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Environmental GIS Database for the White Sea Proceedings of the Open source GIS - GRASS users conference 2002 - Trento, Italy, 11-13 September 2002 Environmental GIS database for the White Sea Seppo Kaitala*, Anatoly Shavykin**, Vladimir A. Volkov*** * Finnish Institute of Marine Research, PO Box 33, FIN-00931 Helsinki, Finland , tel. ++ 358-9-61394417, fax ++ 358-9-6139 4494, e-mail [email protected] ** Murmansk Marine Biological Institute, Vladimirskaya 17,183010 Murmansk, Russia, tel. ++ 7 8152 56- 52-35 fax ++ (Norwegian line) 47-789-10-288 e-mail [email protected] *** Nansen International Environmental and Remote Sensing Centre, B.Monetnaya Str. 26/28,197101 St.Petersburg, Russia tel. ++ 7 8122343865 fax ++ 7 8122343865 e-mail [email protected] 1 Introduction The European Commission INCO Copernicus project was promoted in autumn 2000 as "Sustainable management of the marine ecosystem and living resources of the White Sea". One of the scientific and technical objectives is to create dedicated environmental, ecological and socio-economic databases integrated in a Geographical Information System (GIS) for the White Sea region. To ensure the access to the database development also in the future, the open source gis approach as GRASS5.0 was chosen [1]. Into the White Sea GRASS-GIS database the bathymetry data with resolution 1 by 0.5 minutes was used to model the bottom surface of the White Sea. Russian coordinate system of Pulkova 42 was used. DCW vector data were used for the shoreline and the White Sea was divided to 7 traditional geographic areas. Raster layer of the bathymetry was divided with vector polygons to appropriate geographic areas and the area and volume were calculated. The hydrological and chemical parameters as water temperature, salinity, inorganic nutrients were included for the years 1985 1986, 1989. Data was collected mainly once in a month during the ice free periods. The change of the ratio of inorganic nutrients is used to evaluate the regulating factors of phytoplankton succession during the growth season. The database is used to validate numerical ecosystem modeling applications in purpose to evaluate possible effects of the climate change and growing human impact on the ecosystem. 2 Methodology The White Sea is located in the North-West of Russia with the geographical extend from about lattitude 64o N to 67o N and from longitude 320 E to 440 E. Murmansk Marine Biological Institute had sampled hydrographical and hydrochemical data for the years 1984, 1985, 1986, and 1989 and 1990. The database was recorded as location in degrees and for the depths 0, 10, 20, 50 100 m and for the near bottom layers. About 700 stations were recorded. The original data was in MS-excel formats. The data was prepared to suitable format to import to GRASS-GIS base with OpenOffice1.0, Emacs and AWK programms under Linux RedHat 7.3 and GRASS 5.0 pre3 software. For graphics, GIMP image software was used. The coastline boundary was created form the Digital Chart of the World (DCW) on cd- rom with DCWmanager3.1 in longitude and lattitude degrees and in DXF format. The data was fist imported to longitude lattitude location in GRASS database and the reprojected to Pulkova 42 coordite system. To the vector polygons the area lines were digitized and the appropriate polygons were used define the areas in square kilometers 2 Environmental GIS database for the White Sea and also to cut the the raster layers for the volume calculations. The geographic regions were determined according to Nadezhin [2]. The bathymetry for the White Sea was derived from a digital grid compiled by TRANSAS 2001 for NIERSC. The grid has a resolution of two minutes in the east-west direction and one minute in the north-south direction. For the comparison IBCAO data with 2.5 km grid size was used [3]. Coordinate Pulkova 42 system: Ellipsoid: Krassovski 1940 Projection: Gauss-Kruger, (transverse mercator, zone 37) Table 1. Geographic coordinate system parameters for the White Sea GIS database The bathymetry data with longitude, lattitude and depth records as well as hydrographical data with 24 colums were imported as ascii files into a longitude/lattitude location in the GIS database with the command s.in.ascii in in 3 dimensional format and the site data was projected to Pulkova42 location with the s.proj command. The raster surfaces were build up with s.surf.idw command with 250 m resolution. The volumes for different areas were determined with the r.volume command with the appropriate mask for the area and changing the depth values to positive ones, as r.volume can not handle negative volumes. 