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Optimizing a high-resolution river temperature model for Alaskan Rivers

River temperature is a critical variable that influences the physical, chemical, and biological functions of ecosystems. Climate change is predicted to increase river temperatures worldwide, adding additional stress to these water bodies and the people who depend on them. However, river temperature and discharge observations are spatially and temporally sparse in Alaska, which makes it difficult to understand the impacts of changing river temperature. In this study, we develop a high-resolution river temperature and discharge dataset for rivers in Alaska and the Canadian Yukon River Basin from 1990 to 2021 coupling the physically based river routing (mizuRoute) and river temperature models (River Basin Model) with the 4 km resolution Regional Arctic System Model. We optimize RBM using an adaptive surrogate-based model on eleven sensitive parameters across nine river temperature gages within our study domain. RBM was validated on 18 gages, of which nine were out-of-sample. The mean root-mean-square error of daily temperature decreased in a four-year evaluation, indicating the effectiveness of our optimization. Our model will produce a high-resolution river temperature dataset, which improves the data availability for Alaska that can help inform management and conservation efforts in the region.

Civil, Environmental, and Architectural Engineering Graduate Student, 精品SM在线影片