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Soil erosion is a potentially important source of microplastic (MP) entering aquatic ecosystems. However, little is known regarding the erosion and transport processes of MP from agricultural topsoils. The aim of this study is to analyze the erosion and transport behavior of MP during heavy rainfall events, whereas a specific focus is set to preferential MP transport and MP-soil interactions potentially leading to a more conservative transport behavior. The study is based on a series of rainfall simulations on paired-plots (4.5 m × 1.6 m) of silty loam and loamy sand located in Southern Germany. The simulations (rainfall intensity 60 mm h-1) were repeated 3 times within 1.5 years. An amount of 10 g m-2 of fine (MPf, size 53-100 μm) and 50 g m-2 of coarse (MPc, size 250-300 μm) high-density polyethylene as common polymer was added to the topsoil (

Sediment fingerprinting in data sparse regions, such as the mountainous areas of Iran, is more suited to a confluence-based sample design wherein tributary sub-basins are characterised by sediment samples using different size fractions. Our objective was therefore to fingerprint spatial source contributions to the < 37 and 37–63 μm fractions of fine-grained channel bed sediment samples collected in a large erodible mountainous river basin in Iran based on a number of statistical and machine learning approaches. Geochemical elements were measured in channel bed surface drape sediments from seven sub-basins and in delivered sediments from the basin outlet. A Bayesian mass balance model (modified MixSIR) was applied to apportion sub-basin spatial sources with four composite signatures selected using the different statistical approaches. For the < 37 and 37–63 μm fractions, the signatures all indicated that sub-basins 3 (Andajroud; 46.7%) and 7 (Ninehroud; 36.8%) were the dominant spatial sources of the fine-grained bed drape sediment samples, respectively, identifying the most active erosional zones spatially. The statistical error between known and predicted spatial source contributions using virtual mixture tests for both size fractions demonstrated the importance of using multiple different composite fingerprints to decrease the model prediction uncertainties. Despite the difficult terrain in such data sparse areas, the source fingerprinting approach provides a basis for assembling new evidence which, in turn, is of interest to scientists and managers alike.

Stabilization of organic carbon in soils (SOC) depends on several soil properties, including the soil weathering stage and the mineralogy of parent material. As such, tropical SOC stabilization mechanisms likely differ from those in temperate soils due to contrasting soil development. To better understand these mechanisms, we investigated SOC dynamics at three soil depths under pristine tropical african mountain forest along a geochemical gradient from mafic to felsic and a topographic gradient covering plateau, slope and valley positions. We conducted a series of soil C fractionation experiments in combination with an analysis of the geochemical composition of soil and a sequential extraction of pedogenic oxides. Overall, we found that reactive secondary mineral phases drive SOC properties together with aggregation. These key mineral stabilization mechanisms for SOC were strongly related to soil geochemistry and independent of topography in the absence of detectable erosion processes. We also detected fossil organic carbon (FOC) at several sites, constituting up to 52.0 ± 13.2 % of total SOC stock in the C depleted subsoil. FOC decreased strongly towards more shallow soil depths, indicating decomposability of FOC by microbial communities under topsoil conditions. Regression analysis showed that variables affiliated with soil weathering, parent material geochemistry and soil fertility, together with soil depth, explained up to 75 % of the variability of SOC stocks and Δ14C. Furthermore, the same variables explained 44 % of the variability in the relative abundance of C associated with microaggregates versus free silt and clay associated C fractions. We conclude that despite long-lasting weathering, geochemical properties of soil parent material leave a footprint in tropical soils that affects SOC stocks and links two of the most important mineral related C stabilization mechanisms. While the identified stabilization mechanisms and controls are similar to less weathered soils in other climate zones, their relative importance is markedly different in the investigated tropical soils., EGUsphere

Three-dimensional numerical simulations were performed for different flow rates and various geometrical parameters of step-pools in steep open channels to gain insight into the occurrence of energy loss and its dependence on the flow structure. For a given channel with step-pools, energy loss varied only marginally with increasing flow rate in the nappe and transition flow regimes, while it increased in the skimming regime. Energy loss is positively correlated with the size of the recirculation zone, velocity in the recirculation zone and the vorticity. For the same flow rate, energy loss increased by 31.6% when the horizontal face inclination increased from 2&deg, to 10&deg, while it decreased by 58.6% when the vertical face inclination increased from 40&deg, to 70&deg, In a channel with several step-pools, cumulative energy loss is linearly related to the number of step-pools, for nappe and transition flows. However, it is a nonlinear function for skimming flows.

Due to the rapidly growing population in tropical Africa, a substantial rise in food demand is predicted in upcoming decades, which will result in higher pressure on soil resources. However, there is limited knowledge on soil redistribution dynamics following land conversion to arable land in tropical Africa that is partly caused by challenging local conditions for long-term landscape scale monitoring. In this study, fallout radionuclides 239+240Pu are used to assess soil redistribution along topographic gradients at two cropland sites and at three nearby pristine forest sites located in the DR Congo, Uganda and Rwanda. In the study area, a relatively high 239+240Pu baseline inventory is found (mean forest inventory 41 Bq m−2). Pristine forests show no indication for soil redistribution based on 239+240Pu along topographical gradients. In contrast, soil erosion and sedimentation on cropland reached up to 37 and 40 cm within the last 55 years, respectively. Cropland sites show high intra-slope variability with locations showing severe soil erosion located in direct proximity to sedimentation sites. This study shows the applicability of a valuable method to assess tropical soil redistribution and provides insight on soil degradation rates and patterns in one of the most vulnerable regions of the World.

Prediction of dissolved organic carbon (DOC) based on catchment characteristics is a useful tool for efficient and effective water management, but in the case of arid and semi-arid regions, such predictive capacity is scarce. Accordingly, the main objective of this study was to evaluate the significance of principal components for predicting DOC concentrations and fluxes in nine headwater catchments of the Hiv catchment located in the Southern Alborz Mountains in the west of Tehran, Iran. To achieve this aim, data were assembled on 24 headwater catchment characteristics comprising soil properties, physiography, seasonal rainfall, and flow attributes, as well as estimates of DOC concentrations and fluxes across four seasons. The results revealed a major positive correlation between DOC and soil organic matter parameters related to soil biological processes. Using general linear modelling, an organic matter component related to soil biology, a seasonal component related to the dummy effect of sampling seasons, and a soil physical component related to soil texture were found to be the best predictors for DOC responses in the study area.

