Hydrologic connectivity is critical to the structure, function, and dynamic process of river ecosystems and represents an attainable, low risk form of river restoration. Dams, road crossings, water diversions, channelization, and other alterations to boundary conditions, the hydraulic environment, and water quality impact connectivity by altering flow regimes, behavioral cues, local geomorphology, and nutrient cycling. Longitudinal fragmentation of river ecosystems also increases genetic and reproductive isolation of aquatic biota such as migratory fishes. The cumulative effects of many structures along a river are often substantial, even when individual barriers have minor or negligible impact. Habitat connectivity can be restored through dam removal or other means of fish passage improvement (e.g., ladders, bypasses, culvert improvement). Environmental managers require techniques for comparing alternative restoration actions at single or multiple locations. This talk presents a refined graph-theoretic algorithm for assessing upstream habitat connectivity to investigate both basic and applied fish passage connectivity problems. First, we use hypothetical watershed configurations to assess general alterations to upstream fish passage connectivity with changes in watershed network topology (e.g., linear v. highly-dendritic) and the quantity, location, and passability of each barrier. Our hypothetical network modeling indicates that locations of dams with limited passage efficiency near the watershed outlet create a strong fragmentation signal, but are often not individually sufficient to disconnect the system. Furthermore, there exists a threshold in the number of dams beyond which connectivity declines precipitously, regardless of watershed morphology and dam configuration. Second, we apply the model to prioritize barrier improvement in the mainstem of the Truckee River, Nevada. The Truckee River application demonstrates the ability of the algorithm to address conditions common in fish passage projects including incomplete data, parameter uncertainty, and rapid application. This study demonstrates the utility of a graph-theoretic approach for assessing fish passage connectivity in dendritic river networks.