Best locations for river water quality monitoring sensors through fuzzy interpolation

Angelo Marcello Anile 1, Salvatore Spinella 2 and Marco Ostoich
1 Università degli studi di Catania
Dipartimento di Matematica e Informatica,
viale A. Doria 6, 95125 Catania, Italy
2 Consorzio Catania Ricerche
Via A. Sangiuliano 262, I95124 Catania, Italy
3 ARPAV - Dipartimento Prov. Padova
Osservatorio Regionale Acque Interne
Ufficio Studi e Progetti
Piazzale Stazione n. 1 35131 Padova, Italy

This work concerns the interpolation of environmental data using fuzzy splines in order to monitor water quality in a river. A fuzzy interpolated model representing the river water quality is constructed and  then queried in order to retrieve information useful for planning precautionary measures. Moreover the information retrieved can be used in order to improve the distribution of the monitoring sensors on  the basin area for optimizing the coverage. Geographical data concerning environment pollution consist of a large set of temporal measurements (representing,  e.g .monthly measurements for  one year) at a few scattered spatial sites. In this case the temporal data at a given site must be summarized in some form in order to employ it as input to build a spatial model. Summarizing the temporal data (data reduction) will necessarily introduce some form  of uncertainty which must be taken into account. Fuzzy numbers can represent this uncertainty in a  conservative way without any statistical “a priori” hypothesis. This method has been employed for ocean floor geographical data by Patrikalakis (1995), in  the interval case, and Anile et al. (2000), for fuzzy numbers, and to environmental pollution data by Anile et al.(2004) Fuzzy interpolation is carried out with splines to get a deterministic model for environmental pollution data. Then the model is interrogated by fuzzy queries to find the sites exceeding a quality threshold. The results suggest the areas of the basin which should be subjected to a further rigorous examination; therefore the methods could be useful for monitoring network reorganization in order to be better representative of water quality.

Keywords: uncertain, fuzzy number, fuzzy interpolation, fuzzy queries, spline

In: Caetano, M. and Painho, M. (eds). Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5 – 7 July 2006, Lisboa, Instituto Geográfico Português

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