Hummocky landscapes under intensive arable use are substantially affected by erosion processes. Data from the Quillow catchment (size: 196 km2; mean annual precipitation: 500 mm) in North-East Germany are used to estimate landscape-scale water and tillage erosion with the model SPEROS-C. Recent results show that tillage erosion causes substantial soil redistribution that can distinctively exceed water erosion. In consequence, truncated soil profiles can be found on hilltops and steep slopes, whereas colluvial material is accumulated in depressions and along downslope field boarders. The resulting spatial variability of soil types with different properties and conditions is known to influence crop growth and leads to a highly variable biomass pattern in hummocky landscapes under highly mechanised arable cultivation. The main goal of our study is to link tillage-induced erosion rates to landscape development at centennial time scales. By modelling the development of the hummocky moraine landscape of North-Eastern Germany, we explain the spatial distribution of the current soil erosion state. Furthermore, the soil erosion induced impact on crop biomass patterns and the redistribution of soil organic carbon since the beginning of human land use in this area is assessed. To address this goal, a new model component is implemented into SPEROS-C that iteratively rejuvenates topography backwards in time considering modelled erosion and deposition rates. Afterwards, modelling forward in time allows estimating carbon fluxes due to soil redistribution. Furthermore, the extent and location of truncated soils will be validated with historic aerial photographs at different time steps. The benefits of implementing landscape development into SPEROS-C are that (i) an annual update of topography generates a more realistic soil erosion pattern, (ii) the current crop biomass pattern may be explained by erosion history, and (iii) estimates about the future development of crop yield patterns considering ongoing tillage practices can be drawn from a validated soil erosion and landscape development model., EGUsphere

Soil redistribution on arable land is a major threat for a sustainable use of soil resources. The soil redistribution process most studies focus on is water erosion, while wind and tillage erosion also induce pronounced redistribution of soil materials. Especially, tillage erosion is understudied, as it does not lead to visible off-site damages. The analysis of on-site/in-field soil redistribution is mostly based on tracer studies, whereas radionuclide tracers (e.g. 137Cs, 239+240Pu) from nuclear weapon tests are commonly used to derive the erosion history over the past 50–60 yr. Tracer studies allow to determine soil redistribution patterns, but integrate all kinds of soil redistribution processes and hence do not allow to unravel the contribution of different erosion processes. The aim of this study is to understand the contribution of water and tillage erosion leading to soil patterns found in a small hummocky ground moraine catchment under intensive agricultural use. Therefore, 239+240Pu derived soil redistribution patterns were analysed using an inverse modelling approach accounting for water and tillage erosion processes. The results of this analysis clearly point out that tillage erosion is the dominant process of soil redistribution in the small catchment, which also affects the hydrological and sedimentological connectivity between arable land and the kettle hole. A topographic change up to 17 cm (53 yr)−1 in the eroded parts of the catchment is not able to explain the current soil profile truncation that exceeds the 239+240Pu derived topographic change substantially. Hence, tillage erosion is not limited to the time since the onset of intense mechanisation since the 1960s. In general, the study stresses the urgent need to consider tillage erosion as a very important soil degradation process that drives patterns of soil properties in our arable landscapes.

Agricultural soils play a key role as sink of microplastic (MP) coming from different sources, especially via the application of sewage sludge, compost, the decay of plastic mulch, and tire ware particles along streets. However, the effectiveness of this sink might be substantially reduced in areas subjected to water erosion. The aim of this study is to determine the transport potential of MP during water erosion events on agricultural land. More specifically, we are interested if MP is preferentially transported or if it is attached or associated to soil minerals and aggregates leading to a more conservative transport behavior. The transport behavior is studied based on a series of plot rainfall simulations on a silty loam (16% sand, 59% silt, 25% clay; 1.3% OC) and a loamy sand soil (72% sand, 18% silt, 10% clay; 0.9% OC) located at experimental farms in Southern Germany. To simulate heavy rain on dry and wet soil a sequence of two simulations with a gap of 30 min was performed for 30 min each (rainfall intensity 60 mm/h) on each of the four plots (2 m x 5 m). The simulations are repeated in spring and autumn for two years. Before the beginning of the experiment all plots were prepared, adding fine (53-100 μm) and coarse (250-300 μm) microplastic (high density polyethylene) in a topsoil (< 10 cm) concentration of 10 g/m-2 and 50 g m-2. The different soils show similar mean runoff rates for the dry run (2 l min-1), whereas the wet run produced slightly higher rates on the silty loam (5.5 l min-1) compared to the loamy sand soil (4 l min-1). In contrast, MP erosion and transport under the loamy sand was more selective, leading to MP enrichment for the first set of experiments of a factor of 3 to 20, compared to MP under silty loam with an enrichment factor of 0,4 to 0,8. The results from the first set of rainfall simulations clearly underlines the selective nature of MP erosion and transport leading to a disproportionate loss of MP from eroding sites into inland waters. The degree of MP enrichment in surface runoff is heavily depending on soil texture and especially moisture status at the beginning of an erosive rainfall event. Further investigations regarding more long-term MP enrichment effects depending on MP association to soil minerals and aggregates are under preparation.

There is growing concern regarding the pollution of our environment with plastic materials, whereas especially the dimension of microplastic pollution and its ecological effect is widely discussed. Most studies focus on aquatic environments, while studies in terrestrial systems (mainly soils) are rare. This partly results from the challenges arising when microplastic particles need to be separated from organic and mineral particles. Key analytic techniques for microplastic detection in aquatic and terrestrial systems include Fourier transformation-infrared (FT-IR) and micro-Raman spectroscopy, as well as thermal extraction desorption-gas chromatography-mass spectrometry (TED-GC-MS) and pyrolysis-gas chromatography-mass spectrometry (pyr-GC-MS). While the mass spectrometric methods lack to determine particle sizes, the FT-IR and micro-Raman spectroscopy are very costly and time consuming. Moreover, the latter detection methods are very sensitive to organic matter particles, which are difficult to remove fully during soil sample preparation. Hence, a faster and more robust method to determine microplastic in soils is essential for a wider analysis of this environmental problem. In this study, we combine a density separation scheme with a 3D Laser Scanning Confocal Microscope (Keyence VK-X1000, Japan) analysis to determine the number and size of microplastic particles in soil samples. For the analysis a silty loam (16% sand, 59% silt, 25% clay, 1.3% organic carbon) and a loamy sand (72% sand, 18% silt, 10% clay, 0.9% organic carbon) were spiked with different concentrations of high density Polyethylene (HDPE), low density Polyethylene (LDPE) and Polystyrene (PS) microplastic (HDPE 50 - 100 and 250 - 300 µm, LDPE

Tropical ecosystems and the soils therein have been reported as one of the most important and largest terrestrial carbon (C) pools and are considered important climate regulator. Carbon stabilization mechanisms in these ecosystems are often complex, as these mechanisms crucially rely on the interplay of geology, topography, climate, and biology. Future predictions of the perturbation of the soil carbon pool ultimately depend on our mechanistic understanding of these complex interactions. Using laboratory incubation experiments, we investigated if carbon release from soils through heterotrophic respiration in the African highland forests of the Eastern Congo Basin follows predictable patterns related to topography, soil depth or geochemical soil properties that can be described at the landscape scale and ultimately be used to improve the spatial accuracy of soil C respiration in mechanistic models. In general, soils developed on basalt and granite parent material (mafic and felsic geochemistry of parent material) showed significantly (p, EGUsphere

