.png){kind=icon}
.png){kind=icon}
Return
Towards surface-based hydraulic conductivity mapping using seismoelectric signals and data-driven models
.png){kind=icon}
OA
AI
DOI：10.1016/j.acags.2026.100377.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• Integration of seismoelectric coupling mechanisms into a robust data-driven framework for KV mapping. • Theoretical refinement linking electrokinetic responses directly to permeability-related processes. • Enhanced feature engineering that incorporates multidimensional signal interactions and topographic context. • Model validation through spatially blind tests and SHAP-based interpretability analysis to ensure reliability. • Discussion prioritizing hydrogeological plausibility and consistency over traditional statistical performance metrics.
Keywords:
Seismoelectric method
Vertical hydraulic conductivity
Hydrogeophysics
Machine learning
Feature engineering
Subsurface mapping
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.2
Papers:
159
Citations:
375
Organization
View more organizations