Paying attention to hydrometric stations in most of the countries is on an increase in recent years which might be due to applying the received information of these stations, the importance of data in designing and managing planning for water resources and also the need for reliable and precise data. Thus, choosing the best location for installing hydrometric stations based on installation costs and the policies of each region is of paramount importance (other factors such as safety matters and availability potential etc. should be also taken into consideration while installing new hydrometric stations). In this study, the data from 44 hydrometric stations in Karkhe basin with a 25-year statistical period (1370-1394) was used and some statistical investigations such as data normalization and outlier data testing were applied. Furthermore, unrecorded data of the stations was rebuilt. The average amount of annual discharge was standardize to neuter the effect of the area of subbasin. Simple, ordinary and universal interpolation kriging methods were used to estimate the amount of discharge in the areas without any statio bat evolutionary algorithm which is iired by its hunting style was applied to achieve the location and optimize the hydrometric stations. Two scenarios were assessed in this study and different interpolation kriging methods and waterways maps were used to determine the location of hydrometric stations. In the first scenario, 43 points for reinstalling stations were obtained by providing the distribution map of discharge in the region and choosing ordinary kriging with spherical variogram as the best model to fit the average annual discharge and usage of bat algorithm for increasing correlation coefficient among the data assuming no station exists. In the second scenario, transinformation Entropy in the region was calculated and 18 potential points (the ones with the minimum amount of entropy in the region) were recommended for installing new stations. This was done by using universal kriging with gussian variogram which best fits among kriging methods with the purpose of increasing the amount of transinformation among the existing stations in the region. Key words: Entropy, bat algorithm, kriging, optimization, hydrometric, variogram, special discharge