Citation:

essd-10-1527-2018

Always quote citation above when using data! You can download the citation in several formats below.

RIS Citation BibTeX Citation Text Citation Facebook Twitter

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.

Further details:

Phyton scripts for analysis and visualization

Brito, J; Campos, J; Gangkofner, U; Odermatt, Daniel; Philipson, Petra; Brockmann, C (2015): Products Quality Report v4 (ESA DUE Project Diversity II). European Space Agency (esa), (pdf 11 MB), 140 pp, http://www.diversity2.info/products/documents/DEL7/DIV2_Products_Quality_Report_v4.pdf

Lehner, Bernhard; Döll, Petra (2004): Global Lakes and Wetlands Database GLWD (documentation). Center for Environmental Systems Research, University of Kassel; World Wildlife Fund US, Washington, (pdf 471 kB), 7 pp, GLWD_Data_Documentation.pdf

Odermatt, Daniel; Brito, J; Philipson, Petra; Hahn, N; Brockmann, C (2015): Products User Handbook Inland Waters v2.1 (ESA DUE Project Diversity II). European Space Agency (esa), (pdf 4.7 MB), 40 pp, DIV2_Products_User_Handbook_Inlandwaters_v2_1.pdf

Odermatt, Daniel; Gangkofner, U; Ratzmann, G; Ruescas, A B; Stelzer, K; Philipson, Petra; Brockmann, C (2015): Algorithm Theoretic Baseline Document v2.4 (ESA DUE Project Diversity II). European Space Agency (esa), (pdf 19 MB), 156 pp, http://www.diversity2.info/products/documents/DEL5/DIV2_Algorithm_Theoretical_Basis_Document_v2.4.pdf

Coverage:

Median Latitude: 33.211711 * Median Longitude: -8.201091 * South-bound Latitude: -54.560000 * West-bound Longitude: -160.690000 * North-bound Latitude: 81.790000 * East-bound Longitude: 175.890000

Comment:

Over ten years, the European Space Agency operated the largest Earth observation satellite built to date, ENVISAT. Its instruments provided optical and thermal observations, and allowed for retrieval accuracies not previously achieved by spaceborne remote sensing. Using these observations, we created a comprehensive database consisting of water quality parameters for more than 300 lakes in the whole World. The Diversity II inland water database is designed to meet the requirements of the aquatic biodiversity community, but represents beyond this purpose the first globally consistent and reproducible knowledge basis of its kind.

We processed various water quality parameters and adopted lake surface water temperature from the ESA ARC Lake database. Monthly, yearly and a 9-year aggregated geophysical maps are provided. The potential of these products is demonstrated in the context of several case studies, wherein local experts assess the information content against the background of issues such as eutrophication and hypoxia, floating vegetation proliferation and the occurrence of cyanobacteria blooms. Qualitative links are established between those phenomena and biodiversity trends.

File format is geotif. Minimal granularity is one geotif per month in zip archives per year. All 11 zip archives (2002-2012) of one lake are combined with the lake's annual and 9-year averaged zip archives in one *.7z archive. The table lists metadata and basic data of the 343 lakes with links to the *.7z archives. File size is between 100 kB and 20 GB.

Legend for GLWD Use1, 2 and 3: c flood control, f fish breeding, h hydropower, i irrigation, n navigation, r recreation, s water supply, x others

Parameter(s):

#	Name	Short Name	Unit	Comment
1	ORDINAL NUMBER	Ord No		Geocode
2	Identification	ID		DIV2
3	Name	Name		DIV2
4	Name	Name		alternate
5	Name	Name		Arclakes
6	Name	Name		Hydroweb
7	Name	Name		Worldlakes
8	Name	Name		Google
9	Country	Country		1
10	Country	Country		2
11	Country	Country		3
12	Country	Country		4
13	Ratio	Ratio		490 threshold; Odermatt et al (2015) ATBD document
14	Area	Area	km²	SAR-WB polygon
15	LATITUDE	Latitude		Geocode – SAR-WB controled
16	LONGITUDE	Longitude		Geocode – SAR-WB controled
17	Type	Type		GLWD 1
18	Type	Type		GLWD 2
19	Area	Area	km²	GLWD
20	ELEVATION	Elevation	m a.s.l.	Geocode – GLWD
21	Area	Area	km²	GLWD catchment
22	Flow rate	Q	m³/s	GLWD inflow
23	Volume	Vol	km³	GLWD
24	Use	Use		GLWD 1
25	Use	Use		GLWD 2
26	Use	Use		GLWD 3
27	Uniform resource locator/link to reference	URL ref		description of lake in Wikipedia
28	File name	File name		of zip-archive
29	File size	File size	kByte
30	Uniform resource locator/link to file	URL file		to zip-archive

License:

Creative Commons Attribution 3.0 Unported (CC-BY-3.0)

Size:

5515 data points

Download Data

Download dataset as tab-delimited text — use the following character encoding:

View dataset as HTML (shows only first 2000 rows)