Journal
WATER
Volume 7, Issue 12, Pages 6827-6846Publisher
MDPI
DOI: 10.3390/w7126660
Keywords
land surface temperature; MODIS; stream temperature models
Categories
Funding
- Bonneville Power Administration projects [2003-017, 2011-006]
- American Reinvestment and Recovery Act
- USDA Forest Service, Pacific Northwest Research Station
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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 r(2) = 0.95, Root Mean Squared Error (RMSE) = 1.25 degrees C; subwatershed r(2) = 0.88, RMSE = 2.02 degrees C; and basin-wide r(2) = 0.87, RMSE = 2.12 degrees 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: r(2) = 0.91, RMSE = 1.29 degrees 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.
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