Connectivity has been embraced by the geosciences community as a useful concept to understand and describe hydrological functioning and sediment movement through catchments. Mathematical modelling has been used for decades to quantify and predict erosion and transport of sediments, e.g. in scenarios of land use change or conservation measures. Being intrigued by both models and the connectivity concept, as a group of modellers we aimed at investigating what different models could tell us about connectivity. Therefore, we evaluated the response of contrasted spatially-distributed models to landscape connectivity features and explained the differences based on different model structures. A total of 53 scenarios were built with varying field sizes and orientations, as well as the implementation of soil conservation measures. These scenarios were simulated, for two rainfall intensities, with five event- and process-based water and soil erosion models – EROSION3D, FullSWOF_2D, LandSoil, OpenLISEM and Watersed. Results showed that rainfall amount plays the most important role in determining relative export and connected area of runoff and sediment in all models, indicating that functional aspects of connectivity were more important than structural connectivity. As for the role of structural landscape elements, there was no overall agreement between models regarding the effects of field sizes, crop allocation pattern, and conservation practices; agreement was also low on the spatial patterns of connectivity. This overall disagreement between models was unexpected. The results of this exercise suggest that the correct parameterization of runoff and sediment production and of routing patterns may be an important issue. Thus, incorporating connectivity functions based on routing would help modelling forward. Our results also suggest that structural connectivity indices may not suffice to represent connectivity in this type of catchment (relatively simple and monotonous land cover), and functional connectivity indices should be applied. ISSN:0169-555x ISSN:1872-695X

Soil mineralogy plays an important role in stabilizing soil organic carbon (SOC) against decomposition by forming organo-mineral complexes with reactive mineral surfaces. However, few studies take the influence of parent material geochemistry on the development of C stabilization mechanisms into account. In addition, studies evaluating C stabilization in soil are often limited to temperate climate zones with young to intermediate aged soils. This is not representative for older, deeply weathered and leached tropical systems and limits our understanding of the relationship between geology, soil formation and their effect on C stabilization. Here, we study the relationship between soil carbon stabilization and the geochemical properties of soils developed on different parent material along geomorphic transects in pristine tropical forest systems under comparable climate. Our study is located in the eastern part of the Congo basin along the East African Rift Mountain System where we sampled 36 one meter soil cores along nine geomorphic transects on geologies ranging from mafic to felsic geochemistry. Carbon stocks ranged between 2.67 tC ha-1 to 85.75 tC ha-1 and were on average composed of 4.5% (±5.3% SD) coarse particulate organic matter, 46.0% (±10.3% SD) (micro)aggregates associated C and 49.6% (±11.2% SD) free silt and clay associated C. Our analysis shows that the topographic position of the investigated soils had no effect on SOC stocks and the distribution of soil C fractions. Regression models and partial correlation analysis reveal that strong correlations of SOC stocks exists to geochemical properties of the solid phase of soil but not to the distribution of soil C fractions. SOC decreased strongly with soil depth on soils developed on felsic parent material, but less so on mafic or intermediate parent material. In addition, mafic geochemistry shows significantly higher SOC stocks compared to their felsic counterparts. We conclude that despite long-lasting weathering, the contrasting geochemistry of the underlying parent material leaves a footprint in soil geochemistry that affects C stocks but less so on stabilization mechanisms. We hypothesis that carbon dynamics in these undisturbed tropical forest systems are more driven by C input and nutrient recycling than by variation in C stabilization potential., EGUsphere

Apart from being considered a potential threat to ecosystems and human health, the ubiquity of microplastics presents analytical challenges. There is a high risk of sample contamination during sampling, sample preparation, and analysis. In this study, the potential of sample contamination or misinterpretation due to substances associated with disposable laboratory gloves or reagents used during sample preparation was investigated. Leachates of 10 different types of disposable gloves were analyzed using Raman microspectroscopy (μ-Raman), Fourier-transform infrared microspectroscopy (μ-FTIR), and pyrolysis-gas chromatography/mass spectrometry (pyr-GC/MS). There appeared to be polyethylene (PE) in almost all investigated glove leachates and with all applied methods. Closer investigations revealed that the leachates contained long-chain compounds such as stearates or fatty acids, which were falsely identified as PE by the applied analytical methods. Sodium dodecyl sulfate, which is commonly applied in microplastic research during sample preparation, may also be mistaken for PE. Therefore, μ-Raman, μ-FTIR, and pyr-GC/MS were further tested for their capability to distinguish among PE, sodium dodecyl sulfate, and stearates. It became clear that stearates and sodium dodecyl sulfates can cause substantial overestimation of PE.

Representations of land use change in hydrologic impact assessment studies mostly rely on static land use information of two points in time, even though the availability of dense time series of land use data allows for the incorporation of dynamic land use changes. We compare the hydrologic impacts of dynamic land use change assessments to those of static land use change assessments. These effects are illustrated with the help of two land use scenarios applied to a hydrologic model of a rapidly developing meso-scale (2036 km2) catchment upstream of Pune, India. The results show that a linear dynamic land use development could be better approximated with the static approach than a non-linear development. An analysis of the impact of the frequency of land use updates indicates that the prediction of non-linear land use change impacts already improves substantially when frequent land use information every five to nine years is used.

Quantifying soil carbon dynamics is of utmost relevance in the context of global change because soils play an important role in land-atmosphere gas exchange. Our current understanding of both present and future carbon dynamics is limited because we fail to accurately represent soil processes across temporal and spatial scales, partly because of the paucity of data on the relative importance and hierarchical relationships between microbial, geochemical and climatic controls. Here, using observations from a 3,000-kyr-old soil chronosequence preserved in alluvial terrace deposits of the Merced River, California, we show how soil carbon dynamics are driven by the relationship between short-term biotic responses and long-term mineral weathering. We link temperature sensitivity of heterotrophic respiration to biogeochemical soil properties through their relationship with microbial activity and community composition. We found that soil mineralogy, and in particular changes in mineral reactivity and resulting nutrient availability, impacts the response of heterotrophic soil respiration to warming by altering carbon inputs, carbon stabilization, microbial community composition and extracellular enzyme activity. We demonstrate that biogeochemical alteration of the soil matrix (and not short-term warming) controls the composition of microbial communities and strategies to metabolize nutrients. More specifically, weathering first increases and then reduces nutrient availability and retention, as well as the potential of soils to stabilize carbon.

Trabajo presentado en la European Geosciences Union General Assembly (EGU 2017), celebrada en Viena del 23 al 28 de abril de 2017., In undulating arable landscapes tillage erosion is one of the dominant processes initiating lateral transfer of soil and soil constituents. Especially, in relatively dry regions, where tillage erosion can be much larger than water erosion, the associated changes in soil hydraulic properties might have substantial effects upon the sustainable use of soil resources. There have been some studies using different techniques to determine tillage erosion which build the basis for tillage erosion modelling approaches. However, tillage erosion is rather understudied compared to water erosion. The goal of this study was to bring together experts using different techniques to determine tillage erosion in an experimental set-up and to analyse the different results and assess the uncertainties associated with typical model inputs. Tillage erosion on a 50 x 10 m plot was determined after two phases of seven tillage passes performed within a week (simulating 10-14 yrs of tillage). As tracers, two different micro-tracers (magnetite mixed with soil and fluorescent sand) and one macro-tracer (passive Radio-Frequency Identification (RFID) transponders; dia. 3 mm, length 20 mm) were used. Moreover, tillage induced changes in topography were spatially determined for the entire plot with two different terrestrial laser scanners and an UAV-based structure by motion topography analysis. Topography changes were also evaluated at 12 points using buried concrete flagstones as reference. A preliminary analysis of tracer movement indicates substantial differences in tillage induced translocation depending on type of tracer. While the mean translocation of the RFIDs was 0.47 m per pass the mean movement of the micro-tracers was 0.70 m. Substantial differences were also found for the different techniques to determine changes in topography. Overall the experiment underlines the importance of tillage erosion for the lateral transfer of soil and soil constituents, but also shows the large discrepancies between measurements based on different techniques. The latter introduces substantial uncertainties in any existing tillage erosion modelling approach.

