This study developed a station optimization framework integrating stratified random sampling （without replacement） and spatial clustering， using the offshore waters of Ningbo as a case study. The framework was based on data from 92 stations and 16 water quality parameters collected during summer in 2024. Area-weighted means based on Thiessen polygons served as the primary benchmark for comparison， with additional comparisons made against means from a regular 0.05° grid. The estimation performance under different station densities was evaluated using the Relative Estimation Error （REE） and Relative Bias （RB）. Following range standardization and the calculation of a composite index， UPGMA clustering was applied to identify the optimal station configuration.The results revealed pronounced spatial heterogeneity in the water environment. Elevated levels of salinity， dissolved oxygen， pH， total alkalinity， and ammonium nitrogen were mainly observed in Sanmen Bay and the eastern Xiangshan waters. Higher concentrations of chemical oxygen demand， silicate， reactive phosphate， particulate organic carbon， total nitrogen， nitrate nitrogen， and total phosphorus were concentrated along the southern coast of Hangzhou Bay-northern Beilun and the Xiangshan Port-southern Beilun regions. In contrast， suspended matter， Chl.a， nitrite nitrogen， and dissolved organic carbon exhibited relatively uniform spatial distributions. The REE decreased rapidly with increasing station numbers， with Chl.a， particulate organic carbon， nitrite nitrogen， and reactive phosphate showing the highest sensitivity to station density.By applying an REE threshold of 10% and considering clustering coverage， management constraints， and the need to retain long-term trend stations， an optimal network of 72 stations was determined for the entire study area. These were allocated to four subregions with 18， 17， 25， and 12 stations， respectively. The proposed framework balances statistical robustness and spatial representativeness and provides a practical reference for optimizing monitoring networks in Ningbo and other similar coastal seas.