Refine
Has Fulltext
- no (67)
Year of publication
Document Type
- Article (67) (remove)
Language
- English (67)
Is part of the Bibliography
- yes (67)
Keywords
- Wind erosion (6)
- Biosilicification (4)
- Soil erosion (4)
- Biogenic silica (3)
- Computational fluid dynamics (2)
- Euglyphida (2)
- Grassland (2)
- Open source (2)
- SAMT (2)
- Si fractions (2)
The detection of auto-fluorescence in phytogenic, hydrated amorphous silica depositions (phytoliths) has been found to be a promising approach to verify if phytoliths were burnt or not, especially in archaeological contexts. However, it is unknown so far at what temperature and how auto-fluorescence is induced in phytoliths. We used fluorescence microscopy, scanning electron microscope-energy dispersive X-ray spectroscopy (SEM-EDX), and Fourier transform infrared spectroscopy to analyze auto-fluorescence in modern phytoliths extracted from plant samples or in intact leaves of winter wheat. Leaves and extracted phytoliths were heated at different temperatures up to 600 degrees C. The aims of our experiments were i) to find out what temperature is needed to induce auto-fluorescence in phytoliths, ii) to detect temperature-dependent changes in the molecular structure of phytoliths related to auto-fluorescence, and iii) to derive a mechanistic understanding of auto-fluorescence in phytoliths. We found organic compounds associated with phytoliths to cause auto-fluorescence in phytoliths treated at temperatures below approx. 400 degrees C. In phytoliths treated at higher temperatures, i.e., 450 and 600 degrees C, phytolith auto-fluorescence was mainly caused by molecular changes of phytolith silica. Based on our results we propose that auto-fluorescence in phytoliths is caused by clusterization-triggered emissions, which are caused by overlapping electron clouds forming non-conventional chromophores. In phytoliths heated at temperatures above about 400 degrees C dihydroxylation and the formation of siloxanes result in oxygen clusters that serve as non-conventional chromophores in fluorescence events. Furthermore, SEM-EDX analyses revealed that extractable phytoliths were dominated by lumen phytoliths (62%) compared to cell wall phytoliths (38%). Our findings might be not only relevant in archaeological phytolith-based examinations, but also for studies on the temperature-dependent release of silicon from phytoliths and the potential of long-term carbon sequestration in phytoliths.
Provisioning a sufficient stable source of food requires sound knowledge about current and upcoming threats to agricultural production. To that end machine learning approaches were used to identify the prevailing climatic and soil hydrological drivers of spatial and temporal yield variability of four crops, comprising 40 years yield data each from 351 counties in Germany. Effects of progress in agricultural management and breeding were subtracted from the data prior the machine learning modelling by fitting smooth non-linear trends to the 95th percentiles of observed yield data. An extensive feature selection approach was followed then to identify the most relevant predictors out of a large set of candidate predictors, comprising various soil and meteorological data. Particular emphasis was placed on studying the uniqueness of identified key predictors. Random Forest and Support Vector Machine models yielded similar although not identical results, capturing between 50% and 70% of the spatial and temporal variance of silage maize, winter barley, winter rapeseed and winter wheat yield. Equally good performance could be achieved with different sets of predictors. Thus identification of the most reliable models could not be based on the outcome of the model study only but required expert's judgement. Relationships between drivers and response often exhibited optimum curves, especially for summer air temperature and precipitation. In contrast, soil moisture clearly proved less relevant compared to meteorological drivers. In view of the expected climate change both excess precipitation and the excess heat effect deserve more attention in breeding as well as in crop modelling.
