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Essential soil functions such as plant productivity, C storage, nutrient cycling and the storage and purification of water all depend on soil biological processes. Given this insight, it is remarkable that in modeling of these soil functions, the various biological actors usually do not play an explicit role. In this review and perspective paper we analyze the state of the art in modeling these soil functions and how biological processes could more adequately be accounted for. We do this for six different biologically driven processes clusters that are key for understanding soil functions, namely i) turnover of soil organic matter, ii) N cycling, iii) P dynamics, iv) biodegradation of contaminants v) plant disease control and vi) soil structure formation. A major conclusion is that the development of models to predict changes in soil functions at the scale of soil profiles (i.e. pedons) should be better rooted in the underlying biological processes that are known to a large extent. This is prerequisite to arrive at the predictive models that we urgently need under current conditions of Global Change.

The need to develop and provide integrated observation systems to better understand and manage global and regional environmental change is one of the major challenges facing Earth system science today. In 2008, the German Helmholtz Association took up this challenge and launched the German research infrastructure TERrestrial ENvironmental Observatories (TERENO). The aim of TERENO is the establishment and maintenance of a network of observatories as a basis for an interdisciplinary and long-term research programme to investigate the effects of global environmental change on terrestrial ecosystems and their socio-economic consequences. State-of-the-art methods from the field of environmental monitoring, geophysics, remote sensing, and modelling are used to record and analyze states and fluxes in different environmental disciplines from groundwater through the vadose zone, surface water, and biosphere, up to the lower atmosphere. Over the past 15 years we have collectively gained experience in operating a long-term observing network, thereby overcoming unexpected operational and institutional challenges, exceeding expectations, and facilitating new research. Today, the TERENO network is a key pillar for environmental modelling and forecasting in Germany, an information hub for practitioners and policy stakeholders in agriculture, forestry, and water management at regional to national levels, a nucleus for international collaboration, academic training and scientific outreach, an important anchor for large-scale experiments, and a trigger for methodological innovation and technological progress. This article describes TERENO’s key services and functions, presents the main lessons learned from this 15-year effort, and emphasises the need to continue long-term integrated environmental monitoring programmes in the future.

Here, we investigated the effects of biogas digestate application on flow pathways and soil properties in a sandy soil aiming at unraveling phosphorus accumulation and depletion processes in fertilized soils. Dye tracer experiments were conducted to visualize and distinguish between various flow pathways, while X-ray tomography was utilized to characterize the soil structure. The dye tracer experiments revealed differences between the control and the digestate-treated group of soil profiles in the top-soils although no statistical verification was possible amid a single plot per treatment. The stained soil profiles in both treatments indicate extensive areas of homogeneous and heterogeneous matrix flow. However, the digestate-treated group showed a decrease in homogeneous matrix flow and a notable presence of preferential flow with low interaction. The application of biogas digestate impacted various soil properties, including organic carbon content, water drop penetration time, and pH levels. Accordingly, the topsoil experienced an increase in soil organic carbon, water repellency, and a decrease in pH levels. The fraction of macropores also increased in the topsoil of the digestate-treated group, accompanied by an increase in tortuosity. Double lactate-extractable phosphorus (DL-P) distribution varied across the different flow pathways, with higher concentrations detected in matrix flow and a depletion observed in preferential flow regions in both treatments. These findings confirm the close relationship between the type of flow pathway and phosphorus distribution in soils. Additionally, a significant correlation was observed between pH levels and DL-P in the digestate-treated group, indicating potential implications for phosphorus availability. Overall, the results of this study suggest that the long-term application of biogas digestate is likely to improve soil properties as related to soil organic matter content, particularly in the topsoil of sandy soils. The

In 1991, at the launch of a national symposium devoted to soil structure, the Australian Society of Soil Science invited Professor John Letey to deliver a keynote address, which was later published in the society’s journal. In his lecture, he shared the outcome of his reflexion about what the assessment of soil structure should amount to, in order to produce useful insight into the functioning of soils. His viewpoint was that the focus should be put on the openings present in the structure, rather than on the chunks of material resulting from its mechanical dismantlement. In the present article, we provide some historical background for Letey’s analysis, and try to explain why it took a number of years for the paradigm shift that he advocated to begin to occur. Over the last decade, his perspective that soil structure needs to be characterised via nondestructive methods appears to have gained significant momentum, which is likely to increase further in the near future, as we take advantage of recent technological advances. Other valuable lessons that one can derive from Letey’s pioneering article relate to the extreme value for everyone, even neophytes, to constantly ask questions about where research on given topics is heading, what its goals are, and whether the methods that are used at a certain time are optimal

