicit image based models for root water uptake are relatively recent and are based on 2D imaged or idealised architectures (Doussan et al., 2006, Koebernick et al., 2015). Such models have also been realized in three dimensions based either on spatially averaged uptake terms (Dunbabin et al., 2013, Koebernick et al., 2015) or by representing the root with an explicit three dimensional boundary (Daly et al., 2017).
Whilst the focus of the review is modelling, we also discuss how soil imaging restrictions affect our understanding of rhizosphere water dynamics, and how these limitations might be overcome. In general, the multi-scale nature of the air, water and soil solid phases observed in the rhizosphere will significantly alter the description of physics in this region. Specifically, on the pore scale we observe different regions of air and water that interact and flow about the soil; on the macro-scale we see an average of these quantities described by the saturation. We will base the review around a recently developed method through which Richards’ equations can be derived and parameterized based on images obtained via X-ray Computed Tomography (Daly and Roose, 2015). We will review how the contact angle, surface tension, viscosity and geometry affect the macro-scale parameters in this model and discuss the implications of these observations. In addition, we will show that hydraulic properties of soils are highly sensitive to noise, image processing techniques and the physical assumptions used. This we illustrate through calculations of the water release curve and permeability for saturated and partially saturated soils.
Section snippets
Soil water dynamics
The more traditional mathematical models applied to study water dynamics in the rhizosphere are based on macro-scale measurements and observations. In this review we shall consider the macro-scale to be synonymous with the root or soil continuum scale. The scales we consider in this review are defined in Table 1. However, the current drive to consider how small scale features affect large scale observations means that a new generation of measurement techniques are required to parameterize
The effect of soil properties on rhizosphere water dynamics
Before we describe how image based modelling can be extended to partially saturated flow in the rhizosphere we consider how changes in soil parameters affect porosity, permeability and the water release curve. These parameters can all be influenced by plants and plant exudates such as mucilage (Aravena et al., 2010, Carminati et al., 2017, Carminati et al., 2016, Koebernick et al., 2017, Naveed et al., 2017).
Illustrative example
We now consider an illustrative example that highlights the importance of soil properties in the rhizosphere and how its effects can be captured and upscaled using image based modelling. As illustrated for single phase flow in Section 2.2, the method of homogenization provides a link between what we observe on the micro-scale and what is measured and observed on the macro-scale. In order to link macro-scale flow properties and observations to the physical parameters and measurements on the
Conclusions
Soil water dynamics is complex and our ability to predict water dynamics on the plant scale depends on our ability to accurately observe and measure what happens at the pore scale. Image based modelling provides a tool which enables pore scale measurements and observations to be upscaled in order to provide information on the plant scale.
In the rhizosphere, soil water dynamics become even more complicated as the physical properties of soil can vary significantly from bulk soil. In this review
Acknowledgements
KRD, SDK, AvV and TR are funded by ERC Consolidator grant 646809 (Data Intensive Modelling of the Rhizosphere Processes). NK and LC are funded by BBSRC grant BB/L026058/1 (Rhizosphere by design: breeding to select root traits that physically manipulate soil). SDK is also supported by a University of Southampton New Frontiers Fellowship. JE is funded by the University of Nevada Reno Vice President of Research and Innovation. The authors acknowledge the use of the IRIDIS High Performance
References (143)
- et al.
Pore-scale contact angle measurments at reservoir conditions using X-ray microtomography
Adv. Water Resour.
(2014) - et al.
Root exudates: the hidden part of plant defense
Trends Plant Sci.
(2014) Flow in porous media - pore-network models and multiphase flow
Curr. Opin. Colloid Interface Sci.
(2001)- et al.
Pore-scale imaging and modelling
Adv. Water Resour.
(2013) - et al.
The extent of errors associated with contact angles 3. The influence of surface roughness effects on angles measured using a Wilhelmy plate technique for powders
Coll. Surf. A: Physicochem. Eng. Asp.
(1995) - et al.
High-resolution X-ray computed tomography in geosciences: a review of the current technology and applications
Earth-Sci. Rev.
(2013) - et al.
Application of smoothed particle hydrodynamics (SPH) and pore morphologic model to predict saturated water conductivity from X-ray CT imaging in a silty loam Cambisol
Geoderma
(2015) - et al.
