Combatting Nutrient Spillage in the Archipelago Sea—A Model System

Combatting nutrient spillage in the

Archipelago Sea—a model system for coastal management support

H. Lauri% H. Ylinen*, J. Koponen*, H. Helminen* & P. Laihonen*

' Environmental Impact Assessment Centre of Finland Ltd, Finland ^ South-West Finland Regional Environment Centre, Finland

Abstract

The Archipelago Sea is a sea area in the Baltic Sea between Aland and the Finnish mainland strongly influenced by the Baltic Sea forcing. Archipelago Sea waters are relatively clean but threatened from the southern and eastern sides by more nutrient rich waters from the Gulf of Finland and the Baltic Proper, and also from local nutrient loads from Finnish mainland and fish farming. In order to find out the relative impact of different nutrient sources a hydrodynamic model was applied to the area. Modelling the Archipelago Sea required taking into account large scale variations of the Baltic Sea as well as the small scale topography created by the numerous islands, therefore a nested three- dimensional grid with three grid refinement levels was used. Flows in the Archipelago Sea are dominantly wind-induced but affected by salinity and temperature gradients. Computed flows were compared to flow measurements performed in the

Archipelago Sea during the open water periods of 1993 and 1994. These simulated flows were then used to model transport in the area to investigate the effect of local nutrient sources and water exchange between the Archipelago Sea and neighbouring sea areas. Transport computations were further verified using salinity measurements.

In order to make the model more usable a model management system was constructed. The system simplifies model input data handling, model computation, and result visualisation. As a basis of the user interaction a map- based view of the modelled area is shown, including a set of interactive symbols that allow geographic location-based data access and model parameter manipulation.

194 Environmental Coastal Regions HI

Introduction

Archipelago Sea is one of the most complicated archipelago areas in the world, numerous small and big islands and rocks make the archipelago highly fractal in character. Large open water area and main channels form the central part of the archipelago that is strongly influenced by the Baltic Sea forcing, while intermediate and inner archipelago areas surround the central part on the Aland

Island and Finnish mainland sides. Inner archipelago areas are to a large extent isolated from the main Baltic Sea influence, storm events, however, can be important for the exchange of the inner archipelago waters.

Figure 1. Archipelago Sea

The Archipelago Sea is affected by nutrient transport from the surrounding seas, mainly Baltic Proper, and nutrient loads from land runoff and point sources, and internal bottom load from sediments. Some areas of the Archipelago Sea suffer from excessive eutrofication demonstrating itself as sliming, extensive growth of filamentous algae, oxygen depletion and algae blooms.

In order to better understand the origin nutrients causing the eutrofication, the influence of the surrounding seas to the Archipelago sea was investigated by computing the water flows in the area and water exchange with the neighbouring seas. The goal was to achieve information on the relative importance of local nutrient sources compared to long distance transport (Helminen 1998). The flow computations were verified using set of flow measurements performed during open water period in several locations on years 1993 and 1994. In addition to computation results a modelling support system was built to enable generation and investigation of computation results by the end users, that is, the local environmental office. The complete modelling system consist of a hydrodynamic and water quality models, and a model management system

Environmental Coastal Regions HI 195

helping users in the complex task of input data management, model running and result visualisation (Lauri 1998).

Computational model

The hydrodynamic model used is a 3D primitive equation, z-coordinate, free surface model, with constant eddy viscosity coefficients (Koponen 1992, Simons

1980). The model grid covers the whole Baltic Sea with two nestings that locally increase the model resolution. The grid box sizes used are 24, 6 and 1.5 km, where the finest grid covers the Archipelago Sea. Vertically there are ten layers with thickness of one meter at the surface and increasing downwards.

Figure 2. Part of the model grid showing the two finest grid nestings.

As the whole Baltic Sea was modelled there are no open boundaries. The water exchange through the Danish straits and fresh water river inputs were either neglected or taken into account as constant concentrations, and in the model initial state. As the tide in the Baltic Sea is negligible, the main current driving forcing in is wind.

