Authors: Daniel Philippus, Katie Schneider, Ashley Rust, Anneliese Sytsma, and Terri S. Hogue – Colorado School of Mines
Title: Near-Term, Seasonal, and Long-Term River Temperature Forecasting with the National Water Model
Abstract: River management operations, such as dam release management to support fish populations, would benefit from forecasting daily or weekly stream temperatures several days in advance. However, such forecasts are not readily available at the scale of the contiguous United States. As part of the river temperature model for NWM NextGen, this study aims to develop near-term (weather forecast-based), seasonal, and long-term (climate model-based) river temperature forecasting models for rivers of any size. The models will be trained on a large, remote sensing-based historical river temperature dataset and NOAA historical reforecast archives, to account for weather forecast uncertainty, as well as observed weather data. Especially as the uncertainty is expected to be large, the models will output probability distributions rather than only expected temperatures. We will present preliminary results and seek feedback on ongoing model development as well as outputs and capabilities of interest to potential users.