The role of soil dispersivity and initial moisture content in splash erosion: Findings from consecutive single-drop splash tests

Li, Xingyao; Fan, Henghui; Xie, Feihan; Lei, Baofeng; Ren, Guanzhou

doi:10.1016/j.biosystemseng.2024.05.001

Biosystems Engineering

2024

DOI: 10.1016/j.biosystemseng.2024.05.001

|View full text |Cite

The role of soil dispersivity and initial moisture content in splash erosion: Findings from consecutive single-drop splash tests

Xingyao Li,

Henghui Fan,

Feihan Xie

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 80 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Triaxial testing and model study on lime modified dispersive soil considering age effects

He,

Gao,

Yang

et al. 2024

Bull Eng Geol Environ

View full text Add to dashboard Cite

Triaxial testing and model study on lime modified dispersive soil considering age effects

He,

Gao,

Yang

et al. 2024

Bull Eng Geol Environ

View full text Add to dashboard Cite

Spatial Prediction of Soil Water Content by Bayesian Optimization–Deep Forest Model with Landscape Index and Soil Texture Data

Yang,

Zhen,

Meng

et al. 2024

Agronomy

View full text Add to dashboard Cite

The accurate prediction of the spatial variability for soil water content (SWC) in farmland is essential for water resource management and sustainable agricultural development. However, natural factors introduce uncertainty and result in poor alignment when predicting farmland SWC, leading to low accuracy. To address this, this study introduced a novel indicator: landscape indices. These indices include the largest patch index (LPI), edge density (ED), aggregation index (AI), patch cohesion index (COH), contagion index (CON), landscape division index (DIV), percentage of like adjacencies (PLA), Shannon evenness index (SHEI), and Shannon diversity index (SHDI). A Bayesian optimization–deep forest (BO–DF) model was developed to leverage these indices for predicting the spatial variability of SWC. Statistical analysis revealed that landscape indices exhibited skewed distributions and weak linear correlations with SWC (r < 0.2). Despite this, incorporating landscape index variables into the BO–DF model significantly improved prediction accuracy, with R2 increasing by 35.85%. This model demonstrated a robust nonlinear fitting capability for the spatial variability of SWC. Spatial mapping of SWC using the BO–DF model indicated that high-value areas were predominantly located in the eastern and southern regions of the Yellow River Delta in China. Furthermore, the SHapley additive explanation (SHAP) analysis highlighted that landscape indices were key drivers in predicting SWC. These findings underscore the potential of landscape indices as valuable variables for spatial SWC prediction, supporting regional strategies for sustainable agricultural development.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

The role of soil dispersivity and initial moisture content in splash erosion: Findings from consecutive single-drop splash tests

Cited by 2 publications

References 80 publications

Triaxial testing and model study on lime modified dispersive soil considering age effects

Triaxial testing and model study on lime modified dispersive soil considering age effects

Spatial Prediction of Soil Water Content by Bayesian Optimization–Deep Forest Model with Landscape Index and Soil Texture Data

Contact Info

Product

Resources

About