Erosion Prediction Research Articles

Seasonal variation in soil erosion resistance to overland flow in gully-filled farmland on the Loess Plateau, China

Large areas of farmland have been established in China’s Loess Plateau region by backfilling forest and grasslands in gullies with topsoil from hillslopes. High amounts of plant litter are incorporated into the topsoil during such processes; however, their effects on soil erosion resistance under natural conditions are not fully understood. Therefore, the present study investigated seasonal variation in soil erosion resistance to overland flow and the underlying factors in the gully-filled farmland. Two typical plant litter species were selected in this study, i.e., Artemisia sacrorum Ledeb. (ASL) and Bothriochloa ischaemum (L.) Keng. (BIL). Overland water flow was tested under six shear stress levels (5.66–22.11 Pa) in natural soil samples incorporated with plant litter and without plant litter to determine soil erosion resistance parameters (rill erodibility Kr and critical shear stress τc). The study was conducted over 524 days (through May 6, 2017, to October 11, 2018), covering two rainy seasons and one winter. Soil properties changed significantly over time, with physical crust thickness and cohesion increasing from 0 to 10.7 mm and 2.9–13.4 kPa, respectively. In contrast, the mass density of incorporated plant litter decreased from 0.7 to 0.2 kg m−2. Soil erosion resistance increased with time, which showed that Kr decreased (from 0.516 to 0.021 s m−1) and τc increased (from 0.49 to 7.98 Pa). Compared with the initial state of new farmland (Kr = 0.507 s m−1,τc= 0.48 Pa), Kr decreased by 77–96% and τc increased 8–14 times at the end of the study. Plant litter incorporation markedly enhanced soil erosion resistance in a time- and species-dependent manner. Compared with the bare soil without plant litter, the Kr values of ASL and BIL treatments were 3–64% and 2–83% lower, and their τc values were 0–81% and 0–55% higher, respectively. Kr was significantly and positively correlated with cumulative precipitation, cumulative rainfall kinetic energy, soil cohesion, and physical soil crust thickness, while τc was negatively correlated with the influencing factors. Further, both Kr and τc could be well predicted by physical soil crust thickness and cohesion (R2 = 0.79 and 0.87, p < 0.01, n = 27). According to the results, seasonal patterns of soil erosion resistance in the gully-filled farmland established under plant litter incorporation were mainly controlled by rainfall and physical soil crust structure. This study provides a reference resource for soil erosion prediction in farmland ecosystems on the Loess Plateau.

Graphite Nozzle Erosion Trends in Paraffin/Oxygen Hybrid Rockets

Nozzle erosion predictions are fundamental to increase the technology readiness level of hybrid rocket engines. In this work, Reynolds-averaged Navier–Stokes simulations of the internal ballistics of paraffin/oxygen engines coupled with graphite nozzle ablation are performed under various operating conditions. Additional simulations considering uniform inlet conditions at the postchamber entrance underline the complex interaction between nozzle erosion and the radially nonuniform flowfield originating from incomplete mixing and combustion. Moreover, the favored combustion efficiency resulting from an increase of the postchamber length is evaluated in terms of nozzle erosion in a wide range of oxidizer-to-fuel ratios. Because of the interaction between wall and gas-phase reactions, erosion mass fluxes are observed to monotonically grow with decreasing equivalence ratios.

Assessing Post-Fire Effects on Soil Loss Combining Burn Severity and Advanced Erosion Modeling in Malesina, Central Greece

Earth’s ecosystems are extremely valuable to humanity, playing a key role ecologically, economically, and socially. Wildfires constitute a significant threat to the environment, especially in vulnerable ecosystems, such as those that are commonly found in the Mediterranean. Due to their strong impact on the environment, they provide a crucial factor in managing ecosystems behavior, causing dramatic modifications to land surface processes dynamics leading to land degradation. The soil erosion phenomenon downgrades soil quality in ecosystems and reduces land productivity. Thus, it is imperative to implement advanced erosion prediction models to assess fire effects on soil characteristics. This study focuses on examining the wildfire case that burned 30 km2 in Malesina of Central Greece in 2014. The added value of remote sensing today, such as the high accuracy of satellite data, has contributed to visualizing the burned area concerning the severity of the event. Additional data from local weather stations were used to quantify soil loss on a seasonal basis using RUSLE modeling before and after the wildfire. Results of this study revealed that there is a remarkable variety of high soil loss values, especially in winter periods. More particularly, there was a 30% soil loss rise one year after the wildfire, while five years after the event, an almost double reduction was observed. In specific areas with high soil erosion values, infrastructure works were carried out validating the applied methodology. The approach adopted in this study underlines the significance of using remote sensing and geoinformation techniques to assess the post-fire effects of identifying vulnerable areas based on soil erosion parameters on a local scale.

