Search

The use of satellite‐based thermal infrared remote sensing has facilitated the assessment of surface water temperature on a large scale. However, the inherent limitations of this remote sensing technique make it difficult to assess rivers unless ambient conditions are cloud‐free, devoid of steep terrain and the rivers are at least 60 m wide. To address these challenges that limit the spatiotemporal continuity of satellite‐based hydro‐thermal data, we harnessed the extensive coverage from the Landsat missions' thermal infrared sensors and data‐driven techniques to estimate surface water temperature of rivers. Out of the tested data‐driven techniques, we selected the Random Forest Regressor as our prime non‐linear approach for estimation of surface water temperature in rivers. Using the selected technique, proposed as THORR (Thermal History of Regulated Rivers), we successfully reconstructed a multi‐decadal, continuous spatiotemporal surface water temperature record for regulated rivers in the Columbia River Basin. Using 42 years of data, the surface water temperature could be predicted on average with 0.71° C of absolute error regardless of the dam's potential thermal influence in the downstream reaches. The reconstructed hydro‐thermal behavior generated from THORR revealed a long‐term downstream warming trend along the Columbia River. The open‐source THORR tool can be extended to any river system around the world that is not gauged with in‐situ temperature measurements for the reconstruction of hydro‐thermal behavior. Plain Language Summary: Surface water temperature of rivers, which is an important ecological parameter for more robust water management, can be estimated in a cost‐effective and globally scalable way from satellite thermal infrared (TIR) remote sensing. However, such a technique is limited to rivers of sufficient width and cloud‐free conditions. In this study, data‐driven techniques were explored to overcome this limitation and reconstruct surface water temperature of rivers in the continuum of space and time. By using a comprehensive record spanning 42 years of satellite remote sensing, we demonstrate that it is possible to recreate robust estimates of long spatiotemporal trends of river temperature to understand how surface waters are being altered thermally due to water management and climate change. Key Points: Thermal Infrared remote sensing from Landsat was used to estimate the surface water temperature of the highly regulated Columbia River BasinUsing 42 years of data, the surface water temperature could be predicted on average with 0.7°C of absolute error regardless of the dam's potential thermal influenceThe reconstructed hydro‐thermal behavior indicated a long‐term downstream warming trend along the Columbia River [ABSTRACT FROM AUTHOR]