Abstract. River ice, like open-water conditions, is an integral component of the cold-climate hydrological cycle. The annual succession of river ice formation, growth, decay and clearance can include low flows and ice jams, as well as midwinter and spring break-up events. Reports and associated data of river ice occurrence are often limited to single locations or regional assessments, are season-specific, and use readily available data. Within Canada, the National Hydrometric Program (NHP) operates a network of gauging stations with water level as the primary measured variable to derive discharge. In the late 1990s, the Water Science and Technology Directorate of Environment and Climate Change Canada initiated a long-term effort to compile, archive and extract river-ice-related information from NHP hydrometric records. This data article describes the original research data set produced by this near 20-year effort: the Canadian River Ice Database (CRID). The CRID holds almost 73 000 recorded variables from a subset of 196 NHP stations throughout Canada that were in operation within the period 1894 to 2015. Over 100 000 paper and digital files were reviewed, representing 10 378 station years of active operation. The task of compiling this database involved manual extraction and input of more than 460 000 data entries on water level, discharge, ice thickness, date, time and data quality rating. Guidelines on the data extraction, rating procedure and challenges are provided. At each location, time series of up to 15 variables specific to the occurrence of freeze-up and winter-low events, midwinter break-up, ice thickness, spring break-up, and maximum open-water level were compiled. This database follows up on several earlier efforts to compile information on river ice, which are summarized herein, and expands the scope and detail for use in Canadian river ice research and applications. Following the Government of Canada Open Data initiative, this original river ice data set is available at https://doi.org/10.18164/c21e1852-ba8e-44af-bc13-48eeedfcf2f4 (de Rham et al., 2020).