Modelling water dynamics in the rhizosphere

Abstract

We review the recent progress in the use of image based modelling to describe water dynamics in the rhizosphere. In addition, we describe traditional modelling and experimental methods, and how images obtained from X-ray Computed Tomography can be used in combination with direct pore-scale modelling to answer questions on water movement in the rhizosphere. The focus of this review is on the need for micro-scale experiments to parameterize image-based modelling on the pore-scale, and to show how variations in these parameters can lead to different macroscopic parameters when considering the movement of water on the plant scale. We finish the review with an illustrative example which highlights the importance of fluid-to-fluid contact angle, and the need for care in image preparation when using detailed models of this type.

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.