Das Kapitel: Geschichte der Bodenphysik und ihre Entwicklung in den verschiedenen Teilbereichen behandelt die Entwicklung in den letzten Jahrzehnten des 20. und im beginnenden 21. Jahrhundert. Zu Beginn werden die Prozesse der Gefügeentwicklung und deren Detektion sowie die damit einhergehenden Modellierungsansätze der Wasserflüsse analysiert, gefolgt von den ausführlichen Beschreibungen der Hydrophobie und der Interaktionen zwischen Bodenphysik und Biologie. Einen weiteren Schwerpunkt bilden die Prozesse in Torfböden, bevor in zwei ausführlichen Beiträgen die physikalisch-mechanischen Prozesse von der rheologischen bis zur Mesoskala – Labor- und Freilanduntersuchungen – zum Thema Belastbarkeit und Folgen für ökologische Bodenfunktionen behandelt werden. Den Abschluss bildet ein Beitrag zur Entwicklung der Geostatistik in der bodenphysikalischen Forschung.  The chapter: history of soil physics and its development in the different subfields deals with the development in the last decades of the 20th century and the beginning of the 21st century. At the beginning, the processes of microstructure development and their detection as well as the associated modeling approaches of water fluxes are analyzed followed by the detailed descriptions of hydrophobicity and the interactions between soil physics and biology. A further focus is on the processes in peat soils before two detailed contributions deal with the physical mechanical processes from the rheological to the mesoscale—laboratory and in situ—investigations of resilience and consequences for ecological soil functions. The paper concludes with a contribution on the development of geostatistics in soil physics research.

In this technical note, we introduce a web-based application, the BonaRes Knowledge Library (KLIB, https://klibrary.bonares.de, last access: 26 July 2023), for the compilation and classification of scientific publications on soil processes according to the specific site conditions and experimental boundary conditions. The tool was developed based on the understanding that experimental findings in soil science are highly dependent on soil type, land use, and climate. The KLIB, therefore, goes beyond other available digital libraries by providing metadata on the site conditions and experimental settings for each publication. A number of visualization tools have been developed in the form of graphical networks to illustrate, for example, publications sharing the same type of scientific questions or soil properties that are affected by different types of drivers. This should help to explore the contents of the literature database more efficiently in order to support and facilitate the literature search efforts of the users. The KLIB is designed as a collaborative effort to encourage soil scientists to participate by entering their own studies and extending the existing database.

Habitat for biodiversity is a crucial soil function. When assessed at large spatial scales, subjective assessment models are usually constructed by integrating expert knowledge to estimate soil biodiversity potentials (SBP) and predict their trends. However, these regional evaluation methods are challenging to apply mechanistically to other regions, especially in China, where soil biodiversity surveys are still in their infancy. Taking China (9.6 × 106 km2) as the study area, we constructed a Decision EXpert (DEX) multi-attribute decision model based on abiotic factors from soil and climate data that are known to be relevant for the habitat of soil biota. It was used to indirectly assess and map national SBP based on the habitat suitability for fungi, bacteria, nematodes, and earthworms in the topsoil. The results show: (1) the SBP in China was classified into five grades: low, covering 19.8% of the area, medium-low (21.2%), medium (16.0%), medium-high (38.5%), and high (4.5%); (2) the national SBP is at a moderate level, with hotspot areas (1.3 × 106 km2) located in the Yangtze Plain Region, the southeastern Southwest China Region, and the central-eastern South China Region; while the coldspot areas (2.6 × 106 km2) are located in the Gansu–Xinjiang Region and the northeastern Qinghai–Tibet Region; (3) Soil (pH, SOC, CEC, texture, total P, and C/N ratio) and climate (arid/humid regions, temperature zones) were identified as driving this SBP variation. This study presents a general approach to describing soil habitat function on a broad scale based on environmental covariates. It provides a systematic basis for selecting indicators and maps them to SBP from an objective perspective. This approach can be applied to regions where no soil organism survey is available and can also serve as a pre-survey for planning soil resource utilization and conservation.

