Effects of Residue Cover on Infiltration Process of the Black Soil Under Rainfall Simulations

Yan, Xiaobing; Xie, Yonghong; Liu, Yuxin

doi:10.3390/w11122593

Cited by 4 publications

(4 citation statements)

References 29 publications

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“…The soil infiltration rate plays a pivotal role in surface runoff and exerts a substantial influence on SWL in sloping farmland. Typically, the soil water infiltration process follows a pattern characterized by an initial rapid infiltration rate that subsequently diminishes, eventually stabilizing (Xin et al, 2019). The results from our experiment revealed that the NT, in comparison to CK, demonstrated an enhanced soil infiltration capacity, corroborating the findings of (Ranaivoson et al, 2017), who attributed this enhancement to straw mulching and no-tillage practices, which effectively mitigated surface runoff while bolstering soil structure.…”

Section: Effects Of Tillage Methods On Soil Infiltration Characteristicssupporting

confidence: 82%

Dynamic change of soil aggregate stability and infiltration properties during crop growth under four tillage measures in Mollisols region of northeast China

Xu,

Liu,

et al. 2024

Front. Earth Sci.

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Introduction: Previous studies have proven that different tillage measures have significant different effects on soil structure, hydrology properties and soil erosion. However, few studies have clarified the dynamic changes in soil aggregate stability and infiltration properties during crop growth under four tillage measures.Methods: Four field plots (150 m × 15 m) managed by four tillage methods including wide ridge tillage (DT), no-tillage (NT), contour ridge tillage (CT) and traditional tillage (CK) were built in 2021 to evaluate their effects on dynamic changes of soil structure and water conductivity during crop growth. Soybean was the seasonal crop. Soil bulk density, soil porosity, soil aggregate stability and soil infiltration characteristics were measured to assess dynamic changes in soil aggregate stability and infiltration from June to October 2022.Results: The results showed that NT significantly increased soil bulk density by up to 21.62% compared with CK, while DT did not show significantly increase in soil bulk density. DT, NT and CT could greatly increase the capillary porosity and proportion of capillary porosity to total porosity. DT and NT also improved the stability of soil water-stable aggregates by 3.37% and 10.6%. In terms of soil infiltration properties, all three tillage methods increased the initial, stable and average infiltration rates by 8.4%–52.94%, of which the DT and NT showed the greatest improvement. The soil infiltration process of four tillage measures could be better fitted by Horton model than Kostiakov and Philip models. Soil saturated hydraulic conductivity (SHC) of CK exhibited a significant negative correlation with soil bulk density and capillary porosity, and showed a positive correlation with total porosity and geometric average diameter of water-stable aggregate (GMD), whereas the other three treatments only displayed a significant correlation with the stability of soil water-stable aggregate.Conclusion: The results suggest that DT, NT and CT have potential to improve soil structure and infiltration capacity compared with CK, and contribute to preventing and controlling soil erosion in sloping farmland of Northeast China.

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Section: Effects Of Tillage Methods On Soil Infiltration Characteristicssupporting

confidence: 82%

Dynamic change of soil aggregate stability and infiltration properties during crop growth under four tillage measures in Mollisols region of northeast China

Xu,

Liu,

et al. 2024

Front. Earth Sci.

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“…The total sediment transport rate formula of Yang's arithmetic coefficients has been transformed into fuzzy numbers by Kaffas et al [35], resulting in a fuzzy relationship that has produced a fuzzy band of in-stream sediment concentration. Xin et al [36] observed simulated rainfall experiments to observe the infiltration processes of black soil slopes under bare and residue-covered situations. A study of the impact of ponds in limnologically rich basins on soil erosion and sediment transport has been reported by Al Sayah et al [37].…”

Section: Literature Reviewmentioning

confidence: 99%

Prediction of the Amount of Sediment Deposition in Tarbela Reservoir Using Machine Learning Approaches

