Soil organic carbon (SOC) plays a large role in sustainable soil management and climate change mitigation. To understand the potential of soils to sequester additional carbon requires detailed knowledge of the underlying processes and drivers. In this study, we use soil evolution model SoilGen3.8.2 to assess the effects of environmental drivers (bioclimate, erosion level and land use) and four protection mechanisms on long-term SOC dynamics. The protection mechanisms (aggregation, clay mineralogy, microporosity and metal oxyhydroxides, MOOHs) showed large differences with different temporal patterns, where aggregation and clay mineralogy dominated during 10 ka of pedogenesis and MOOHs had a negligible effect. Ranking internal and external controls on SOC stocks revealed a decreasing influence of bioclimate > protection mechanism > erosion rate > land use > time. Topsoil and subsoil SOC recovery after agricultural use revealed different dynamics, controlled by the history of environmental drivers and pedogenesis. Natural SOC recovery showed lowest rates for subsoils and highest rates for topsoils, with a strong control of erosion and pedogenetic history. The addition of ground rock of different mineralogies to enhance SOC sequestration had some effect, mainly for goethite, montmorillonite and a temporary effect of calcite. Our simulations demonstrate how SoilGen can improve understanding of soil processes, while also highlighting knowledge gaps, such as missing experimental insights in key SOC stabilization mechanisms. Our study shows that soil models such as SoilGen cannot act as digital twins of a soil that represent the entire soil, as not all processes and parameters of the complex soil system are represented. These models can, however, form the basis of topical digital twins that target specific processes or properties. We provide a roadmap for developing such topical digital twins and recommend to start from a complex model that accounts for pedogenetic history.

Most process-based models of soil development with explicit water transfer are based on an assumption of constant soil volume over time. Nevertheless, the consequences of this simplification on model outputs are not negligible when used on a several decades to a century time scale since, over such a time scale, soils experience strain due to multiple processes, which results in significant change in soil volume over depth and time. We propose in this paper a new approach to considering volume change in a process-based model of soil evolution over short to medium time scales (10 to 70 years). The model takes into account the feedbacks among processes responsible for soil evolution including soil organic carbon dynamics as well as transfer of water, heat and gas while considering the impacts of climate change as well as human activities on soil. To replace the constant volume hypothesis, we introduce in the model an estimation, by a pedotransfer function, of the bulk density that was then used to estimate soil volume in the model. The feasibility of this approach was demonstrated using a simple bulk density pedotransfer function based on soil organic carbon content for three long-term experiment sites with different scenarios of land use or tillage practices on Haplic Luvisols in the north of France. Both versions of the model (constant and changing volume) were tested. Soil dilation was predicted over the top soil (<15 cm) when the tillage practices were reduced. Conversion from agriculture to pasture induced an expansion of all layers of the soil profile. Hydraulic properties of the soil were also impacted by the volume change. Over longer time scales, other pedotransfer functions accounting for the impact of various pedological processes on bulk density should be implemented along with the inclusion of other processes responsible for volume change in order to accurately represent the retroactions between the soil volume and the processes affecting its development.

Historical pathways are described that led to today's soil- and soilscape development models. Distinction is made between functional models and mechanistic models. Functional models describe the result of soil development using the factors of soil formation. These models are widely applied in soil mapping. Mechanistic models describe the processes behind the soil development; the current ones are quantitative and are mainly applied to describe the effects of global change on soils and the critical zone. The object that is modelled may be either the pedon or the soilscape, with at present still marked differences in process coverage and inclusion of transport processes.

This book gives an overview of what such model should entail, with ample descriptions of an implementation of such model, SoilGen

This chapter specifies the processes in SoilGen. The (re-)distribution of mass of elements, gas and water requires the simulation of various transport processes, and these are driven by variations at the soil boundary. The landscape context affects effective infiltration per unit area and is mimicked by slope, its exposition and the main wind direction. Clay transport is simulated. Various processes influencing element cycling are included: the organic and inorganic C-cycles, and the effect of the plant-driven nutrient pump. Processes affecting the solid phase are chemical precipitation and dissolution, weathering and neoformation of minerals and physical weathering. Soil production from bedrock is simulated as a combination of these processes. Plant-related processes are including the water cycle, root distribution and its growth and the nutrient pump effect. Mixing processes such as bioturbation and tillage are an additional form of mass redistribution. Methods to update the CEC, soil texture, bulk density and transport parameters after mass redistributions are described. Simple case studies are included to illustrate weathering and neoformation of soil minerals and soil production.

