Application of remote sensing for the optimization of in-situ sampling for monitoring of phytoplankton abundance in a large lake.

Directives and legislations worldwide aim at representatively and continuously monitoring the ecological status of surface waters. In many countries, chlorophyll-a concentrations (CHL) are used as an indicator of phytoplankton abundance and the trophic level of lakes or reservoirs. In-situ measurements of water quality parameters, however, are time-consuming, costly and of unknown but naturally limited spatial representativeness. In addition, the variety of the involved lab and field measurement methods and instruments complicates comparability and reproducibility. Taking Lake Geneva as an example, 1234 satellite images from the MERIS sensor on the Envisat satellite from 2002 to 2012 are used to quantify the spatial and temporal variations of CHL concentrations. Based on histograms of spring, summer and autumn CHL estimates, the spatial representativeness of two existing in-situ measurement locations is analysed. Appropriate sampling frequencies to capture CHL peaks are examined by means of statistical resampling. The approaches proposed allow determining optimal in-situ sampling locations and frequencies. Their generic nature allows for adaptation to other lakes, especially to establish new survey programmes where no previous records are available.