In recent years, Compound Specific Stable Isotope (CSSI) techniques have enabled promising new tracers to track land-use-specific sediment sources. However, empirical data exploring the technique, ...particularly under controlled conditions, is still scarce. Hence, the main goal of this study is to explore the suitability of CSSI to identify sediment sources under different land use in the small agricultural site of Mistelbach (8.7ha) located in Austria. In a previous study, the authors quantified, with a 137Cs-based reconnaissance approach, a sedimentation magnitude of 4mmyear−1 in the deposition zone at the outlet of that study site. To obtain detailed information on the sediment provenance, CSSI techniques based on the measurement of δ13C signatures of natural fatty acids (FAs), were used. A cost effective sampling approach involving composite sampling, identified potential sediment source materials from the four main agricultural fields. Two long-chain FAs (i.e. C22:0=behenic acid; C24:0=lignoceric acid) as well as bulk δ13C allowed the best statistical discrimination for apportioning the origin of the sediments. Four mixing models (i.e. IsoSource, SIAR, MixSIAR and SIMMR) applied to the data generated similar results. IsoSource performed as well as the other Bayesian models tested.
The main grazed waterway of the basin, identified as one of the four sources of the sediment, was evaluated to have contributed 55.1±5% (IsoSource), 53.9±2.7% (SIAR), 53.9±2.7% (MixSIAR) and 54.0±2.7% (SIMMR) to the sediment. The estimated contributions of the sources to the sediment are consistent with the land use information and the distance of the sources to the outlet. More than 80% of the sediment deposited at the basin exit originates from the two sources which had maize cultivation, one of the more erosive crops, in particular at the beginning of the growing season. This study emphasizes that CSSI and 137Cs techniques are complementary for establishing land sediment redistribution. Their combined use could provide key decision support knowledge for optimised decision-making of land managers to ensure the sustainability of agro-ecosystem management.
•CSSI techniques proposed to track sediment movement within an agricultural basin.•Combined sampling when using CSSI techniques to reduce analytical labour.•Four mixing models (IsoSource, SIAR, MixSIAR, SIMMR) generated similar results.•Historical land use records are key information to understand CSSI findings.•CSSI and FRN techniques are complementary for establishing sediment redistribution.
In a laboratory rainfall simulator study soil surface roughness was measured using contact (roller chain, pin meter) and noncontact devices (laser scanner, photogrammetry). Soil surfaces with two ...initial roughness conditions (aggregates <
20 mm and <
63 mm) were investigated before and after 90 mm of simulated rainfall. Measured plot area was 50 by 55 cm. A comparison of soil roughness measurement techniques was undertaken with regard to data acquisition and computation efforts, resolution, precision and capability to represent soil surface features.
As for the contact methods, resolution (cm range) and precision (mm range) is limited which constrains their application to calculation of simple surface parameters. Resolution and precision in the sub millimeter range could be obtained with the laser scanner, while for the photogrammetric method the measurement uncertainty was approximately 1–2 mm. Measurement time was highest (90 min) for the pin meter technique, though data were ready to use for analyses. Laser scanner measurements took 34 min. Several steps of data post-processing required 30 more minutes. Data acquisition was fastest for photogrammetry (5 min), but expert knowledge as well as special hard- and software were necessary for time-consuming photo analyses, taking about 120 min.
The chain and pin meter were compared using a profile index. Profile lengths matched well for smooth surfaces; on rough surfaces, the chain meter gave shorter profile lines. Between profile index from chain measurements and the random roughness derived from pin meter data a polynomial regression could be found. Parameters of distributions of elevations as well as inclinations and depressions were used to compare the laser scanner and the photogrammetric technique. Generally the laser scanner was able to reproduce small aggregates as well as voids in between them, while DEM from stereophotos was smoothed between major aggregates. This led to skewed distributions of elevations and inclinations, as well as to a lower surface area (up to 39%), and a lower depression volume (up to 68%). Shapes of depressions were significantly different as well. The used photogrammetric technique is supposed to be successful in producing adequate DEMs for already smoothed surfaces, e.g. after rainfall events.
The study revealed different fields of application and limitations of the compared devices. Using a non-adequate technique for certain situations will definitely have implications on further analyses concerning connectivity of runoff pathways, surface protection from raindrop impact or runoff detachment and sediment transport.