Water- and sediment-transfer models are commonly used to explain or predict patterns in the landscape at scales different from those at which observations are available. These patterns are often the result of emergent properties that occur because processes of water and sediment transfer are connected in different ways. Recent advances in geomorphology suggest that it is important to consider, at a specific spatio-temporal scale, the structural connectivity of system properties that control processes, and the functional connectivity resulting from the way those processes operate and evolve through time. We argue that a more careful consideration of how structural and functional connectivity are represented in models should lead to more robust models that are appropriate for the scale of application and provide results that can be upscaled. This approach is necessary because, notwithstanding the significant advances in computer power in recent years, many geomorphic models are still unable to represent the landscape in sufficient detail to allow all connectivity to emerge. It is important to go beyond the simple representation of structural connectivity elements and allow the dynamics of processes to be represented, for example by using a connectivity function. This commentary aims to show how a better representation of connectivity in models can be achieved, by considering the sorts of landscape features present, and whether these features can be represented explicitly in the model spatial structure, or must be represented implicitly at the subgrid scale.

India's rapid population and economic growth leads to fast changing land use and management practices that have a major impact on the environment. Therefore, this study assesses spatio-temporal dynamics of land use and cropping frequencies using moderate resolution spaceborne data (Landsat 7 and LISS III). Based on a hierarchical knowledge-based classification approach, multi-temporal satellite data from the years 2000/2001 and 2010/2011 have been used to derive land use and cropping frequency maps. The approach adopted in this study resulted in a satisfactory classification quality as indicated by overall accuracies >90% for the individual classifications. A reduced land use pressure on mountainous areas was found, indicated by an increasing development of forests within the transition zones between cultivated land and steep slopes. Furthermore, an increase of tree plantations points to a shift from drought vulnerable plants to less risk prone perennial plants. We found a higher cropping frequency in 2010/11 related to both inter-annual precipitation differences over the course of the rainy season and long-term socio-economic changes. While low yield areas are left for natural succession or switched to tree plantations, the cultivation of high yield areas was intensified.

Recently a rainfall erosivity map has been published. We show that the values of this map contain considerable bias because (i) the temporal resolution of the rain data was insufficient, which likely underestimates rain erosivity by about 20%, (ii) no attempt had been included to account for the different time periods that were used for different countries, which can modify rain erosivity by more than 50%, (iii) and likely precipitation data had been used instead of rain data and thus rain erosivity is overestimated in areas with significant snowfall. Furthermore, the seasonal distribution of rain erosivity is not provided, which does not allow using the erosivity map for erosion prediction in many cases. Although a rain erosivity map for Europe would be highly desirable, we recommend using the national erosivity maps until these problems have been solved. Such maps are available for many European countries.

Surface runoff generation on arable fields is an important driver of flooding, on-site and off-site damages by erosion, and of nutrient and agrochemical transport. In general, three different processes generate surface runoff (Hortonian runoff, saturation excess runoff, and return of subsurface flow). Despite the developments in our understanding of these processes it remains difficult to predict which processes govern runoff generation during the course of an event or throughout the year, when soil and vegetation on arable land are passing many states. We analysed the results from 317 rainfall simulations on 209 soils from different landscapes with a resolution of 14 286 runoff measurements to determine temporal and spatial differences in variables governing surface runoff, and to derive and test a statistical model of surface runoff generation independent from an a priori selection of modelled process types. Measured runoff was related to 20 time-invariant soil properties, three variable soil properties, four rain properties, three land use properties and many derived variables describing interactions and curvilinear behaviour. In an iterative multiple regression procedure, six of these properties/variables best described initial abstraction and the hydrograph. To estimate initial abstraction, the percentages of stone cover above 10% and of sand content in the bulk soil were needed, while the hydrograph could be predicted best from rain depth exceeding initial abstraction, rainfall intensity, soil organic carbon content, and time since last tillage. Combining the multiple regressions to estimate initial abstraction and surface runoff allowed modelling of event-specific hydrographs without an a priori assumption of the underlying process. The statistical model described the measured data well and performed equally well during validation. In both cases, the model explained 71 and 58% of variability in accumulated runoff volume and instantaneous runoff rate (RSME: 5.2 mm and 0.23 mm min−1, respectively), while RMSE of runoff volume predicted by the curve number model was 50% higher (7.7 mm). Stone cover, if it exceeded 10%, was most important for the initial abstraction, while time since tillage was most important for the hydrograph. Time since tillage is not taken into account either in typical lumped hydrological models (e.g. SCS curve number approach) or in more mechanistic models using Horton, Green and Ampt, or Philip type approaches to address infiltration although tillage affects many physical and biological soil properties that subsequently and gradually change again. This finding should foster a discussion regarding our ability to predict surface runoff from arable land, which seemed to be dominated by agricultural operations that introduce man-made seasonality in soil hydraulic properties.

For bare soil conditions, the most important process driving and initiating splash and interrill erosion is the detachment of soil particles via raindrop impact. The kinetic energy of a rainfall event is controlled by the drop size and fall velocity distribution, which is often directly or indirectly implemented in erosion models. Therefore, numerous theoretical functions have been developed for the estimation of rainfall kinetic energy from available rainfall intensity measurements. The aim of this study is to assess differences inherent in a wide number of kinetic energy-rainfall intensity (KE-I) relations and their role in soil erosion modelling. Therefore, 32 KE-I relations are compared against measured rainfall energies based on optical distrometer measurements carried out at five stations of two substantially different rainfall regimes. These allow for continuous high-resolution (1-min) direct measurements of rainfall kinetic energies from a detailed spectrum of measured drop sizes and corresponding fall velocities. To quantify the effect of different KE-I relations on sediment delivery, we apply the erosion model WATEM/SEDEM in an experimental setup to four catchments of NE-Germany. The distrometer data shows substantial differences between measured and theoretical models of drop size and fall velocity distributions. For low intensities the number of small drops is overestimated by the Marshall and Palmer (1948; MP) drop size distribution, while for high intensities the proportion of large drops is overestimated by the MP distribution. The distrometer measurements show a considerable proportion of large drops falling at slower velocities than predicted by the Gunn and Kinzer (1949) terminal velocity model. For almost all rainfall events at all stations, the KE-I relations predicted higher cumulative kinetic energy sums compared to the direct measurements of the optical distrometers. The different KE-I relations show individual characteristics over the course of rainfall intensity levels. Our results indicate a high sensitivity (up to a range from 10 to 27 t ha−1) of the simulated sediment delivery related to different KE-I relations. Hence, the uncertainty associated with KE-I relations for soil erosion modelling is of critical importance.