The increasing demand for biomass for food, animal feed, fiber, and bioenergy requires optimization of soil productivity, while at the same time, protecting other soil functions such as nutrient cycling and buffering, carbon storage, habitat for biological activity, and water filter and storage. Therefore, one of the main challenges for sustainable agriculture is to produce high yields while maintaining all the other soil functions. Mechanistic simulation models are an essential tool to fully understand and predict the complex interactions between physical, biological, and chemical processes of soils that generate those functions. We developed a soil model to simulate the impact of various agricultural management options and climate change on soil functions by integrating the relevant processes mechanistically and in a systemic way. As a special feature, we include the dynamics of soil structure induced by tillage and biological activity, which is especially relevant in arable soils. The model operates on a 1D soil profile consisting of a number of discrete layers with dynamic thickness. We demonstrate the model performance by simulating crop growth, root growth, nutrient and water uptake, nitrogen cycling, soil organic matter turnover, microbial activity, water distribution, and soil structure dynamics in a long-term field experiment including different crops and different types and levels of fertilization. The model is able to capture essential features that are measured regularly including crop yield, soil organic carbon, and soil nitrogen. In this way, the plausibility of the implemented processes and their interactions is confirmed. Furthermore, we present the results of explorative simulations comparing scenarios with and without tillage events to analyze the effect of soil structure on soil functions. Since the model is process-based, we are confident that the model can also be used to predict quantities that have not been measured or to estimate the effect o

Hydraulic nonequilibrium in soil during water infiltration and drainage is a well-known phenomenon. During infiltration, water initially invades easily accessible pores before it slowly redistributes towards some state of energetic minimum. In analogy, during drainage, easily drainable pores are emptied more rapidly than those blocked by bottlenecks. The consequence is that the water content is lagging behind the water potential and both state variables do not follow a unique water retention curve as typically assumed when applying Richards equation. Current models that account for nonequilibrium allow for the required decoupling of water content and water potential; however, they do not consider the consequences for the hydraulic conductivity. In this contribution, we present a physically based approach to estimate hydraulic conductivity during nonequilibrium, which depends on both water content and water potential during nonequilibrium conditions. This approach of a dynamic hydraulic conductivity function is demonstrated for an infiltration process into relatively dry soil and for a stepwise drainage and rewetting with decreasing and increasing water fluxes (i.e., multistep flux experiment). The new approach reproduces well-known phenomena such as pressure overshoot and preferential flow across infiltration fronts using a unified concept for hydraulic conductivity. This was not possible with existing models assuming some fixed unsaturated conductivity function depending on either water content or water potential.

A 3–4D soil model represents a logical step forward from one-dimensional soil columns (1D), two-dimensional soil maps (2D), and three-dimensional soil volumes (3D) toward dynamic soil models (4D), with time as the fourth dimension. The challenge is to develop modeling tools that account for the states of soil properties, including the spatial structure of solids and pores, as well as their dynamics, including soil mass and solute transfers in landscapes. Our envisioned 3–4D soil model approach aims at improving the capability to predict fundamental soil functions (e.g., plant growth, storage, matter fluxes) that provide ecosystem services in the socioeconomic context. This study provides a structured overview on current soil models, challenges, open questions, and urgent research needs for developing a 3–4D soil model. A 3–4D soil model should provide an inventory of spatially distributed and temporally variable soil properties. As basis for this, we propose a mass balance model for the solid phase, which needs to be supplemented by a model describing its structure. This should eventually provide adequate 3D parameter sets for the numerical modeling of soil functions (e.g., flow and transport). The target resolution is decameters in the horizontal plane and centimeters to decimeters in the vertical direction to represent characteristic soil properties and soil horizons. The actual state of soils and their properties can be estimated from spatial data that represent the soil forming factors, with the use of machine learning tools. Improved modeling of the dynamics of soil bulk density, biological processes, and the pore structure are required to relate the solid mass balance to matter fluxes. A 3–4D soil model can be built from several types of modeling approaches. We distinguish between (1) process models that simulate mass balances, fluxes and soil structure dynamics, (2) statistical pedometric models using machine learning and geostatistics to estimate the soil in

