Reconstruction of the Hydro‐Thermal Behavior of Regulated River Networks of the Columbia River Basin Using Satellite Remote Sensing and Data‐Driven Techniques

Abstract

Abstract 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.

Keywords

• thermal infrared
• satellite remote sensing
• Landsat
• river temperature
• reservoirs