Pub Date : 2025-04-17DOI: 10.1016/j.ijsrc.2025.04.003
Min Li , Jing Ou , Zhihe Chen
The aggregation of microplastics (MPs) with sediments in natural water plays a crucial role in the general deposition and transport of plastic particles. However, the effect of salinity changes on the settling behavior of aggregates remains unclear. In this study, the aggregation and settling processes of sediment particles with spherical MPs were investigated using a settling tube and a microphotography device, in deionized water (pH 8.0) with 10–35 practical salinity units (PSU). Two-particle and three-particle aggregates were most commonly observed in the experiments. Increasing the salinity promoted the aggregation of MPs, reaching the largest average particle size at 25 PSU, but the mean Corey shape factor values exhibited minimal variations at different salinities. Meanwhile, the settling velocity of the aggregates was directly proportional to their particle size, and thus the average settling velocity also reached a maximum at 25 PSU. Although the settling velocity can be predicted with high correlation coefficients using existing formulas developed for static conditions, dynamic flow may reduce the settling velocity of aggregates and cause overestimation. Herein, a reduction coefficient was used to revise the settling velocity formula and predict the measured values with higher accuracy. This study provides insights into the aggregation and settlement of MPs in estuarine environments with varying salinity, which affect the fate and distribution of plastic particles in natural waters.
{"title":"Settling behavior of microplastic hetero-aggregates in aquatic environments with varying salinity","authors":"Min Li , Jing Ou , Zhihe Chen","doi":"10.1016/j.ijsrc.2025.04.003","DOIUrl":"10.1016/j.ijsrc.2025.04.003","url":null,"abstract":"<div><div>The aggregation of microplastics (MPs) with sediments in natural water plays a crucial role in the general deposition and transport of plastic particles. However, the effect of salinity changes on the settling behavior of aggregates remains unclear. In this study, the aggregation and settling processes of sediment particles with spherical MPs were investigated using a settling tube and a microphotography device, in deionized water (pH 8.0) with 10–35 practical salinity units (PSU). Two-particle and three-particle aggregates were most commonly observed in the experiments. Increasing the salinity promoted the aggregation of MPs, reaching the largest average particle size at 25 PSU, but the mean Corey shape factor values exhibited minimal variations at different salinities. Meanwhile, the settling velocity of the aggregates was directly proportional to their particle size, and thus the average settling velocity also reached a maximum at 25 PSU. Although the settling velocity can be predicted with high correlation coefficients using existing formulas developed for static conditions, dynamic flow may reduce the settling velocity of aggregates and cause overestimation. Herein, a reduction coefficient was used to revise the settling velocity formula and predict the measured values with higher accuracy. This study provides insights into the aggregation and settlement of MPs in estuarine environments with varying salinity, which affect the fate and distribution of plastic particles in natural waters.</div></div>","PeriodicalId":50290,"journal":{"name":"International Journal of Sediment Research","volume":"40 4","pages":"Pages 561-572"},"PeriodicalIF":3.5,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-14DOI: 10.1016/j.ijsrc.2025.04.002
Leo van Rijn , Marcio Boechat Albernaz , Luitze Perk , Bas van Maren
This study is focused on the experimental and numerical modelling of sand and mud transport over mud-sand beds with percentages of fines (< 63 μm) up to 50% in conditions with currents, waves and combined currents and waves. Both field and laboratory experiments with mud-sand beds have been performed. Detailed measurements of near-bed hydrodynamic and sediment transport processes have been made in the muddy tidal ferry channel between Holwerd and Ameland in the Dutch part of Wadden Sea. Laboratory flume experiments with currents and waves over a pure fine sand bed show the generation of small-scale sand ripples and strong ripple-induced vortex motions resulting in relatively high sand concentrations close to the bed. The near-bed sediment dynamics of a fine sand bed change drastically when a small amount of cohesive sediments (mud 10%–15%) is added to the sand bed. Bed properties which are changed are the percentage of fines, the dry bulk density (packing) and the cohesivity. The results of exploratory long-bed experiments with various mud-sand mixtures show that the mud particles at the mud-sand surface are washed out and small-scale isolated barchan-type sand ripples develop at the bed surface. The bed ripple heights are suppressed resulting in flatter ripples with less vorticity and as a consequence lower sand concentrations and transport. The critical bed-shear stress (cbs) is not much influenced by cohesive effects if the percentage of fines (< 63 μm) is smaller than about 15%, while for pfines > 15%, the critical bed-shear stress increases for increasing values of pfines. Laboratory results also indicate that the bed ripple development and near-bed sand transport may already be affected for a lower percentage of fines (10%–15%). Various modelling methods are used and discussed, both for the flume and field data.
