One significant barrier is the disconnect between water experts and AI specialists. promotion of open-access data sharing within and beyond the drinking water research community . The endeavors will enhance collaboration, drive transparency, and support the reproducibility of scientific findings, which are the bedrock of robust research. Furthermore, establishing a comprehensive comparative framework to evaluate different ML models will be instrumental in identifying the optimal solutions for the challenges in drinking water research. By embracing these strategies, we can aspire to not just bridge existing knowledge gaps but also significantly elevate the role of ML in securing safe and more sustainable water supply.