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).