International audience; Recently, connectivity has emerged as a promising concept to understand the transfer of water and sediment in a catchment. Both structural connectivity – i.e. representing the connectivity of system properties such as the (micro)topography, and functional connectivity – i.e. representing connections that may change and evolve over time such as soil moisture, are important to consider. As discussed by Nunes et al. (in press), good models should be effectively connected models, i.e. represent properly the fluxes of water and sediment both within and between its fundamental spatial units. However, there is no clear framework to guide how this should be assessed. In this study we analysed changes in landscape connectivity using six well-known erosion models: Erosion3D, Fullswof, Landsoil, LISEM, MAHLERAN and Watersed. Our objective was to determine if, and how simulated connectivity is linked with model structure. The models all simulated the same, semi-virtual 124 ha watershed, loosely based on the Giser experimental agricultural watershed in Belgium. A total of 53 connectivity scenarios with differences in spatial complexity and presence of connectivity features were simulated using two rainfall events (10- and 50-year return periods). The spatial complexity was varied in terms of field size (5, 10 or 20 ha) and five different land-use patterns with tillage orientation following the axis of the fields. Finally, for mid-sized fields (10 ha) and for each of the five land-use patterns, the following connectivity features were tested: conservation tillage (i.e. orientation of fields along the contour), and presence of grass strips and a grassed waterway. We will discuss the impacts of these scenarios on overland flow and sediment connectivity for each model, in relation with its structure. In the future, these results will be used to investigate the possibility to derive more generic results using model ensembles.

Agricultural management has received increased attention over the last decades due to its central role in carbon (C) sequestration and greenhouse gas mitigation. Yet, regardless of the large body of literature on the effects of soil erosion by tillage and water on soil organic carbon (SOC) stocks in agricultural landscapes, the significance of soil redistribution for the overall C budget and the C sequestration potential of land management options remains poorly quantified. In this study, we explore the role of lateral SOC fluxes in regional scale modelling of SOC stocks under three different agricultural management practices in central Belgium: conventional tillage (CT), reduced tillage (RT) and reduced tillage with additional carbon input (RT+i). We assessed each management scenario twice: using a conventional approach that did not account for lateral fluxes and an alternative approach that included soil erosion-induced lateral SOC fluxes. The results show that accounting for lateral fluxes increased C sequestration rates by 2.7, 2.5 and 1.5 g C m(-2) yr(-1) for CT, RT and RT+i, respectively, relative to the conventional approach. Soil redistribution also led to a reduction of SOC concentration in the plough layer and increased the spatial variability of SOC stocks, suggesting that C sequestration studies relying on changes in the plough layer may underestimate the soil's C sequestration potential due to the effects of soil erosion. Additionally, lateral C export from cropland was in the same of order of magnitude as C sequestration; hence, the fate of C exported from cropland into other land uses is crucial to determine the ultimate impact of management and erosion on the landscape C balance. Consequently, soil management strategies targeting C sequestration will be most effective when accompanied by measures that reduce soil erosion given that erosion loss can balance potential C uptake, particularly in sloping areas.

Summary Soil moisture is a key variable in hydrology, meteorology and agriculture. It is influenced by many factors, such as topography, soil properties, vegetation type, management, and meteorological conditions. The role of these factors in controlling the spatial patterns and temporal dynamics is often not well known. The aim of the current study is to analyze spatio-temporal soil moisture patterns acquired across a variety of land use types, on different spatial scales (plot to meso-scale catchment) and with different methods (point measurements, remote sensing, and modeling). We apply a uniform set of tools to determine method specific effects, as well as site and scale specific controlling factors. Spatial patterns of soil moisture and their temporal development were analyzed using nine different datasets from the Rur catchment in Western Germany. For all datasets we found negative linear relationships between the coefficient of variation and the mean soil moisture, indicating lower spatial variability at higher mean soil moisture. For a forest sub-catchment compared to cropped areas, the offset of this relationship was larger, with generally larger variability at similar mean soil moisture values. Using a geostatistical analysis of the soil moisture patterns we identified three groups of datasets with similar values for sill and range of the theoretical variogram: (i) modeled and measured datasets from the forest sub-catchment (patterns mainly influenced by soil properties and topography), (ii) remotely sensed datasets from the cropped part of the Rur catchment (patterns mainly influenced by the land-use structure of the cropped area), and (iii) modeled datasets from the cropped part of the Rur catchment (patterns mainly influenced by large scale variability of soil properties). A fractal analysis revealed that all analyzed soil moisture patterns showed a multifractal behavior, with at least one scale break and generally high fractal dimensions. Corresponding scale breaks were found between different datasets. The factors causing these scale breaks are consistent with the findings of the geostatistical analysis. Furthermore, the joined analysis of the different datasets showed that small differences in soil moisture dynamics, especially at the upper and lower bounds of soil moisture (at maximum porosity and wilting point of the soils) can have a large influence on the soil moisture patterns and their autocorrelation structure. Depending on the prevalent type of land use and the time of year, vegetation causes a decrease or an increase of spatial variability in the soil moisture pattern.

Soil organic carbon (SOC) is the largest terrestrial organic carbon pool; thus, there is a growing interest in its spatial distribution and potential for carbon sequestration. However, our knowledge about spatial distribution in different soil depths and under different land uses is still limited in many regions of the world. The aim of this study was to analyse the soil depth and land use specific SOC contents in a small catchment (6.46 km2) located in the tropical monsoon climate of South India and to determine potential auxiliary variables suitable to derive high resolution maps. A soil survey was carried out, taking 112 soil cores representing three soil depth increments each (< 0.2 m, 0.2 - 0.5 m, and 0.5 - 0.9 m, respectively) and a number of spatially distributed auxiliary variables (slope; curvature; elevation above the next potential irrigation source; water erosion; wetness index; mean NDVI) were determined. The interrelationship between SOC contents and these variables and their principal components were analysed with a combination of an ANCOVA, an iterative linear regression and a multivariate non-linear regression procedure. The mean SOC contents of 3.4 g kg-1 (upper 0.9 m) are consistent with large scale data. The more detailed analysis of land use specific differences in SOC contents showed that the sampling points of irrigated arable land had the highest mean contents in topsoil and over the whole measured depth. SOC contents under arable land were followed by those under plantations, forests/shrubland and grassland. Within the different land use categories SOC under arable land declines with increasing elevation above the next potential irrigation source, SOC under grassland is positively correlated with mean NDVI, and SOC under forest/shrubland is best described by variables indirectly related to the accessibility of forest areas. Overall, this study indicates that the commonly used relations to estimate spatial distribution of SOC on larger scales might not be adequate for large areas in South India, which are dominated by pronounced dry and wet seasons, intensive irrigation farming and human-induced forest degradation. � 2014 Elsevier B.V. All rights reserved.

Over the last few decades, soil erosion and carbon redistribution modelling has received a lot of attention due to large uncertainties and conflicting results. For a physically based representation of event dynamics, coupled soil and carbon erosion models have been developed. However, there is a lack of research utilizing models which physically represent preferential erosion and transport of different carbon fractions (i.e. mineral bound carbon, carbon encapsulated by aggregates and particulate organic carbon). Furthermore, most of the models that have a high temporal resolution are applied to relatively short time series (

Energy loss in a steep open channel due to randomly spaced spherically shaped macroroughness elements such as boulders was investigated using a three-dimensional fluid dynamics solver. Firs...

