Modeling the water quality of rivers and assessing the effects of changing conditions is often hindered by a lack of in situ measurements for calibration. Here, we use a combination of satellite measurements, statistical models, and numerical modeling with CE-QUAL-W2 to overcome in situ data limitations and evaluate the effect of changing hydrologic and climate conditions on water temperature (Tw
) in the Tigris River, one of the largest rivers in the Middle East. Because few in situ estimates of Tw
were available, remotely-sensed estimates of Tw
were obtained from Landsat satellite images at roughly 2 week intervals for the year 2009 at the upstream model boundary (Mosul Dam) and two locations further downstream, Baeji and Baghdad. A regression was then developed between air temperature and Landsat Tw
in order to estimate daily Tw
. These daily Tw
were then used for the upstream model boundary condition and for model calibration downstream. Modeled Tw
at downstream locations agreed well with Landsat-based statistical estimates with an absolute mean error of <1 °C. A model sensitivity analysis suggested that altering upstream river discharge had little impact on downstream Tw.
By contrast, a climate change scenario in which air temperatures were increased by 2 °C resulted in a 0.9 °C and 1.5 °C increase in Tw
at Baeji and Baghdad, respectively. Since Tw
is a fundamental state variable in water quality models, our approach can be used to improve water quality models when in situ data are scarce.
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