•Higher water content and greater surface seal formation reduces splash erosion.•Soil saturated hydraulic conductivity reflects the changes in surface structure.•Higher rainfall kinetic energy ...contributes to greater surface seal development.•Kinetic energy of simulated rainfall greatly depends on drop velocity spectrum.
Soil erosion by water is one of the most severe soil degradation processes. Splash erosion is the initial stage of soil erosion by water, resulting from the destructive force of rain drops acting on soil surface aggregates. Apart from rainfall properties, constant soil physical properties (texture and soil organic matter) are crucial in understanding the splash erosion. However, there is lack of information about the effect of variable soil properties such as soil initial water content and surface condition (seal formation) on splash erosion. The objective of the present study was to determine how initial water content and surface condition affected soil splash erosion under simulated rainfall. The changes in soil surface condition were characterized by hydraulic variability (saturated hydraulic conductivity) due to surface seal formation. Slit loam and loamy sand soil textures were used in the experiment. The soil samples were collected from the top layer; air dried, and filled into modified Morgan splash cups for splash erosion measurements. Rainfall was created in the laboratory using two types of rainfall simulators covering intensity range from 28 to 54 mm h−1 and from 35 to 81 mm h−1. The soil samples were exposed to three consecutive rainfall simulations with different time intervals between simulations and different initial water content and surface conditions (air-dried, wet-sealed, and dry-crusted). Wet-sealed soil samples had up to 70% lower splash erosion rate compared to air-dried samples, due to surface ponding followed by seal formation. A significant decrease in soil saturated hydraulic conductivity indicated the formation of surface seal for silt loam soils. A non-significant decrease in saturated hydraulic conductivity for loamy sand soil was attributed to earlier formation of stable seals. Two different rainfall simulators produced different amount of splash erosion rates; however, the splash erosion development for increasing rainfall intensity was almost equal considering same initial surface condition. These results provide insight into dynamic changes of individual soil parameters affected by rainfall, and could find wider application for more complex soil erosion prediction models.
Stable isotope techniques can be used to investigate evapotranspiration and its partitioning into evaporation and transpiration. However, verification is often difficult due to missing information ...about actual evapotranspiration. Therefore, in this study a methodology tested for laboratory conditions was modified for field applications. Evapotranspiration, which was determined by weighing lysimeters, and isotope techniques were combined with soil water and lysimeter measurements to calculate evaporation and transpiration rates of soybean under natural conditions. The case study was conducted in 2019 in Groß-Enzersdorf, Austria. The results show that the methodology was suited to measure actual variations of evaporation and transpiration ratios, even during dry periods. Weekly evaporation (0.5-2.2 mm d
−1
) and transpiration (1.3-4.3 mm d
−1
) rates as well as the respective ratios (transpiration 43-85%) agreed with the results of numerical modelling and values from the literature, confirming the applicability of the modified methodology for portioning evapotranspiration in the field.
This article outlines the major scientific objectives of the SHui project that seeks to optimize soil and water use in agricultural systems in the EU and China, by considering major current ...scientific challenges in this area. SHui (for Soil Hydrology research platform underpinning innovation to manage water scarcity in European and Chinese cropping systems) is large cooperative project that aims to provide significant advances through transdisciplinary research at multiple scales (plot, field, catchment and region). This paper explains our research platform of long-term experiments established at plot scale, approaches taken to integrate crop and hydrological models at field scale; coupled crop models and satellite-based observations at regional scales; decision support systems for specific farming situations; and the integration of these technologies to provide policy recommendations through socio-economic analysis of the impact of soil and water saving technologies. It also outlines the training of stakeholders to develop a basic common curriculum despite the subject being distributed across different disciplines and professions. As such, this article provides a review of major challenges for improving soil and water use in EU and China as well as information about the potential to access information made available by SHui, and to allow others to engage with the project.
•We made updated R-factor maps for Austria’s main agricultural production zones.•Significant differences in spatial R-factor distribution were found between studies.•Spatiotemporally distributed ...R-factors revealed areas at risk of soil erosion.
Rainfall erosivity is one of the key parameters influencing the degree of soil erosion. Due to the high spatiotemporal variability of rainfall erosivity and the influence of a changing climate it is crucial to use spatially well-distributed and temporally current rainfall data. Rainfall erosivity in Austria has been estimated by previous studies with varying rainfall data amounts. This study aimed to create an updated R-factor map for Austria and its main agricultural production zones based on a larger number of rainfall stations and a recent time series. As well as, compare R-factors from previous studies to identify differences in erosivity estimation. Rainfall data from 171 stations throughout Austria were gap-filled and corrected to improve data quality. Rainfall erosivity was calculated for 1995–2015 for the vegetation period and annually and used to establish two linear regressions describing rainfall erosivity as a function of mean rainfall amount. The regressions were applied to the 1 km2 daily rainfall grids from the SPARTACUS dataset to create the spatially distributed rainfall erosivity maps. Differences in the temporal and spatial distribution of rainfall erosivity, erosion index and erosivity density between the main agricultural production zones showed areas at risk of soil erosion and timing of vulnerability. The highest rainfall erosivities were found in the agriculturally important eastern regions of Austria during the summer months. Compared to previous studies, considerable differences in local R-factor estimation were found. The significantly larger number of rainfall stations and an updated time series increased the representativeness of rainfall erosivity estimation in Austria, which can contribute to a more precise soil erosion risk assessment.
