https://doi.org/10.5194/hess-28-4383-2024

Gharari, S., Whitfield, P.H., Pietroniro, A., Freer, J., Liu, H., and Clark, M. P. (2024) Exploring the provenance of information across Canadian hydrometric stations: implications for discharge estimation and uncertainty quantification, EGU, Hydrology and Earth System Sciences, Articles Volume 28, issue 19 HESS, 28, 4383–4405, 2024, https://doi.org/10.5194/hess-28-4383-2024

Accurate discharge values form the foundation of effective water resource planning and management. Unfortunately, these data are often perceived as absolute and deterministic by users, modelers, and decision-makers, despite the inherent subjectivity and uncertainty in the data preparation processes. This study is undertaken to examine the discharge estimation methods used by the Water Survey of Canada (WSC) and their impacts on reported discharge values. First, we explain the hydrometric station network, essential terminologies, and fundamental concepts of rating curves. Subsequently, we examine WSC's standard operating procedures (SOPs), including shift, temporary shift, and override, in discharge estimation. Based on WSC's records of ∼ 1800 active hydrometric stations for discharge monitoring, we evaluated sample rating curves and their correlation with stage and discharge measurement. We investigate under-ice measurements, ice condition periods and frequency, and extreme values in contrast to rating curves. Employing an independent workflow, we demonstrate that 69 % of existing records align with the rating curve and temporary shift concept, while the remaining 31 % follow alternative discharge estimation methods (override). Selected example stations illustrate discharge estimation methods over time. We also demonstrate the impact of override and temporary shifts on commonly assumed uncertainty models. Given the practices of override and temporary shifts within WSC, there is a need to explore innovative methods for discharge uncertainty estimation. We hope our research helps in the critical challenge of estimating and communicating uncertainty in published discharge values.

https://doi.org/10.5194/hess-28-4383-2024