Soil erosion is a major global soil degradation threat to land, freshwater, and oceans. Wind and water are the major drivers, with water erosion over land being the focus of this work; excluding ...gullying and river bank erosion. Improving knowledge of the probable future rates of soil erosion, accelerated by human activity, is important both for policy makers engaged in land use decision-making and for earth-system modelers seeking to reduce uncertainty on global predictions. Here we predict future rates of erosion by modeling change in potential global soil erosion by water using three alternative (2.6, 4.5, and 8.5) Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios. Global predictions rely on a high spatial resolution Revised Universal Soil Loss Equation (RUSLE)-based semiempirical modeling approach (GloSEM). The baseline model (2015) predicts global potential soil erosion rates of
43
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7
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9.2
Pg yr−1, with current conservation agriculture (CA) practices estimated to reduce this by ∼5%. Our future scenarios suggest that socioeconomic developments impacting land use will either decrease (SSP1-RCP2.6–10%) or increase (SSP2-RCP4.5 +2%, SSP5-RCP8.5 +10%) water erosion by 2070. Climate projections, for all global dynamics scenarios, indicate a trend, moving toward a more vigorous hydrological cycle, which could increase global water erosion (+30 to +66%). Accepting some degrees of uncertainty, our findings provide insights into how possible future socioeconomic development will affect soil erosion by water using a globally consistent approach. This preliminary evidence seeks to inform efforts such as those of the United Nations to assess global soil erosion and inform decision makers developing national strategies for soil conservation.
•Erosion pins and ANNs were successfully used to assess the spatial variation of soil erosion.•Splash erosion is the dominant type of erosion in the study area compared to the erosion caused by ...surface runoff.•The highest soil erosion rates occur on the lower half of the hillslopes.
Assessment of soil erosion is crucial for any long-term soil conservation plan. Traditional in-situ measurements provide a precise amount of erosion rate; however, the procedure is costly and time-consuming when applied over an extensive area. This study aimed to investigate the use of erosion pins and artificial neural networks (ANNs) to assess the spatial distribution of annual soil erosion rates in the mountainous areas of the north of Iran. First, annual surface erosion and splash erosion were measured using two types of erosion pins. Next, the variables affecting soil erosion (vegetation canopy, the shape of slope, slope gradient, slope length, and soil properties) were identified and estimated through field studies and analysis of a digital elevation model (DEM) and the data set were divided into three subsets of training, cross-validation, and testing. Seven artificial neural network algorithms were used and evaluated to estimate the annual soil erosion rates for the areas without recorded erosion data. Finally, the modeled values were mapped in GIS, and the longitudinal profiles of soil erosion were extracted. Findings showed that (1) Consideration should be given to the generalized feed forward (GFF) network, given the high accuracy rate (NMSE:0.1; R-sqr:0.9) compared to other tested ANN algorithms. (2) Vegetation canopy was found to be the most significant variable in annual soil erosion rate (R: −0.75 to −0.85) compared to other input variables. And (3) Annual measurements of erosion pins revealed that the splash erosion is higher (contributing 62 percent to total erosion) compared to surface runoff erosion (contributing 38 percent to total erosion).
During the storage period of the Three Gorges Reservoir, the bank erosion caused by wind-induced wave is getting more serious, especially for the crushed stone soil bank. The continuous wave scouring ...and erosion destabilize the bank slope and even induce the occurrence of landslides. Based on the energy conservation theory, the bank slope will reach a stable state after continuous wave erosion. Regarding this, this paper derives the prediction formula of the stable slope angle and erosion width when the wave erodes the crushed stone soil bank slope. Model tests on bank slopes with different dry densities and different crushed stone contents under the action of waves were conducted to observe the erosion process of wave-induced crushed stone soil bank slope and verify the proposed prediction formula. The results show that under the action of wave erosion, erosion ridge and collapse steep angle would form at the upper edge of the bank slope and the controlling factors of this process are the dry density of the crushed stone soil and the wave energy. When the content of crushed stone soil gradually increases, the ability of the bank slope to resist wave erosion weakens at first and then gradually strengthens. Comparing the erosion stable slope angle obtained from the model tests with the calculated results using the proposed prediction formula, a linear relationship could be observed, indicating that the proposed prediction formula is reliable for further analysis.
•Rainfall intensity affects both soil detachment and sediment transport.•Sediment transport process controls sheet erosion rate.•Sediment transport modes vary with flow depth and slope ...length.•Optimal mean flow depth for maximal sheet erosion rate was less than 0.1mm.•Slope length was negatively related to sheet erosion rate per unit area.