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•Indoor rainfall simulation with undisturbed soil monoliths.•Rain intensity and antecedent moisture affect transport pathways for organic carbon.•Rain intensity and antecedent ...moisture affect organic carbon losses.•Rain intensity and antecedent moisture affect quality of organic carbon losses.
Under conditions of climate change, the severity and probability of storm events and droughts are expected to increase, this may affect the partitioning into surface and subsurface runoff. However, there is still a debate on how such extreme weather conditions affect the leaching of soil organic carbon. The aim of this study was to ascertain the impact of rainfall intensity (63 vs 79 mm h−1) and antecedent soil moisture (Matric potential: −10 hPa vs −450 hPa) on flow partitioning in the transportation (fluxes and timing) of dissolved (DOC) and particulate organic carbon (POC). Rainfall simulation experiments using undisturbed soil monoliths (1 m × 0.5 m × 0.3 m) allowed to monitor the transport of water, sediments, DOC, and POC via surface and shallow subsurface runoff. In addition, the composition of the leached organic matter was analysed using photometric and fluorometric methods.
Most of the organic carbon was transported as POC via surface runoff. In the surface runoff, the influence of antecedent soil moisture on POC loss was larger than rainfall intensity, while rainfall intensity had a greater influence on DOC losses. Under initially unsaturated conditions, surface sealing reduced the infiltration rate, thus fuelling the total surface runoff, which, in turn, enhanced the transported total sediment and POC load of the surface runoff. While POC dominated surface runoff, DOC played a crucial role in the subsurface runoff with higher DOC concentrations under unsaturated conditions. In contrast to other treatments, DOC exported from unsaturated soils rained with high intensity had a unique composition with the highest proportion of humic-like peaks (A, M, C), protein-like peaks (T) and components (C4), suggesting a concentrating effect on DOC at those soils. Altogether, this research acquires new insights into how flow partitioning under extreme weather conditions affects organic carbon losses and which transport mechanism might pose a risk for aquatic systems.
Tillage is an essential practice for soil preparation in agriculture that influences a broad variety of soil parameters. However, the long-term implications of tillage on soil health are complex, ...context specific, and need to be better understood. The aim of our study is to evaluate soil physical, chemical, and biological effects of three different tillage practices: conventional tillage (CT), mulch tillage (MT), and no-till (NT). A long-term experiment in Mistelbach, Lower Austria, was launched in 1994 and comprehensively sampled in 2002 and 2021. To evaluate tillage-impacts over the two decadal monitoring we assessed soil health indicators in the 0–20 cm soil depth (conventional ploughing layer) and below 20 cm. A "Soil Management Assessment Framework" (SMAF) procedure was applied to assess and compare soil quality using the Soil Quality Index (SQI). Considering multiple indicators, we found overall quality improvements in all three tillage-experiments over time. However, particularly the conservation practices (MT and NT) enhanced soil quality, predominately soil organic carbon (SOC) and soil physical indicators (e.g. water holding capacity, coarse pores). The study confirms that SOC in the 0–20 cm layer significantly increased under no-till (46 Mg C ha−1) compared to conventional tillage (26 Mg C ha−1). At the same time aggregate stability and water holding capacity increased under conservation agriculture (MT and NT). The proven positive impacts on soil health will further help to promote agricultural practices that sustain productivity while pushing forward climate change mitigation actions in temperate climate.
•Mulch and no-tillage significantly enhanced soil quality over two decades.•Soil organic carbon increased under mulch and no-tillage in the upper soil horizon.•Soil Quality Index provides a holistic overview of long-term tillage impacts.
Rainfall erosivity in Europe Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale ...
Science of the total environment,
04/2015, Volume:
511
Journal Article
Peer reviewed
Open access
Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most ...commonly expressed as the R-factor in the USLE model and its revised version, RUSLE. At national and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based on the best available datasets. Data have been collected from 1541 precipitation stations in all European Union (EU) Member States and Switzerland, with temporal resolutions of 5 to 60min. The R-factor values calculated from precipitation data of different temporal resolutions were normalised to R-factor values with temporal resolutions of 30min using linear regression functions. Precipitation time series ranged from a minimum of 5years to a maximum of 40years. The average time series per precipitation station is around 17.1years, the most datasets including the first decade of the 21st century. Gaussian Process Regression (GPR) has been used to interpolate the R-factor station values to a European rainfall erosivity map at 1km resolution. The covariates used for the R-factor interpolation were climatic data (total precipitation, seasonal precipitation, precipitation of driest/wettest months, average temperature), elevation and latitude/longitude. The mean R-factor for the EU plus Switzerland is 722MJmmha−1h−1yr−1, with the highest values (>1000MJmmha−1h−1yr−1) in the Mediterranean and alpine regions and the lowest (<500MJmmha−1h−1yr−1) in the Nordic countries. The erosivity density (erosivity normalised to annual precipitation amounts) was also the highest in Mediterranean regions which implies high risk for erosive events and floods.
