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.