To date interrill erosion processes are not fully understood under different rainfall and soil conditions. The objectives are to 1) identify the interrill erosion regime and limiting process under the study condition, 2) characterize the interactive effects of rainfall intensity and flow depth on sediment transport competency and mode, and 3) develop a lumped interrill erosion model. A loess loam soil with 39% sand and 45% silt was packed to flumes and exposed to simulated rainfall. A complete factorial design with three factors was used, which included rainfall intensity (48, 62, 102, 149, and 170mmh−1), slope gradient (17.6, 26.8, 36.4, 46.6, and 57.7%), and slope length (0.4, 0.8, 1.2, 1.6, and 2m). Rain splash, sediment discharge in runoff, and flow velocity were measured. Results showed that rainfall intensity played a dual role not only in detaching soil materials but also in enhancing sediment transport. Sediment transport was the process limiting interrill erosion rate under the study condition. Two major sediment transport modes were identified: rainfall-driven rolling/creeping and flow-driven rolling/sliding. The relative importance of each mode was largely determined by flow depth. The competence of the flow in transporting sediment decreased downslope as flow depth increased due to increased dissipation of raindrop energy. The optimal mean flow depth for the maximal interrill erosion rates was <0.1mm, which is much shallower than the widely reported 2mm. Slope length was negatively related to interrill erosion rate. The negative correlation seemed stronger for heavier rains, indicating the cushioning effects of flow depth. Lumped interrill erosion models, developed from short slopes, are likely to overestimate erosion rates. Given transport as the limiting process, the so called erodibility value, estimated with those models, is indeed sediment transportability under the study condition. The effects of slope length on interrill erosion regimes need to be studied further under a wider range of conditions.
Surface erosion is a critical factor in the design and operation of components in particulate handling services. It affects their performance, reliability, and service life. In spite of decades of ...investigations and research, the complete phenomenon of surface erosion has not been exactly known. A fundamental requirement from the design perspective is to enhance the service life of the components subjected to erosion. It requires an understanding of erosion mechanisms, factors affecting the erosion rate, and approaches to model the erosion. The erosive wear mechanism depends on material properties and operating conditions. The present work describes the various erosion mechanisms associated with different types of target materials and factors affecting them. The measurement technologies and test methods used to determine the erosion. Further, different theoretical and empirical models available for erosion prediction are discussed. In that, the mechanisms considered, as well as various assumptions used to derive the theoretical models are presented. The numerical modeling methods to predict the erosion, difficulties, and recent progress in erosion prediction investigations are discussed as well. Finally, the needs for future investigations are indicated.
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•The effect of global warming on soil erosion was quantified.•The suitability of soil erosion models for global scale assessment was evaluated.•Spatial patterns of soil erosion under global warming ...were analyzed comprehensively.•The main climatic forces driving changes in soil erosion were analyzed.
Climate warming has widely variable effects on terrestrial ecosystems, and warming-induced changes in soil erosion could accelerate or slow down future warming. Numerous methods and models have been developed to evaluate soil erosion. However, the quantification of the impact of climate change on soil erosion and selection of the most appropriate soil erosion model for a particular study area remain unclear. With the intensification of climate warming, solutions to these problems are becoming increasingly more important. In this study, we performed a meta-analysis of research on global soil erosion to verify the effects of climate warming on soil erosion. Four databases were searched for relevant peer-reviewed publications from 1980 to 2019 using five keywords. The results showed that soil erosion has increased worldwide, mainly in semiarid areas (p < 0.001). While soil erosion has decreased at high latitudes, it has increased at middle and low latitudes. Different soil erosion models provided significantly different simulation results. Among various models, the Revised Universal Soil Loss Equation and Wind Erosion Equation models showed the highest simulation accuracies for water erosion (p < 0.001) and wind erosion (p < 0.05), respectively. At present, the factors driving soil erosion under climate warming remain highly uncertain. In addition, differences in underlying surfaces and the number of study samples also affect soil erosion assessments. In the future, interactions between climate warming and soil erosion (especially in wind erosion models) should be studied in more detail, and the relationship between the UN Sustainable Development Goals and soil erosion should be further considered.
