Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. In this paper, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.

Core Ideas: Understanding of preferential flow is improving, stimulated partly by new technologies. Empirical process understanding has outstripped the capability of models to predict. Better models must await future advances in computational power. In this update, we review some of the more significant advances that have been made in the last decade in the study of preferential flow through the vadose zone as well as suggest some research needs in the coming years. We focus mostly on work that aims to improve understanding of the processes themselves and less on more applied aspects concerning the various consequences of preferential flow (e.g., for surface water and groundwater quality). In recent years, the research emphasis has shifted somewhat toward the two extremes of the scale continuum, the pore scale and the scale of management (field, catchments, and landscapes). This trend has been facilitated by significant advances in both measurement technologies (e.g., noninvasive imaging techniques and high frequency–high spatial resolution monitoring of soil moisture at field and catchment scales) and application of novel methods of analysis to large datasets (e.g., machine learning). This work has led to a better understanding of how pore network properties control preferential flow at the pore to core scales as well as some new insights into the influence of site attributes (climate, land uses, soil types) at field to landscape scales. We conclude that models do not at present fully reflect the current state of process understanding and empirical knowledge of preferential flow. However, we expect that significant advances in computational techniques, computer hardware, and measurement technologies will lead to increasingly reliable model predictions of the impacts of preferential flow, even at the larger scales relevant for management.

Increasing the potential of soil to store carbon (C) is an acknowledged and emphasized strategy for capturing atmospheric CO₂. Well-recognized approaches for soil C accretion include reducing soil disturbance, increasing plant biomass inputs, and enhancing plant diversity. Yet experimental evidence often fails to support anticipated C gains, suggesting that our integrated understanding of soil C accretion remains insufficient. Here we use a unique combination of X-ray micro-tomography and micro-scale enzyme mapping to demonstrate for the first time that plant-stimulated soil pore formation appears to be a major, hitherto unrecognized, determinant of whether new C inputs are stored or lost to the atmosphere. Unlike monocultures, diverse plant communities favor the development of 30–150 µm pores. Such pores are the micro-environments associated with higher enzyme activities, and greater abundance of such pores translates into a greater spatial footprint that microorganisms make on the soil and consequently soil C storage capacity.

Due to inadequate data support, existing algorithms used to estimate soil hydraulic conductivity, K, in (eco)hydrological models ignore the effects of key site factors such as land use and climate and underplay the significant effects of soil structure on water flow at and near saturation. These limitations may introduce serious bias and error into predictions of terrestrial water balances and soil moisture status, and thus plant growth and rates of biogeochemical processes. To resolve these issues, we collated a new global database of hydraulic conductivity measured by tension infiltrometer under field conditions. The results of our analyses on this data set contrast markedly with those of existing algorithms used to estimate K. For example, saturated hydraulic conductivity, K_s, in the topsoil (< 0.3 m depth) was found to be only weakly related to texture. Instead, the data suggests that K_s depends more strongly on bulk density, organic carbon content and land use. In this respect, organic carbon was negatively correlated with K_s, presumably due to water repellency, while K_s at arable sites was, on average, ca. 2–3 times smaller than under natural vegetation, forests and perennial agriculture. The data also clearly demonstrates that clay soils have smaller K in the soil matrix and thus a larger contribution of soil macropores to K at and near saturation.

The characteristics of the soil macropore network determine the potential for fast transport of agrochemicals and contaminants through the soil. The objective of this study was to examine the relationships between macropore network characteristics, hydraulic properties and state variables and measures of preferential transport. Experiments were carried out under near-saturated conditions on undisturbed columns sampled from four agricultural topsoils of contrasting texture and structure. Macropore network characteristics were computed from 3-D X-ray tomography images of the soil pore system. Non-reactive solute transport experiments were carried out at five steady-state water flow rates from 2 to 12 mm h−1. The degree of preferential transport was evaluated by the normalised 5% solute arrival time and the apparent dispersivity calculated from the resulting breakthrough curves. Near-saturated hydraulic conductivities were measured on the same samples using a tension disc infiltrometer placed on top of the columns. Results showed that many of the macropore network characteristics were inter-correlated. For example, large macroporosities were associated with larger specific macropore surface areas and better local connectivity of the macropore network. Generally, an increased flow rate resulted in earlier solute breakthrough and a shifting of the arrival of peak concentration towards smaller drained volumes. Columns with smaller macroporosities, poorer local connectivity of the macropore network and smaller near-saturated hydraulic conductivities exhibited a greater degree of preferential transport. This can be explained by the fact that, with only two exceptions, global (i.e. sample scale) continuity of the macropore network was still preserved at low macroporosities. Thus, for any given flow rate, pores of larger diameter were actively conducting solute in soils of smaller near-saturated hydraulic conductivity. This was associated with larger local transport velocities and, hence, less time for equilibration between the macropores and the surrounding matrix which made the transport more preferential. Conversely, the large specific macropore surface area and well-connected macropore networks associated with columns with large macroporosities limit the degree of preferential transport because they increase the diffusive flux between macropores and the soil matrix and they increase the near-saturated hydraulic conductivity. The normalised 5% arrival times were most strongly correlated with the estimated hydraulic state variables (e.g. with the degree of saturation in the macropores R2 = 0.589), since these combine into one measure the effects of irrigation rate and the near-saturated hydraulic conductivity function, which in turn implicitly depends on the volume, size distribution, global continuity, local connectivity and tortuosity of the macropore network.

The connectivity of macropore networks is thought to exert an important control on preferential flow in soil, although little progress has been made towards incorporating an understanding of these effects into management-oriented flow and transport models. In principle, concepts from percolation theory should be well suited to quantify the connectivity of preferred flow pathways, but so far its relevance for natural soils in the field has not been tested. To investigate this question, X-ray tomography was used to measure soil pore space architecture at an image resolution of 65μm for 64 samples taken in two consecutive years in the harrowed and ploughed layers of a silt loam soil a few weeks after spring cultivation. The results showed that the pore networks displayed key features predicted by classical percolation theory: a strong relationship was found between the percolating fraction and the imaged porosity, with a percolation threshold of ca. 0.04 to 0.06m3m−3 in the harrowed layer. A percolation threshold was less clearly identifiable in topsoil that had not been recently tilled, although this may probably be attributed to finite size sampling effects in this layer, which showed a more heterogeneous and structured distribution of the pore space. Although further work on more strongly structured soil horizons, especially subsoils, would be desirable, it is tentatively suggested that percolation concepts could prove useful to estimate the conducting macroporosity in management models of preferential flow and transport