Hands-on model application requires a description of how to create and edit input files and run the program. This chapter gives a step-by-step guideline on the usage of the graphical user interface for (i) the creation and editing of the files describing the initial situation, and (ii) the creation of the files containing the external forcings.

The limitations of SoilGen are described in terms of maximum simulation period, model discretization and stability issues. The latter are often associated with unrealistic inputs. Approaches to dealing with spatial heterogeneity with a pedon model as well as the assessment of prediction accuracy are discussed. To improve model accuracy, calibration preceded by a sensitivity analysis is useful. Both are discussed in general terms and also a case on parametrizing the clay migration sub-model is elaborated.

A definition is given of what a soil development model entails. Five types of users of soil development models are identified and what their purposes with such model may be. The main sections of this book are introduced.

The capability of any soil development model to simulate the effects of global change is demonstrated by its ability to explain the diversity of soils worldwide, as these result from various histories of global change. In literature, 17 generalized soil formation processes were distinguished to explain this diversity. The relevance of these generalized processes to model the effects of global change is specified, with associated physico-chemical processes.

The soil development model SoilGen is introduced. Four purposes of the pursued model are named, and the consequences for model functionality are identified. These purposes are: (i) its potential use to interpolate the soil status along the pathway from parent material to soil or critical zone in response to external forcings; (ii) its ability to accommodate both yearly and within-yearly variations of at least the climate parameters; (iii) its ability to represent a wide range of processes with different temporal dynamics and their mutual feedbacks; (iv) a maximized process coverage and, in case of incomplete knowledge, the possibility to include user input or empirical formulations instead.

The loess-paleosol sequences in the Chinese Loess Plateau (CLP) are an important terrestrial paleoclimate record. However, quantitative understanding of the response of paleosol development to various climate and environmental factors remains poor. Based on simulations with combined soil-climate models (SoilGen2-LOVECLIM1.3), this study investigates the sensitivity of paleosol development to different soil forming factors as well as the influence of ice sheets and astronomical forcing during the interglacials of the past 500 ka. Sensitivity analyses show that precipitation, dust addition and evapotranspiration are the dominant factors controlling the interglacial paleosol formation, but their relative importance varies between intergalcials and for different soil properties such as calcite and clay contents. Our results show that the simulated S1, S2, S3, S5-1 paleosols, which correspond to MIS 5, 7, 9 and 13 respectively, exhibit strong relationship with precession through its control on precipitation, whereas the precession signal is weak in the simulated S4 paleosol, in line with the weak precession variation during MIS 11. The results also show variable length of lags between different soil properties and precession and also in different interglacials. The lag between the simulated calcite and precession is shorter than that of clay. Moreover, clay content also shows strong relation with temperature during MIS 5 and MIS 13. Large ice sheets in the early and late phases of the interglacials have substantial impact on both temperature and precipitation in the CLP and thus on carbonate leaching and clay migration. Therefore, the simulated paleosols result mainly from the joint effect of precession and ice sheets via their control on local climate, and they show qualitative agreement with observations.

We assessed long-term trends in soil organic carbon (SOC) in volcanic soils with a process-based soil genesis model, SoilGen2.25. The relation between soil geochemistry and SOC was applied in a model context, where significant soil properties were identified and used to modify the decay rates of SOC pools. We used data from Indonesian sites with different land use (tropical primary forest, secondary pine forest, and agricultural land) and calibrated major soil processes in volcanic soils, viz. clay migration and weathering of primary minerals. The model evaluated the decay rates of SOC pools using three calibration approaches: (i) a site-specific calibration, (ii) a generic calibration, and (iii) a generic calibration modified by a geochemical proxy. The best calibration for each approach was then used to estimate the future of SOC under different climate projection scenarios, viz. representative concentration pathways (RCP) 2.6 and 8.5. The SoilGen2.25 model was generally sensitive to the change of selected soil process parameters. A four-pool SOC model (Roth-C) with site-specific decay rates best reproduced total SOC with a percentage difference between measured and simulated SOC between 1 and 10%. Application of a geochemical proxy to modify the generic rate calibration also improved, relative to a generic calibration, the simulation quality of the included humus pool and total SOC in most study sites. Agricultural soil showed higher susceptibility to global warming (i.e. RCP 8.5) than forest soils. Projective scenarios based on the three calibration scenarios highlighted the importance of the calibration method on the accuracy of SOC projection.