Whereas current erosion models are successful in quantitative estimates of soil erosion by water flow, modeling the coevolution of geomorphological features, particularly rill network properties and ...soil erosion on hillslopes, is still a major challenge. In this study, we propose a rill evolution modeling approach and combine it with a rainfall‐runoff and soil erosion model to simulate the feedback loop of hillslope geomorphic development and soil erosion processes. Rill evolution is mainly characterized by three rill network attributes, rill density, orientation angle, and rill width, all modeled with physical equations. The entire rainfall‐runoff‐erosion and rill evolution model is tested against a set of rill network evolution and soil erosion data from an experimental hillslope subjected to successive rainfall events. The simulated spatial and temporal variations of rill network characteristics and soil erosion agree well with the measured data. The results demonstrate that the three rill network characteristics continually alter the partitioning of interrill and rill flows and affect the interrill and rill flow erosivity and soil erosion, which in turn modify the rill geometry and rill network planform. Comparatively, existing approaches such as Water Erosion Prediction Project (WEPP) that ignore the rill evolution processes largely underestimate the hillslope soil erosion when using time independent model parameters. Moreover, a sensitivity analysis indicates that both the rill evolution and soil erosion processes are sensitive to the rill evolution parameters, rainfall intensity, and slope angle. These results can inform the development of general geomorphic evolution and soil erosion models on evolving rilled hillslopes.
Key Points
A set of conceptual equations using flow hydraulic and erosion properties are proposed to simulate evolving rill characteristics
A theoretical framework is presented to simulate coupled rill evolution and soil erosion processes
The coupled model is sensitive to the rill evolution parameters, rainfall intensity, and slope angle
Despite many efforts over the last decades to understand rill erosion processes, they remain unclear. This paper presents the results of rill experiments accomplished in Andalusia in September 2008 ...using a novel experimental set up. 72
L of water are introduced with an intensity of 9
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into a rill. Rill cross sections, slope values, flow velocities and sediment concentrations were measured and these values were used to calculate sediment detachment and transport. Each experiment was repeated once within 15
min. With this new experimental setup it is possible to calculate several hydraulic parameters like hydraulic radius, wetted perimeter, flow cross section, transport rate and transport capacity which are usually estimated from coarse flow and rill parameters. In rill experiments, four different natural rills were flooded with the same experimental setup. Several processes like transport of loose material, erosion, bank failure and knickpoint retreat and the runoff effectiveness showed different and variable intensities. The sediment concentrations ranged between 5.2 and 438
g
L
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. In most cases, detachment rates are close to the transport capacity and, in some cases, the transport capacity is even exceeded. This can be explained by the occurrence of different erosion processes within a rill (e.g. detachment, bank failure, and headcut retreat) which are not all explained by the given equations. The results suggest that the existing soil erosion equations based on shear forces exerted by the flowing water are not able to describe rill erosion processes satisfactory. Too many different processes with a high spatial and temporal variability are responsible for rill development.
► Using the new setup input parameters for models can be directly measured. ► Different erosion processes show very different spatial and temporal distributions. ► In some experiments transport rates clearly exceed transport capacities. ► Most running processes are not accounted for in model equations.
Severe equipment degradation in production piping can occur for gas–solid flows. Advances in modeling and solid particle erosion simulations are gained through matching computer generated predictions ...to real-world experimental results. This paper presents a comprehensive approach in modeling and computational study to determine erosion in elbows due to sand particles entrained in air. Firstly, utilizing a particle image velocimetry (PIV) technique, the slip velocity between the gas and sand particles in a direct impact geometry has been measured. Secondly, an erosion equation has been generated based on PIV results and erosion testing of stainless steel in air. Thirdly, erosion patterns are measured in a 76.2mm ID standard elbow for air-sand flows using a state-of-the-art non-invasive Ultrasonic Technology (UT) device. The metal loss is measured at 16 different locations in the elbow using dual element ultrasonic transducers. Erosion experiments in the vertical to horizontal elbow are performed with gas velocities ranging from 11m/s to 27m/s at nearly atmospheric pressure. Two different sand sizes (150 and 300μm sand) were used for performing tests. The shapes of the sand are also different with the 300μm sand being sharper than the 150μm sand. Finally, the new erosion equation has been implemented into a commercially available Computational Fluid Dynamics (CFD) code to predict erosion ratios in elbows for a variety of flow conditions and particle sizes. The predicted CFD erosion magnitudes are compared with present and previous UT erosion data in elbows. The comparisons show that CFD predictions are within a factor of two of present and previous UT single-phase erosion data. Four correlations for erosion from literature are also studied and validated in simulations. The correlation developed and validated in this work can be used to predict the bend lifetime for particular operating conditions.
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•The slip velocity between the gas and sand particles has been measured using PIV.•An erosion equation has been generated based on PIV results and erosion testing.•Sand erosion is measured in a 76.2mm ID standard elbow using ultrasonic probes.•Predicted CFD erosion magnitudes are compared with UT erosion data in elbows.•CFD predictions are within a factor of two of present and previous UT erosion data.
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