Water Temperature Ensemble Forecasts: Implementation Using the CEQUEAU Model on Two Contrasted River Systems

Abstract

Abstract:In some hydrological systems, mitigation strategies are applied based on short-range water temperature forecasts to reduce stress caused to aquatic organisms. While various uncertainty sources are known to affect thermal modeling, their impact on water temperature forecasts remain poorly understood. The objective of this paper is to characterize uncertainty induced to water temperature forecasts by meteorological inputs in two hydrological contexts. Daily ensemble water temperature forecasts were produced using the CEQUEAU model for the Nechako (regulated) and Southwest Miramichi (natural) Rivers for 1-5-day horizons. The results demonstrate that a larger uncertainty is propagated to the thermal forecast in the unregulated river (0.92-3.14 • C) than on the regulated river (0.73-2.29 • C). Better performances were observed on the Nechako with a mean continuous ranked probability score (MCRPS) <0.85 • C for all horizons compared to the Southwest Miramichi (MCRPS ≈ 1 • C). While informing the end-user on future thermal conditions, the ensemble forecasts provide an assessment of the associated uncertainty and offer an additional tool to river managers for decision-making.

Modelling the impacts of climate change on riverine thermal regimes in western Canada’s largest Pacific watershed

“…The Nechako River has been regulated by Alcan (now owned by Rio Tinto) since the construction of the Kenney Dam, the Skins Lake Spillway, and the Nechako Reservoir in the 1950s 61,62 . Summer flows in the Nechako River are further regulated in response to forecasted air temperatures owing to a 1980 court injunction 42,50,63 . Following the court ruling, Rio Tinto implemented the STMP in 1981 to suppress river water temperatures to <20 °C for the Nechako River at Finmoore (~40 km downstream from NVH) from 20 July to 20 August through controlled releases from Skins Lake Spillway for the benefit of migrating salmon.…”

“…This analysis also considered the impact of the Summer Temperature Management Project (STMP) in the Nechako River (NVH) by comparing results prior to and after its implementation in 1981. The STMP regulates water temperatures through additional releases of flows from the Nechako reservoir via the Skins Lake Spillway into the Nechako River for the benefit of salmon migration 42 .…”

Hydrological Evaluation of PERSIANN-CDR Rainfall over Upper Senegal River and Bani River Basins

“…However, simulations at time steps less than a day have rarely been done with this model due to the scarcity of hydrometeorological data at these time steps. The model allows also simulations of some variables of water quality; for instance, Ouellet-Proulx et al [30] used CEQUEAU to simulate the water temperature of two Canadian rivers.…”

A Near‐Term Iterative Forecasting System Successfully Predicts Reservoir Hydrodynamics and Partitions Uncertainty in Real Time

“…Real-time forecasts of water temperature with fully-specified uncertainties are particularly valuable for managers that oversee drinking water supply lakes and reservoirs, as waterbody temperatures can be very dynamic due to meteorological forcing, management, the evaluation of both forecast accuracy and the reliability of uncertainty estimation. Despite the importance of quantifying multiple uncertainty sources, few water resource forecasting studies quantify more than one or two sources of uncertainty and when they do, they typically only include initial conditions uncertainty (via data assimilation) and meteorological uncertainty (via ensemble weather forecasts) [e.g., Baracchini et al, 2020b;Komatsu et al, 2007;Ouellet-Proulx et al, 2017a;Ouellet-Proulx et al, 2017b;Page et al, 2018].…”

“…Fourth, FLARE propagates and partitions multiple sources of forecast uncertainty, which are updated over time, allowing for the evaluation of both forecast accuracy and the reliability of uncertainty estimation. Despite the importance of quantifying multiple uncertainty sources, few water resource forecasting studies quantify more than one or two sources of uncertainty and when they do, they typically only include initial conditions uncertainty (via data assimilation) and meteorological uncertainty (via ensemble weather forecasts) (e.g., Baracchini, Wuest, & Bouffard, 2020; Komatsu et al, 2007; Ouellet‐Proulx, Chimi Chiadjeu, et al, 2017; Ouellet‐Proulx, St‐Hilaire, & Boucher, 2017; Page et al, 2018). Furthermore, they rarely partition the relative contributions of the individual sources of uncertainty to the total forecast uncertainty (but see Ouellet‐Proulx, Chimi Chiadjeu, et al, 2017).…”