{"title":"Transport of suspended sand and mud over a mud-sand bed","authors":"Leo van Rijn , Marcio Boechat Albernaz , Luitze Perk , Bas van Maren","doi":"10.1016/j.ijsrc.2025.04.002","DOIUrl":"10.1016/j.ijsrc.2025.04.002","url":null,"abstract":"<div><div>This study is focused on the experimental and numerical modelling of sand and mud transport over mud-sand beds with percentages of fines (< 63 μm) up to 50% in conditions with currents, waves and combined currents and waves. Both field and laboratory experiments with mud-sand beds have been performed. Detailed measurements of near-bed hydrodynamic and sediment transport processes have been made in the muddy tidal ferry channel between Holwerd and Ameland in the Dutch part of Wadden Sea. Laboratory flume experiments with currents and waves over a pure fine sand bed show the generation of small-scale sand ripples and strong ripple-induced vortex motions resulting in relatively high sand concentrations close to the bed. The near-bed sediment dynamics of a fine sand bed change drastically when a small amount of cohesive sediments (mud 10%–15%) is added to the sand bed. Bed properties which are changed are the percentage of fines, the dry bulk density (packing) and the cohesivity. The results of exploratory long-bed experiments with various mud-sand mixtures show that the mud particles at the mud-sand surface are washed out and small-scale isolated barchan-type sand ripples develop at the bed surface. The bed ripple heights are suppressed resulting in flatter ripples with less vorticity and as a consequence lower sand concentrations and transport. The critical bed-shear stress (cbs) is not much influenced by cohesive effects if the percentage of fines (< 63 μm) is smaller than about 15%, while for <em>p</em><sub>fines</sub> > 15%, the critical bed-shear stress increases for increasing values of <em>p</em><sub>fines</sub>. Laboratory results also indicate that the bed ripple development and near-bed sand transport may already be affected for a lower percentage of fines (10%–15%). Various modelling methods are used and discussed, both for the flume and field data.</div></div>","PeriodicalId":50290,"journal":{"name":"International Journal of Sediment Research","volume":"40 4","pages":"Pages 537-550"},"PeriodicalIF":3.5,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-15DOI: 10.1016/j.ijsrc.2025.03.002
Yenesew Assaye , Gizaw Desta , Eyayu Molla , Zenebe Adimassu
The Beles River Basin is facing severe soil erosion driven by human-induced activities, leading to significant losses of soil organic carbon (SOC) and nutrients (nitrogen (N) and phosphorus (P)). Effective land management practices (LMPs), including mechanical, biological, and agronomic techniques, are potential strategies for mitigating this degradation, but their effectiveness depends on site-specific and agroecological conditions. However, limited information is available on this aspect of the study area. The objective of the current study was to evaluate the effects of LMPs in the warm subhumid lowlands of the Beles River Basin on runoff, soil loss, and sediment-associated losses of SOC, N, and P from agricultural land. Four LMPs (vetiver grass strips (VGS), conservation agriculture (CA), soil bunds (SB), and fanya juu (FJ)) were evaluated via runoff plots arranged in a randomized complete block design (RCBD) with three replicates. Farmer practices were used as a control (C). The experiments, which were performed over three years (2021–2023), generated runoff, soil loss, and nutrient loss data. The three-year mean annual runoff ranged from 58.5 to 407.5 mm, and the soil loss ranged from 4.3 to 45.4 t/ha, whereas the annual rainfall varied between 1,402 mm in 2021, 1,254 mm in 2022, and 1,261 mm in 2023. On average, runoff was reduced by 36%–85%, and soil loss was reduced by 53%–91% in the LMP-treated plots. Additionally, sediment-associated losses of SOC, N, and P were reduced by 55%–90%, 52%–90%, and 28%–72%, respectively. The results revealed significant differences (p < 0.05) among the treatments in terms of reducing runoff, soil loss, and sediment-associated losses of SOC, N, and P. The mean annual runoff and soil loss rates during the study were 407.5, 230.3, 136.3, 59.6, and 58.5 mm and 45.4, 21.5, 11.1, 4.5, and 4.3 t/ha under the control, VGS, CA, SB, and FJ practices, respectively. The highest rates of runoff and soil loss were observed under the control conditions (407.4 mm and 45.4 t/ha). Runoff, soil loss, SOC, and nutrient (N and P) losses were significantly lower (p < 0.05) in the plots treated with FJ and SB than in the other plots. However, CA and VGS also significantly varied (p < 0.05) in reducing runoff, soil, SOC, and nutrient losses over the years. These results highlight the key role of LMPs in warm subhumid lowland rainfed agroecosystems as effective land management techniques for controlling soil and nutrient loss.