Abstract
Every application of soil erosion models brings the need of proper parameterisation, that is, finding physically or conceptually plausible parameter values that allow a model to reproduce ...measured values. No universal approach for model parameterisation, calibration and validation exists, as it depends on the model, spatial and temporal resolution and the nature of the datasets used. We explored some existing options for parameterisation, calibration and validation for erosion modelling exemplary with a specific dataset and modelling approach. A new Morgan‐Morgan‐Finney (MMF)‐type model was developed, representing a balanced position between physically‐based and empirical modelling approaches. The resulting model termed ‘calculator for soil erosion’ (CASE), works in a spatially distributed way on the timescale of individual rainfall events. A dataset of 142 high‐intensity rainfall experiments in Central Europe (AT, HU, IT, CZ), covering various slopes, soil types and experimental designs was used for calibration and validation with a modified Monte‐Carlo approach. Subsequently, model parameter values were compared to parameter values obtained by alternative methods (measurements, pedotransfer functions, literature data). The model reproduced runoff and soil loss of the dataset in the validation setting with
R
2
adj
of 0.89 and 0.76, respectively. Satisfactory agreement for the water phase was found, with calibrated saturated hydraulic conductivity (k
sat
) values falling within the interquartile range of k
sat
predicted with 14 different pedotransfer functions, or being within one order of magnitude. The chosen approach also well reflected specific experimental setups contained in the dataset dealing with the effects of consecutive rainfall and different soil water conditions. For the sediment phase of the tested model agreement between calibrated cohesion, literature values and field measurements were only partially in line. The methods we explored may specifically be interesting for use with other MMF‐type models, or with similar datasets.
Managing agricultural watersheds in an environmentally friendly manner necessitate the strategic implementation of well-targeted sustainable land management (SLM) practices that limit soil and ...nonpoint source pollution losses and translocation. Watershed-scale SLM-scenario modeling has the potential to identify efficient and effective management strategies from the field to the integrated landscape level. In a case study targeting a 66-hectare watershed in Petzenkirchen, Lower Austria, the Soil and Water Assessment Tool (SWAT) was utilized to evaluate a variety of locally adoptable SLM practices. SWAT was calibrated and validated (monthly) at the catchment outlet for flow, sediment, nitrate-nitrogen (NO
3
–N), ammonium nitrogen (NH
4
–N), and mineralized phosphorus (PO
4
–P) using SWATplusR. Considering the locally existing agricultural practices and socioeconomic and environmental factors of the research area, four conservation practices were evaluated: baseline scenario, contour farming (CF), winter cover crops (CC), and a combination of no-till and cover crops (NT + CC). The NT + CC SLM practice was found to be the most effective soil conservation practice in reducing soil loss by around 80%, whereas CF obtained the best results for decreasing the nutrient loads of NO
3
–N and PO
4
–P by 11% and 35%, respectively. The findings of this study imply that the setup SWAT model can serve the context-specific performance assessment and eventual promotion of SLM interventions that mitigate on-site land degradation and the consequential off-site environmental pollution resulting from agricultural nonpoint sources.
Mapping monthly rainfall erosivity in Europe Ballabio, Cristiano; Borrelli, Pasquale; Spinoni, Jonathan ...
The Science of the total environment,
02/2017, Volume:
579
Journal Article
Peer reviewed
Open access
Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale ...(REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315MJmmha−1h−1) compared to winter (87MJmmha−1h−1).
The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be applied in different seasons of the year.
Display omitted
•Rainfall erosivity is mapped intra-annually for the first time at European scale.•The modelling is based on a developed monthly Rainfall Erosivity Database at European Scale (REDES).•REDES data is modelled with WorldClim covariates using Cubist regression trees.•Using Cubist erosivitiy is effectively spatially estimated over Europe for each month.•Seasonal patterns of erosivity are further analyzed using clustering techniques.
