Existing water contaminant identification systems based on emission–emission matrix (EEM) mostly focus on the data level using a 2-D matrix, which makes it difficult to distinguish the EEM with similar location and shape owing to the insensitivity of a matrix in contrast to the 3-D morphology. In this study, a system of water contaminant identification was presented with an innovative approach based on the theory of 3-D topology and the EEM-oriented Reeb graph was proposed as a new spectral feature. In this system, an automatic scanning system for EEM was designed and constructed, and relevant procedures of analysis algorithms were integrated in it. The EEM-oriented Reeb graph describes the key 3-D morphological characteristics of fluorescence peaks without redundant information so that they are sensitive to the change of spatial structure and benefit for distinguishment. In addition, owing to topological invariance, the EEM-oriented Reeb graph is insensitive to factors, such as concentration and peak shift, and is therefore more robust for substance identification. The new method for water contaminant identification was assessed through controlled laboratory experiments for simulating the presence of six typical contaminants commonly found in the river. The samples containing multiple pollutants were identified, and the accuracy was 75% all correct and 16.7% partial correct better than principal component analysis (PCA), wavelet decomposition, and conventional peak picking. In addition, the time consumed in constructing models was only around 23 ms, shorter than PCA and wavelet decomposition.