Assessment of surface energy balance algorithm for land and operational simplified surface energy balance algorithm over freshwater and saline water bodies in Urmia Lake Basin

Abstract

To manage inland water resources, surveying the performance of remote sensing models for estimating the actual evaporation in arid regions is so important. Hence, this study aimed to assess the performance of two energy balance algorithms including surface energy balance algorithm for land (SEBAL) and operational simplified surface energy balance (SSEBop) in freshwater and saline water bodies. Another purpose of the present study was efficiency improvement in hypersaline lakes. In this regard, a practical salinity correction coefficient was used to overcome shortcomings of the selected models over saline Lake. The analysis of yearly lake water budget was used to assess the selected energy balance algorithms’ performance with a novel approach. These algorithms were investigated at Shahid Kazemi Dam Reservoir (as a freshwater body) and Urmia Lake (as a hypersaline water body) in Iran. The results showed that two selected algorithms estimated the evaporation rate at the selected freshwater body with a proper accuracy. The results showed the root mean square error for SEBAL result (RMSESEBAL) as 2.0 mm/day, correlation coefficient for SEBAL result (RSEBAL) as 0.80 mm/day, and RMSESSEBop and RSSEBop as 1.7 and 0.80 mm/day, respectively. However, these models overestimated evaporation over the hypersaline water body (RMSESEBAL =\u200988.4 mm/month, RSEBAL =\u20090.90 and RMSESSEBop =\u200939.9 mm/month, RSSEBop =\u20090.94). Salinity correction coefficient improved the results as RMSESEBAL =\u200919.8 mm/month, RSEBAL =\u20090.90 and RMSESSEBop =\u200913.4 mm/month, and RSSEBop =\u20090.94. In general, the algorithm performance was improved using the salinity correction coefficient in the chosen hypersaline water body.