A detailed analysis of horizontal and vertical particulate matter (PM) fluxes during wind erosion has been done, based on measurements of PM smaller than 10, 2.5, and 1.0 mu mm, at windward and leeward positions on a measuring field. The three fractions of PM measurement are differently influenced by the increasing wind and shear velocities of the wind. The measured concentrations of the coarser fractions of the fine dust, PM10, and PM2.5, increase with wind and shear velocity, whereas the PM1.0 concentrations show no clear correlation to the shear velocity. The share of PM2.5 on PM10 depends on the measurement height and wind speed and varies between 4 and 12 m/s at the 1 m height ranging from 25% to 7% (average 10%), and at the 4 m height from 39% to 23% (average 30%). Although general relationships between wind speed, PM concentration, and horizontal and vertical fluxes could be found, the contribution of the measuring field was very low, as balances of incoming and outgoing fluxes show. Consequently, the measured PM concentrations are determined from a variety of sources, such as traffic on unpaved roads, cattle drives, tillage operations, and wind erosion, and thus, represent all components of land use and landscape structure in the near and far surroundings of the measuring field. The current results may reflect factors from the landscape scale rather than the influence of field-related variables. The measuring devices used to monitor PM concentrations showed differences of up to 20%, which led to considerable deviations when determining total balances. Differences up to 67% between the calculated fluxes prove the necessity of a previous calibration of the devices used. (c) 2022 International Research and Training Centre on Erosion and Sedimentation/the World Association for Sedimentation and Erosion Research.
From gustiness to dustiness
(2022)
This study delivers the first empirical data-driven analysis of the impact of turbulence induced gustiness on the fine dust emissions from a measuring field. For quantification of the gust impact, a new measure, the Gust uptake Efficiency (GuE) is introduced. GuE provides a percentage of over- or under-proportional dust uptake due to gust activity during a wind event. For the three analyzed wind events, GuE values of up to 150% could be found, yet they significantly differed per particle size class with a tendency for lower values for smaller particles. In addition, a high-resolution correlation analysis among 31 particle size classes and wind speed was conducted; it revealed strong negative correlation coefficients for very small particles and positive correlations for bigger particles, where 5 mu m appears to be an empirical threshold dividing both directions. We conclude with a number of suggestions for further investigations: an optimized field experiment setup, a new particle size ratio (PM1/PM0.5 in addition to PM10/PM2.5), as well as a comprehensive data-driven search for an optimal wind gust definition in terms of soil erosivity.
Wind erosion of agricultural soils affects their stock of essential elements for plants, like phosphorus (P). It is known that the composition of the eroded sediments varies with height, according to the size and density of the transported substances. Aim of this study was to analyze the concentration and enrichment ratios of P forms in sediments transported by the wind. A wind-tunnel study was performed on a sandy-and a sandy loam soil in order to measure P forms concentrations in the saltating sediments. P concentrations were also measured in the particulate matter (PM) of each soil, gained with the Easy Dust Generator. In both soils, inorganic-(Pi) and organic P (Po) were preferentially transported in PM, with enrichment ratios of 1.8 and 5.5, respectively. Nevertheless, a Pi/Po of 0.9 indicated that the accumulation of the minor Po in PM was more pronounced than Pi. This agrees with P-rich light and easily erodible organic compounds, almost exclusively accumulated in PM, and in relatively heavy and less erodible minerals, like apatites, in lower height sediments. Labile P (Pl) was preferentially transported in saltating sediments of both soils. This was attributed to the selective Bray & Kurtz I's extraction of the abundant inorganic P forms of these sediments. Total P (Pt) copied the transport trends of Pi, the major form. According to the transporting trends, Pi and Po would be re-sedimented at longer distances from the source than Pl. Outcomes become useful for modeling the influence of wind erosion on P cycling.
