Indicators sensitivity analysis for environmental engineering geological patterns caused by underground coal mining...

Area of Science:

• Environmental Engineering
• Geology
• Mining Engineering

Background:

• Underground coal mining poses significant environmental engineering geological challenges.
• Understanding environmental engineering geological patterns (EEGPs) is vital for sustainable mining.
• Existing models require refinement for accurate sensitivity analysis of EEGPs.

Purpose of the Study:

• To perform an indicator sensitivity analysis for four distinct EEGPs using advanced modeling.
• To identify critical environmental indicators influencing geological stability during coal mining.
• To propose tailored mining strategies based on identified sensitive indicators.

Main Methods:

• Utilized Variable Weight Theory (VWT) and an improved Matter-Element Extension Model (MEEM).
• Defined four types of EEGPs: unaffected, gradually restored, gradually deteriorated, and disaster models.
• Conducted sensitivity analysis on 13 selected indicators with ±10-50% value variations.

Main Results:

• Rainfall capacity, evaporation capacity, and Normalized Difference Vegetation Index (NDVI) are sensitive indicators for unaffected models.
• Coal seam thickness and laterite thickness are sensitive indicators for gradually restored, gradually deteriorated, and disaster models.
• VWT and improved MEEM demonstrated accuracy and reasonability compared to traditional MEEM.

Conclusions:

• Specific environmental indicators are critical for different EEGPs related to underground coal mining.
• Findings provide a basis for selecting appropriate mining methods (e.g., layered, stripe, filling, grouting).
• This research supports decision-making for the mining industry and environmental protection agencies.