A river is a naturally formed freshwater stream that traverses land and eventually flows into a lake, sea, or another body of water. River provides fresh water for human activities such as irrigation for their paddy fields, aquaculture, industrial purposes, and many other purposes. At the same time, there exists an inherent disparity in the demand, availability, and quality of river water, often giving rise to significant challenges and issues. Environmental experts, commonly use a multivariate statistical method such as Principal Component Analysis (PCA), Storage and Retrieval (STORET), and cluster analysis for water quality analysis. However, those methods are numerical and limited in spatial visualization. Inverse Distance Weighting (IDW) interpolation, Voronoi, and Kriging were applied to obtain the spatial representation of water quality distribution Welang, Gembong, and Rejoso rivers in Pasuruan as study. The objectives are to locate on a map any river segments that experienced poor water quality throughout the observation period. We successively combined STORET with those spatial interpolation. The result shows that IDW interpolation, Voronoi, and Kriging can visualize and map river segments that had poor water quality during the observation time. However, due to the limited input data, the interpolation results exhibit variability. For instance, at a measured location with a STORET value of -28, IDW yielded -28, Voronoi -28, and Kriging -27. Beyond the measurement points, each interpolation method began to produce less accurate values. This study involves interpolating dynamic objects with limited measurements data in narrow channels, which differs from interpolating elevation in broader area, in terms of the accuracy of representation or visualization obtained from this spatial analysis still remain unresolved in this study.