Coupled modelling of soil erosion, carbon redistribution, and turnover has received great attention over the last decades due to large uncertainties regarding erosion-induced carbon fluxes. For a process-oriented representation of event dynamics, coupled soil–carbon erosion models have been developed. However, there are currently few models that represent tillage erosion, preferential water erosion, and transport of different carbon fractions (e.g. mineral bound carbon, carbon encapsulated by soil aggregates). We couple a process-oriented multi-class sediment transport model with a carbon turnover model (MCST-C) to identify relevant redistribution processes for carbon dynamics. The model is applied for two arable catchments (3.7 and 7.8 ha) located in the Tertiary Hills about 40 km north of Munich, Germany. Our findings indicate the following: (i) redistribution by tillage has a large effect on erosion-induced vertical carbon fluxes and has a large carbon sequestration potential; (ii) water erosion has a minor effect on vertical fluxes, but episodic soil organic carbon (SOC) delivery controls the long-term erosion-induced carbon balance; (iii) delivered sediments are highly enriched in SOC compared to the parent soil, and sediment delivery is driven by event size and catchment connectivity; and (iv) soil aggregation enhances SOC deposition due to the transformation of highly mobile carbon-rich fine primary particles into rather immobile soil aggregates.

An in-depth analysis of the interannual variability of storms is required to detect changes in soil erosive power of rainfall, which can also result in severe on-site and off-site damages. Evaluating long-term rainfall erosivity is a challenging task, mainly because of the paucity of high-resolution historical precipitation observations that are generally reported at coarser temporal resolutions (e.g., monthly to annual totals). In this paper we suggest overcoming this limitation through an analysis of long-term processes governing rainfall erosivity with an application to datasets available the central Ruhr region (Western Germany) for the period 1701-2011. Based on a parsimonious interpretation of seasonal rainfall-related processes (from spring to autumn), a model was derived using 5-min erosivity data from 10 stations covering the period 1937-2002, and then used to reconstruct a long series of annual rainfall erosivity values. Change-points in the evolution of rainfall erosivity are revealed over the 1760s and the 1920s that mark three sub-periods characterized by increasing mean values. The results indicate that the erosive hazard tends to increase as a consequence of an increased frequency of extreme precipitation events occurred during the last decades, characterized by short-rain events regrouped into prolonged wet spells. (C) 2016 Elsevier B.V. All rights reserved.

The K factor of the Universal Soil Loss Equation is the most important measure of soil erodibility that was adopted in many erosion models. The K factor can be estimated from simple soil properties by a nomograph. Later, the classical K factor equation was published to assist the calculation of K. This equation, however, does not fully agree with the nomograph, which still has to be used in these deviating cases. Here we show for a large soil data set from Central Europe (approximately 20,000 soil analyses) that the equation fails in considerably more than 50% of all cases. The failure can be large and may amount to half of the K factor. To facilitate the K factor calculation, we developed a set of equations that fully emulates the nomograph and supersedes the cumbersome reading of the nomograph.

Soil and carbon redistribution on arable land and the associated impacts on carbon sequestration and mineralisation may play an important role in the global carbon cycle. While our insight in the process-chain of erosion, transport and deposition has significantly grown over recent years, there are still major gaps in understanding making it difficult to make an overall assessment of erosion processes on carbon exchange between the soil and the atmosphere. One issue is the potential effect soil degradation and erosion processes may have on CO2 effluxes at eroding sites. The major goal of this study was therefore to analyse and understand the effects of interrill erosion, soil crusting and soil aggregate breakdown on in situ CO2 effluxes. Therefore a set of rainfall simulations were carried out on bare loess-burden soil with different antecedent soil moisture content. All treatments were compared with controls protected from rain drop impact using a fine-meshed geotextile. As expected, runoff and sediment delivery was significantly larger on bare compared to covered soils, while surface runoff and sediment delivery increased (in most cases) with rising antecedent soil moisture as well as rainfall duration. Crust thickness increased with antecedent soil moisture and rainfall intensity and was in general smaller for the controls. However, variations in crust thickness did not result in significant differences in in situ measured CO2 effluxes. Also the destruction of the soil crust after six to seven days of measurements did not have a significant effect. This leads to the conclusion that crusting and interrill erosion has no or only a minor effect on in situ CO2 effluxes. Nevertheless, it should be recognised that topsoil carbon is preferentially removed due to interrill erosion which may result in additional CO2 release at depositional sites or in stream and/or standing water bodies. � 2012 Elsevier B.V.

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

The role of soil erosion in terrestrial carbon (C) sequestration and release remains one of the most important uncertainties in our attempts to determine the potential of soils to mediate climate change. Despite its widely recognized importance for terrestrial C sequestration, to date, no Earth System Model (ESM) implements soil erosion effects on carbon cycling in sufficient detail. So far, available studies have mostly investigated the magnitude of erosional C transport and in-situ measurements of vertical C fluxes on the catchment or regional scale. Recognizing the need to adequately represent C erosion processes and controls in ESMs, we provide a comprehensive cross-disciplinary review on lateral C redistribution in the landscape and discuss the implications for biogeochemical cycling of carbon. We present current knowledge on the role of erosional C distribution in controlling the stabilization and release of C in soils, taking into consideration the important geomorphic, ecological, hydrologic, pedologic and micro-climatic processes and controls that affect soil organic carbon (SOC) stock, fluxes, and persistence in dynamic landscapes. Further, we provide an overview on latest experimental and modelling approaches that are being used to investigate the role of erosion in the carbon cycle. Finally, to advance our understanding of the role of soil redistribution in biogeochemical cycles of essential elements, we discuss the most promising topics for future research in this field.

In terrestrial ecosystems, soil respiration is a key pathway of carbon to the atmosphere. It is highly variable in time and space. Its temporal variability at a single point can be reasonably described by changes in soil temperature and moisture. However, it is much more difficult to determine the drivers of its spatial variability. The aim of this study was to elucidate the interrelationship between the spatial variability of soil respiration and the spatial variability of soil redistribution as well as other soil and crop properties. The study was carried out in a small agricultural watershed (4.2ha) subjected to water and tillage erosion processes. During three crop cycles (one of sugar beet, two of winter wheat) soil respiration, soil temperature, and soil moisture were measured in situ at least bi-weekly at 20-22 locations. The first stage was to analyse the interrelation of soil temperature as an important control of soil respiration and soil redistribution. In the second stage, measured CO 2 effluxes were standardised to 15�C and mean fluxes at each location were calculated for the sugar beet year, as well as two growing phases under winter wheat. The mean CO 2 effluxes for the five resulting phases at each measuring location were correlated to soil and crop properties and modelled soil redistribution. Moreover, the intercorrelation of all explanatory variables was analysed using principal component analyses, and these principal components were correlated to standardised CO 2 effluxes. Except for the second phase in 2009 with combined autotrophic and heterotrophic respiration, which was dominated by root respiration, in all phases there was a tendency that CO 2 effluxes at erosional sites were smaller than at depositional sites. The combined analysis of CO 2 effluxes, erosion, and other explanatory variables indicates that for heterotrophic respiration (between rows in the case of sugar beet and before significant plant growth in the case of winter wheat) the spatial variability of median grain size and bulk density had the most consistent effect on the spatial variability of soil respiration. In contrast, soil moisture was less important and topsoil SOC had more or less no effect on CO 2 effluxes. Only in two measuring phases (Phase 2 2008 and Phase 1 2009) did the combined analysis show that total erosion was one of the dominant variables for the spatial variability in CO 2 effluxes. In general, the relatively inconsistent effect of soil erosion status on spatial variability of CO 2 effluxes is somewhat surprising, as there are a number of different reasons which support the assumption that CO 2 effluxes at erosional sites should be smaller than at depositional sites. A major reason for the observed behaviour might be the compensating effect of tillage and water erosion and the counteracting effects of both processes on soil respiration. This underlines the importance of field-scale studies to gain further insight into the interrelation of soil redistribution and CO 2 effluxes. � 2011 Elsevier B.V.