Remote sensing plays an increasingly key role in the determination of soil organic carbon (SOC) stored in agriculturally managed topsoils at the regional and field scales. Contemporary Unmanned Aerial Systems (UAS) carrying low-cost and lightweight multispectral sensors provide high spatial resolution imagery (<10 cm). These capabilities allow integrate of UAS-derived soil data and maps into digitalized workflows for sustainable agriculture. However, the common situation of scarce soil data at field scale might be an obstacle for accurate digital soil mapping. In our case study we tested a fixed-wing UAS equipped with visible and near infrared (VIS-NIR) sensors to estimate topsoil SOC distribution at two fields under the constraint of limited sampling points, which were selected by pedological knowledge. They represent all releva nt soil types along an erosion-deposition gradient; hence, the full feature space in terms of topsoils' SOC status. We included the Topographic Position Index (TPI) as a co-variate for SOC prediction. Our study was performed in a soil landscape of hummocky ground moraines, which represent a significant of global arable land. Herein, small scale soil variability is mainly driven by tillage erosion which, in turn, is strongly dependent on topography. Relationships between SOC, TPI and spectral information were tested by Multiple Linear Regression (MLR) using: (i) single field data (local approach) and (ii) data from both fields (pooled approach). The highest prediction performance determined by a leave-one-out-cross-validation (LOOCV) was obtained for the models using the reflectance at 570 nm in conjunction with the TPI as explanatory variables for the local approach (coefficient of determination (R-2) = 0.91; root mean square error (RMSE) = 0.11% and R-2 = 0.48; RMSE = 0.33, respectively). The local MLR models developed with both reflectance and TPI using values from all points showed high correlations and low prediction errors for SOC content (R-2 = 0.88, RMSE = 0.07%; R-2 = 0.79, RMSE = 0.06%, respectively). The comparison with an enlarged dataset consisting of all points from both fields (pooled approach) showed no improvement of the prediction accuracy but yielded decreased prediction errors. Lastly, the local MLR models were applied to the data of the respective other field to evaluate the cross-field prediction ability. The spatial SOC pattern generally remains unaffected on both fields; differences, however, occur concerning the predicted SOC level. Our results indicate a high potential of the combination of UAS-based remote sensing and environmental covariates, such as terrain attributes, for the prediction of topsoil SOC content at the field scale. The temporal flexibility of UAS offer the opportunity to optimize flight conditions including weather and soil surface status (plant cover or residuals, moisture and roughness) which, otherwise, might obscure the relationship between spectral data and SOC content. Pedologically targeted selection of soil samples for model development appears to be the key for an efficient and effective prediction even with a small dataset.
The precise and accurate assessment of carbon dioxide (CO2) exchange is crucial to identify terrestrial carbon (C) sources and sinks and for evaluating their role within the global C budget. The substantial uncertainty in disentangling the management and soil impact on measured CO2 fluxes are largely ignored especially in cropland. The reasons for this lies in the limitation of the widely used eddy covariance as well as manual and automatic chamber systems, which either account for short-term temporal variability or small-scale spatial heterogeneity, but barely both. To address this issue, we developed a novel robotic chamber system allowing for dozens of spatial measurement repetitions, thus enabling CO2 exchange measurements in a sufficient temporal and high small-scale spatial resolution. The system was tested from 08th July to 09th September 2019 at a heterogeneous field (100 m x 16 m), located within the hummocky ground moraine landscape of northeastern Germany (CarboZALF-D). The field is foreseen for a longer-term block trial manipulation experiment extending over three erosion induced soil types and was covered with spring barley. Measured fluxes of nighttime ecosystem respiration (R-eco) and daytime net ecosystem exchange (NEE) showed distinct temporal patterns influenced by crop phenology, weather conditions and management practices. Similarly, we found clear small-scale spatial differences in cumulated (gap-filled) R-eco, gross primary productivity (GPP) and NEE fluxes affected by the three distinct soil types. Additionally, spatial patterns induced by former management practices and characterized by differences in soil pH and nutrition status (P and K) were also revealed between plots within each of the three soil types, which allowed compensating for prior to the foreseen block trial manipulation experiment. The results underline the great potential of the novel robotic chamber system, which not only detects short-term temporal CO2 flux dynamics but also reflects the impact of small-scale spatial heterogeneity.
