Urbanski, JA, Grusza, G, Chlebus, N, Kryla, L (2008). A GIS-based WFD oriented typology of shallow micro-tidal soft bottom using wave exposure and turbidity mapping. ESTUARINE COASTAL AND SHELF SCIENCE, 78(1), 27-37.
Our GIS based project aims at producing a classification scheme to develop a typology of the bottom of the Bay of Gdansk in the southern Baltic. The typology was based on the abiotic factors which are used to define water body types by the European Water Framework Directive (WFD). Significance analysis of particular factors has shown that within the discussed area wave exposure seems to play the most important role. All other factors are to a greater or lesser degree correlated with these two. Taking into consideration the shallows and the varied coastline of the investigated area it was decided to make use of the SWAN numerical wave model to determine the influence of wave impact upon the bottom. The model was used to produce raster maps of orbital velocity near the bottom for each wind scenario. With the help of the GIS analysis the maps were turned into layers: the mean velocity and the maximum velocity at the bottom. To produce the layer of yearly amount of solar radiation a GIS model was built which main parameters were the layer of depth and three layers of turbidity for three seasons. The layers of the maximum orbital velocity and of the solar radiation at the bottom were then used in a classificatory procedure consisted in an iterative sequence of the three following steps: cluster formation, dendrogram analysis and classification using the maximum likelihood method. Ecological importance of the classification has been obtained by means of the aggregation of a part of classes based upon the statistics calculated for them within the GIS system with the help of the zonal function out of the following parameters: salinity, depth, mean and maximum orbital velocity at the bottom, temperature differences between warm and cold seasons, solar radiation, and type of sediments. The method proposed here makes it possible to produce high resolution thematic maps of the bottom even with incomplete data cover of the investigated area. (C) 2007 Elsevier Ltd. All rights reserved.