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Especially for extreme precipitation or floods, there is considerable spatial and temporal variability in long term trends or in the response of station time series to large-scale climate indices. Consequently, identifying trends or sensitivity of these extremes to climate parameters can be marked by high uncertainty. When one develops a nonstationary frequency analysis model, a key step is the identification of potential trends or effects of climate indices on the station series. An automatic clustering procedure that effectively pools stations where there are similar responses is desirable to reduce the estimation variance, thus improving the identification of trends or responses, and accounting for spatial dependence. This paper presents a new hierarchical Bayesian approach for exploring homogeneity of response in large area data sets, through a multicomponent mixture model. The approach allows the reduction of uncertainties through both full pooling and partial pooling of stations across automatically chosen subsets of the data. We apply the model to study the trends in annual maximum daily stream flow at 68 gauges over Germany. The effects of changing the number of clusters and the parameters used for clustering are demonstrated. The results show that there are large, mainly upward trends in the gauges of the River Rhine Basin in Western Germany and along the main stream of the Danube River in the south, while there are also some small upward trends at gauges in Central and Northern Germany. [ABSTRACT FROM AUTHOR]

Effect-directed analysis (EDA) can be useful in identifying and evaluating potential toxic chemicals in matrixes. Previous investigations of extracts of sediments from the upper Danube River in Germany revealed acute nonspecific and mechanism-specific toxicity as determined by several bioassays. In the present study, EDA was used to further characterize these sediments and identify groups of potentially toxic chemicals. Four extracts of sediments were subjected to a novel fractionation scheme coupled with identification of chemicals to characterize their ability to disrupt steroidogenesis or cause mutagenic and/or teratogenic effects. All four whole extracts of sediment caused significant alteration of steroidogenesis and were mutagenic as well as teratogenic. The whole extracts of sediments were separated into 18 fractions and these fractions were then subjected to the same bioassays as the whole extracts. Fractions 7 to 15 of all four extracts were consistently more potent in both the Ames fluctuation and H295R assays. Much of this toxicity could be attributed to polycyclic aromatic hydrocarbons, sterols, and in fraction 7-naphthoic acids. Because the fraction containing polychlorinated biphenyls, polychlorodibenzodioxin/furan, dichlorodiphenyltrichloroethane, and several organophosphates did not cause any observable effects on hormone production or a mutagenic response, or were not detected in any of the samples, these compounds could be eliminated as causative agents for the observed effects. These results demonstrate the value of using EDA, which uses multiple bioassays and new fractionation techniques to assess toxicity. Furthermore, to our knowledge this is the first study using the recently developed H295R assay within EDA strategies. Environ. Toxicol. Chem. 2012; 31: 1053-1062. © 2012 SETAC [ABSTRACT FROM AUTHOR]