Various studies have been performed to quantify silicon (Si) stocks in plant biomass and related Si fluxes in terrestrial biogeosystems. Most studies are deliberately designed on the plot scale to ensure low heterogeneity in soils and plant composition, hence similar environmental conditions. Due to the immanent spatial soil variability, the transferability of results to larger areas, such as catchments, is therefore limited. However, the emergence of new technical features and increasing knowledge on details in Si cycling lead to a more complex picture at landscape and catchment scales. Dynamic and static soil properties change along the soil continuum and might influence not only the species composition of natural vegetation but also its biomass distribution and related Si stocks. Maximum likelihood (ML) classification was applied to multispectral imagery captured by an unmanned aerial system (UAS) aiming at the identification of land cover classes (LCCs). Subsequently, the normalized difference vegetation index (NDVI) and ground-based measurements of biomass were used to quantify aboveground Si stocks in two Si-accumulating plants (Calamagrostis epige-jos and Phragmites australis) in a heterogeneous catchment and related corresponding spatial patterns of these stocks to soil properties. We found aboveground Si stocks of C. epige-jos and P. australis to be surprisingly high (maxima of Si stocks reach values up to 98 g Sim(-2)), i.e. comparable to or markedly exceeding reported values for the Si storage in aboveground vegetation of various terrestrial ecosystems. We further found spatial patterns of plant aboveground Si stocks to reflect spatial heterogeneities in soil properties. From our results, we concluded that (i) aboveground biomass of plants seems to be the main factor of corresponding phytogenic Si stock quantities, and (ii) a detection of biomass heterogeneities via UAS-based remote sensing represents a promising tool for the quantification of lifelike phytogenic Si pools at landscape scales.
Silicon (Si) speciation and availability in soils is highly important for ecosystem functioning, because Si is a beneficial element for plant growth. Si chemistry is highly complex compared to other elements in soils, because Si reaction rates are relatively slow and dependent on Si species. Consequently, we review the occurrence of different Si species in soil solution and their changes by polymerization, depolymerization, and condensation in relation to important soil processes. We show that an argumentation based on thermodynamic endmembers of Si dependent processes, as currently done, is often difficult, because some reactions such as mineral crystallization require months to years (sometimes even centuries or millennia). Furthermore, we give an overview of Si reactions in soil solution and the predominance of certain solid compounds, which is a neglected but important parameter controlling the availability, reactivity, and function of Si in soils. We further discuss the drivers of soil Si cycling and how humans interfere with these processes. The soil Si cycle is of major importance for ecosystem functioning; therefore, a deeper understanding of drivers of Si cycling (e.g., predominant speciation), human disturbances and the implication for important soil properties (water storage, nutrient availability, and micro aggregate stability) is of fundamental relevance.
Due to the fact that silicon (Si) increases the resistance of plants against diverse abiotic and biotic stresses, Si nowadays is categorized as beneficial substance for plants. However, humans directly influence Si cycling on a global scale. Intensified agriculture and corresponding harvest-related Si exports lead to Si losses in agricultural soils. This anthropogenic desilication might be a big challenge for modern agriculture. However, there is still only little knowledge about Si cycling in agricultural systems of the temperate zone, because most studies focus on rice and sugarcane production in (sub)tropical areas. Furthermore, many studies are performed for a short term only, and thus do not provide the opportunity to analyze slow changes in soil-plant systems (e.g., desilication) over long periods. We analyzed soil and plant samples from an ongoing long-term field experiment (established 1963) in the temperate zone (NE Germany) to evaluate the effects of different nitrogen-phosphoruspotassium (NPK) fertilization rates and crop straw recycling (i.e., straw incorporation) on anthropogenic desilication in the long term. Our results clearly show that crop straw recycling not only prevents anthropogenic desilication (about 43-60% of Si exports can be saved by crop straw recycling in the long term), but also replenishes plant available Si stocks of agricultural soil-plant systems. Furthermore, we found that a reduction of N fertilization rates of about 69% is possible without considerable biomass losses. This economy of the need for N fertilizers potentially can be combined with the benefits of crop straw recycling, i.e., enhancement of carbon sequestration via straw inputs and prevention of anthropogenic desilication of agricultural soil-plant systems. Thus crop straw recycling might have the potential to act as key management practice in sustainable, low fertilization agriculture in the temperate zone in the future.