Soil structure in terms of the spatial arrangement of pores and solids is highly relevant for most physical and biochemical processes in soil. While this was known for a long time, a scientific approach to quantify soil structural characteristics was also missing for a long time. This was due to its buried nature but also due to the three-dimensional complexity. During the last two decades, tools to acquire full 3D images of undisturbed soil became more and more available and a number of powerful software tools were developed to reduce the complexity to a set of meaningful numbers. However, the standardization of soil structure analysis for a better comparability of the results is not well developed and the accessibility of required computing facilities and software is still limited. At this stage, we introduce an open-access Soil Structure Library (https://structurelib.ufz.de/, last access: 22 July 2022) which offers well-defined soil structure analyses for X-ray CT (computed tomography) data sets uploaded by interested scientists. At the same time, the aim of this library is to serve as an open data source for real pore structures as developed in a wide spectrum of different soil types under different site conditions all over the globe, by making accessible the uploaded binarized 3D images. By combining pore structure metrics with essential soil information requested during upload (e.g., bulk density, texture, organic carbon content), this Soil Structure Library can be harnessed towards data mining and development of soil-structure-based pedotransfer functions. In this paper, we describe the architecture of the Soil Structure Library and the provided metrics. This is complemented by an example of how the database can be used to address new research questions.

Lateral subsurface flow (LSF) is a phenomenon frequently occurring in the field induced by local water saturation along horizon boundaries under nonequilibrium conditions. However, observations of LSF in undisturbed soils under controlled irrigation in the laboratory are limited but needed for model improvement, prediction, and quantification of LSF. We present a method for extracting an undisturbed soil monolith along a soil horizon boundary and introduce an experimental setup for the measurement of LSF and an irrigation device for simulating rainfall. An experimental test run was simulated using HYDRUS 2D. Water infiltrating into the monolith and flowing either laterally along the horizon boundary or vertically through the bottom horizon could be separately captured by suction discs at the side and the bottom. Thus, a clear distinction between lateral and vertical flow was possible. Pressure heads and water contents were recorded by tensiometers and frequency domain reflectometry (FDR) sensors distributed across the monolith in a regular two-dimensional, vertical, cross-sectional pattern. Sensor readings indicated the presence of nonequilibrium conditions within the monolith. Modeling results could reproduce the lateral and vertical outflow of the monolith under constant irrigation, thus showing that water flow within the monolith under steady-state conditions can be explained by the Richards equation and the van Genuchten-Mualem model. The presented method can be used to improve and verify models designed for the prediction of the onset of LSF including that induced by local nonequilibrium conditions.

The mechanical strength of agricultural soils depends on many soil properties and functions. The database, “soil strength and consequences for sustainable land use and soil management SOILMECHDAT-Kiel”, originates from the “Horn Research Group” includes analyses of undisturbed soil samples taken from more than 460 profiles in and is developed in collaboration with BONARES, a funding initiative of the German Federal Ministry for Education and Research that focuses on the sustainable use of soils. For over 40 years, over 42 different authors recorded 59 physical and 29 chemical parameters for complete soil profiles. In order to the aim of the initial analyses of this data is to determine the influence of bulk density (BD) organic matter (OM) and time (year) on precompression stress (Pc) and saturated hydraulic conductivity (ks) as a function of Pc. Three main textural groups sand, loam, and silt for both topsoils and subsoils (SS) were studied. In loamy and silty subsoils BD and OM are not related to Pc (R2 = 0.17 and R2 = 0.25). OM and bulk density are more related to Pc in sandy soils (R2 0.55–0.59). The link between ks and Pc showed that sandy soils have a significantly higher Pc (>150 kPa) and conductivities did not change much. In loamy soils, with a Pc > 90 kPa, 50% of the ks fell below the critical value of 10 cm d−1. For silty soils, at a Pc of 60 kPa, 50% of the data fall below the critical value of ks. These findings suggest that the stability of loamy and silty soils not only depends on OM and BD, but requires further data to explain the variation in the measurements. With respect to ks, the results show that fertile silty soils are more sensitive than formerly defined.