Quantifying Uncertainty in Predictions of Spacecraft Erosion Induced by a Hall Thruster

The impact of sputtering yield model uncertainty on the predicted erosion of a meshed reflector wire exposed to a Hall effect thruster plume is investigated. Quantifying this uncertainty is critical for making informed assessments of reflector lifetime. The erosion is modeled by assuming known ion current density and energy distribution at the location of the wire. The wire surface is then discretized, and wear is evaluated incrementally over time. The confidence in model predictions is quantified where the major source of uncertainty is assumed to stem from the material sputtering yield. The model is run to simulate reflector erosion after 10 h of exposure to a 3 kW class Hall thruster operating at 300 V. The simulated results then are compared to experimental measurements from a dedicated wear test performed on a series of mesh coupon samples. The experimental results are shown to fall largely within the 95% credible intervals from model predictions, though the uncertainty in the maximum predicted erosion is found to be up to 190% of the maximum predicted erosion. These results are discussed in the context of predicting lifetime of reflectors on orbit and the need for margin in this component design.

Modeling soil erodibility and critical shear stress parameters for soil loss estimation

The rate of soil erosion from agricultural fields is driven by climate erosivity and by soil erodibility or resistance, commonly represented through the interrill (Ki) and rill erodibility (Kr), and critical shear stress (τc) parameters. These parameters are affected by factors showing high variability in time and space, such as soil properties, land use, and management practices. Estimating the site-specific time-varying values for Ki, Kr, and τc can require laborious field or laboratory experiments and detailed datasets. The objective of this research was to develop a non-linear regression model for estimating temporal adjustments for Ki, Kr, and τc considering different types of crops and management practices. One thousand sampling sites were randomly selected across the Kaskaskia watershed in Illinois, and the needed parameters to develop the regression models were extracted from the two-year simulation results of the Water Erosion Prediction Project (WEPP) model on a daily basis. The predicted values of the regression models showed good agreements with the sample data, with the coefficient of determination (r2) ranging from 0.62 to 0.98, capturing the spatio-temporal variations of the three variables under different crops and management practices. In addition, daily soil loss estimations using the predicted adjustments showed good agreements with the WEPP simulations, with r2 ranged from 0.98 to 0.99, confirming their possible use in soil erosion models. This is especially useful as the regression models require only a few explanatory variables, which are available at high resolution across the United States. Therefore, the models will facilitate estimating spatio-temporal variations of interrill and rill erodibility, and critical shear stress and thus a new platform of large-scale soil erosion models can be developed using readily available environmental datasets.

Soil loss and PM10 emissions from agricultural fields in the Junggar Basin over the past six decades

The Junggar Basin in north Xinjiang Province is regarded as one of the important dust sources in China. There is, however, a lack of information on long-term dust emissions originating from the basin. In these largely agricultural communities, wind erosion is a major concern that results in a threat to sustainable agriculture and environmental quality. This study assesses dust emissions from the agricultural community of the Junggar Basin in north Xinjiang based on soil and land use types extracted from remote sensing data in response to weather and climate over the past six decades. The Wind Erosion Prediction System (WEPS) was used to simulate annual soil loss and PM10 (particulate matter ≤10 μm in aerodynamic diameter) emissions at 11 meteorological stations across the Junggar Basin. From 1958 to 2018, annual soil loss and PM10 emissions significantly decreased 3.65 and 0.2 kg m^–2 y^–1, respectively. This decrease was likely due to decreasing wind speed, but also associated with increased precipitation and temperature, and decreased solar radiation. Wind erosion occurred most frequently during April and May, accounting for 39% of the annual soil loss and 40% of the annual PM10 emission. In contrast, no erosion occurred in January, February, and December as a result of low temperature (&lt;–8.6°C), frozen soil conditions, and snow cover. Wind erosion risk appeared to decrease during the past six decades in response to observed climate change across the basin; however the southeast part of the basin experienced increasing wind erosion risk over the six decades. Projects to control wind erosion risk and combat dust emission should be given priority in the southeast part of the basin. Frequency of dust events was compared to simulated erosion; a strong linkage was found between simulated soil loss and frequency of dust storms based on regression analysis. This demonstrated that the modelling was acceptable in the conditions of this study and the results were prone to be reliable.