Drought and the availability of mineable phosphorus minerals used for fertilization are two of the important issues agriculture is facing in the future. High phosphorus availability in soils is necessary to maintain high agricultural yields. Drought is one of the major threats for terrestrial ecosystem performance and crop production in future. Among the measures proposed to cope with the upcoming challenges of intensifying drought stress and to decrease the need for phosphorus fertilizer application is the fertilization with silica (Si). Here we tested the importance of soil Si fertilization on wheat phosphorus concentration as well as wheat performance during drought at the field scale. Our data clearly showed a higher soil moisture for the Si fertilized plots. This higher soil moisture contributes to a better plant performance in terms of higher photosynthetic activity and later senescence as well as faster stomata responses ensuring higher productivity during drought periods. The plant phosphorus concentration was also higher in Si fertilized compared to control plots. Overall, Si fertilization or management of the soil Si pools seem to be a promising tool to maintain crop production under predicted longer and more serve droughts in the future and reduces phosphorus fertilizer requirements.
Large-scale crop yield failures are increasingly associated with food price spikes and food insecurity and are a large source of income risk for farmers. While the evidence linking extreme weather to yield failures is clear, consensus on the broader set of weather drivers and conditions responsible for recent yield failures is lacking. We investigate this for the case of four major crops in Germany over the past 20 years using a combination of machine learning and process-based modelling. Our results confirm that years associated with widespread yield failures across crops were generally associated with severe drought, such as in 2018 and to a lesser extent 2003. However, for years with more localized yield failures and large differences in spatial patterns of yield failures between crops, no single driver or combination of drivers was identified. Relatively large residuals of unexplained variation likely indicate the importance of non-weather related factors, such as management (pest, weed and nutrient management and possible interactions with weather) explaining yield failures. Models to inform adaptation planning at farm, market or policy levels are here suggested to require consideration of cumulative resource capture and use, as well as effects of extreme events, the latter largely missing in process-based models. However, increasingly novel combinations of weather events under climate change may limit the extent to which data driven methods can replace process-based models in risk assessments.
Forested areas are assumed not to be influenced by erosion processes. However, forest soils of Northern Germany in a hummocky ground moraine landscape can sometimes exhibit a very shallow thickness on crest positions and buried soils on slope positions. The question consequently is: Are these on-going or ancient erosional and depositional processes? Plutonium isotopes act as soil erosion/deposition tracers for recent (last few decades) processes. Here, we quantified the 239+240PU inventories in a small, forested catchment (ancient forest "Melzower Forst", deciduous trees), which is characterised by a hummocky terrain including a kettle hole. Soil development depths (depth to C horizon) and 239+240PU inventories along a catena of sixteen different profiles were determined and correlated to relief parameters. Moreover, we compared different modelling approaches to derive erosion rates from Pu data. <br /> We find a strong relationship between soil development depths, distance-to-sink and topography along the catena. Fully developed Retisols (thicknesses > 1 m) in the colluvium overlay old land surfaces as documented by fossil Ah horizons. However, we found no relationship of Pu-based erosion rates to any relief parameter. Instead, 239+240PU inventories showed a very high local, spatial variability (36-70 Bq m(-2)). Low annual rainfall, spatially distributed interception and stem flow might explain the high variability of the 239+240PU inventories, giving rise to a patchy input pattern. Different models resulted in quite similar erosion and deposition rates (max: -5 t ha(-1) yr(-1) to +7.3 t ha(-1) yr(-1)). Although some rates are rather high, the magnitude of soil erosion and deposition - in terms of soil thickness change - is negligible during the last 55 years. The partially high values are an effect of the patchy Pu deposition on the forest floor. This forest has been protected for at least 240 years. Therefore rather natural events and anthropogenic activities during medieval times or even earlier must have caused the observed soil pattern, which documents strong erosion and deposition processes.
