Assessment of coastal bedrock groundwater quality in Jiaodong Peninsula via extension cloud model and resampling strategy

Groundwater safety in coastal tourism regions is increasingly compromised by the conflict between rigorous quality standards and diffuse agricultural pollution. Traditional linear assessment methods often mask specific high-risk indicators through mathematical averaging. To address this challenge, this study applies the Extension Cloud Model using data from 18 monitoring wells in the Jiaodong Peninsula. To robustly quantify uncertainty despite the limited sample size, the framework is integrated with the Multi-step Backward Cloud Transformation based on Sampling with Replacement algorithm. While hydrochemical analysis indicates that rock weathering controls the regional baseline, water quality is significantly degraded by where potassium shows a strong correlation coefficient of 0.90 with chemical oxygen demand. The assessment results indicate that 38.9% of the groundwater samples fall into Class IV or V which are unsuitable for drinking purposes. A comparative analysis confirms that the Extension Cloud Model successfully identified critical contamination risks masked by the eclipsing effect in the Entropy Weighted Water Quality Index. Furthermore, the resampling algorithm calculated a regional expectation value of 0.3609 quantifying that the overall water quality is in a critical transition state between Class III and IV. This framework offers a scientifically robust tool for diagnosing groundwater safety in data-scarce coastal zones.