abandoned surface mine excavations can be a major environmental, social and/or human healthproblem for the mining industry as well as for the community living nearby. this problem is exacerbated by therapidly growing population encroaching on areas of historic mined lands. the aim of this studywas to assess thesafety status of the historic nyala mine excavation with the purpose of coming up wit...

The prediction of the small-scale spatial-temporal pattern of intense rainfall events is crucial for flood risk assessment in small catchments and urban areas. In the absence of a full deterministic modelling of small-scale rainfall, it is common practice to resort to the use of stochastic downscaling models to generate ensemble rainfall predictions to be used as inputs to rainfall-runoff model...

A rainfall–runoff (RR) model considering the spatial variation of rainfall, soil infiltration capability and soil storage capacity over a catchment and based on probability distribution functions, is used for rainfall–runoff modelling. The model combines infiltration excess (Horton) and saturation excess (Dunne) mechanisms. Moreover, it is applied to a data sparse catchment. Model parameters of...

Degradation of coastal ecosystems in the Great Barrier Reef (GBR) lagoon, Australia, has been linked with increased land-based runoff of suspended solids, nutrients and pesticides since European settlement. This study estimated the increase in river loads for all 35 GBR basins, using the best available estimates of pre-European and current loads derived from catchment modelling and monitoring. ...

This paper describes a new method for creating polynomial regression models. The new method is compared with stepwise regression and symbolic regression using three example problems. The first example is a polynomial equation. The two examples that follow are real-world problems, approximating the Colebrook–White equation and rainfall-runoff modelling. The three example problems illustrate the ...

This paper presents a distributed model that is in operational use for forecasting flash floods in northern Austria. The main challenge in developing the model was parameter identification which was addressed by a modelling strategy that involved a model structure defined at the model element scale and multi-source model identification. The model represents runoff generation on a grid basis and...

Artificial neural networks (ANN) are modelling tools that can be of great utility in studies of microbial water quality. The ability of ANNs to work with complex, inter-related multiparameter databases and provide superior predictive power in non-linear relationships suits their application to microbial water quality studies. To date ANNs have been successfully applied (a) for the prediction of...