Interaction effects of rainfall and soil factors on runoff, erosion, and their predictions in different geographic regions

Water erosion is a complex process driven by many factors, such as rainfall, soil, topography, vegetation, and land use management practices. Much research has been done to assess the separate effect of every single factor, while studies devoted to the interaction effects among these factors are rarely reported. The complex interactions among factors are generally poured into the pool of soil erodibility (K factor) in the USLE-based models, which induces uncertainty of the K factor and thus causes prediction errors. The interaction between rainfall (R) and soil (K) factors is the first and foremost step to dissect the entire interaction complex, but also the objective this study intended to investigate. Quality-controlled data from long-term field observations on four bare steep slopes in different geographic regions of China were selected and standardized to exclude the effect of unconcerned factors. The interaction effects of rainfall and soil factors were visualized by the nonlinearities of accumulative rainfall-runoff-erosion relationships and then further quantified by the evaluation of prediction errors for the cases that ignore the nonlinearities and by the approach of partial least squares-structural equation modelling (PLS-SEM). The results indicated that the interaction between rainfall and soil factors exists in water erosion processes and obscures the hydrological and erosion prediction. (1) The potentialities of both runoff and erosion varied with the level of rainfall erosivity in different patterns among soils, indicating diverse nonlinearities of rainfall-runoff-erosion relationships and the complex interaction effects behind it. (2) The addition of the interaction effects in the SEM model constructions increased 9.2% and 6.0% of variance explanations for the predictions of annual runoff and erosion, respectively. Whereas, the exclusion of interaction effects tended to cause overestimations on steep slopes that were hard to be calibrated by existing formulas. (3) The well-known tendency to underestimate small and overestimate large events does not suit every soil, especially for the soil with coarse texture and shallow soil with fractured bedrock. And prediction bias was found predictable and rooted in the interaction between rainfall and soil. This study yields a deeper understanding of interaction effects, and is helpful for the improvement of runoff and erosion predictions.

PREDIKSI EROSI DENGAN METODE USLE DI PERKEBUNAN KELAPA SAWIT PTPN XIII GUNUNG MELIAU KECAMATAN MELIAU KABUPATEN SANGGAU

The research location that is in Afdeling 3 PTPN XIII Mount Meliau Meliau District of Sanggau. This study aims to predict the magnitude of the erosion and the amount of erosion that can still be tolerated. The method used in this study was calculated using the USLE by knowing the value of the R factor, K, L, S, C and P which are the root causes of erosion in the area of oil palm plantations in the study sites. Further erosion of values that can be tolerated in comparison to the predicted value erosion. Having compared the predictive value of the erosion of the value erosion that can be tolerated, it is necessary to do the conservation measures recommended.The results of this study found that the rate of erosion prediction (A) reached 140.16 to 9737.28 tons / ha / year. Value erosion prediction that can be tolerated (Etol) ranged from 48.22 to 32.13 tonnes / ha / year. In Ult4 land value (A) is greater than the value of Etol with moderate erosion hazard level, while on land Ult18, Ult24, Ult36 value (A) is greater than the value of Etol with severe erosion hazard level. Planning and prevention of erosion is the appropriate planting bench terracing of good construction. Special to land Ult4 and Ult18 can in recommend also with planting LCC and making the porch kontruksi was.

