Metaheuristic algorithms have been increasingly used in different fields. The application of these algorithms for identifying and modelling natural phenomena such as flood and drought in terms of complexity and non-linear interactions can be considered as their capability in hydrology. In this paper, Symbiotic Organism Search (SOS) algorithm was first introduced, then its application in tuning fuzzy expert system, aiming to find the region of influence area of hydrometric stations in the Southern Caspian Sea Basin. This basin has regularly experienced flood events, causing human loss and properties damages every year. The outcome of this research is used to estimate floods, and subsequently, to design flood control structures. A total of 61 hydrometric stations were selected in the study area and their physical, climatic and hydrologic characteristics including area, perimeter, minimum elevation, maximum elevation, mean slope, stream length, slope of main stream, equivalent rectangle length, equivalent rectangle width, form factor, shape coefficient, Gravelious factor, round coefficient, and mean annual precipitation were determined. Results indicated that out of 16 parameters, area, mean elevation, form factor, Gravelious factor, and mean annual rainfall, were the most significant parameters in relation to flood by employing the SOS. These variables were used as the input variables into the fuzzy system and SOS algorithm to tune the fuzzy system. Finally, the efficiency of the SOS algorithm was evaluated using the linear torque heterogeneity statistic. Therefore, 61 influence areas were determined that show HOMOGENOUS areas in 61 watersheds. Results indicated the performance of SOS in determining region of influence of the sub-basins in the study area. In addition, the geographical vicinity is not a suitable criterion for finding HOMOGENOUS areas.