In this work, the analytical performance of a third-order/four-way calibration is evaluated to model a highly overlapped system, where two spectral dimensions are extremely similar, and the results are then compared with the results of second-order/three-way calibration. The four-way data were obtained during the photodegradation of fluoroquinolones (ciprofloxacin, norfloxacin and flumequine) in the form of excitation-emission matrices and modeled by unfolded partial least squares coupled to residual trilinearization (U-PLS-RTL). According to the results, the model obtained with the second-order algorithm (unfolded partial least squares coupled to residual bilinearization: U-PLS-RBL) was unsatisfactory due to high spectral overlap. The third-order approach obtained a satisfactory fit and better figures of merit (LOD, REP, RMSEP, and sensitivity, among others) even in the presence of unexpected interferences due to third-order advantages. Finally, the analytical method based on third-order multivariate calibration was applied to quantify these fluoroquinolones in spiked fish-farming water samples. In this case, the third-order advantage allowed us to satisfactorily model the data and to quantify these compounds in this complex matrix, demonstrating the superior analytical performance of the high-order data that were evaluated.