Understanding and managing groundwater resources requires the integration of large amounts of high quality data from different sources. With the recent advances in GIS, data storage, web-based applications, and visualisation technologies, groundwater data management has entered a new phase....

The paper examines how empirical models can be constructed to describe the dependence of the error in fitting data to parametric models of probability distributions on the type of distribution, sample size, parent parameter values and percentiles of interest. Such models are important in...

Knowledge-based or Artificial Intelligence techniques are used increasingly as alternatives to more classical techniques to model environmental systems. We review some of them and their environmental applicability, with examples and a reference list. The techniques covered are case-based...