The Lasting Signatures of Past Landslides on Soil Stripping From Landscapes

AbstractRainfall‐induced shallow landslides scar the Earth surface and deliver sediment pulses into fluvial systems and thus play an important role in landscape evolution. Previous landslide legacy affects local soil depths and soil regeneration rates thus modifying future landslide susceptibility and sediment dynamics. Here, we couple an advanced hydromechanical landslide model with a soil depth regeneration model and quantify landslide legacy effects by placing landslide dynamics in a perspective of landscape soil depth evolution. Results show increased landslide susceptibility near recently failed regions due to alteration of hydrological processes in a thinner soil mantle that imposes constraints on released soil volumes. Landslide recurrence in failed regions levels off when soil depths are gradually restored to steady state pre‐failure values. Cumulative effects of past landslides divert future landslide activity from steep hillslopes to alluvial channels and valley margins thus affecting sediment dynamics and yields. Consideration of landslide legacy improves landslide prediction and quantification of landslide erosion and fluvial sediment yield rates.

Investigation of surface damage of ductile materials caused by rotating particles

The influence of rotating particles on surface damage should be considered to improve the accuracy of erosion prediction. In the present study, numerical simulations were carried out to investigate the wear morphology and stress distribution of a target material subjected to rotating particle impacts. A new experimental method was established to validate the model. The model was then used to study the influence of rotating particle impacts at different impact velocities and angles on wear behavior of the material. Correlation between the severity impact wear and particle rotation was observed and quantified. The results show that rotation of solid particles impacting a material can significantly affect the magnitude and pattern of impact wear. Particles with a forward spin were found to promote forward movement of the material surface, whereas particles with a backward spin contributed to vertical deformation of the material. Finally, impact wear profiles produced by different particles with different rotation modes were compared. These results provide insights into the damage mechanism of rotating particles and a theoretical basis for further investigations.

Prediction of Cavitation Evolution and Cavitation Erosion on Centrifugal Pump Blades by the DCM-RNG Method.

Cavitation can reduce the efficiency and service life of the centrifugal pumps, and a long-term operation under cavitation conditions will cause cavitation damage on the surface of material. The external characteristic test of the IS65-50-174 single-stage centrifugal pump was carried out. Moreover, the cavitation mechanism under specific conditions was analyzed by numerical simulation. Considering the macroscopic cavitation flow structure in the centrifugal pump, three different cavitation erosion prediction methods were used to predict the erodible areas. The results show that the calculation results obtained by the density correction method (DCM) can well match the flow characteristics of the centrifugal pump under the rated conditions. When the centrifugal pump head drops by 3%, cavitation mainly occurs on the suction surface, and the cavity on the pressure surface is mainly concentrated near the front cover. The cavitation prediction method based on the time derivation of pressure change is not suitable for centrifugal pumps, while the prediction result of the erosive power method is more reasonable than the others. At time 0.493114 s, the maximum erosive power appears on the blade near the volute tongue, and its value is 1.46e − 04 W.

Prediction of erosion and sedimentation rates using SWAT (Soil and Water Assessment Tool) method in the Jenelata Sub Watershed

Erosion and sedimentation are problems that often occur in watershed ecosystems. The SWAT model (Soil and Water Assessment Tool) can be used to determine the output of a watershed’s performance. Jenelata sub-watershed area is one of the largest sub-watersheds of the Jeneberang watershed with 22.800 ha. This study aims to determine the spatial distribution of the hydrologic response unit (HRU) and analyze the rate of erosion and sedimentation in the Jenelata sub-watershed. The results showed that most HRUs are in secondary dryland forests with 447 HRU (19.09%). The level of erosion in the very light category, namely 5.74 ton/ha/year (37.53%) and light 34.71 ton/ha/year (27.76%), was in the villages of Moncongloe, Tana Karaeng, Sicini, Paladindang, Towata, Parang Lampoa, Manuju, and Buakkang. Meanwhile, moderate erosion was 104.07 ton/ha/year (23.92%), high 289.65 ton/ha/year (9.59%), and very high 553.74 ton/ha/year (1.20%) located in the villages of Pattallikang, Mangempang, Bontomanai, Bissoloro, Rannaloe, Jenebatu, and Sapaya. The largest sedimentation is 133.18 ton/ha/year in sub-watershed17, located in Bissoloro and Rannaloe villages.

