New paper about data-driven behavioral modeling of water reservoir operators

Our paper recently published on Advances of Water Resoruces proposes a new approach to infer the typical operations of water reservoirs from historical observations, using data-driven behavioral modeling based on eigenbehavior analysis. We extend the original eigenbehavior analysis by Eagle and Pentland (2009) used also by Cominola et al. (2018) to characterize typical operating strategies across 172 water reservoirs in California. We show that the proposed method identifies four typical behavioral profiles, which are strongly linked to key features of the reservoirs. Moreover, we illustrate how the identified models can be used for discovering behavioral profiles, and associated reservoir characteristics, that are vulnerable to drought conditions. Read more HERE.

Giuliani, M. and J.D. Herman (2018), Modeling the behavior of water reservoir operators via eigenbehavior analysis, Advances in Water Resources, 122