Abstract
Abstract. 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/.
Highlights
Freshwater ecosystems have undergone more dramatic changes than any other type of ecosystem (Sectretariat of the Convention on Biological Diversity, 2010)
The first globally representative lake water quality dataset from remote sensing provided a snapshot of chlorophyll-a concentrations in 80 000 lakes worldwide based on Medium Resolution Imaging Spectrometer (MERIS) full-resolution (FR) data acquired in 2011 (Sayers et al, 2015)
For the Diversity II production the Maximum Peak Height algorithm (MPH; Matthews et al, 2012) was developed further and implemented in a Sentinel Application Platform (SNAP) operator (Block, 2016) because it outperformed other red-NIR reflectance peak algorithms in the algorithm intercomparison study (Matthews and Odermatt, 2015; Odermatt et al, 2015a). It uses bottom-of-Rayleigh reflectance (BRR) in MERIS bands 6–10 and 14 for the retrieval of the red-NIR reflectance peak height and position, which allow for the identification of cyanobacteria- and eukaryote-dominated pixels, water surface covering by cyanobacteria scum or floating vegetation, and chl-a quantification
Summary
Freshwater ecosystems have undergone more dramatic changes than any other type of ecosystem (Sectretariat of the Convention on Biological Diversity, 2010). Sensed products for water availability and quality are complementary to in situ data in terms of spatial and temporal coverage. They provide synoptic views of spatial distribution unachievable by other means and are ideally suited to covering the broad range of space scales and timescales associated with inland water applications. The first globally representative lake water quality dataset from remote sensing provided a snapshot of chlorophyll-a (chl-a) concentrations in 80 000 lakes worldwide based on MERIS full-resolution (FR) data acquired in 2011 (Sayers et al, 2015). Several case studies are available that demonstrate such assessments with lake-specific foci (Odermatt et al, 2015b), but the larger part of the dataset is yet to be exploited
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