| Models of physical processes in fluvial systems are useful for improving understanding of hydrologic systems and for predicting future conditions. Process-based models of fluid flow and heat transport in fluvial systems can be used to quantify unknown spatial and temporal patterns of hydrologic fluxes, such as groundwater discharge, and to predict system response to future change. Recently, advances in field methods for heat tracing have introduced high resolution datasets to be used for model parameterization and calibration; Distributed Temperature Sensing (DTS) technology, for example, generates stream temperature data at high spatial (meter-scale) and temporal (minute-scale) resolution. Fully distributed stream heat budget models that take into account the various meteorological and hydrological energy inputs to a stream can be of great utility beyond simply predicting stream temperature, and a publicly available, user-friendly model would be a beneficial addition to currently existing heat budget tools.;In this study, a deterministic stream heat budget model called the HFLUX Stream Temperature Solver is developed and verified using temperature data from both DTS and point-in-space measurements for two streams. The one-dimensional (longitudinal), transient stream temperature model is programmed in MATLAB and solves the equations for heat and fluid transport using a finite difference method.;Following development and verification, applications of the HFLUX Stream Temperature Solver are explored. The effects of changing environmental variables, calibration to observed temperature data in order to quantify groundwater contributions, and a sensitivity analysis are all demonstrated using HFLUX. A comprehensive study of temperature dynamics within a stream using a heat budget offers insight into how changing climate variables, stream flow, and groundwater-surface water interactions impact in-stream temperatures. |
