Water quality assessment has become an important aspect for environmental monitoring, control of public health, and management of resources. In water quality evaluation, traditional methods such as techniques based on crisp set theory, are largely based on deterministic models that fail to recognize the uncertainties as well as complexities found in environmental data. This research proposes a new approach to water quality assessment using Probabilistic Hesitant Fuzzy Sets (PHFSs). These days, aggregation operators (AOs) are frequently used to compile imprecise and unclear data. For probabilistic hesitant fuzzy (PHF) data, we develop a new AO called the generalized PHF weighted averaging geometric (GPHFWAG) operator. The key characteristics of the recommended operators are highlighted along with their complex interconnection. The proposed concepts are shown with real-life example about water quality assessment. In comparison to traditional techniques, the results show that PHFS-based evaluation procedures using new AOs offer greater accuracy and precision in assessing the state of water quality. Moreover, this research opens doors for more complex and refined tools necessary for environmental control as well as decision-making that are able to tackle intricate issues pertaining to water quality data.