4.7 Article

Water temperature controls in low arctic rivers

期刊

WATER RESOURCES RESEARCH
卷 52, 期 6, 页码 4358-4376

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1002/2015WR017965

关键词

river temperature; heat fluxes; mechanistic modeling; Arctic hydrology; energy budget; lateral inflows

资金

  1. National Science Foundation Office of Polar Programs [NFS-ARC 1204220, NSF-ARC 1204216]
  2. Utah Water Research Laboratory
  3. University of Alaska Fairbanks Water and Environment Research Center
  4. Arctic Long Term Ecological Research grant [NSF-DEB 1026843]
  5. Office of Polar Programs (OPP)
  6. Directorate For Geosciences [1204220] Funding Source: National Science Foundation

向作者/读者索取更多资源

Understanding the dynamics of heat transfer mechanisms is critical for forecasting the effects of climate change on arctic river temperatures. Climate influences on arctic river temperatures can be particularly important due to corresponding effects on nutrient dynamics and ecological responses. It was hypothesized that the same heat and mass fluxes affect arctic and temperate rivers, but that relative importance and variability over time and space differ. Through data collection and application of a river temperature model that accounts for the primary heat fluxes relevant in temperate climates, heat fluxes were estimated for a large arctic basin over wide ranges of hydrologic conditions. Heat flux influences similar to temperate systems included dominant shortwave radiation, shifts from positive to negative sensible heat flux with distance downstream, and greater influences of lateral inflows in the headwater region. Heat fluxes that differed from many temperate systems included consistently negative net longwave radiation and small average latent heat fluxes. Radiative heat fluxes comprised 88% of total absolute heat flux while all other heat fluxes contributed less than 5% on average. Periodic significance was seen for lateral inflows (up to 26%) and latent heat flux (up to 18%) in the lower and higher stream order portions of the watershed, respectively. Evenly distributed lateral inflows from large scale flow differencing and temperatures from representative tributaries provided a data efficient method for estimating the associated heat loads. Poor model performance under low flows demonstrated need for further testing and data collection to support the inclusion of additional heat fluxes.

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