Comparison of computed and measured flows

To investigate model reliability model results were compared to measured flows performed with recording current meters at ten-minute intervals. There were three point measurements from summer -93 and four from summer -94. The measurement points were mostly located on straits on the Archipelago Sea. The comparison between computed and measured flows were performed using along the strait flow component, typically the cross-strait flow components were significantly smaller in magnitude.

196 Environmental Coastal Regions III

Goodness of fit of computed flow to measured flow was estimated using goodness of fit (R?) coefficient. For the two whole measurement periods the R varied from negative values to 0.51 at different points. Below a figure showing comparisons performed using a moving one-week time range for year -94 data, from which periods of good and bad modelfi tca n be identified. As a reference the lighter colored line in the figures identifies the values of R? achieved when using a constant zero as the computed flow.

940606 940613 940620 940627 940704 940711 940718 940603 940605 940607 940600 940611 940613 940615 940617 940619 Bano Kumlinge

Figure 3. Time-dependent R2 coefficient between computed and measured flows

The model performance goes in some cases below the reference line. However, in this kind of comparison a slight phase error may cause poor values for the R* coefficient. Also this comparison was done with measured point flow data, while the model always computes average flow of 1.5 x 1.5 km grid box. Generally the modelled results compared to measured values rather well, and in some cases the model fit could be called good, taking into account the above limitations.

Water exchange

Water exchange was computed using an initial state where Baltic, Gulf of Finland, Bothnian Bay and Archipelago Sea were marked individually. The movement of these waters was then followed for eight months in different years. The water exchange varied greatly between different years, mainly due to strong winds occurring most often during spring and autumn. A difference between outer (left) and inner archipelago is demonstrated in the figure below.

1 Gulf of Finlad 0.8 Baltic proper 0.6 Bothnian Bay Archipelago Sea 0.4

0.2 0 940402940502940601940701940731940830940929941029941128

Kihti, outer archipelago Turku, inner archipelago Figure 4. Water exchange timeseries for eight-month simulation.

Environmental Coastal Regions HI 197

Nutrient dispersion

To find out the relative importance of local nutrient sources in different areas of

Archipelago Sea the local nutrient sources were mapped and divided into three main categories: 1. loads from Finnish shoreline including river discharges as well as municipal and industrial sources, 2. Loads in eastern archipelago including mostly fish farming, and 3. Loads in Ahvenanmaa archipelago. In the figure below the load locations are shown on the map. Distribution of nutrients was then estimated by letting the released tracker spread with the computed flow and plotting timeseries of tracker concentrations on given locations for the eight month simulation period. A clear distinction can be seen between the inner archipelago, where local source are significant due to smaller water exchange and large loads from shore, and the outer archipelago, where local loading disperse quickly.

# Ahvenanmaa archipelago

m. Finnish shore

O Eastern achipelago

Point loads on the Finnish shore, Eastern and Ahvenanmaa archipelago

• Ahvenanmaa archipelago I I Finnish shore Eastern achipelago

12 140*01 MO701 940731 MM30 140921 M10M Mil Turku, inner archipelago Kihti, outer archipelago

Figure 5. Simulated relative active phosphorous fractions from different load areas in two points on Archipelago Sea during eight-month simulation.

198 Environmental Coastal Regions HI

Model management system

The Archipelago Sea model management system to integrates a set of existing modelling and data processing software tools into a modelling system, and provides a basis for fiirther development of modelling tools. The integration was done by providing a common base for starting individual tools and sharing data. Different user needs from model result viewing to model application building can be supported by providing different tool sets for different modelling tasks. A common software tool launching system was implemented by using a standard operating system file browser and file system. The user sees a list of model related files, where double clicking a file will start a corresponding modelling tool. The tool launch environment consist thus a set of file type - software tool associations, which can be modified according the user needs. Additionally the model related files are associated to a specific model run, for example, information about the model parameters used computation is available to visualisation tool. A database server for holding model run information is being developed, which will further increase the possibilities to share model information between different modelling tools. Below a figure of the system structure and a list of modelling tasks and related software tools.

