Quantifying and modelling urban stream temperature: a central US watershed study

Hydrologic models that rely on site specific linear and non‐linear regression water temperature (T_w) subroutines forced solely with observed air temperature (T_a) may not accurately estimate T_w in mixed‐use urbanizing watersheds where hydrogeological and land use complexity may confound common T_w regime assumptions. A nested‐scale experimental watershed study design was used to test T_w model predictions in a representative mixed‐use urbanizing watershed of the central USA. The linear regression T_w model used in the Soil and Water Assessment Tool (SWAT), a non‐linear regression T_w model, and a process‐based T_w model that accounts for watershed hydrology were evaluated. The non‐linear regression T_w model tested at a daily time step performed significantly (P < 0.01) better than the linear T_w model currently used in SWAT. Both regression T_w models overestimated T_w in lower temperature ranges (T_w < 10.0 °C) with percent bias (PBIAS) values ranging from ?28.2% (non‐linear T_w model) to ?66.1% (linear regression T_w model) and underestimated T_w in the higher temperature range (T_w > 25.0 °C) by 3.2%, and 7.2%, respectively. Conversely, the process‐based T_w model closely estimated T_w in lower temperature ranges (PBIAS = 4.5%) and only slightly underestimated T_w in the higher temperature range (PBIAS = 1.7%). Findings illustrate the benefit of integrating process‐based T_w models with hydrologic models to improve model transferability and T_w predictive confidence in urban mixed‐land use watersheds. The findings in this work are distinct geographically and in terms of mixed‐land use complexity and are therefore of immediate value to land‐use managers in similarly urbanizing watersheds globally. Copyright © 2015 John Wiley & Sons, Ltd.