{"title":"Effects of land management practices on runoff and soil and nutrient losses in the rainfed agroecosystem of the Beles River Basin, Ethiopia","authors":"Yenesew Assaye , Gizaw Desta , Eyayu Molla , Zenebe Adimassu","doi":"10.1016/j.ijsrc.2025.03.002","DOIUrl":"10.1016/j.ijsrc.2025.03.002","url":null,"abstract":"<div><div>The Beles River Basin is facing severe soil erosion driven by human-induced activities, leading to significant losses of soil organic carbon (SOC) and nutrients (nitrogen (N) and phosphorus (P)). Effective land management practices (LMPs), including mechanical, biological, and agronomic techniques, are potential strategies for mitigating this degradation, but their effectiveness depends on site-specific and agroecological conditions. However, limited information is available on this aspect of the study area. The objective of the current study was to evaluate the effects of LMPs in the warm subhumid lowlands of the Beles River Basin on runoff, soil loss, and sediment-associated losses of SOC, N, and P from agricultural land. Four LMPs (vetiver grass strips (VGS), conservation agriculture (CA), soil bunds (SB), and fanya juu (FJ)) were evaluated via runoff plots arranged in a randomized complete block design (RCBD) with three replicates. Farmer practices were used as a control (C). The experiments, which were performed over three years (2021–2023), generated runoff, soil loss, and nutrient loss data. The three-year mean annual runoff ranged from 58.5 to 407.5 mm, and the soil loss ranged from 4.3 to 45.4 t/ha, whereas the annual rainfall varied between 1,402 mm in 2021, 1,254 mm in 2022, and 1,261 mm in 2023. On average, runoff was reduced by 36%–85%, and soil loss was reduced by 53%–91% in the LMP-treated plots. Additionally, sediment-associated losses of SOC, N, and P were reduced by 55%–90%, 52%–90%, and 28%–72%, respectively. The results revealed significant differences (<em>p</em> < 0.05) among the treatments in terms of reducing runoff, soil loss, and sediment-associated losses of SOC, N, and P. The mean annual runoff and soil loss rates during the study were 407.5, 230.3, 136.3, 59.6, and 58.5 mm and 45.4, 21.5, 11.1, 4.5, and 4.3 t/ha under the control, VGS, CA, SB, and FJ practices, respectively. The highest rates of runoff and soil loss were observed under the control conditions (407.4 mm and 45.4 t/ha). Runoff, soil loss, SOC, and nutrient (N and P) losses were significantly lower (<em>p</em> < 0.05) in the plots treated with FJ and SB than in the other plots. However, CA and VGS also significantly varied (<em>p</em> < 0.05) in reducing runoff, soil, SOC, and nutrient losses over the years. These results highlight the key role of LMPs in warm subhumid lowland rainfed agroecosystems as effective land management techniques for controlling soil and nutrient loss.</div></div>","PeriodicalId":50290,"journal":{"name":"International Journal of Sediment Research","volume":"40 4","pages":"Pages 651-665"},"PeriodicalIF":3.5,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-05DOI: 10.1016/j.ijsrc.2025.03.001
Yang Li , Jianjun Zhang , Yawei Hu , Jiongchang Zhao , Peng Tang
Flow discharge, slope gradient, and erosion time are widely recognized as crucial factors in determining rill erosion and its morphological characteristics. However, the relative importance of these three factors needs to be further elaborated to refine the understanding of rill erosion. In the current study, scour experiments were done under various conditions, including five flow discharges (0.5, 1.0, 1.5, 2.0, and 2.5 mm/min), five slope gradients (5°, 10°, 15°, 20°, and 25°), and durations of 20, 40, and 60 min. The resulting rill erosion process and its related morphological characteristics have been documented and analyzed. The results demonstrate that the average soil loss rate increased significantly with the increase inflow discharge and slope gradient. The individual effect of flow discharge (38.35%) was more pronounced than that of slope gradient (18.38%). Increasing flow discharge, slope gradient, and scouring time intensified the occurrence of headward erosion. Over extended erosion durations, rill length, width, depth, and volume all experienced increases. Additionally, with higher flow discharge and steeper slope gradient, the rill width-depth ratio decreased, indicating that rills became narrower and deeper. The individual effect of flow discharge on all rill morphological characteristics was more pronounced than that of slope gradient and scouring time. Except for rill length, the slope gradient had a greater impact on rill morphological characteristics than scouring time. Importantly, a significant portion of the runoff's potential energy was channeled into soil erosion rather than kinetic energy in sediment-laden flow. Based on the principle of energy conservation, the occurrence of rills reduced the energy required for soil erosion from 83.84 to 598.96 J/kg to 2.22–37.53 J/kg. The current study deepens the understanding of rill erosion mechanisms on the Loess Plateau in China and provides a scientific foundation for soil erosion control.
