Precise identification of riverine microhabitats, such as pools, runs, and riffles, is fundamental to effective river management and the conservation of aquatic ecosystems. This study evaluates and compares visual and computational methods, specifically those based on the Froude number, for the identification of microhabitats in the Jajroud River, Iran. Seventy-one sampling points were assessed, with depth and velocity measurements recorded to calculate the Froude number. Visual classification relied on observable features such as surface water texture and flow patterns. Results revealed a 60.56% agreement between the two approaches, with a Kappa coefficient of 0.408, indicating a moderate level of concordance. Discrepancies between methods were largely attributed to the subjective nature of visual assessments and the inherent simplifications of the Froude number method. A strong positive correlation was observed between the Froude number and flow velocity (r = 0.85), whereas a moderate inverse correlation was found with water depth (r = -0.65). Statistical analyses, including a Chi-square test (p-value < 0.05), confirmed a significant association between visual and computational classifications. These findings underscore the need for an integrated approach to microhabitat identification and suggest that advanced modeling techniques may further enhance habitat assessment. Overall, this study advances efforts towards sustainable river management and the preservation of aquatic biodiversity.