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Geographic Information Systems (GIS) as Supporting Tools in the Monitoring and Water Management of Lakes in Poland: A Review Cover

Geographic Information Systems (GIS) as Supporting Tools in the Monitoring and Water Management of Lakes in Poland: A Review

Open Access
|Mar 2022

Figures & Tables

Figure 1

Scheme of the relationship between tables in the database LAKES 2 [after Kutyła, Pasztaleniec 2013]

Figure 2

Lake basin visualization: (a) 2D bathymetric plan (b) 3D model [authors’ own elaboration based on data from Inland Fisheries Institute in Olsztyn]

Figure 3

Scheme of the analysis of the delimitation of the catchment area based on the Digital Terrain Model in GIS systems [after Gudowicz, Zwoliński 2009; modified]

Figure 4

Interpolation of an example parameter using various methods: (a) IDW, (b) kriging, (c) spline [after Wu, Hung 2016]

Calculation of lake surface characteristics using GIS tools [after Urbański, Kryla-Straszewska 2010; modified]; N/A – not applicable

ParameterDefinitionFormulaNecessary layersDetermination method in GIS
Lake area characteristics
Height above sea levelThe location of the lake above sea level (m a.s.l.)N/ADigital Terrain Model and a polygon layer with the lake areaZonal Statistics
Area (A)Water surface area without taking the area of islands into accountN/APolygon layer with the lake areaOption calculate geometry area (in the attribute table)
Maximum length (l)The shortest distance between the most distant points of the lake shore when measured along the line, without extending beyond the lake’s boundaryN/APolygon layer with the lake areaRequires a Python script
Maximum breadth (b)The greatest distance between opposite shores measured along a line perpendicular to the maximum length of the lakeN/APolygon layer with the lake areaRequires a Python script
Mean breadth ()The ratio of the lake area to the maximum lake length = A/lPolygon layer with the lake areaRequires a Python script that counts l and the calculate option (in the attribute table)
Perimeter (L)The length of the lake shoreline measured along the 0 isobathN/APolygon layer with the lake areaOption calculate geometry perimeter (in the attribute table)
Elongation index (λ)This parameter gives an overview of the shape of the lake surface. The greater its value, the more elongated the lake isλ = l/Polygon layer with the lake areaRequires a Python script that counts l and the calculate option (in the attribute table)
Shoreline development (DL)This parameter shows how close the shape of the shoreline is to the shape of a circleDL=L/(2√π⋅A)Polygon layer with the lake areaOptions of calculation several geometric and algebraic parameters (in the attribute table)

Calculation of morphometric characteristics related to lake bathymetry using GIS tools [after Urbański, Kryla-Straszewska 2010; modified]; abbreviations – see Table 1, N/A – not applicable

ParameterDefinitionFormulaNecessary layersDetermination method in GIS
Bathymetric characteristics
Volume (V)Lake volumeV = A · Polygon layer with the lake shorelineCalculation option within the attribute table
Maximum depth (Zm)Depth at the deepest point of the lakeN/APolygon layer with lake shoreline and raster bathymetry mapZonal Statistics
Mean depth ()The ratio of the lake’s volume to its area = V/APolygon layer with lake shoreline and raster bathymetry mapZonal Statistics
Exposure or openness (Wo)Indicator that allows assessing the intensity of the impact of external factors on the lakeWo = A/Calculation option within the attribute tableCalculation option within the attribute table
Relative depth (Zr)The ratio of the maximum depth to the diameter of a circle equal to the area of the lake, expressed as a percentageZr=50 ⋅ Zm ⋅ √π⋅(√A)−1Calculation option within the attribute tableCalculation option within the attribute table
Littoral zoneThe percentage of the lake area covered by macrophytesN/ARaster bathymetry mapReclassification of the bathymetric plan into two depth classes depending on the depth of the macrophyte occurrence. Then, calculation of the percentage of the class in the attribute table
DOI: https://doi.org/10.2478/oszn-2022-0001 | Journal eISSN: 2353-8589 | Journal ISSN: 1230-7831
Language: English
Page range: 1 - 16
Published on: Mar 31, 2022
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
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© 2022 Aleksandra Bielczyńska, Sebastian Kutyła, published by National Research Institute, Institute of Environmental Protection
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.