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USING DISTRIBUTED TEMPERATURE SENSING FIBER-OPTICS AND HEAT SOURCE MODELING TO CHARACTERIZE A NORTHERN CALIFORNIA STREAM’S THERMAL REGIME
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Created: | Apr 01, 2018 at 4:51 p.m. | |
Last updated: | Apr 09, 2018 at 7:03 p.m. | |
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Abstract
This study employed Distributed Temperature Sensing (DTS) and Heat Source modeling to quantify the thermal regime of a one-kilometer section of the North Fork of the Salmon River, a tributary of the Klamath River, northern California, USA. The study collected eight days of temperature data using DTS at one-meter, 15-minute intervals during July 2012. The research aimed to: 1) investigate the geomorphic and thermal conditions of the study reach and their impact on native Salmonids. 2) identify and quantify groundwater seeps; and 3) employ and calibrate Heat Source to predict effects of riparian management, channel geometry, and climate change on stream temperature over the study reach. DTS observations revealed nearly uniform warming over the study reach, a diel heating cycle of 5 °C, a small groundwater spring (7 % of mainstem flow), and a Maximum Weekly Maximum Temperature (MWMT) of 23.00 °C. Statistical modeling of salmonid distribution field observations with AICc found that depth was the most explanatory parameter. Habitat inventory of the study reach indicated poor salmonid habitat quality with low habitat complexity with no large woody debris or instream cover. Heat Source model performance (Bias, RMSE, MARE, and NSE), compared to DTS iii observations, were all within the range of previous Heat Source applications. Heat Source modeling of reforestation of denuded legacy gravel bars from historic gold mining and areas of low vegetation in the study reach indicated that reforestation buffered daily maximum stream temperatures. Modeled channel restoration scenarios reduced the rate of heating (ºC /90 m) in the treatment area by a maximum of 34 %. Climate changescenarios were simulated with a uniform increase of air temperature by 2 °C, 4 °C, and 6 °C which warmed stream temperatures by 0.09 ºC / km per 2 ºC air temperature increase. Warming predicted by climate change was ameliorated with reforestation (0.11 ºC /km and 0.26 ºC per 2 ºC /km air temperature increase for partial and fully forested respectively).
Raw project data is available by contacting ctemps@unr.edu
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