Soil erosion model tested on experimental data of a laboratory flume with a pre-existing rill

Aksoy, Hafzullah; Gedikli, Abdullah; Yilmaz, Murat; Eriş, Ebru; Ünal, N. Erdem; Yoon, Jaeyoung; Kavvas, M. L.; Tayfur, Gökmen

doi:10.1016/j.jhydrol.2019.124391

Cited by 11 publications

(5 citation statements)

References 91 publications

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“…A full factorial experimental plan was designed considering possible coupled effects of combinations of low and high levels of all parameters [56]. To meet the practical engineering slope design, as suggested by [57], [58], and [59], the authors considered mild (7 • ) and moderate slopes (20 • ) in combination with four other factors (slope gradient, compaction, rainfall, and slope length) [57][58][59]. The soil-biochar mix was subjected to 60 mm/hour and 90 mm/hour rainfall intensity.…”

Section: Test Plan and Proceduresmentioning

confidence: 99%

Application of Artificial Intelligence for Predicting Erosion of Biochar Amended Soils

2022

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Recently, incentives have been provided in developed countries by the government for commercial production of biochar for soil treatment, and other construction uses with an aim to reduce a significant amount of carbon emissions by 2030. Biochar is an important material for the development of circular economy. This study aims to develop a simple Artificial Neural Network (ANN) based model to predict erosion of biochar amended soils (BAS) under varying conditions (slope length, slope gradient, rainfall rate, degree of compaction (DoC), and percentage of biochar amendments). Accordingly, a model has been developed to estimate the total erosion rate and total water flow rate as a function of the above conditions. The model was developed based on available data from flume experiments. Based on ANN modelling results, it was observed that slope length was the most important factor in determining total erosion rate, followed by slope gradient, DoC, and percentage of biochar amendment. The percentage of biochar amendment was a leading factor in the total water flow rate determination as compared to other factors. It was also found that the reduction in erosion is relatively minimal during an increase in slope length up to 1.55 m, reducing sharply beyond that. At a slope length of 2 m, erosion is found to be reduced by 33% (i.e., 2.6 to 1.75), whereas the total flow rate decreases linearly from 1250 mL/m2/min to 790 mL/m2/min. The ANN model developed shows that soil biochar composite (SBC) with 5% biochar amendment gave the best results in reducing soil erosion. This study can be a helpful tool in providing preliminary guidelines for using biochar in erosion control.

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Section: Test Plan and Proceduresmentioning

confidence: 99%

Application of Artificial Intelligence for Predicting Erosion of Biochar Amended Soils

2022

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“…Subsequent to further scouring by concentrated flow at the rill base, the accumulation of overhanging soils escalates, initiating random collapses along the rill walls, thereby augmenting rill width and intensifying sidewall erosion rates, especially in response to slope gradients and the confluence of upstream flows [20][21][22][23][24][25]. Current investigations into pivotal processes governing rill sidewall expansive erosion, notably focusing on rill base scouring and the inception and evolution of tension fissures, remain notably deficient, necessitating extensive in situ observations and model simulations to elucidate their underlying mechanisms and characteristics [26][27][28][29][30][31][32][33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

The Collapse Mechanism of Slope Rill Sidewall under Composite Erosion of Freeze-Thaw Cycles and Water

