Environmental data modeling

In the statistical analysis of environmental data, space and time are often disregarded by the use of classical methods such as hydrological analysis of frequencies or factor analysis. But these methods, based on the assumptions of independent identically distributed observations, cannot be efficient. This article discusses more appropriate approaches regarding the space and time influences, and surveys some important proposals of modeling environmental data. Three examples show the workability of the presented theory. Within the first example, a system to detect abnormal occurrences in water quality as early as possible depending in quasi-continuous data is developed. A second example decomposes a water quality time series into three unobservable components. Finally, it is shown how the factor model can be extended to time series data.