{"title":"Contributions of flow discharge, slope gradient, and scouring time on rill erosion: A quantitative study of exposed slopes in the loess region","authors":"Yang Li , Jianjun Zhang , Yawei Hu , Jiongchang Zhao , Peng Tang","doi":"10.1016/j.ijsrc.2025.03.001","DOIUrl":"10.1016/j.ijsrc.2025.03.001","url":null,"abstract":"<div><div>Flow discharge, slope gradient, and erosion time are widely recognized as crucial factors in determining rill erosion and its morphological characteristics. However, the relative importance of these three factors needs to be further elaborated to refine the understanding of rill erosion. In the current study, scour experiments were done under various conditions, including five flow discharges (0.5, 1.0, 1.5, 2.0, and 2.5 mm/min), five slope gradients (5°, 10°, 15°, 20°, and 25°), and durations of 20, 40, and 60 min. The resulting rill erosion process and its related morphological characteristics have been documented and analyzed. The results demonstrate that the average soil loss rate increased significantly with the increase inflow discharge and slope gradient. The individual effect of flow discharge (38.35%) was more pronounced than that of slope gradient (18.38%). Increasing flow discharge, slope gradient, and scouring time intensified the occurrence of headward erosion. Over extended erosion durations, rill length, width, depth, and volume all experienced increases. Additionally, with higher flow discharge and steeper slope gradient, the rill width-depth ratio decreased, indicating that rills became narrower and deeper. The individual effect of flow discharge on all rill morphological characteristics was more pronounced than that of slope gradient and scouring time. Except for rill length, the slope gradient had a greater impact on rill morphological characteristics than scouring time. Importantly, a significant portion of the runoff's potential energy was channeled into soil erosion rather than kinetic energy in sediment-laden flow. Based on the principle of energy conservation, the occurrence of rills reduced the energy required for soil erosion from 83.84 to 598.96 J/kg to 2.22–37.53 J/kg. The current study deepens the understanding of rill erosion mechanisms on the Loess Plateau in China and provides a scientific foundation for soil erosion control.</div></div>","PeriodicalId":50290,"journal":{"name":"International Journal of Sediment Research","volume":"40 3","pages":"Pages 500-511"},"PeriodicalIF":3.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143932152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Accurately predicting suspended sediment concentration (SSC) in fluvial systems is essential for environmental monitoring, flood management, and riverine engineering applications. This study introduces a novel hybrid approach for forecasting SSC by leveraging advanced deep learning algorithms. Daily datasets from the U.S. Geological Survey, including discharge (Q) and SSC measurements, were analyzed from 2007 to 2017 at two key locations on the Mississippi River: Chester (CH) and Thebes (TH). The proposed framework integrates feedforward neural networks (FFNN), long short-term memory (LSTM) networks, stochastic gradient descent (SGD), and radial basis function (RBF) models, augmented with a first-order differencing technique. Additionally, hybrid models, including Supervised FFNN-LSTM and Supervised FFNN-SGD, were developed to enhance predictive performance. The dataset was partitioned into training (70%, 2,747 d) and testing (30%, 1,178 d) subsets, with daily temporal resolution. Six input scenarios incorporating lagged parameters were evaluated using performance metrics, including the correlation coefficient (CC), Nash–Sutcliffe efficiency (NSE), scatter index (SI), and Willmott’s index (WI). Sensitivity analysis identified SSCt-1 (i.e., one day before) as the most influential predictor for short-term forecasting. Among the models, the SFFNN-LSTM-6 achieved the highest performance, with CC values of 0.976 for CH and 0.960 for TH, demonstrating the ability to predict SSC effectively even in the absence of current-day discharge data. The proposed hybrid models exhibited exceptional robustness across diverse flow regimes, including extreme environmental conditions, establishing a reliable tool for SSC forecasting in complex fluvial systems.