The significance of phytoliths for the control of silicon (Si) fluxes from terrestrial to aquatic ecosystems has been recognized as a key factor. Humankind actively influences Si fluxes by intensified land use, i.e., agriculture and forestry, on a global scale. We hypothesized phytolith distribution and assemblages in soils of agricultural and forestry sites to be controlled by vegetation (which is directed by land use) with direct effects on extractable Si fractions driven mainly by phytolith characteristics, i.e., dissolution status (dissolution signs) and morphology (morphotype proportions). To test our hypothesis we combined different chemical extraction methods (calcium chloride, ammonium oxalate, Tiron) for the quantification of different Si fractions (plant available Si, Si adsorbed to/occluded in pedogenic oxides/hydroxides, amorphous Si) and microscopic techniques (light microscopy, confocal laser scanning microscopy, scanning electron microscopy) for detailed analyses of phytoliths extracted using gravimetric separation (physical extraction) from exemplary loess soils of agricultural (arable land and grassland/meadow) and forestry (beech and pine) sites in Poland. We found differences in dissolution signs, morphotype proportions, and vertical distribution of phytoliths in soil horizons per site. In general, dominant morphotypes of assignable phytoliths in the studied soil profiles were elongate phytoliths and short cells, both of which are typical for grass-dominated vegetation. However, the organic layers of forest soils were dominated by globular phytoliths, which are typical indicators for mosses. As expected soil horizons under different vegetation generally were characterized by differences in extractable Si fractions, especially in the upper soil horizons. However, phytogenic Si pools counter-intuitively showed no correlations with chemically extracted Si fractions and soil pH at all. Our findings indicate that it is necessary to combine microscopic analyses and Si extraction techniques for examinations of Si cycling in biogeosystems, because extractions of Si fractions alone do not allow drawing any conclusions about phytolith characteristics or interactions between phytolith pools and chemically extractable Si fractions and do not necessarily reflect phytogenic Si pool quantities in soils and vice versa.
Reconstructing rates and patterns of colluvial soil redistribution in agrarian (hummocky) landscapes
(2019)
Humans have triggered or accelerated erosion processes since prehistoric times through agricultural practices. Optically stimulated luminescence (OSL) is widely used to quantify phases and rates of the corresponding landscape change, by measuring the last moment of daylight exposure of sediments. However, natural and anthropogenic mixing processes, such as bioturbation and tillage, complicate the use of OSL as grains of different depositional ages become mixed, and grains become exposed to light even long after the depositional event of interest. Instead, OSL determines the stabilization age, indicating when sediments were buried below the active mixing zone. These stabilization ages can cause systematic underestimation when calculating deposition rates. Our focus is on colluvial deposition in a kettle hole in the Uckermark region, northeastern Germany. We took 32 samples from five locations in the colluvium filling the kettle hole to study both spatial and temporal patterns in colluviation. We combined OSL dating with advanced age modelling to determine the stabilization age of colluvial sediments. These ages were combined with an archaeological reconstruction of historical ploughing depths to derive the levels of the soil surface at the moment of stabilization; the deposition depths, which were then used to calculate unbiased deposition rates. We identified two phases of colluvial deposition. The oldest deposits (similar to 5 ka) were located at the fringe of the kettle hole and accumulated relatively slowly, whereas the youngest deposits (<0.3 ka) rapidly filled the central kettle hole with rates of two orders of magnitude higher. We suggest that the latter phase is related to artificial drainage, facilitating accessibility in the central depression for agricultural practices. Our results show the need for numerical dating techniques that take archaeological and soil-geomorphological information into account to identify spatiotemporal patterns of landscape change, and to correctly interpret landscape dynamics in anthropogenically influenced hilly landscapes. (c) 2019 The Authors. Earth Surface Processes and Landforms Published by John Wiley & Sons Ltd.
