A Reduced Parameter Stream Temperature Model (RPSTM) for basin-wide simulations

Water temperature is a crucial variable that shapes biological communities and controls rates of ecosystem processes in rivers. Fully parameterized heat balance models have been used to provide accurate estimates, but high parameterization costs make them difficult to apply at basin-wide scales. As parts of a collaborative modeling project to address future impacts of climate and land-use management on the Muskegon River, we developed a Reduced Parameter Stream Temperature Model (RPSTM), a mechanistic, spatially explicit but easier to parameterize model. Here we describe and test RPSTM's applicability by conducting a series of daily water temperature simulations (1985-2005). RPSTM performed well along the river network. The predictions were most sensitive to air temperature, depth, and solar radiation, but relatively insensitive to rates of surface runoff. This modeling approach is easily integrated into complex multi-modeling systems to evaluate effects of long-term changes in watershed hydrology, climate, and land management across river networks. A new physically-based heat balance model with reduced parameterization processes.Theoretical derivation and an application to a large river system are shown explicitly.Accuracy of RPSTM is reasonably good (MABSE around 1ź°C).RPSTM is most sensitive to air temperature, hydraulic depth, and solar radiation.Integrated with appropriate hydrologic models, the reduced parameter approach is useful for dynamic basin-wide simulations of temperature.