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The deduction by conventional means of qualitative and quantitative information about groundwaterdischarge into lakes is complicated. Nevertheless, atleast for semi-arid regions with limited surface water availability, thisinformation is crucial to ensure future water availability for drinking andirrigation purposes.  Overcoming this lack of discharge information, we present a satellite-basedmulti-temporal sea-surface-temperature (SST) approach. It exploits theoccurrence of thermal anomalies to outline groundwater discharge locationsusing the example of the Dead Sea. Based on a set of 19 Landsat Enhanced Thematic Mapper (ETM+) images6.2 (high gain), recorded between 2000 and 2002, we developed a novelapproach which includes (i) an objective exclusion of surface-runoff-influenced data which would otherwise lead to erroneous results and (ii) atemporal SST variability analysis based on six statistical measuresamplifying thermal anomalies caused by groundwater.  After excluding data influenced by surface runoff, we concluded that spatialanomaly patterns of the standard deviation and range of the SST data seriesspatially fit best to in situ observed discharge locations and, hence, aremost suitable for detecting groundwater discharge sites

How to identify groundwater-caused thermal anomalies in lakes based on multi-temporal satellite data in semi-arid regions