Soil redistribution on arable land significantly affects lateral and vertical soil carbon (C) fluxes (caused by C formation and mineralization) and soil organic carbon (SOC) stocks. Whether this serves as a (C) sink or source to the atmosphere is a controversial issue. In this study, the SPEROS-C model was modified to analyse erosion induced lateral and vertical soil C fluxes and their effects upon SOC stocks in a small agricultural catchment (4·2ha). The model was applied for the period between 1950 and 2007 covering 30years of conventional tillage (1950-1979) followed by 28years of conservation tillage (1980-2007). In general, modelled and measured SOC stocks are in good agreement for three observed soil layers. The overall balance (1950-2007) of erosion induced lateral and vertical C fluxes results in a C loss of -4·4gCm -2 a -1 at our test site. Land management has a significant impact on the erosion induced C fluxes, leading to a predominance of lateral C export under conventional and of vertical C exchange between soil and atmosphere under conservation agriculture. Overall, the application of the soil conservation practices, with enhanced C inputs by cover crops and decreased erosion, significantly reduced the modelled erosion induced C loss of the test site. Increasing C inputs alone, without a reduction of erosion rates, did not result in a reduction of erosion induced C losses. Moreover, our results show that the potential erosion induced C loss is very sensitive to the representation of erosion rates (long-term steady state versus event driven). A first estimate suggests that C losses are very sensitive to magnitude and frequency of erosion events. If long-term averages are dominated by large magnitude events modelled erosion induced C losses in the catchment were significantly reduced. © 2011 John Wiley & Sons, Ltd.

Surface runoff and associated erosion processes adversely affect soil and surface water quality. There is increasing evidence that a sound understanding of spatial-temporal dynamics of land use and management are crucial to understanding surface runoff processes and underpinning mitigation strategies. In this review, we synthesise the effects of (1) temporal patterns of land management of individual fields, and (2) spatio-temporal interaction of several fields within catchments by applying semivariance analysis, which allows the extent and range of the different patterns to be compared. Consistent effects of management on the temporal dynamics of surface runoff of individual fields can be identified, some of which have been incorporated into small-scale hydrological models. In contrast, the effects of patchiness, the spatial organisation of patches with different soil hydrological properties, and the effects of linear landscape structures are less well understood and are rarely incorporated in models. The main challenge for quantifying these effects arises from temporal changes within individual patches, where the largest contrasts usually occur in mid-summer and cause a seasonally varying effect of patchiness on the overall catchment response. Some studies indicate that increasing agricultural patchiness, due to decreasing field sizes, reduces the catchment-scale response to rainfall, especially in cases of Hortonian runoff. Linear structures associated with patchiness of fields (e.g. field borders, ditches, and ephemeral gullies) may either increase or decrease the hydraulic connectivity within a catchment. The largest gap in research relates to the effects and temporal variation of patch interaction, the influence of the spatial organisation of patches and the interaction with linear structures. In view of the substantial changes in the structure of agricultural landscapes occurring throughout the world, it is necessary to improve our knowledge of the influence of patchiness and connectivity, and to implement this knowledge in new modelling tools.

Monsoon regions are characterized by a pronounced seasonality of rainfall. Model-based analysis of water resources in such an environment has to take account of the specific natural conditions and the associated water management. Especially, plant phenology, which is predominately water driven, and water management, which aims at reducing water shortage, are of primary importance. The aim of this study is to utilize the Soil and Water Assessment Tool (SWAT) in a monsoon-driven region in the Indian Western Ghats by using mainly generally available input data and to evaluate the model performance under these conditions. The test site analyzed in this study is the meso-scale catchment of the Mula and Mutha Rivers (2036 km 2 ) upstream of the city of Pune, India. Most input data were derived from remote sensing products or from international archives. Forest growth in SWAT was modified to account for the seasonal limitation of water availability. Moreover, a dam management scheme was derived by combining general dam management rules with reservoir storage capacity and estimated monthly outflow rates from river discharge. With these model adaptations, SWAT produced reasonable results when compared to mean daily discharge measured in three of four subcatchments during the rainy season (Nash-Sutcliffe efficiencies 0.58, 0.63, and 0.68). The weakest performance was found at the gauge downstream of four dams, where the simple dam management scheme failed to match the combined management effects of the four dams on river discharge (Nash-Sutcliffe efficiency 0.10). Water yield was underestimated by the model, especially in the smallest (headwater) subcatchment (99 km 2 ). Due to the absence of rain gauges in these headwater areas, the extrapolation errors of rainfall estimates based on measurements at lower elevations are expected to be large. Moreover, there is some indication that evapotranspiration might be underestimated. Nevertheless, it can be concluded that using generally available data in SWAT model studies of monsoon-driven catchments provides reasonable results, if key characteristics of monsoon regions are accounted for and processes are parameterized accordingly.

The study aimed to analyze the spaƟ al variability of surface soil moisture at diff erent spaƟ al scales based on fi eld measurements and remote sensing esƟ mates. MulƟ temporal Envisat satellite Advanced SyntheƟ c Aperture Radar (ASAR) data were used to derive the surface soil moisture uƟ lizing an empirical C-band retrieval algorithm. Eight wide-swath (WS) images with a spaƟ al resoluƟ on of 150 m acquired between February and October 2008 were used to determine the surface soil moisture contents. The accuracy of the surface soil moisture retrievals was evaluated by comparison with in situ measurements. This comparison yielded a root mean square error of 5% (v/v). Based on our in situ measurements as well as remote sensing results, the relaƟ onship of the coeffi cient of variaƟ on of the spaƟ al soil moisture paƩ erns and the mean soil moisture was analyzed at diff erent spaƟ al scales ranging from the catchment scale to the fi eld scale. Our results show that the coeffi cient of variaƟ on decreases at all scales with increasing soil moisture. The gain of this relaƟ onship decreases with scale, however, indicaƟ ng that at a given soil moisture state, the spaƟ al variaƟ on at the large scale of whole catchments is larger than at the fi eld scale. Knowledge of the spaƟ al variability of the surface soil moisture is important to beƩ er understand energy exchange processes and water fl uxes at the land surface as well as their scaling properƟ es. AbbreviaƟ ons: ASAR, Advanced SyntheƟ c Aperture Radar; SAR, syntheƟ c aperture radar; WS, wide swath. Soil moisture and its distribu�u on in space and time plays a critical role in the surface energy balance at the soil–atmosphere interface; it is a key variable infl uencing the partitioning of solar energy into latent and sensible heat fl ux as well as the partitioning of precipitation into runoff and percolation. In situ measurements of soil moisture are time and cost intensive. Due to their large spatial variability, estimation of spatial patterns of soil moisture from fi eld measurements is rather diffi cult and not feasible for large-scale analyses. Although hydrologic models have shown their capability to derive spatial soil moisture patterns, their application is a challenging task, requiring a multitude of input data (such as soil properties, i.e., hydraulic characteristics and permeability, along with meteorologic and climatologic data). Neither the full spatial variability of these environmental parameters nor the full details of the processes are typically known, thus modeled spatial patterns tend to reduce spatial variability. Th erefore, as well as due to the need for independent validation, direct and repeatable soil moisture measurements covering large spatial scales obtained from remote sensing instruments is becoming increasingly necessary and now, with the advent of new sensor generations, feasible.

