This review considers the application of artificial neural networks (ANNs) to rainfall–runoff modelling and flood forecasting. This is an emerging field of research, characterized by a wide variety of techniques, a diversity of geographical contexts, a general absence of intermodel comparisons, and inconsistent reporting of model skill. This article begins by outlining the basic principles of A...

La escasa comprensión sobre el funcionamiento hidrológico de muchas cuencas zonas secas desafía modelado en forma discreta y continua. Este trabajo implementa un modelo conceptual simple, pero robusto (GR2M) para predecir la escorrentía mensual cuenca del río Sauce Grande (Argentina). El mismo pretende determinar a) eficacia modelos conceptuales simples secas, b) potencial transferencia los par...

This paper explores potential flood resilience approaches for the highly urbanised Wortley Beck river basin, south west of the City of Leeds, UK. Integrated 1D and 2D hydrodynamic modelling, using the ISIS and TUFLOW has been utilised to explore potential impact of SuDS on the flood hazard for three (1:15, 1:50 and 1:100) flood events. A direct rainfall runoff modelling approach has been employ...

The expansion of built-up areas within urban and peri-urban river catchments has the potential to increase flooding. Hydrological modelling these is an important tool analyse manage increasing flood hazard, but it requires understanding contributing runoff from parts catchment. This difficult as in many fine resolution data not available connectivity impervious areas, sewer networks drainage ne...