A High-Resolution, Daily Hindcast (1990-2021) of Alaskan River Discharge and Temperature From Coupled and Optimized Physical Models

Water quality and freshwater ecosystems are affected by river discharge and temperature. Models are frequently used to estimate river temperature on large spatial and temporal scales due to limited observations of discharge and temperature. In this study, we use physically based river routing and temperature models to simulate daily discharge and river temperature for rivers in 138 basins in Alaska, including the entire Yukon River basin, from 1990-2021. The river temperature model was optimized for ice free months using a surrogate-based model optimization method, improving model performance at uncalibrated river gages. A common statistical model relating local air and water temperature was used as a benchmark. The physically based river temperature model exhibited superior performance compared to the benchmark statistical model after optimization, suggesting river temperature model optimization could become more routine. The river temperature model demonstrated high sensitivity to air temperature and model parameterization, and lower sensitivity to discharge. Validation of the models showed a Kling-Gupta Efficiency of 0.46 for daily river discharge and a root mean square error of 2.04 degrees C for daily river temperature, improving on the non-optimized physical model and the benchmark statistical model, which had root mean square errors of 3.24 and 2.97 degrees C, respectively. The simulation shows that rivers in northern Alaska have higher maximum summer temperatures and more variability than rivers in the Central and Southern regions. Furthermore, this framework can be readily adapted for use across models and regions. Accurate data on the volume and temperature of river water are essential for understanding how changing river conditions affect water quality and freshwater ecosystems. However, direct measurements of river parameters are often lacking, leading researchers to rely on models for estimation. In this study, we utilized advanced models and techniques to compute daily water volume and temperature in 138 basins across Alaska, including the entirety of the Yukon River basin, spanning from 1990 to 2021. Our findings indicated that rivers in northern Alaska exhibited higher maximum summer water temperatures and more significant temperature fluctuations compared to those in the central and southern regions. Our analysis highlighted that adjusting air temperature and the model's internal variables were crucial in minimizing errors in river temperature prediction. We improved the accuracy of the river temperature model by applying a technique to refine the model output based on the limited available river measurements. Comparing our enhanced model to a simpler statistical approach, we observed superior performance once the necessary adjustments were implemented. Our model system produced an accurate, high-resolution, daily hindcast of Alaskan river temperature and discharge from 1990 to 2021 We increased model performance by employing a new optimization of the River Basin Model and forcing it with a climate-land surface model A sensitivity analysis highlights important drivers of river temperatures in each region and the need for optimization