Soil landscape research is faced with wide-ranging questions of soil erosion, precision farming, and agricultural risk management. Digital Soil Morphometrics is a powerful tool to provide respective answers or recommendations but requires soil data from the pedon-to-field scale with high horizontal and vertical resolutions, including the subsoil. We present an efficient sampling and measurement method for easily obtainable soil driving cores with low-destructive preparation. Elemental contents and soil organic and mineral matter composition were measured rapidly and in large numbers using a multi-sensor approach, i.e., visible and near infrared (Vis-NIR), diffuse reflectance infrared Fourier transform (DRIFT), and X-ray fluorescence (XRF) spectroscopy. The suitability of the approach with respect to three-dimensional soil landscape models was tested using soils along a slope representing different stages of erosion and deposition in a hummocky landscape under arable land use (Calcaric Regosols, Calcic Luvisols, Luvic Stagnosols, Gleyic-Colluvic Regosols). The combination of soil core sampling, pedological description, and three spectroscopic techniques enabled rapid determination and interpretation of horizontal and vertical spatial distributions of soil organic carbon (SOC), soil organic and mineral matter composition, as well as CaCO3, Fe, and Mn contents. Depth profiles for SOC, CaCO3, and Fe contents were suitable indicators for site-specific degrees of erosion and matter transport processes at the pedon-to-field scale. Fe and Mn profiles helped identifying zones of reductive and oxic domains in subsoils (gleyzation). Further methodical developments should implement plant-availability of nutrients, characterization of Fe oxides, and calibration of the spectroscopic techniques to field-moist samples.
Two principal groups of processes shape mass fluxes from and into a soil: vertical profile development and lateral soil redistribution. Periods having predominantly progressive soil forming processes (soil profile development) alternate with periods having predominantly regressive processes (erosion). As a result, short‐term soil redistribution – years to decades – can differ substantially from long‐term soil redistribution; i.e. centuries to millennia. However, the quantification of these processes is difficult and consequently their rates are poorly understood. To assess the competing roles of erosion and deposition we determined short‐ and long‐term soil redistribution rates in a formerly glaciated area of the Uckermark, northeast Germany. We compared short‐term erosion or accumulation rates using plutonium‐239 and ‐240 (239+240Pu) and long‐term rates using both in situ and meteoric cosmogenic beryllium‐10 (10Be). Three characteristic process domains have been analysed in detail: a flat landscape position having no erosion/deposition, an erosion‐dominated mid‐slope, and a deposition‐dominated lower‐slope site. We show that the short‐term mass erosion and accumulation rates are about one order of magnitude higher than long‐term redistribution rates. Both, in situ and meteoric 10Be provide comparable results. Depth functions, and therefore not only an average value of the topsoil, give the most meaningful rates. The long‐term soil redistribution rates were in the range of −2.1 t ha‐1 yr‐1 (erosion) and +0.26 t ha‐1 yr‐1 (accumulation) whereas the short‐term erosion rates indicated strong erosion of up to 25 t ha‐1 yr‐1 and accumulation of 7.6 t ha‐1 yr‐1. Our multi‐isotope method identifies periods of erosion and deposition, confirming the ‘time‐split approach’ of distinct different phases (progressive/regressive) in soil evolution. With such an approach, temporally‐changing processes can be disentangled, which allows the identification of both the dimensions of and the increase in soil erosion due to human influence
The ability of water to transport and transform soil materials is one of the main drivers of soil and landscape development. In turn, soil and landscape properties determine how water is distributed in soil landscapes. Understanding the complex dynamics of this co-evolution of soils, landscapes and the hydrological system is fundamental in adapting land management to changes in climate. Soil-Landscape Evolution Models (SLEMs) are used to simulate the development and evolution of soils and landscapes. However, many hydrologic processes, such as preferential flow and subsurface lateral flow, are currently absent in these models. This limits the applicability of SLEMs to improve our understanding of feedbacks in the hydro-pedo-geomorphological system. Implementation of these hydrologic processes in SLEMs faces several complications related to calculation demands, limited methods for linking pedogenic and hydrologic processes, and limited data on quantification of changes in the hydrological system over time. In this contribution, we first briefly review processes and feedbacks in soil-landscape-hydrological systems. Next, we elaborate on the development required to include these processes in SLEMs. We discuss the state-of-the-art knowledge, identify complications, give partial solutions and suggest important future development. The main requirements for incorporating hydrologic processes in SLEMs are: (1) designing a model framework that can deal with varying timescales for different sets of processes, (2) developing and implementing methods for simulating pedogenesis as a function of water flow, (3) improving and implementing knowledge on the evolution and dynamics of soil hydraulic properties over different timescales, and (4) improving the database on temporal changes and dynamics of flow paths.