{"title":"Prediction of suspended sediment concentration in fluvial flows using novel hybrid deep learning model","authors":"Sadra Shadkani , Yousef Hemmatzadeh , Amirreza Pak , Soroush Abolfathi","doi":"10.1016/j.ijsrc.2025.02.004","DOIUrl":"10.1016/j.ijsrc.2025.02.004","url":null,"abstract":"<div><div>Accurately predicting suspended sediment concentration (SSC) in fluvial systems is essential for environmental monitoring, flood management, and riverine engineering applications. This study introduces a novel hybrid approach for forecasting SSC by leveraging advanced deep learning algorithms. Daily datasets from the U.S. Geological Survey, including discharge (Q) and SSC measurements, were analyzed from 2007 to 2017 at two key locations on the Mississippi River: Chester (CH) and Thebes (TH). The proposed framework integrates feedforward neural networks (FFNN), long short-term memory (LSTM) networks, stochastic gradient descent (SGD), and radial basis function (RBF) models, augmented with a first-order differencing technique. Additionally, hybrid models, including Supervised FFNN-LSTM and Supervised FFNN-SGD, were developed to enhance predictive performance. The dataset was partitioned into training (70%, 2,747 d) and testing (30%, 1,178 d) subsets, with daily temporal resolution. Six input scenarios incorporating lagged parameters were evaluated using performance metrics, including the correlation coefficient (CC), Nash–Sutcliffe efficiency (NSE), scatter index (SI), and Willmott’s index (WI). Sensitivity analysis identified SSC<sub>t-1</sub> (i.e., one day before) as the most influential predictor for short-term forecasting. Among the models, the SFFNN-LSTM-6 achieved the highest performance, with CC values of 0.976 for CH and 0.960 for TH, demonstrating the ability to predict SSC effectively even in the absence of current-day discharge data. The proposed hybrid models exhibited exceptional robustness across diverse flow regimes, including extreme environmental conditions, establishing a reliable tool for SSC forecasting in complex fluvial systems.</div></div>","PeriodicalId":50290,"journal":{"name":"International Journal of Sediment Research","volume":"40 4","pages":"Pages 573-587"},"PeriodicalIF":3.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-28DOI: 10.1016/j.ijsrc.2025.02.003
Yanjie Sun , Xiaolong Song , Zhi Li , Haijue Xu , Yuchuan Bai
This study introduces an innovative approach to modeling meandering river morphology, integrating and investigating the effects of geometric characteristics and vegetation-induced channel coarsening. The developed comprehensive framework combines several advanced techniques: Genetic Programming for refining the scour factor of transverse bed slope, a Leaf Area Index (LAI)-enhanced analytical model for quantifying vegetative flow resistance, and an upstream-weighted moving average method for efficient approximation of the convolution integral in meander migration calculations. The model is validated against both an idealized Kinoshita meander and a natural bend of the Tumen River (China) in equilibrium, demonstrating its robustness across diverse scales and conditions. The model's ability to simulate the long-term evolution, including cutoff events, provides valuable insight for river management strategies. The current findings demonstrate that channel geometry, particularly width-to-depth ratio, plays a dominant role in meander evolution, with wider channels prone to more complex and rapid morphological changes. Vegetation effects are most pronounced in channels with moderate width-to-depth ratios, where they can significantly influence migration rates and bed topography. A combination of channel widening and deepening, coupled with strategic vegetation management, can effectively enhance navigability while maintaining channel stability in the studied Tumen River reach. Sensitivity analyses highlight the complex interplay between hydraulic conditions, sediment characteristics, and vegetation in shaping river morphology. This research advances understanding of the multifaceted nature of meandering river systems and offers practical tools for informed decision-making in river engineering and environmental management, particularly in the context of climate change and increasing anthropogenic pressures on fluvial ecosystems.