Prediction of erosion using the USLE method in the Malino Sub Watershed

One of the problems that occur in the Sub DAS Malino is population growth. The increase in population in an area will increase demand to encourage the community to convert forest land into non-forest land, especially agricultural land. It has an impact on erosion and flooding during the rainy season. The amount of erosion that occurs can result in damage and a decrease in soil quality; therefore, it is necessary to predict erosion using the Universal Soil Loss Equation (USLE) method. This study aims to determine the level of erosion hazard in the Malino sub-watershed, Jeneberang watershed. The data used in this study include data on land cover, rainfall, soil, and slope. The results showed that Sub DAS Malino has high erosion on the open land cover with 800.02 ton/ha/year of 0.44% area of the Sub DAS Malino.

Prediction of erosion and sedimentation rates using SWAT (soil and water assessment tool) method in Malino Sub Watershed Jeneberang Watershed

The increase in population will encourage the community to transfer the function of agricultural land in the Malino sub-watershed. Land use dramatically affects the level of erosion and sedimentation. The use of SWAT models can identify, assess, and evaluate the extent of a watershed’s problems. This study aims to determine the spatial distribution of HRU and analyze the rate of erosion and sedimentation in the Malino sub-watershed. The results showed that the most HRU is found in secondary dryland forests, as much as 624 HRU (32.21%). The level of erosion rate of the category is very light with an erosion value of 5.21 tons/ha/year, light 31.19 tons/ha/year, moderate 104.91 tons/ha/year, weight 267.10 tons/ha/year, and hefty 616.74 tons/ha/year. The most significant sedimentation rate was found in sub-watershed 18 of 71.97 tons/ha/year and subwatershed 10 of 13.31 tons/ha/year.

Forecasting East Belitung Regency Rainfall Data by Reviewing Heteroscedasticity

East Belitung Regency is one of the regencies located on Belitung Island. East Belitung Regency has a tropical and wet climate with a fairly high variation of rainfall. Rainfall forecasting is an important thing to model because of the many uses of rainfall forecasting results such as irrigation planning, flood prediction, erosion prediction and others. This study aims to predict rainfall for the next 5 years by using a time series model by reviewing the heteroscedasticity of the data. From the results of the analysis of rainfall in East Belitung Regency with a seasonal pattern. The best model used is ARIMA (0, l, l)(2, l, l)12 with insignificant heteroscedasticity.

Mathematical Multiobjective Optimization for Metal Hip Arthroplasty with Medical Physics Applications

Total hip metal arthroplasty (THA) model-parameters for a group of commonly used ones is optimized and numerically studied. Based on previous ceramic THA optimization software contributions, an improved multiobjective programming method/algorithm is implemented in wear modeling for THA. This computational nonlinear multifunctional optimization is performed with a number of THA metals with different hardnesses and erosion in vitro experimental rates. The new software was created/designed with two types of Sytems, Matlab and GNU Octave. Numerical results show be improved/acceptable for in vitro simulations. These findings are verified with 2D Graphical Optimization and 3D Interior Optimization methods, giving low residual-norms. The solutions for the model match mostly the literature in vitro standards for experimental simulations. Numerical figures for multifunctional optimization give acceptable model-parameter values with low residual-norms. Useful mathematical consequences/calculations are obtained for wear predictions, model advancements and simulation methodology. The wear magnitude for in vitro determinations with these model parameter data constitutes the advance of the method. In consequence, the erosion prediction for laboratory experimental testing in THA add up to the literature an efficacious usage-improvement. Results, additionally, are extrapolated to efficient Medical Physics applications and metal-THA Bioengineering designs.

An Enhanced Flume Testing Procedure for the Study of Rill Erosion

This paper presents the development and verification of an improved and cost-effective flume apparatus and corresponding testing methodology. A rigorous analysis of the flow conditions during testing was considered and an interpretation of test results was carried out following the premises of the Water Erosion Prediction Project (WEPP) rill erosion model. The apparatus and methodology were verified using statically compacted specimens of a latosol from the central region of Brazil. Tests were performed on samples with void ratios of 1.0 and 1.5 and under variable hydraulic conditions to verify the repeatability and ideal analysis time for the soil loss curves. The soil loss curves presented hyperbolic behavior, with a maximum value that appeared to be randomly behaved, which can be attributed to the complex nature of the erosion processes at later stages. The equipment and testing methodology produced erosion curves with repeatability that were superior with respect to their initial linear and transition portions. Recommendations are made regarding the adequate interpretation of the testing data and the selection of the ideal elapsed time for soil loss analysis.