Hassan

Shaukat

Ahmad

et al. 2022

Water

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Tarbela is the largest earth-filled dam in Pakistan, used for both irrigation and power production. Tarbela has already lost around 41.2% of its water storage capacity through 2019, and WAPDA predicts that it will continue to lose storage capacity. If this issue is ignored for an extended period of time, which is not far away, a huge disaster will occur. Sedimentation is one of the significant elements that impact the Tarbela reservoir’s storage capacity. Therefore, it is crucial to accurately predict the sedimentation inside the Tarbela reservoir. In this paper, an Artificial Neural Network (ANN) architecture and multivariate regression technique are proposed to validate and predict the amount of sediment deposition inside the Tarbela reservoir. Four input parameters on yearly basis including rainfall (Ra), water inflow (Iw), minimum water reservoir level (Lr), and storage capacity of the reservoir (Cr) are used to evaluate the proposed machine learning models. Multivariate regression analysis is performed to undertake a parametric study for various combinations of influencing parameters. It was concluded that the proposed neural network model estimated the amount of sediment deposited inside the Tarbela reservoir more accurately as compared to the multivariate regression model because the maximum error in the case of the proposed neural network model was observed to be 4.01% whereas in the case of the multivariate regression model was observed to be 60.7%. Then, the validated neural network model was used for the prediction of the amount of sediment deposition inside the Tarbela reservoir for the next 20 years based on the time series univariate forecasting model ETS forecasted values of Ra, Iw, Lr, and Cr. It was also observed that the storage capacity of the Tarbela reservoir is the most influencing parameter in predicting the amount of sediment.

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“…Several studies have shown that the level of accuracy of the infiltration model (Horton, Kostiakov and Kostiakov Lewis) is quite good for field data with an R 2 value > 0.9 [14]. However, in several other research studies, the infiltration model produced less accurate results when compared to field data [19,20]. The analysis of related sources revealed that the behaviors of the infiltration models varied depending on the land use, climate, and field situations.…”

Section: Introductionmentioning

confidence: 98%

“…Higher model performance is indicated by a smaller RMSE value [5]. The RMSE statistics perform best when the value is close to zero [19].…”

mentioning

confidence: 99%

Evaluation of Infiltration Modeling in the Cisadane Watershed in Indonesia: Existing and New Approach Equation

Hidayat,

Darsono,

Farid

2023

Water

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This study aims to evaluate the accuracy of semi-empirical models for determining infiltration based on the existing equations (Horton, Kostiakov and Kostiakov–Lewis) and a new form equation with optimized parameters which has good accuracy (lowest RMSE and MBE), sufficient linearity (highest R2), and a Willmott index close to 1. The location of this study was the Cisadane watershed, which is a priority watershed in Indonesia. The lowest values of average RMSE and MBE and highest values of R2 and Willmott index are given by Equation 1, which indicated that the model was closest to the field infiltration conditions. The distribution of the RMSE values for all survey points using Equation 1 resulted in small RMSE values ranging from 0.09 to 1.83. The distribution of R2 values for all survey points using Equation 1 yielded R2 values close to 1 (high linearity) with values ranging from 0.96 to 1. Based on these results, it can be concluded that Equation 1 is the most accurate infiltration model for the Cisadane watershed compared to the existing infiltration rate equation. This research can be used as an initial idea to create the infiltration rate model using other forms of equations with optimization parameters to produce a more representative model with field data.

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Effects of Residue Cover on Infiltration Process of the Black Soil Under Rainfall Simulations

Cited by 4 publications

References 29 publications

Dynamic change of soil aggregate stability and infiltration properties during crop growth under four tillage measures in Mollisols region of northeast China

Dynamic change of soil aggregate stability and infiltration properties during crop growth under four tillage measures in Mollisols region of northeast China

Prediction of the Amount of Sediment Deposition in Tarbela Reservoir Using Machine Learning Approaches

Evaluation of Infiltration Modeling in the Cisadane Watershed in Indonesia: Existing and New Approach Equation

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