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Developing an Effective Model for Predicting Spatially and Temporally Continuous Stream Temperatures from Remotely Sensed Land Surface Temperatures

1
South Fork Research, Inc., 44842 SE 145th St. North Bend, WA 98045, USA
2
Northwest Fisheries Science Center, NOAA Fisheries 2725 Montlake Blvd E., Seattle, WA 98112, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Y. Jun Xu
Water 2015, 7(12), 6827-6846; https://doi.org/10.3390/w7126660
Received: 8 October 2015 / Revised: 16 November 2015 / Accepted: 23 November 2015 / Published: 4 December 2015
Although water temperature is important to stream biota, it is difficult to collect in a spatially and temporally continuous fashion. We used remotely-sensed Land Surface Temperature (LST) data to estimate mean daily stream temperature for every confluence-to-confluence reach in the John Day River, OR, USA for a ten year period. Models were built at three spatial scales: site-specific, subwatershed, and basin-wide. Model quality was assessed using jackknife and cross-validation. Model metrics for linear regressions of the predicted vs. observed data across all sites and years: site-specific r2 = 0.95, Root Mean Squared Error (RMSE) = 1.25 °C; subwatershed r2 = 0.88, RMSE = 2.02 °C; and basin-wide r2 = 0.87, RMSE = 2.12 °C. Similar analyses were conducted using 2012 eight-day composite LST and eight-day mean stream temperature in five watersheds in the interior Columbia River basin. Mean model metrics across all basins: r2 = 0.91, RMSE = 1.29 °C. Sensitivity analyses indicated accurate basin-wide models can be parameterized using data from as few as four temperature logger sites. This approach generates robust estimates of stream temperature through time for broad spatial regions for which there is only spatially and temporally patchy observational data, and may be useful for managers and researchers interested in stream biota. View Full-Text
Keywords: land surface temperature; MODIS; stream temperature models land surface temperature; MODIS; stream temperature models
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MDPI and ACS Style

McNyset, K.M.; Volk, C.J.; Jordan, C.E. Developing an Effective Model for Predicting Spatially and Temporally Continuous Stream Temperatures from Remotely Sensed Land Surface Temperatures. Water 2015, 7, 6827-6846. https://doi.org/10.3390/w7126660

AMA Style

McNyset KM, Volk CJ, Jordan CE. Developing an Effective Model for Predicting Spatially and Temporally Continuous Stream Temperatures from Remotely Sensed Land Surface Temperatures. Water. 2015; 7(12):6827-6846. https://doi.org/10.3390/w7126660

Chicago/Turabian Style

McNyset, Kristina M., Carol J. Volk, and Chris E. Jordan 2015. "Developing an Effective Model for Predicting Spatially and Temporally Continuous Stream Temperatures from Remotely Sensed Land Surface Temperatures" Water 7, no. 12: 6827-6846. https://doi.org/10.3390/w7126660

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