Climate change introduces substantial uncertainty to water resources planning and raises
the key question: when, or under what conditions, should adaptation occur? A number of …

Surrogate models are popular tool to approximate the functional relationship of expensive
simulation models in multiple scientific and engineering disciplines. Successful use of …

Complex mathematical and computational models are used in all areas of society and
technology and yet model based science is increasingly contested or refuted, especially …

This is a revised version of the 1984 book of the same name but considerably modified and
enlarged to accommodate the developments in recursive estimation and time series …

We review the problem of estimating parameters and unobserved trajectory components
from noisy time series measurements of continuous nonlinear dynamical systems. It is first …

The predominant philosophy underlying most environmental modelling is a form of
pragmatic realism. The limitations of this approach in practical applications are discussed, in …

In this article, a chaotic computing paradigm is investigated for the parameter estimation of
the autoregressive exogenous (ARX) model by exploiting the optimization knacks of an …

The Data-Based Mechanistic (DBM) modelling philosophy emphasises the importance of
parametrically efficient, low order,'dominant mode'models, as well as the development of …

Spatio-temporal statistical models are increasingly being used across a wide variety of
scientific disciplines to describe and predict spatially-explicit processes that evolve over …

This paper discusses the modelling of rainfall–flow (rainfall–run–off) and flow–routeing
processes in river systems within the context of real–time flood forecasting. It is argued that …