Quantitative modeling of risk and hazard from flooding involves decisions regarding the choice of model and goal of the modeling exercise, expressed by some measure of performance. This paper shows how the subjectivity in the choices of performance measures and observation sets used for model...

The objective of this contribution is to form a clear picture of uncertainties we encounter in flood estimation, including both real-time flood forecasting and simulation for flood risk estimation. In simulation, we prefer the thesis of equifinality to obtain global optima. Many models producing...

The generalized likelihood uncertainty estimation (GLUE) methodology is applied to the problem of predicting the spatially distributed, time-varying probabilities of inundation of all points on a floodplain. Advantage is taken of the relative independence of different effective conveyance...

It may be endemic to mechanistic modelling of complex environmental systems that there are many different model structures and many different parameter sets within a chosen model structure that may be behavioural or acceptable in reproducing the observed behaviour of that system. This has been...

This paper describes data assimilation (DA) and adaptive forecasting techniques for flood forecasting and their application to forecasting water levels at various locations along a 120 km reach of the river Severn, United Kingdom. The methodology exploits the top-down, data-based mechanistic...

Quantitative modeling of risk and hazard from flooding involves decisions regarding the choice of model and goal of the modeling exercise, expressed by some measure of performance. This paper shows how the subjectivity in the choices of performance measures and observation sets used for model...

Operational flood forecasting requires accurate forecasts with a suitable lead time, in order to be able to issue appropriate warnings and take appropriate emergency actions. Recent improvements in both flood plain characterization and computational capabilities have made the use of distributed...

In recent years, the increasing popularity of eCommerce, and particularly online auctions has stirred a great amount of scholarly research, especially in information systems, economics,and marketing, but little or no attention has been received from statistics. ECommerce arrives with enormous...

Generalized Linear Mixed Models (GLMMs) extend the framework of Generalized Linear Models (GLMs) by including random effects into the linear predictor. This will achieve two main goals ofincorporating correlation and allowing broader inference. This thesis investigates estimation of fixed...