Huang,

Shao,

Liu

et al. 2024

Sustainability

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The composite erosion of freeze-thaw and water flow on slope rills is characterized by periodicity and spatial superposition. When revealing the collapse mechanism of slope rill sidewalls under the composite erosion of freeze-thaw and water flow, it is necessary to fully consider the effect of water migration and its impact on the stability of the rill sidewall. In this paper, we placed the self-developed collapse test system in an environmental chamber to carry out model tests on rill sidewall collapse on slopes under the composite erosion of freeze-thaw and water flow. We utilized three-dimensional reconstruction technology and the fixed grid coordinate method to reproduce the collapse process of the rill sidewall and precisely locate the top crack. We obtained the relationship between the water content of the specimen and mechanical indexes through the straight shear test. The main conclusions are as follows: The soil structure of the rill sidewall is significantly affected by the freeze-thaw cycle, which benefits capillary action in the soil. One freeze-thaw cycle has the most serious effect on the soil structure of the rill sidewall, and the change in the moisture field is more intense after the soil temperature drops below zero. The friction angle of the soil increases with the number of freeze-thaw cycles and tends to stabilize gradually. The effect of the freeze-thaw cycle on the rate of change of the water content of the soil at each position of the wall can be accurately described by a logarithmic function. The expression of the two-factor interaction effect on the rate of change of water content of soil at each position of the rill sidewall can be accurately fitted. We propose a calculation system for locating cracks at the top of the rill sidewall and determining the critical state of instability and collapse of the rill sidewall during the process of freeze-thaw and water flow composite erosion. The results of this research can help improve the accuracy of combined freeze-thaw and water flow erosion test equipment and the development of a prediction model for the collapse of the rill sidewall under compound erosion. This is of great significance for soil and water conservation and sustainability.

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“…The establishment of MUSLE has played a pivotal role in advancing global soil erosion prediction, serving as the foundation for numerous region‐specific theoretical models proposed for practical implementation. Aksoy et al (2020) established a two‐dimensional deterministic unsteady process‐based mathematical model to simulate soil erosion well in rill and inter‐rill areas on hillslopes. Similarly, Feng et al (2020) developed a mathematical model of inter‐rill erosion on a purple soil steep slope to improve the accuracy of soil erosion calculation in the Three Gorges reservoir area of China.…”

Section: Introductionmentioning

confidence: 99%

“…The establishment of MUSLE has played a pivotal role in advancing global soil erosion prediction, serving as the foundation for numerous region-specific theoretical models proposed for practical implementation. Aksoy et al (2020) SWAT code integration and revision (T. Ma et al, 2019). For example, Y.…”

mentioning

confidence: 99%

Developing SWAT‐S to strengthen the soil erosion forecasting performance of the SWAT model

Long,

Gao,

Shao

et al. 2023

Land Degrad Dev

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Soil erosion is an important cause of global land degradation, and accurate monitoring of it is essential. The Soil and Water Assessment Tool (SWAT), a distributed hydrological model, is an advanced technique for predicting soil erosion at watershed scale. However, as the erosion framework was established in gently sloping land, SWAT is limited in predicting soil erosion in some highland and mountainous regions. Therefore, this study suggested a method to integrate the sediment transport theoretical formula that can reflect the morphology of gully regions into SWAT to obtain SWAT‐S to enhance the calculation performance of sediment load, and the SWAT‐S was evaluated according to the coefficient of determination (R2), Nash‐Sutcliffe coefficient (NSE), Percent‐Bias (P‐BIAS) and root mean square errors (RMSE)‐observations SD ratio (RSR) in the Yanhe basin on the Chinese Loess Plateau. The results showed that SWAT‐S is more successful in reproducing the monthly sediment load, with R2, NSE, |P‐BIAS| and RSR were changed by 5.08%, 17.65%, −2.92% and −10.00% in the calibration, as well as by 1.18%, 10.39%, 45.45% and −18.75% in the validation of the SWAT‐S compared to SWAT. Meanwhile, SWAT‐S estimates 2.66 × 106 t more sediment than SWAT during the June–September flood season and better matches observed data. In total, the revised SWAT can improve the performance of sediment estimation, which is beneficial for the wider application of the model in more regions of the world.

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Soil erosion model tested on experimental data of a laboratory flume with a pre-existing rill

Cited by 11 publications

References 91 publications

Application of Artificial Intelligence for Predicting Erosion of Biochar Amended Soils

Application of Artificial Intelligence for Predicting Erosion of Biochar Amended Soils

The Collapse Mechanism of Slope Rill Sidewall under Composite Erosion of Freeze-Thaw Cycles and Water

Developing SWAT‐S to strengthen the soil erosion forecasting performance of the SWAT model

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