Optimising an observational water monitoring network for Archipelago Sea, South West Finland |
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Authors: | Mika Murtojärvi Tapio SuominenEsa Uusipaikka Olli S Nevalainen |
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Affiliation: | a Department of Information Technology and Turku Centre for Computer Science (TUCS), University of Turku, FI-20014, Finland b Department of Geography, University of Turku, FI-20014, Finland c Department of Statistics, University of Turku, FI-20014, Finland |
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Abstract: | Water quality monitoring in topographically fragmented archipelago coasts calls for a dense observational network. However, visiting multiple sites and analyzing the samples requires a significant amount of work, leading to considerable economic cost. It is of interest to determine an efficient set of sites, which still offers adequate information on the water quality with a sufficient spatial accuracy. A method for optimizing an existing observational network is proposed. The method is concretized by applying it for an observational network in the Archipelago Sea, South West Finland. The network is pruned with the requirement that the observations of the removed sites can be estimated using those of the remaining sites. Suboptimal heuristics are used in pruning to keep the computational time acceptable. Some observations are not available and need to be estimated (imputed) before the pruning. For the network in the Archipelago Sea, the results of the pruning are somewhat sensitive to differences in imputed datasets and heuristics used for site selection. |
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Keywords: | Water quality The Baltic Sea Observational network Pruning algorithms |
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