Abstract. Inclination and spatial variability in soil and litter properties influence soil greenhouse gas (GHG) fluxes and thus ongoing climate change, but their relationship in forest ecosystems is poorly understood. To elucidate this, we explored the effect of inclination, distance from a stream, soil moisture, soil temperature, and other soil and litter properties on soil–atmosphere fluxes of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) with automated static chambers in a temperate upland forest in eastern Austria. We hypothesised that soil CO2 emissions and CH4 uptake are higher in sloped locations with lower soil moisture content, whereas soil N2O emissions are higher in flat, wetter locations. During the measurement period, soil CO2 emissions were significantly higher on flat locations (p<0.05), and increased with increasing soil temperature (p<0.001) and decreasing soil moisture (p<0.001). The soil acted as a CH4 sink, and CH4 uptake was not significantly related to inclination. However, CH4 uptake was significantly higher at locations furthest away from the stream as compared to at the stream (p<0.001) and positively related to litter weight and soil C content (p<0.01). N2O fluxes were significantly higher on flat locations and further away from the stream (p<0.05) and increased with increasing soil moisture (p<0.001), soil temperature (p<0.001), and litter depth (p<0.05). Overall, this study underlines the importance of inclination and the resulting soil and litter properties in predicting GHG fluxes from forest soils and therefore their potential source-sink balance.

Land use is recognized to impact soil geochemistry on the centennial to millennial timescale, with implications for the distribution and stability of soil organic carbon (SOC). Young volcanic soils in tropical areas are subject to much faster pedogenesis, noticeable already on the centennial or even decadal timescale. As land use is a recognized factor for soil formation, it is thus conceivable that even relatively recent land use conversion in such areas would already bear a significant impact on the resulting formed soils., e.g., in terms of content of pedogenic oxides. Very scarce observational evidence exists, so such indirect implications of land use on SOC cycling are largely unknown. We here investigated SOC fractions, substrate-specific mineralization (SOC or added plant residue), and net priming of SOC as a function of forest or agricultural land use on Indonesian volcanic soils. The content of oxalate-extracted Al (Alo) correlated well with organic carbon (OC) associated with sand-sized aggregates, particularly in the subsoil. The proportion of SOC in sand-sized ultrasonication-resistant (400 J mL−1) aggregates was also higher in agricultural land use compared to pine forest land use, and a likewise contrast existed for Alo. These combined observations suggest that enhanced formation of Al (hydr)oxides promoted aggregation and physical occlusion of OC. This was, importantly, also consistent with a relatively lesser degradability of SOC in the agricultural sites, though we found no likewise difference in degradability of added 13C-labeled ryegrass or in native SOC priming between the pine forest and agricultural land uses. We expected that amorphous Al content under agricultural land use would mainly have promoted mineral association of SOC compared to under pine forest land use but found no indications for this. Improved small-scale aggregation of tropical Andosols caused by conversion to agriculture and high carbon input via organic fertilizer may thus partially counter the otherwise expectable decline of SOC stocks following cultivation. Such indirect land use effects on the SOC balance appeared relevant for correct interpretation and prediction of the long-term C balance of (agro)ecosystems with soil subject to intense development, like the here-studied tropical Andosols.

We quantified some mental and qualitative concepts about the soil-landscape relationships by numerical analysis of landforms in soil identification using diversity indices and conditional probability with a given sample size in Darab and Khosuyeh plains (a rural district) in the south of Iran in Fars province. The geomorphology map was prepared based on the Zinck method and used as a basic design for soil sampling. Finally, 200 soil profiles (0-150 cm) were excavated and described. Diversity indices and conditional probability were calculated based on soil taxonomic and geomorphological hierarchies. The results showed that diversity indices increase from landscape to landform level. The lowest and highest diversity indices were obtained at each geomorphic level for the soil order and soil family. The geomorphic diversity based on the soil taxonomy hierarchy showed that soil orders, including Entisols and Inceptisols, are observed in various landscapes and landforms. In contrast, some soil classes, such as Mollisols and its lower levels (suborder, great group, etc.), did not have geomorphic diversity. The conditional probability based on the geomorphological hierarchy indicated that the presence possibility of specific soil at the higher level (landscape) is less than, the lower level (landform), which indicates the more homogeneity of soils at lower geomorphic levels. However, the probability of observing a certain geoform increased according to the soil classification hierarchy, consistent with the results of diversity indices. The efficiency of diversity indices and conditional probability in showing the distribution and possibility of soil separation depends on the alignment of soil and geomorphological processes and the diagnosis of these processes.

