Assessment and ranking flood events in a regulated river using information and complexity measures

Abstract

Abstract The availability of a robust approach that describe the hidden features of flood events in regulated rivers is of great importance. The key goal of this research is to utilize some of information and complexity measures to assess and rank flood patterns within a regulated river system. To meet this goal, the Metric Entropy (ME) as measure of information content and Rényi Complexity (CR) as a quantification for complexity content were employed. To examine the role of river regulation on flood risk control, river stage records of two monitoring stations located at downstream of two different dams were considered in this research. The findings show that information and complexity metrics offer an image of the randomness embedded in dataset and the presence of internal patterns in studied data records. In general, this research shows that natural environmental risks and disasters can be assessed and ranked using a promising physical scheme based on information and complexity measures.