{"title":"Analytical simulation of meander morphology from equilibrium to long-term evolution: Impacts of channel geometry and vegetation-induced coarsening","authors":"Yanjie Sun , Xiaolong Song , Zhi Li , Haijue Xu , Yuchuan Bai","doi":"10.1016/j.ijsrc.2025.02.003","DOIUrl":"10.1016/j.ijsrc.2025.02.003","url":null,"abstract":"<div><div>This study introduces an innovative approach to modeling meandering river morphology, integrating and investigating the effects of geometric characteristics and vegetation-induced channel coarsening. The developed comprehensive framework combines several advanced techniques: Genetic Programming for refining the scour factor of transverse bed slope, a Leaf Area Index (LAI)-enhanced analytical model for quantifying vegetative flow resistance, and an upstream-weighted moving average method for efficient approximation of the convolution integral in meander migration calculations. The model is validated against both an idealized Kinoshita meander and a natural bend of the Tumen River (China) in equilibrium, demonstrating its robustness across diverse scales and conditions. The model's ability to simulate the long-term evolution, including cutoff events, provides valuable insight for river management strategies. The current findings demonstrate that channel geometry, particularly width-to-depth ratio, plays a dominant role in meander evolution, with wider channels prone to more complex and rapid morphological changes. Vegetation effects are most pronounced in channels with moderate width-to-depth ratios, where they can significantly influence migration rates and bed topography. A combination of channel widening and deepening, coupled with strategic vegetation management, can effectively enhance navigability while maintaining channel stability in the studied Tumen River reach. Sensitivity analyses highlight the complex interplay between hydraulic conditions, sediment characteristics, and vegetation in shaping river morphology. This research advances understanding of the multifaceted nature of meandering river systems and offers practical tools for informed decision-making in river engineering and environmental management, particularly in the context of climate change and increasing anthropogenic pressures on fluvial ecosystems.</div></div>","PeriodicalId":50290,"journal":{"name":"International Journal of Sediment Research","volume":"40 4","pages":"Pages 675-689"},"PeriodicalIF":3.5,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fluvial sediment pulses pose a significant threat to the overall ecological health of river systems. Nonetheless, the scarcity of monitored and published data underscores the importance of devising innovative methods for understanding and measuring how river systems react to the introduction of sediments across the fluvial domain. The objective of this study was to create a modeling framework based on reflectance–turbidity that can be applied in regions with both limited and abundant data. Various combinations of predictor variables, training algorithms including linear regression and additional machine learning methods, and input data availability scenarios were examined to comprehend the factors influencing turbidity prediction on a regional scale. The results indicated that, for Washington state, the random forest algorithm, utilizing a combination of reflectance-based predictors and sediment delivery index (SDI) as predictors, produced the most accurate outcomes (data rich: NSE = 0.54, RSR = 0.68, data scarce: NSE = 0.47, RSR = 0.73). However, when tested on three locations in Washington experiencing sediment pulses, the reflectance–based turbidity prediction model consistently underestimated the peak high and peak low turbidity levels for the Elwha River. The model also exhibited consistent inaccuracies in predicting the initial phase of sediment pulses following the Oso Landslide. Nevertheless, promising results were observed for the Toutle River, downstream to the St. Mt. Helens Volcanic eruption site. Overall, the inclusion of SDI in the model enhanced its efficiency and transferability. By enabling the reconstruction of fluvial sediment pulses in data-scarce regions following dam removals, this integrated approach contributes to advancing our understanding of how rivers respond quantitatively and predictively to these disturbances in sediment supply.
{"title":"Simulating fluvial sediment pulses using remote sensing and machine learning: Development of a modeling framework applicable to data rich and scarce regions","authors":"Abhinav Sharma , Celso Castro-Bolinaga , Natalie Nelson , Aaron Mittelstet","doi":"10.1016/j.ijsrc.2025.02.002","DOIUrl":"10.1016/j.ijsrc.2025.02.002","url":null,"abstract":"<div><div>Fluvial sediment pulses pose a significant threat to the overall ecological health of river systems. Nonetheless, the scarcity of monitored and published data underscores the importance of devising innovative methods for understanding and measuring how river systems react to the introduction of sediments across the fluvial domain. The objective of this study was to create a modeling framework based on reflectance–turbidity that can be applied in regions with both limited and abundant data. Various combinations of predictor variables, training algorithms including linear regression and additional machine learning methods, and input data availability scenarios were examined to comprehend the factors influencing turbidity prediction on a regional scale. The results indicated that, for Washington state, the random forest algorithm, utilizing a combination of