The use of ground sampled water quality information for global studies is
limited due to practical and financial constraints. Remote sensing is a
valuable means to overcome such limitations and to provide synoptic views of
ambient water quality at appropriate spatio-temporal scales. In past years
several large data processing efforts were initiated to provide corresponding
data sources. The Diversity II water quality dataset consists of several
monthly, yearly and 9-year averaged water quality parameters for 340 lakes
worldwide and is based on data from the full ENVISAT MERIS operation period
(2002–2012). Existing retrieval methods and datasets were selected after an
extensive algorithm intercomparison exercise. Chlorophyll-a, total
suspended matter, turbidity, coloured dissolved organic matter, lake surface
water temperature, cyanobacteria and floating vegetation maps, as well as
several auxiliary data layers, provide a generically specified database that
can be used for assessing a variety of locally relevant ecosystem properties
and environmental problems. For validation and accuracy assessment, we
provide matchup comparisons for 24 lakes and a group of reservoirs
representing a wide range of bio-optical conditions. Matchup comparisons for
chlorophyll-a concentrations indicate mean absolute errors and bias in the
order of median concentrations for individual lakes, while total suspended
matter and turbidity retrieval achieve significantly better performance
metrics across several lake-specific datasets. We demonstrate the use of the
products by illustrating and discussing remotely sensed evidence of
lake-specific processes and prominent regime shifts documented in the
literature. The Diversity II data are available from
https://doi.pangaea.de/10.1594/PANGAEA.871462, and Python scripts for
their analysis and visualization are provided at
https://github.com/odermatt/diversity/.</p