•Rainfall erosivity in Europe & Switzerland is estimated to 722MJmmha−1h−1yr−1.•Rainfall Erosivity Database at European Scale (REDES) includes 1541 stations.•The highest R-factor is in Mediterranean & Alpine regions and lowest in Scandinavia.•The erosivity density shows high variability of the R-factor per precipitation unit.•High resolution (1km grid cell) dataset of R-factor is available for modelling.
•Gridded daily data underestimates rainfall erosivity due to scaling differences.•Bias-correction factors: medians of 0.80 (R-factor) and 0.66 (10-year storm EI).•Future china is expected to ...experience rising rainfall erosivity by 14% ∼ 47%.•Increasing erosivity mainly due to the rising probability of extreme precipitation.
This study focuses on improving the accuracy of projections for future rainfall erosivity by selecting five CMIP6-based and bias-adjusted Global Climate Models (GCMs) in China. These models provide more precise estimations of rainfall erosivity under two future periods (2041–2065 and 2076–2100) and two emission scenarios (SSP1-RCP2.6 and SSP5-RCP8.5). The evaluation of the models' performance involved comparing their estimations of two erosivity indices, namely the annual average rainfall erosivity (R-factor) and the extreme storm EI30 with a 10-year return period (10-year storm EI), with reference erosivity maps of China interpolated from hourly observations at 2381 stations. The results indicate that three models, GFDL-ESM4, IPSL-CM6A-LR, and UKESM1-0-LL, outperform the others in terms of higher Nash-Sutcliffe efficiencies and better spatial correlation, especially in regions prone to water erosion. However, it was observed that the R-factor and 10-year storm EI estimated using Multi-Model Ensembles (MMEs) were significantly underestimated for the historical period due to scaling differences. To address this issue, bias-correction factors were determined for each grid cell to improve future projections. The medians of these correction factors were found to be 0.80 for the R-factor and 0.66 for the 10-year storm EI. Overall, the study projects an increase in rainfall erosivity for most regions in China. Under the SSP1-RCP2.6 and SSP5-RCP8.5 scenarios, the R-factor is expected to rise by 18.9% and 19.8% for the near-term and 26.0% and 46.5% for the long-term, respectively. Similarly, the 10-year storm EI is projected to increase by 14.2% and 17.4% for the near-term and 14.9% and 45.0% for the long-term, respectively. These projected increases are primarily attributed to the elevated probability of extreme precipitation events, highlighting the need for enhanced soil and water conservation measures in China to mitigate the challenges posed by global warming.
Developing countries with an increasing population like Ethiopia experience degradation of land and water resources. To tackle this problem soil and water conservation (SWC) has been practiced and ...recently promoted by the Ethiopian government. However, the effectiveness of SWC practices on runoff and soil erosion have not been studied in detail for their long- and short-term effects. An integrated measurement and modeling study was conducted from 2012 to 2014 in the Gumara-Maksegnit sub watershed to assess the impacts of SWC structures on runoff and sediment yield using the Geospatial Interface for the Water Erosion Prediction Project (GeoWEPP) model. The study was conducted in two adjacent, smaller watersheds where SWC structures were constructed in one of the watersheds (treated sub watershed), while the other one was a control watershed without SWC structures (untreated sub watershed). The treated sub watershed has an area of 27.1 ha and the untreated sub watershed has an area of 31.7 ha. Runoff and sediment yield were compared based on the observations and GeoWEPP model simulations. The GeoWEPP model simulation results predicted the daily runoff satisfactorily for both sub watersheds (R2 = 0.68 and NSE = 0.43 for untreated and R2 = 0.61 and NSE = 0.84 for treated sub watershed). Similarly, the model prediction showed satisfactory results in sediment yield (R2 = 0.61 and NSE = 0.59 for untreated and R2 = 0.57 and NSE = 0.81 for treated sub watershed). SWC structures reduced slope gradient and changed flow accumulation. The observation and simulation study concluded that the treated sub watershed surface runoff was reduced by about 19% as compared to the untreated sub watershed. Similarly, the model estimated that SWC structures constructed in the treated sub watershed reduced the total area that generates soil loss above the set target limit of 10 t ha−1 y−1 from 49% to 38% of the watershed area. SWC has led to a significant reduction in sediment yield by 28 to 38% in these highland watersheds of Ethiopia. The results confirmed that SWC structures have a significant impact to prevent land degradation in the Ethiopian highlands.
•The research relies on comparison of paired watershed, treated and untreated watersheds.•Application of GeoWEPP model in the Gumara-maksegnit watersheds.•Measured runoff and sediment yield are better fitted with the predicted runoff and sediment yield in the both watersheds.•Soil and water conservation structures have a great impact on runoff and sediment yield.
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.
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