reflectance-based predictors and sediment delivery index (SDI) as predictors, produced the most accurate outcomes (data rich: NSE = 0.54, RSR = 0.68, data scarce: NSE = 0.47, RSR = 0.73). However, when tested on three locations in Washington experiencing sediment pulses, the reflectance–based turbidity prediction model consistently underestimated the peak high and peak low turbidity levels for the Elwha River. The model also exhibited consistent inaccuracies in predicting the initial phase of sediment pulses following the Oso Landslide. Nevertheless, promising results were observed for the Toutle River, downstream to the St. Mt. Helens Volcanic eruption site. Overall, the inclusion of SDI in the model enhanced its efficiency and transferability. By enabling the reconstruction of fluvial sediment pulses in data-scarce regions following dam removals, this integrated approach contributes to advancing our understanding of how rivers respond quantitatively and predictively to these disturbances in sediment supply.</div></div>","PeriodicalId":50290,"journal":{"name":"International Journal of Sediment Research","volume":"40 3","pages":"Pages 523-536"},"PeriodicalIF":3.5,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143932153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biochar, as a viable substrate and soil amendment, has the potential to improve the physical and chemical properties of soils, consequently affecting soil erosion. However, few studies have explored the impacts of different types of biochar on soil detachment rates in the hillslope rill erosion process due to overland flow in deforested areas. To fill this knowledge gap, this study evaluated the soil detachment capacity (Dc) and rill erodibility (Kr) of soil samples amended with four different biochars (wood, rice, olive, and almond shells) collected from deforested hillslopes in northern Iran. Dc was measured via a hydraulic flume at three-bed slopes (8.5%, 16.9%, and 25.4%) and five flow discharges (0.21, 0.32, 0.43, 0.55, and 0.63 L/(m·s)). Moreover, key properties of the amended soils and the control soil, including organic matter (OM), aggregate stability (MWD), bulk density (BD), and cation exchange capacity (CEC), were measured. Compared with the control treatment, the application of the four types of biochar significantly (p < 0.01) decreased the Dc (with at least a 41% reduction). The application of almond shell and rice biochars significantly increased the OM and MWD, thus effectively decreasing Dc (−76% compared with that of wood biochar) and (−47% compared with that of olive biochar). The correlation analysis revealed significant associations between OM, MWD, and BD on the one hand and Dc on the other hand. Overall, the soils treated with almond shell and rice biochars could be distinguished from the other soils into distinct groups via principal component analysis. The linear relationship between Dc and shear stress was used to reflect the relationship between the dependent and independent variables (coefficient of determination, R2 > 0.71). The multiple regression equation developed to estimate Dc from the OM, MWD, and BD data was also accurate (R2 > 0.83). This study demonstrated that almond shells and rice biochars can be effective factors in controlling and reducing Dc and Kr on deforested and steep hillslopes. The findings of this study can help land managers select the most effective organic substrate for soil conservation purposes as well as hydrologists to support the estimation of rill erosion on steep hillslopes.
{"title":"Efficiency of four types of biochar to improve soil properties and decrease soil detachment in vulnerable hillslopes to rill erosion","authors":"Fateme Sedaghatkish, Safoora Asadi Kapourchal, Misagh Parhizkar","doi":"10.1016/j.ijsrc.2025.01.012","DOIUrl":"10.1016/j.ijsrc.2025.01.012","url":null,"abstract":"<div><div>Biochar, as a viable substrate and soil amendment, has the potential to improve the physical and chemical properties of soils, consequently affecting soil erosion. However, few studies have explored the impacts of different types of biochar on soil detachment rates in the hillslope rill erosion process due to overland flow in deforested areas. To fill this knowledge gap, this study evaluated the soil detachment capacity (<em>D</em><sub>c</sub>) and rill erodibility (<em>K</em><sub>r</sub>) of soil samples amended with four different biochars (wood, rice, olive, and almond shells) collected from deforested hillslopes in northern Iran. <em>D</em><sub>c</sub> was measured via a hydraulic flume at three-bed slopes (8.5%, 16.9%, and 25.4%) and five flow discharges (0.21, 0.32, 0.43, 0.55, and 0.63 L/(m·s)). Moreover, key properties of the amended soils and the control soil, including organic matter (OM), aggregate stability (MWD), bulk density (BD), and cation exchange capacity (CEC), were measured. Compared with the control treatment, the application of the four types of biochar significantly (<em>p</em> < 0.01) decreased the <em>D</em><sub>c</sub> (with at least a 41% reduction). The application of almond shell and rice biochars significantly increased the OM and MWD, thus effectively decreasing <em>D</em><sub>c</sub> (−76% compared with that of wood biochar) and (−47% compared with that of olive biochar). The correlation analysis revealed significant associations between OM, MWD, and BD on the one hand and <em>D</em><sub>c</sub> on the other hand. Overall, the soils treated with almond shell and rice biochars could be distinguished from the other soils into distinct groups via principal component analysis. The linear relationship between <em>D</em><sub>c</sub> and shear stress was used to reflect the relationship between the dependent and independent variables (coefficient of determination, <em>R</em><sup>2</sup> > 0.71). The multiple regression equation developed to estimate <em>D</em><sub>c</sub> from the OM, MWD, and BD data was also accurate (<em>R</em><sup>2</sup> > 0.83). This study demonstrated that almond shells and rice biochars can be effective factors in controlling and reducing <em>D</em><sub>c</sub> and <em>K</em><sub>r</sub> on deforested and steep hillslopes. The findings of this study can help land managers select the most effective organic substrate for soil conservation purposes as well as hydrologists to support the estimation of rill erosion on steep hillslopes.