Tidal energy is a renewable resource that helps meet growing energy demands, but uncertainties remain about environmental impacts of device installation and operation. Monitoring programs are used to detect impacts caused by anthropogenic disturbances and are a mandatory requirement of project operating licenses in the United States. Because tidal technology is new, studies describing environmental change due to tidal devices are scarce, limiting the information that can be used to characterize environmental impacts for monitoring requirements. Extreme value analysis (EVA) was used to characterize infrequent values from monitoring studies that are potentially associated with impact, defined as relevant biological change as a consequence of human activity, at a tidal energy site. EVA was adapted for monitoring aquatic organisms in the water column using an active acoustic dataset from Admiralty Inlet, a proposed tidal energy site. First derivatives were used to identify extreme value thresholds to improve estimation precision. Return level plots, which indicate the average period that extreme values are expected to appear, and uncertainty estimates of return level predictions, were generated using Markov Chain Monte Carlo (MCMC) simulations. Managers and site developers could use EVA to characterize rare values that may be associated with impacts, and tailor monitoring programs to include operational protocols for conditions under which these events occur. To characterize the generality of tidal energy sites, metrics describing temporal and spatial distributions of fish and macrozooplankton at the Admiralty Inlet site and a second tidal energy site from the Fall of Warness, Scotland were compared using statistical methods (t-test, F-test, linear regression), spectral analysis, and EVA. General biological characteristics were similar enough that generic biological monitoring programs could be implemented at these two sites, which would streamline the permitting process as well as facilitate site comparison and detection of environmental impact due to tidal technology deployment.