Abstract
Main purpose of this article is to classify reservoirs corresponding to their physical characteristics, for example, dam height, dam width, age, repair-works history. First of all, data set of 13,976 reservoirs was analyzed using k means and self organized maps. As a result of these analysis, lots of reservoirs have been classified into four clusters. Factors and their critical values to classify the reservoirs into four groups have been founded by generating a decision tree. The path rules to each group seem reasonable since their survivor function showed unique pattern.
