Implication of evaporative loss estimation methods in discharge and water temperature modelling in cool temperate climates

Abstract

Evaporative flux is a key component of hydrological budgets. Water loss through evapotranspiration reduces volumes available for run‐off. The transition from liquid to water vapour on open water surfaces requires heat. Consequently, evaporation act as a cooling mechanism during summer. Both river discharge and water temperature simulations are thus influenced by the methods used to model evaporation. In this paper, the impact of evapotranspiration estimation methods on simulated discharge is assessed using a semidistributed model on two Canadian watersheds. The impact of evaporation estimation methods on water temperature simulations is also evaluated. Finally, the validity of using the same formulation to simulate both of these processes is verified. Five well‐known evapotranspiration models and five evaporation models with different wind functions were tested. Results show a large disparity (18–22% of mean annual total evapotranspiration) among the evapotranspiration methods, leading to important differences in simulated discharge (3–25% of observed discharge). Larger differences result from evaporation estimation methods with mean annual divergences of 34–48%. This translates into a difference in mean summer water temperature of 1–15%. Results also show that the choice of model parameter has less influence than the choice of evapotranspiration method in discharge simulations. However, the parameter values influence thermal simulations in the same order of magnitude as the choice of evaporation estimation method. Overall, the results of this study suggest that evapotranspiration and open water evaporation should be represented separately in a hydrological modelling framework, especially when water temperature simulations are required.

Combining Landsat TIR‐imagery data and ERA5 reanalysis information with different calibration strategies to improve simulations of streamflow and river temperature in the Canadian Subarctic

“…This is the traditional approach used by researchers and modellers, and consists of calibrating the CEQUEAU temperature module by using each of the individual selected CP sites separately. We used the Root Mean Square Error (RMSE) as the objective function, as the strong seasonality of river temperature inhibits the use of other metrics (e.g., NSE and KGE) commonly used for assessing the performance of discharge (rather than temperature) simulations (Ouellet‐Proulx et al, 2019). The RMSE for a given CP is estimated using the Equation (). $$$$ RMSE=\sqrt{\frac{1}{n}\sum \limits_{i=1}^n{\left({\hat{y}}_t-{y}_t\right)}^2}, $$$$ where $$$ {\hat{y}}_t $$$ and $$$ {y}_t $$$ are the simulated and observed values at each time step, respectively.…”

Predicting Latent and Sensible Heat Fluxes in Stream Temperature Models: Current Challenges and Potential Solutions

“…To our knowledge, no studies have compared the PCE with stream evaporation measured by in‐stream pans or an energy‐balance approach. However, the PCE or a variation thereof has been found to predict higher daily evaporation rates than empirical wind functions (Benyahya et al., 2010; Ouellet‐Proulx et al., 2019). Glose et al.…”

“…To our knowledge, no studies have compared the PCE with stream evaporation measured by in-stream pans or an energy-balance approach. However, the PCE or a variation thereof has been found to predict higher daily evaporation rates than empirical wind functions (Benyahya et al, 2010;Ouellet-Proulx et al, 2019). Glose et al (2017) found that the PCE predicted condensation during winter due to negative net radiation, which is physically unrealistic given that humidity gradients typically drive stream evaporation during winter even when net radiation can be chronically negative (e.g., Dugdale et al, 2018;Leach & Moore, 2010;Webb & Zhang, 1997).…”

“…Considering this potential for the latent heat flux to moderate daily maximum stream temperature, it is critical that it be accurately represented in stream temperature models, especially for evaluating thermal mitigation activities (Trimmel et al., 2018; Wondzell et al., 2019). The two most common approaches are mass transfer equations, dominantly in the form of Dalton‐style wind functions (e.g., Dugdale et al., 2018; Garner et al., 2014; King & Neilson, 2019; Leach & Moore, 2011; Webb & Zhang, 1997) and the Penman combination equation (PCE) (Kaandorp et al., 2019; Ouellet et al., 2014; Ouellet‐Proulx et al., 2019; Trimmel et al., 2018; Westhoff et al., 2007, 2010). The sensible heat flux is commonly calculated either by multiplying the latent heat flux by the Bowen ratio (e.g., Garner et al., 2014; Khamis et al., 2015; Leach & Moore, 2010; Webb & Zhang, 1997) or by using a bulk aerodynamic equation (e.g., Glose et al., 2017).…”

Future flow and water temperature scenarios in an impounded drainage basin: implications for summer flow and temperature management downstream of the dam

“…Ouellet-Proulx et al (2017a) studied ensemble water temperature forecasting using water temperature and flow assimilation. The model's source code for the evaporative heat loss module is improved (Ouellet-Proulx et al, 2019). However, deterministic modeling using CEQUEAU is still needed to assess the combined impact of flow regime change and climate change on the Nechako.…”