Tools

Model Management

Browser

C Local files ^

Figure 6. Model management system structure

System management • Model data browser (operating system file browser used) Input data handling • Model grid generation tool • Timeseries import tool

Environmental Coastal Regions HI 199

• Data conversion tools Model run management: • Model run management tool

• Computational model Data visualisation & reporting • Flow and scalarfiel dvisualisatio n tool • Timeseries data visualisation tool

• Report generator

The above set of tools consists mostly of custom software implemented using a GUI development system. Currently the system works a stand-alone version on a workstation.

Model run management and 2d field visualisation tools

The model run management tool is used to manage model input data and parameters. It is based on following ideas : • The main window contains a view of the model grid, a toolbar and a menu. • The window menu contains the following menu items: File, View, Source data, Computation, and Results.

• Model simulation parameter sets can loaded and stored tofile ssimilarl y to text documents. Each parameter set contains all model input parameters and access information of the timeseries input data and result files. • Model input data and suitable model parameters are shown on the model

grid as symbols, where each symbol can be used to access corresponding information. Same data is also accessible through menu selections. • Model parameters are set using dialog boxes accessible through the computation menu or map symbols. There are automated routines and help available for setting the parameters.

• Timeseries measurement data exists separately, and does not depend on the model cases. Model can use this data, for example, for input boundary conditions. • Result data, such as timeseries and 2d fields, is accessible within the model

run manager can be easily visualised and exported to documents.

Below in afigur e 7 the main window of the water quality model with a zoomed view into the Archipelago Sea grid. A Id-field visualisation tool is used to inspect 2d and slices of 3d fields.

Figure 8 shows the main window of this tool. Similarly to CIS programs a concept of data layers is used. The main window consists of a picture area for displaying data layers and a list of layers in a box on the left part of the window, through which layers can be added, removed and selected independently. Cursor coordinates and corresponding data values are displayed in the toolbar. Other miscellaneous data such as animation time, depth layer and length scale is shown in the left part of the window.

200 Environmental Coastal Regions HI

Figure 7. Water quality model main window

E*t Compute $ 580392,728850 (1^t»*OJ[»OOv* 0,0000 Wo

Figure 8. 2d field visualisation tool

Typical tasks possible using the 2d visualisation tool include • Displaying map information from the model area.

• Displaying measurement data from the model area. • Displaying selected model results, for example, as timeseries, 2d fields, or 2d animations. • Comparing modelled and measured data using visual comparison and statistical analyses.

Environmental Coastal Regions III 201

• Computing statistical information from the model and measurements data. • Computation of differences between two fields.

• Exporting modelled and measured data as numbers or figures for further processing.

Conclusions

A hydrodynamic model was applied with a 1.5 km resolution to the Archipelago Sea area. Comparisons with measured currents were used to calibrate the model and also to verify the model results. Calibrated currents were then applied to water exchange and nutrient dispersion computations. Further use of the model will include applications using more refined scale in specific parts of the Archipelago Sea. The model results were transferred to end users in the form of an interactive modelling system. This way the computation results could be investigated for any given time period and location with given wind and boundary condition data. The model is being taken into use but for now not much data is available about the usability of the system. Further development of the system will include streamlining the system user interface, further integration with databases and a toolkit usable though a web browser.

Acknowledgements

The work here was partly funded by the European Commission under the DGXII MAST Programme (MAS3-CT97-0089).

References

[1] Helminen, H., Juntura E., Koponen J. and Ylinen H. Assessing of Long Distance Background Nutrient Loading to the Archipelago Sea, Northern Baltic with a Hydrodynamic Model. Environmental Modelling & Software 13, pp 511-518. Elsevier, 1998.

[2] Koponen, J., Alasaarela, E., Lehtinen, K., Sarkkula, J., Simbierowicz, P., Vepsa, H., Virtanen, M., Modelling the dynamics of a large sea area. Publications of the Water and Environment Research Institute, 7. National

Board of Waters and Environment: Helsinki, Finland, 1991.. [3] Simons, T.J., Circulation models of lakes and inland seas. Can. Bull. Fish. Aquat. Sci. 203, 145, 1980.

[4] Lauri H., Koponen J., Virtanen M., Alasaarela E., Integrated water quality management supported by graphical user interface, Proc. of the 3rd Int. Conf On Hydroinformatics, eds. V.Babovic, L.C.Larsen, Balkema: Rotterdam, pp. 309-314, 1998.