2.1 Difficulties in collecting and accessing data
The use of field data is fundamental to hydrological research;
observations underlie our understanding of processes, assessment of
model performance and application of remote sensing products. Canada’s
vast and sparsely populated area presents an important challenge to
collecting representative data and affects both the direction and scope
of field-based studies. The cost and logistical challenges of working in
remote and northern areas are rarely explicitly mentioned in
publications (e.g. Petrone et al., 2006; Shatilla & Carey, 2019).
However, these factors cause research resources to be funneled into a
handful of long-term monitoring sites with existing support (e.g. Scotty
Creek (Quinton et al., 2019); Baker Creek (Spence and Hedstrom, 2018);
Wolf Creek (Rasouli et al., 2019); Utikuma Region Study Area (Devito,
2012)). These observatories are extremely valuable, as they provide
long-term high spatial and temporal resolution datasets that improve
process understanding and predictive modelling, and are essential in
identifying hydrological trends (e.g. Rasouli et al., 2013; Spence et
al., 2014; DeBeer et al., 2015; Teztlaff et al., 2017).
Outside of these heavily monitored sites, large expanses of the Canadian
landscape remain data sparse. For comparison, the US has approximately
eight times more government-run stream gauging stations than Canada,
despite similar land mass (USGS, 2014). In data-poor areas, it can be
particularly difficult to capture hydrological processes such as
snowmelt or river ice break-up that require high temporal resolution
data, or to capture long term trends in discharge and hydrochemistry.
Where data exist, they are sometimes difficult or impossible for ECRs to
access due to a lack of consistency in data reporting and presentation.
This “hidden data” can take many forms. It can be unprocessed, held by
a given lab group, owned or rendered confidential by an industry
stakeholder, or fragmented between several publications, online data
repositories and branches of federal, territorial and provincial
governments. This accessibility issue can be particularly detrimental to
ECRs, who lack the extensive network or experience to know if “hidden”
data exist and where to look for them.
Even when data are accessible, metadata are often lacking. Metadata
include vital information about the instrumentation used in data
collection, analytical methods employed, data processing procedures and
how quality control protocols were applied. This supporting information
is particularly important in the context of Canadian hydrology, where
conducting fieldwork over large and remote landscapes may lead to
difficulties in following standard protocols. Without metadata, it is
difficult for the user to determine the quality or applicability of the
data and to combine data from different sources.