</div></div>","PeriodicalId":50290,"journal":{"name":"International Journal of Sediment Research","volume":"40 3","pages":"Pages 489-499"},"PeriodicalIF":3.5,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143932149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, the effectiveness of different stabilization techniques implemented on the forest road cut slopes was investigated in terms of controlling erosion and runoff. Wood production residues, hydroseeding, and jute geotextile treatments were applied on study plots located on the example road. The amount of erosion and runoff were measured on the study plots which were established for different slope grades of 20°, 30°, and 40°. Then, the amount of erosion and runoff measured from the plots were compared to determine the performance of stabilization techniques on the cut slope. In the solution process, an Artificial Neural Network (ANN) model, which is one of the machine learning algorithms, was used to predict sediment yield from forest road cut slopes. The sediment yields averaged over the three slope grades from highest to lowest were measured as 6.41, 1.16, 0.65, and 0.45 g/m2 in the control plot with no treatment, jute geotextile, hydroseeding, and wood production residues, respectively. The averaged over the three runoff amounts slope grades from the highest to the lowest were determined as 6.82, 3.71, 1.64, and 1.30 mm/m2 in control the plot, jute geotextile, hydroseeding, and wood production residues, respectively. Comparing to the control plot, wood production residues, hydroseeding, and jute geotextile treatments reduced the sediment yields by 14, 10, and 5 times, respectively. On the other hand, wood production residues, hydroseeding, and jute geotextile applications reduced the runoff amount by 5, 4, and 2 times, respectively. As a result, it was found that wood production residues and hydroseeding treatment can be more efficient in reducing the amount of runoff and sediment yield compared to the jute geotextile treatment. The ANN method achieved high accuracy in predicting sediment yield and it was concluded that the ANN can be used as an effective method to evaluate soil slope stabilization techniques.
{"title":"Evaluation of eco-friendly soil slope stabilization techniques for forest roads by using an Artificial Neural Network (ANN)","authors":"Kıvanç Yüksel , Neşe Gülci , Abdullah Emin Akay , Sercan Gülci","doi":"10.1016/j.ijsrc.2025.01.011","DOIUrl":"10.1016/j.ijsrc.2025.01.011","url":null,"abstract":"<div><div>In this study, the effectiveness of different stabilization techniques implemented on the forest road cut slopes was investigated in terms of controlling erosion and runoff. Wood production residues, hydroseeding, and jute geotextile treatments were applied on study plots located on the example road. The amount of erosion and runoff were measured on the study plots which were established for different slope grades of 20°, 30°, and 40°. Then, the amount of erosion and runoff measured from the plots were compared to determine the performance of stabilization techniques on the cut slope. In the solution process, an Artificial Neural Network (ANN) model, which is one of the machine learning algorithms, was used to predict sediment yield from forest road cut slopes. The sediment yields averaged over the three slope grades from highest to lowest were measured as 6.41, 1.16, 0.65, and 0.45 g/m<sup>2</sup> in the control plot with no treatment, jute geotextile, hydroseeding, and wood production residues, respectively. The averaged over the three runoff amounts slope grades from the highest to the lowest were determined as 6.82, 3.71, 1.64, and 1.30 mm/m<sup>2</sup> in control the plot, jute geotextile, hydroseeding, and wood production residues, respectively. Comparing to the control plot, wood production residues, hydroseeding, and jute geotextile treatments reduced the sediment yields by 14, 10, and 5 times, respectively. On the other hand, wood production residues, hydroseeding, and jute geotextile applications reduced the runoff amount by 5, 4, and 2 times, respectively. As a result, it was found that wood production residues and hydroseeding treatment can be more efficient in reducing the amount of runoff and sediment yield compared to the jute geotextile treatment. The ANN method achieved high accuracy in predicting sediment yield and it was concluded that the ANN can be used as an effective method to evaluate soil slope stabilization techniques.</div></div>","PeriodicalId":50290,"journal":{"name":"International Journal of Sediment Research","volume":"40 3","pages":"Pages 476-488"},"PeriodicalIF":3.5,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143932148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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