A Risk-Based Approach to Mine-Site Rehabilitation: Use of Bayesian Belief Network Modelling to Manage Dispersive Soil and Spoil

Dispersive spoil/soil management is a major environmental and economic challenge for active coal mines as well as sustainable mine closure across the globe. To explore and design a framework for managing dispersive spoil, considering the complexities as well as data availability, this paper has developed a Bayesian Belief Network (BBN)-a probabilistic predictive framework to support practical and cost-effective decisions for the management of dispersive spoil. This approach enabled incorporation of expert knowledge where data were insufficient for modelling purposes. The performance of the model was validated using field data from actively managed mine sites and found to be consistent in the prediction of soil erosion and ground cover. Agreement between predicted soil erosion probability and field observations was greater than 74%, and greater than 70% for ground cover protection. The model performance was further noticeably improved by calibration of Conditional Probability Tables (CPTs). This demonstrates the value of the BBN modelling approach, whereby the use of currently best-available data can provide a practical result, with the capacity for significant model improvement over time as more (targeted) data come to hand.

Dampak Perubahan Curah Hujan Terhadap Tingkat Kerentanan Erosi Tanah Di Sub DAS Merawu, Jawa Tengah

This research was held to estimate rainfall and change in soil erosion vulnerability from 2020 to 2050 in Merawu Sub-Watershed, Banjanegara District with RCP 2.6, 4.5 and 8.5. The RCP is an overview of the concentration trends for greenhouse gases, aerosols and land use change created by the climate modeling community. Rainfall prediction was generated from SDSM Software and combined with USLE to predict soil erosion in ArcGIS 10.4. Changes in rainfall intensity are an important factor in changes of soil erosion rates because the kinetic energy of falling rainwater can cause soil erosion.The results showed rainfall in Banjarnegara Station at 2020-2050 with RCP 2.6,4.5 and 8.5 were increasing by +0,26%; +0,60%; +0,52%, while in Kalisapi Station were decreasing by -1,54%; -1,65% dan -2,20%. The change of soil erosion vulnerability prediction showed that soil erosion in Sub-DAS Merawu at 2020-2050 with RCP 2.6,4.5 and 8.5 in very light category were -0,02%;-0,02%;-0,03%, light category were -0,17%;-0,17%;-0,17%, moderate category -0,05%;-0,05%;-0,04%, heavy category -0,26%;-0,35%;-0,37%, and very heavy category were +1,46%;+1,88%;+1,95%. While the average soil erosion prediction at RCP 2.6, 4.5 and 8.5 were +0,86, +1,19% and +1,03%, respectively. Keywords: soil erosion prediction, rainfall prediction, SDSM Software, Sub-DAS Merawu

Bathymetric Data Requirements for Operational Coastal Erosion Forecasting Using XBeach

There is an increasing interest in the broad-scale implementation of coastal erosion early warning systems (EWS) with the goal of enhancing community preparedness to extreme coastal storm wave events. These emerging systems typically rely on process-based models to predict the storm-induced morphological change. A key challenge with incorporating these models in EWSs is the need for up-to-date nearshore and surf zone bathymetry data, which is difficult to measure routinely, but potentially important for accurate erosion forecasting. This study evaluates the degree to which up-to-date bathymetry is required for accurate coastal erosion predictions using the morphodynamic model XBeach and, subsequently, whether a range of “representative” and/or “synthetic” bathymetries can be used for the bottom boundary, when a survey of the immediate pre-storm bathymetry is not available. Twelve storm events at two contrasting sites were modelled using six different bathymetry scenarios, including the expected “best case” bathymetry surveyed immediately pre-storm. These results indicate that alternative bathymetries can be used to obtain sub-aerial erosion predictions that are similar (and in some cases better) than those resulting from the use of an immediately pre-storm surveyed bathymetry, provided that rigorous model calibration is undertaken prior. This generalized finding is attributed to specific parametrizations in the XBeach model structure that are optimized during the calibration process to match the particular bottom boundary condition used. This study provides practical guidance for the selection of suitable nearshore bathymetry for use in operational coastal erosion EWSs.