Construction of dams and the resulting water impoundments are one of the most common engineering procedures implemented on river systems. One major problem in dams’ impact studies is the lack of reliable methods for simulating reservoir operation. We have used Artificial Neural Networks to parameterize actual dam operations and developed a General Reservoir Operation Scheme (GROS) which may be added to daily hydrologic routing models for simulating the releases from dams in regional and global-scale studies. GROS is sufficiently accurate in simulating the operation of existing reservoirs and is specifically designed to provide a broad perspective of the general behavior of dams and improve the understanding of the large-scale hydrological impact of dams operation in a relatively easy and efficient way. Embedding GROS in a water balance model (WBMplus), we are analyzing the hydrological impact of dams on the thirteen states of the Northeastern United States. Our analysis shows the changing trends in hydrological characteristics of each state for the period of 1950 to 2099 under the four Representative Concentration Pathways (RCPs). We demonstrate how the magnitude and timing of minimum and maximum monthly flows change as a result of climate change and explore the role of reservoirs in that change. In addition, we investigate whether building new dams can provide engineered resilience to climate change and enhance future water security.