3 Results The White Sea is situated in the Northern West of Russia with the outlet to the Barents Sea. The northern boundary of the White Sea is determined by the line connecting the capes Svyatoy Nos on Kola Peninsula and Kanin Nos as the most northern point on the Kanin Peninsula (area 7). Figure 1: Elevation model derived from IBCAO data in Pulkova42 grid and geographic areas. Seppo Kaitala, Anatoly Shavykin, Vladimir A. Volkov 3 No Area Square kilometers Volume cubic km 1 Kandalaksha Bay 5016 567.59 2 Basin 24700 2775.01 3 Onega Bay 13202 215.17 4 Dvina Bay 7995 324.78 5 Gorlo 9030 323.17 6 Mezen Bay 6630 63.26 7 Voronka 24300 845.97 Table 1. The areas and volumes for the White Sea sub-basins. IBCAO data NIERSC data Depth m Depth m Figure 2. Bathymetry models derived from IBCAO and NIERSC data and the depth histogram. NIERSC bathymetry model showed more details and the depth histogram distribution was more realistic than the those of IBCAO bathymetry model. For further calculations of areas and volumes only NIERSC bathymetry model was used. From the bathymetry model shows how shallow the Mesen Bay is (average about 10 m), while the Kandalksa 4 Environmental GIS database for the White Sea Bay has the direct connection to the deeper parts of the Basin. The Gorlo Strait is also relatively shallow ( about 50 m) determining the water exchange with the Barents Sea. 1986 Surface 1986 bottom 1989 Surface 1989 bottom May June July August October Novembe r -2 0 5 10 15 22 Co Figure 3. Temperature distributions in the surface layer and in the near bottom layer. Seppo Kaitala, Anatoly Shavykin, Vladimir A. Volkov 5 The database includes data on temperature, salinity, concentration and saturation for oxygen, pH, alkalinity and inorganic nutrients as phosphate, silicate, nitrite, nitrate and ammonia. For the display the temperature on the surface and in the near bottom layer and silicate in the surface layer are demonstrated for the years 1986 and 1989. 1986 1989 May June July 0 5 10 15 20 25 Figure 4a. Silicate( µM) concentrations in the surface layer(0 m). The distribution of the data parameters were determine only for areas with data recording with appropriate masks for the regions. Temperature distributions show clear 6 Environmental GIS database for the White Sea stratification in June, July and August but especially on October the distribution patterns look similar for surface and near bottom layers indicating also vertical mixing in the autumn. In May silicate concentrations are already under 5 µM in Kandalaksha Bay, Voronka and Basin areas indicating early spring blooms of diatom algae. Only near the Northern Dvina outlet to the Dvina Bay shows higher values due to the freshwater run-off with high concentrations of silicate. In October 1986 the silicate concentrations were regenerated because of vertical mixing and in the absence of diatom algae. 1986 1989 August October 0 5 10 15 20 25 Figure 4b. Silicate( µM) concentrations in the surface layer(0 m). 4 Discussion IBCAO data consists 2.5 km grid size and NIERSC consisted from approximately 1.85 km grid size. From the histograms is obvious that also data collection methods have been different as NIERSC data seems to be recorder by direct measurements and IBCAO data derived from different sources. The maximal depth record in NIER data is -331.4 m. Babkov and Golikov [4] reported for the maximal depth as -343 m in the central part of the Basin. Also their area and volume values are similar to our values and the the Seppo Kaitala, Anatoly Shavykin, Vladimir A. Volkov 7 differences seems to be derivate d from the sightly different definitions of Gorlo and Mezen Bay areas. In the Basin the water remains cold in the near bottom layer even during the summer indicating stabile water layer without intensive mixing.. Arzhanova [5] recorded silicate distribution patterns quite similar for the in June-July 1991 as our data shows for August 1986. Silicate is usually not considered to be as important regulating nutrient for phytoplankton as inorganic compounds of nitrogen and phosphorus. However Egge and Aksnes [6] demonstrated, that diatom algae dominance occurred irrespective of th season if silicate concentrations exceeded a threshold of approximately 2 µM. If the diatom dominance change to flagellate dominance such as Phaecystis sp. and They can form nuisance blooms such as had occurred in along the Norwegian coast [7] Acknowledgments: The work is a contribution to the European Commission INCO Copernicus project: Sustainable management of the marine ecosystem and living resources of the White Sea; CONTRACT No: ICA2-CT-2000-10014 References [1] Neteller M., Mitasova H. Open source GIS: a grass GIS approach. Kluwer Academic Publishers. Boston 2002. [2] NadezhinV.M. Characteristics of hydrobiology of the White Sea. Pages 237-248, Works of PINRO: vol 17, 1966. [3] Jakobsson M., Norman Cherkis N. International Chart of the Arctic Ocean (IBCAO), Version 1.0, 2001. [4] Babkov A.I., Golikov A.N.
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