Quantifying the Effect of Xiluodu Reservoir on the Temperature of the Surrounding Mountains. (2nd May 2020)

• Record Type: Journal Article
• Authors: Wang, D.C.; Liu, J.Y.; Huang, Y.; Duan, X.W.; Wang, X.; Zhang, X.; Sun, Z.C.; Chen, J.H.; Zhang, W.
• Is Part Of: GeoHealth. Volume 4:Number 5(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-05-02
• Subjects: effect threshold -- factor analysis -- partial correlation analysis -- temperature differences -- Xiluodu Reservoir; Environmental health -- Periodicals; Electronic journals; Periodicals; 616.98
• DOI: 10.1029/2019GH000242
• Languages: English
• ISSNs: 2471-1403

Abstract

Abstract: To quantitatively determine the effect of Xiluodu Reservoir on the temperature of the surrounding mountains, the temperature differences between various locations and the reservoir were calculated based on Landsat 8 thermal infrared sensor (TIRS) data. Elevation, slope, aspect, normalized difference vegetation index (NDVI), and visual field were selected as the impact factors, and the most significant grid size used to explore the effect of reservoir on the surrounding mountains was determined by spatial analysis and partial correlation analysis. The effect of the Xiluodu Reservoir on the surrounding mountains' temperature was then quantitatively studied while accounting for the effect of water surface width on temperature. The results are summarized as follows. The most significant grid size for determining the influence of Xiluodu Reservoir on the surrounding mountains' temperature is 90 m. The effect range threshold of the entire reservoir on the temperature of the surrounding mountains is approximately 600 m, and the partial correlation coefficient in each buffer area decreases gradually with increasing distance from the reservoir. The effect threshold of the reservoir on the temperature of the surrounding mountains is approximately 1, 500 m in the head area with a water surface width approximately 1, 000 m, but it is negligible in the tributary area where the width is approximately 60 m. Key Points: Elevation, slope, aspect, normalized difference vegetation index (NDVI), and visual field were selected as the impact factors To overcome the scale‐dependence of LST, the most significant grid size was determined by spatial analysis and partial correlation analysis Study the effect of reservoir on the surrounding mountains' temperature while accounting for the effect of water surface width