The exposure of the Earth's surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil ...degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have large uncertainties. This hampers the implementation of effective soil degradation mitigation and restoration strategies. Quantifying rainfall erosivity is challenging as it requires high temporal resolution(<30 min) and high fidelity rainfall recordings. We present the results of an extensive global data collection effort whereby we estimated rainfall erosivity for 3,625 stations covering 63 countries. This first ever Global Rainfall Erosivity Database was used to develop a global erosivity map at 30 arc-seconds(~1 km) based on a Gaussian Process Regression(GPR). Globally, the mean rainfall erosivity was estimated to be 2,190 MJ mm ha
h
yr
, with the highest values in South America and the Caribbean countries, Central east Africa and South east Asia. The lowest values are mainly found in Canada, the Russian Federation, Northern Europe, Northern Africa and the Middle East. The tropical climate zone has the highest mean rainfall erosivity followed by the temperate whereas the lowest mean was estimated in the cold climate zone.
Optical disdrometers can be used to estimate rainfall erosivity; however, the relative accuracy of different disdrometers is unclear. This study compared three types of optical laser-based ...disdrometers to quantify differences in measured rainfall characteristics and to develop correction factors for kinetic energy (KE). Two identical PWS100 (Campbell Scientific), one Laser Precipitation Monitor (Thies Clima) and a first-generation Parsivel (OTT) were collocated with a weighing rain gauge (OTT Pluvio
2
) at a site in Austria. All disdrometers underestimated total rainfall compared to the rain gauge with relative biases from 2% to 29%. Differences in drop size distribution and velocity resulted in different KE estimates. By applying a linear regression to the KE-intensity relationship of each disdrometer, a correction factor for KE between the disdrometers was developed. This factor ranged from 1.15 to 1.36 and allowed comparison of KE between different disdrometer types despite differences in measured drop size and velocity.
Soil erosion is a major form of land degradation throughout the world and the key environmental problem that threatens the ecosystem of the Chinese Loess Plateau. In this study, we determined the ...sediment yield from a small dam-controlled watershed in the Huangfuchuan watershed, northern Loess Plateau, with a drainage area of 0.64km2. The dam infill sediment provided evidence of at least 31 flood couplets, which corresponded to rain storms during 1958–1972. In total, 1.65×105t sediment was accumulated within the whole check dams in this period. The annual sediment yield ranged from null in 1965 to 59,990t in 1959. We used the modified WATEM/SEDEM model to simulate soil erosion and the sediment yield in the watershed and the sedimentation records were used for model verification. The model produced satisfactory results; the total soil erosion and sediment delivery ratio were estimated to be 1.97×105t and 83.6%, respectively. Bare weathered stone in the steep gullies contributed >90% of the sediment yield, while the remainder was derived mainly from bare loess slopes and the alluvial plain. This study suggests that analyzing sedimentation behind check dams and applying the WATEM/SEDEM model are useful for the quantitative analysis of sediment dynamics in ungauged basins on the Loess Plateau.
•Sediment yield was estimated using check dam sedimentation data and the WATEM/SEDEM model.•In total, 1.65×105t sediment was accumulated behind the check dam during 1958–1972.•The model simulation agreed well with the estimated dam sedimentation rates.•Bare weathered stone in the steep gullies contributed ca. 93% of the sediment yield.
The Lake Basaka catchment (Ethiopia) has undergone a significant land use–land cover (LULC) change and lake level rise over the past five decades. Significant quantities of water and sediment flow ...annually into the lake through erosion processes. An appropriate method of estimating the surface run‐off from such ungauged and dynamic catchment is extremely important for delineating sensitive areas (based on run‐off responses) to be protected and for development of suitable measures to reduce run‐off and associated soil loss. Reliable prediction of run‐off, however, is very difficult and time‐consuming for catchments such as that of Lake Basaka. The present study estimated the dynamics of surface (direct) run‐off using the NRCS‐CN model in ArcGIS, assisted by remote sensing and ancillary data. The results indicated the Lake Basaka catchment experienced significant temporal and spatial variability in its run‐off responses, depending on the rainfall (amount and distribution) pattern and LULC changes. A significant run‐off increase occurred after 1973, consistent with significant LULC changes and lake level increments occurring after that period. A reduced vegetation cover also resulted in increased run‐off coefficient of the lake catchment from 0.11 in the 1970s to 0.23 in the 2000s, indicating the important need to consider possible future LULC evolution when forecasting the lake catchment run‐off behaviour.
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