Browsing by Author "Goovaerts, Pierre"
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- Benthic biotope index for classifying estuarine habitatsPublication . Caeiro, S.; Costa, Maria H.; Goovaerts, Pierre; Martins, Flávio Augusto Bastos da CruzAn integration of sediment physical, chemical, biological, and toxicity data is necessary for a meaningful interpretation of the complex sediment conditions in the marine environment. Assessment of benthic community is a vital component for that interpretation, yet their evaluation is complex and requires a large expenditure of time and funds. Thus, there is a need for new tools that are less expensive and more understandable for managers. This paper presents a benthic biotope index to predict from physical and chemical variables the occurrence of macrobenthic habitats, applied to Sado Estuary, as a case of study.
- Optimization of an estuarine monitoring program: selecting the best spatial distributionPublication . Caeiro, S.; Nunes, L.; Goovaerts, Pierre; Ribeiro, Luís; Painho, M.; Costa, Maria H.Monitoring estuarine programs are fundamental to evaluate the status and trends of pollution abatement actions, fulfillment of environmental quality standards and compliance with permit conditions. Their sampling designs should provide statistically unbiased estimates of the status and trends with quantitative confidence limits on both spatial and temporal scales. Variance reduction techniques have proved to be good methodologies for choosing better spatial and temporal designs. The aim of this work is to select a subset of monitoring sampling stations based on locations from an extensive estuarine sediment campaign. In this campaign 153 sites were sampled in the Sado estuary (southern Portugal). In each location three sediment parameters were determined with the objective of defining spatially homogenous environmental areas. The new monitoring program is based on fewer and on the most representative monitoring stations inside each homogeneous environmental area for their future contaminant assessment. Simulated annealing was used to iteratively improve on the mean square error of estimation, by removing one station at a time and estimating it by indicator kriging using the remaining stations in the sub-set, within a controlled non-exhaustive looping scheme. Different sub-set cardinalities were tested in order to determine the optimal cost-benefit relationship between the number of stations and monitoring costs. The model results indicate 60 station design to be optimal, but 17 additional stations with expertise criteria of proximity to point sources and characterization of all homogenous areas were added.