Agricultural soil landscapes of hummocky ground moraines are characterized by 3D spatial patterns of soil types that result from profile modifications due to the combined effect of water and tillage erosion. We hypothesize that crops reflect such soil landscape patterns by increased or reduced plant and root growth. Root development may depend on the thickness and vertical sequence of soil horizons as well as on the structural development state of these horizons at different landscape positions. The hypotheses were tested using field data of the root density (RD) and the root lengths (RL) of winter wheat using the minirhizotron technique. We compared data from plots at the CarboZALF-D site (NE Germany) that are representing a non-eroded reference soil profile (Albic Luvisol) at a plateau position, a strongly eroded profile at steep slope (Calcaric Regosol), and a depositional profile at the footslope (Anocolluvic Regosol). At each of these plots, three Plexiglas access tubes were installed down to approx. 1.5 m soil depth. Root measurements were carried out during the growing season of winter wheat (September 2014-August 2015) on six dates. The root length density (RLD) and the root biomass density were derived from RD values assuming a mean specific root length of 100 m g(-1). Values of RD and RLD were highest for the Anocolluvic Regosol and lowest for the Calcaric Regosol. The maximum root penetration depth was lower in the Anocolluvic Regosol because of a relatively high and fluctuating water table at this landscape position. Results revealed positive relations between below-ground (root) and above-ground crop parameters (i.e., leaf area index, plant height, biomass, and yield) for the three soil types. Observed root densities and root lengths in soils at the three landscape positions corroborated the hypothesis that the root system was reflecting erosion-induced soil profile modifications. Soil landscape position dependent root growth should be considered when attempting to quantify landscape scale water and element balances as well as agricultural productivity.
Subsurface lateral flow in hillslope soils depends on lower permeability or texture-contrasting soil horizons. In the arable hummocky soil landscape, erosion processes caused glacial till appearance closer to the soil surface at upslope positions. The objective of this work was to quantify the potential for subsurface lateral flow depending on the erosion-affected spatial hydropedological complexity. The eroded Haplic Luvisol profile was studied due to the presence of a relatively dense C horizon that varied in depth, thickness, and sloping angle. A two-dimensional numerical modeling and sensitivity analysis for the saturated hydraulic conductivity (K-s) of the C horizon and the depth to C horizon (i.e., soil solum thickness) was performed for rainstorms in 2011 and 2012 using HYDRUS-2D. A K-s value of <2.5 cm d(-1) for the C horizon was required for lateral flow initiation. Lateral flow was (i) increasing with decreasing solum thickness, indicating an erosion-induced feedback on subsurface lateral flow, and (ii) dependent on the soil moisture regime prior to rainstorms. The effect of lateral flow on the movement of a conservative tracer was simulated in the form of a "virtual experiment". Simulation scenarios revealed only a relatively small lateral shift of the tracer plume caused by a local decoupling of water (already lateral) from subsequent tracer movement (still vertical). Longer term simulations suggested that, for the present conditions, lateral flow was limited mostly to occasional summer storm events. Even without considering preferential flow contribution to lateral flow, highly complex hydropedologic interactions are present in erosion-affected heterogeneous soil profiles.