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Mapping surface temperature in a hyper-saline lake and investigating the effect of temperature distribution on the lake evaporation

Sima, S ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1016/j.rse.2013.05.014
  3. Publisher: 2013
  4. Abstract:
  5. Remote sensing is an effective tool for capturing spatial and temporal variations of water surface temperature (WST) in large lakes. The WST of Urmia Lake in northwestern Iran was examined from 2007 to 2010, using MODIS land surface temperature (LST) products. Spatial and temporal (diurnal, monthly, seasonal and inter-annual) variations of Urmia Lake WST were also investigated. Results indicate that the MODIS-derived WSTs are in a good agreement with the in situ data (R2=0.92 and bias=-0.27). Spatial analysis of WST revealed that there are three thermal zones along the lake: the shallow region in barriers of the causeway, islands and the shoreline; the south part; and the deep north parts. Using validated MODIS-derived WST, the annual temperature cycles of Urmia Lake were extracted and quadratic curves were fitted to empirically display the monthly lake-averaged variations of the lake WST. Then the effect of including the spatial distribution of WST on the lake evaporation was assessed. According to the results of the energy balance method, a 147mm/year (515millionm3) discrepancy can be expected in the estimated evaporation rate when the spatial distribution in the lake WST is considered in the energy balance equation. Findings of this study confirm the application of MODIS LST products for surface temperature studies in a large hyper-saline lake. Moreover, use of the distributed satellite-derived WST in estimating evaporation from the lake was shown to improve the accuracy of water loss in the lake water budget calculation
  6. Keywords:
  7. Hyper-saline lakes ; MODIS ; Spatial variation ; Temporal variation ; Urmia Lake ; Water surface temperature ; Energy balance equations ; Energy balance method ; Land surface temperature ; Spatial and temporal variation ; Spatial variations ; Atmospheric temperature ; Bridges ; Energy balance ; Evaporation ; Phase transitions ; Radiometers ; Spatial distribution ; Surface properties ; Temperature distribution ; Lakes ; Accuracy assessment ; Lake water ; Land surface ; Mapping method ; Saline lake ; Satellite data ; Spatial analysis ; Surface temperature ; Temperature effect ; Water budget ; Water temperature ; Iran ; Lake Urmia
  8. Source: Remote Sensing of Environment ; Volume 136 , 2013 , Pages 374-385 ; 00344257 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S0034425713001685