Knowledge of erosion rates under real conditions is of great concern regarding sustainability of landuse and off-site effects on water bodies and settlements. Experimentally derived rates of sheet and rill erosion are often biased by experimental settings, which deviate considerably from typical landuse, by short measuring periods and by small spatial extensions, which do not account for the pronounced spatio-temporal variability of erosion events. We compiled data from 27 studies covering 1076 plot years to account for this variability. Modelling was used to correct for deficiencies in the experimental settings, which overrepresented arable land and used steeper and shorter slopes as well as higher erosivity than typically found in reality. For example, the average slope gradient was 5.9° for all arable plot experiments while it is only 2.6° on total arable land in Germany. The expected soil loss by sheet and rill erosion in Germany after taking real slopes, landuse and erosivity into account averaged 2.7 t ha− 1 yr− 1. Annual crops contributed the largest proportion (90%) but hops despite its negligible contribution to landuse (0.06%) still contribute 1.0% due to its extraordinary rapid erosion, which was even faster than the measured bare fallow soil loss standardized to otherwise identical conditions. Bare fallow soil loss, which is often used as baseline, was 80 t ha− 1 yr− 1 when standardized to 5.1° slope gradient, 200 m flow path length, and average German erosivity.

Soil erosion models are essential tools for the successful implementation of effective and adapted soil conservation measures on agricultural land. Therefore, models are needed that predict sediment delivery and quality, give a good spatial representation of erosion and deposition and allow us to account for various soil conservation measures. Here, we evaluate how well a modified version of the spatially distributed multi-class sediment transport model (MCST) simulates the effectiveness of control measures for different event sizes. We use 8 year runoff and sediment delivery data from two small agricultural watersheds (0·7 and 3·7 ha) under optimized soil conservation. The modified MCST model successfully simulates surface runoff and sediment delivery from both watersheds; one of which was dominated by sheet and the other was partly affected by rill erosion. Moreover, first results of modelling enrichment of clay in sediment delivery are promising, showing the potential of MCST to model sediment enrichment and nutrient transport. In general, our results and those of an earlier modelling exercise in the Belgian Loess Belt indicate the potential of the MCST model to evaluate soil erosion and deposition under different agricultural land uses. As the model explicitly takes into account the dominant effects of soil-conservation agriculture, it should be successfully applicable for soil-conservation planning/evaluation in other environments.

Within the GLOWA-Danube project, the integrated decision support system DANUBIA was developed to address effects of global change on water resources of the Upper Danube watershed (∼80,000 km 2 ). Key components of DANUBIA in respect to water quality and plant growth modelling are nitrogen turnover, nitrogen fluxes and storages. This paper discusses an approach to model soil nitrogen dynamics in a mesoscale watershed. Within the model, the soil column is represented by three soil layers. The model components for water fluxes, nitrogen uptake and nitrogen transformation are process-based. To validate the model, field data from four locations were used. Nitrogen modelling results are in good agreement with measured data. Statistical analysis for soil nitrogen and water content resulted in satisfactory indices of agreement. The study demonstrated that the coupled soil moisture and soil nitrogen transformation model is suitable to simulate the fate of mineral nitrogen within the soil profile on the field scale. Sensitivity studies indicate that the model quality for large scale modelling depends particularly upon the appropriate representation of sandy soils, the accurate parameterization of the saturated hydraulic conductivity and the precise initialization of soil mineral nitrogen content.

Rapid land use and land-cover changes strongly affect water resources. Particularly in regions that experience seasonal water scarcity, land use scenario assessments provide a valuable basis for the evaluation of possible future water shortages. The objective of this study is to dynamically integrate land use model projections with a hydrologic model to analyze potential future impacts of land use change on the water resources of a rapidly developing catchment upstream of Pune, India. For the first time projections from the urban growth and land use change model SLEUTH are employed as a dynamic input to the hydrologic model SWAT. By this means, impacts of land use changes on the water balance components are assessed for the near future (2009-2028) employing four different climate conditions (baseline, IPCC A1B, dry, wet). The land use change modeling results in an increase of urban area by +23.1% at the fringes of Pune and by +12.2% in the upper catchment, whereas agricultural land (-14.0% and -0.3%, respectively) and semi-natural area (-9.1% and -11.9%, respectively) decrease between 2009 and 2028. Under baseline climate conditions, these land use changes induce seasonal changes in the water balance components. Water yield particularly increases at the onset of monsoon (up to +11.0mm per month) due to increased impervious area, whereas evapotranspiration decreases in the dry season (up to -15.1mm per month) as a result of the loss of irrigated agricultural area. As the projections are made for the near future (2009-2028) land use change impacts are similar under IPCC A1B climate conditions. Only if more extreme dry years occur, an exacerbation of the land use change impacts can be expected. Particularly in rapidly changing environments an implementation of both dynamic land use change and climate change seems favorable to assess seasonal and gradual changes in the water balance.

There is still an ongoing scientific discussion regarding the importance of erosion-induced lateral soil organic carbon (SOC) redistribution for the burial and/or mineralisation of carbon and the resulting long-term C balance at the catchment scale. Especially the effects of the event driven nature of water erosion and the potentially associated enrichment of SOC in sediment delivery are still unclear. In general, two processes lead to enrichment of SOC: (i) enrichment due to selective interrill erosion at erosion sites, and (ii) enrichment due to selective depletion at deposition sites. In this study, the conceptual soil erosion and SOC turnover model SPEROS-C was adapted to integrate these processes and applied in a small arable catchment (4.2 ha) in Germany for a 57-year period. A total number of 901 model runs were performed with different realisations of frequency and magnitude of water erosion as well as realisations of enrichment and depletion ratios taken from literature and compared to a reference model run representing mean annual erosion without enrichment processes. In general, our modelling study indicates that ignoring temporal variability and enrichment processes may lead to a substantial misinterpretation of erosion-induced C fluxes. Especially the vertical C flux (difference between C inputs from plant assimilates and organic fertilizer and SOC mineralisation) at deposition sites strongly depends on the model parameterisation ranging from a maximum C source of − 336 g C m− 2 to a maximum C sink of 44 g C m− 2. In combination with a substantially higher C export due to enrichment processes, the overall C balance of the catchment potentially turns into a maximum C source of − 44 g C m− 2 at the end of the simulation period compared to a C source of − 1 g C m− 2 for the reference run.