This research was funded partially by Stefan A. Talke. Funding for Stefan A. Talke was provided by the US National Science Foundation (Career Award 1455350).
Water temperature -- Tigris River -- Measurement, Water temperature -- Mathematical models, Remote sensing, Hydrologic models
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 w. 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.
Al-Murib, M. D., Wells, S. A., & Talke, S. A. (2019). Integrating Landsat TM/ETM+ and Numerical Modeling to Estimate Water Temperature in the Tigris River under Future Climate and Management Scenarios. Water, 11(5), 892.