Soil moisture measurement by an improved capacitance technique, Part I. Sensor design and performance
J. Hydrol.
(1987) - et al.
Mucilage and polysaccharides in the halophyte plant species Kosteletzkya virginica: localization and composition in relation to salt stress
J. Plant Physiol.
(2010) - et al.
Effect of scanning and image reconstruction settings in X-ray computed microtomography on quality and segmentation of 3D soil images
Geoderma
(2013)
Imaging and image processing in porous media research
Adv. Water Resour.
Multiple pixel-scale soil water retention curves quantified by neutron radiography
Adv. Water Resour.
Minimum error thresholding
Pattern Recognit.
A review of approaches for evapotranspiration partitioning
Agric. For. Meteorol.
Re-examination of the equations of poroelasticity
Int. J. Eng. Sci.
Extraction of three-dimensional soil pore space from microtomography images using a geometrical approach
Geoderma
New methods to unravel rhizosphere processes
Trends Plant science
Handbook of Mathematical Functions: with Formulas, Graphs, and Mathematical Tables
Measurements of water uptake of maize roots: the key function of lateral roots
Plant Soil
Diffuse-interface methods in fluid mechanics
Annu. Rev. Fluid Mech.
Effects of root-induced compaction on rhizosphere hydraulic properties-x-ray microtomography imaging and numerical simulations
Environ. Sci. Technol.
Synchrotron X-ray microtomography—new means to quantify root induced changes of rhizosphere physical properties
Soil–Water–Root Processes: Adv. Tomogr. Imaging
Quantifying coupled deformation and water flow in the rhizosphere using X-ray microtomography and numerical simulations
Plant Soil
Trainable weka segmentation: a machine learning tool for microscopy image segmentation
Neuroscience
Trainable weka segmentation: a machine learning tool for microscopy pixel classification
Bioinformatics
Convergent approaches to determine an ecosystem's transpiration fraction
Global Biogeochem. Cycles
Measuring soil water content: a review
HortTechnology
Evaporation into the Atmosphere. Theory, History, and Applications
Poroelasticity equations derived from microstructure
J. Acoust. Soc. Am.
Microstructure, chemical composition and mucilage exudation of chia (Salvia hispanica L.) nutlets from Argentina
J. Sci. Food Agric.
A model of root water uptake coupled with rhizosphere dynamics
Vadose Zone J.
When roots lose contact
Vadose Zone J.
Dynamics of soil water content in the rhizosphere
Plant Soil
Biophysical rhizosphere processes affecting root water uptake
Ann. Bot.
Liquid bridges at the root-soil interface
Plant Soil
An Introduction to Homogenization
Fluid flow in porous media using image based modelling to parametrise Richards' equation
Proc. R. Soc Lond. USA
Pore shape and organic compounds drive major changes in the hydrological characteristics of agricultural soils
Eur. J. Soil Sci.
Root- and microbial-derived mucilages affect soil structure and water transport
Eur. J. Soil Sci.
Multiscale modelling of hydraulic conductivity in vuggy porous media
Proc. R Soc. Lond A Math. Phys. Sci.
Homogenization of two fluid flow in porous media
Proc. R Soc. Lond A Math. Phys. Sci.
Assessing the influence of the rhizosphere on soil hydraulic properties using X-ray Computed Tomography and numerical modelling
J. Exp. Bot.
Image-based modelling of nutrient movement in and around the rhizosphere
J. Exp. Bot.
Quantification of root water uptake in soil using X‐ray computed tomography and image based modelling
Plant Cell Environ.
Streamside trees that do not use stream water
Nature
Global soil moisture patterns observed by space borne microwave radiometers and scatterometers
Surv. Geophys.
Compression of soil around roots
Plant Soil
Cited by (15)
Dynamic hydrological niche segregation: How plants compete for water in a semi-arid ecosystem
2024, Journal of HydrologyPerspectives from the Fritz-Scheffer Awardee 2020—The mutual interactions between roots and soil structure and how these affect rhizosphere processes<sup>#</sup>
2022, Journal of Plant Nutrition and Soil ScienceX-ray Imaging of Root–Soil Interactions
2022, X-ray Imaging of the Soil Porous ArchitectureIntegrating X-ray CT Data into Models
2022, X-ray Imaging of the Soil Porous ArchitecturePlant-soil modelling
2021, Annual Plant Reviews Online