Soil development models exist at the pedon scale and the landscape scale. Both groups of models have developed along different pathways, and still differ in the processes covered, state of testing and application domain. An overview of different models indicates that their application domains are converging to simulation of global change scenarios. Prerequisites are that these soil(-scape) models take climate and land use change as input at their upper model boundary, and that they allow the simulation of soil hydrology.

The sensitivity of chemical weathering to climatic and erosional forcing is well established at regional scales. However, soil formation is known to vary strongly along catenas where topography, hydrology, and vegetation cause differences in soil properties and, possibly, chemical weathering. This study applies the SoilGen model to evaluate the link between the topographic position and hydrology with the chemical weathering of soil profiles on a north–south catena in southern Spain. We simulated soil formation in seven selected locations over a 20 000-year period and compared it against field measurements. There was good agreement between simulated and measured chemical depletion fraction (CDF; R2=0.47). An important variation in CDF values along the catena was observed that is better explained by the hydrological variables than by the position along the catena alone or by the slope gradient. A positive trend between CDF data and soil moisture and infiltration and a negative trend with water residence time was found. This implies that these hydrological variables are good predictors of the variability in soil properties. The model sensitivity was evaluated with a large precipitation gradient (200–1200 mm yr−1). The model results show an increase in the chemical weathering of the profiles up to a mean annual precipitation value of 800 mm yr−1, after which it drops again. A marked depth gradient was obtained for CDF up to 800 mm yr−1, and a uniform depth distribution was obtained with precipitation above this threshold. This threshold reflects a change in behaviour, where the higher soil moisture and infiltration lead to shorter water transit times and decreased weathering. Interestingly, this corroborates similar findings on the relation of other soil properties to precipitation and should be explored in further research.

Land use through its control on vegetation and fertilization can impact on soil geochemistry which in turn also influences the stabilization of soil organic carbon (SOC). Here, we assess soil organic carbon pools following a fractionation method by Zimmermann et al. (2007), and analyse the fate of SOC with a process-based soil genesis model, SoilGen2. We hypothesized that geochemical properties influenced the distribution of SOC and these properties can be applied in a model context to modify the decay rate of soil carbon pool. A set of volcanic soils data from Mt.Tangkuban Perahu and Mt. Burangrang in Indonesia covering different land uses (primary forest, pine forest, and agriculture) from Holocene age was used in this study. In the model, calibration was done sequentially including (i) weathering of amorphous and primary minerals, and (ii) decay of soil organic carbon. These processes are represented by various process parameters, and each simulation was run on a 8-10k year time scale. Our SOC fractionation study showed that the dominant SOC pool was located in sand-aggregate fractions and was higher with agricultural land use. This pool was positively correlated to pH, exchangeable Ca, aluminum-oxalate extraction (Alo), and amorphous materials. This result is also in line with a better performance in the SOC model by applying geochemically-modified rates. Our calibrated model shows the advantage of including geochemical rate modifier in the volcanic soils. Further, the SOC levels will also be investigated under different climate projection using SoilGen model.

We investigated changes in geochemical soil properties in response to deposition age and land use management over 30 -50 years on tropical volcanic soils.Our purpose was to find out how weathering stage and land use interactively affect soil properties and organic carbon, and to check if phenoforms (management-related soil subtypes) exist within the genoforms (genetic soil types).Soil samples were taken at land uses that have been converted (pine forest and agricultural land) and a natural forest as the original land use.The results showed that pine forest soil displayed more intense weathering as indicated by higher values of three weathering indices.Intensive agricultural practices also improved soil chemical properties such as pH, exchangeable base cations, base saturation, and organic carbon stock leading to WRB-qualifier of "eutric" in cultivated soils, whereas the average of bulk density was relatively similar between forests and cultivated soils.Positive correlations were found between amorphous materials and Al o , specific surface area, and micropore volume.Correlations between the content of short-range order Al (hydr-) oxides (indicated by Al o ) and organic carbon were found in pine forest and agricultural soils, particularly in subsoils.Our results clearly indicate the increase of base cations retention due to less acidification and an increase of organic carbon stock under agricultural land use, likely due to stabilization with non-crystalline materials.