The rainfall-runoff relationship is one of the most complex hydrological phenomena. In recent years, hydrologists have successfully applied backpropagation neural network as a tool to model various nonlinear hydrological processes because of its ability to generalize patterns in imprecise or noisy and ambiguous input and output data sets. However, the backpropagation neural network convergence ...

[1] Motivated by the recent increasing availability of global remote sensing data for estimating precipitation and describing land surface characteristics, this note reports an approximate assessment of quasi-global runoff computed by incorporating satellite rainfall data and other remote sensing products in a relatively simple rainfall-runoff simulation approach: the Natural Resources Conserva...

The paper presents a one-dimensional hydro-mechanical analysis of rainfall infiltration in a loose volcanic ash and the utilisation of a factor of safety for the implementation of an early-warning system. Three different rainy seasons with different rainfall patterns were analysed . The analysis aims to understand the influence of the antecedent rainfall on the wetting front, the pore-water pre...

rainfall-runoff relationship is very important in many fields of hydrology such as water supply and water resourcemanagement and there are many models in this field. among these models, the artificial neural network (ann) wasfound suitable for processing rainfall-runoff and opened various approaches in hydrological modeling. in addition,anns are quick and flexible approaches which provide very ...

The distributed lag model (DLM), used most prominently in air pollution studies, finds application wherever the effect of a covariate is delayed and distributed through time. We specify modified formulations of DLMs to provide computationally attractive, flexible varying-coefficient models that are applicable in any setting in which lagged covariates are regressed on a time-dependent response. ...

This paper presents rainfall-induced landslide thresholds and predicts landslide hazard in Kuala Lumpur metropolitan city and surrounding areas. Landslide events from 2000 to 2012 were collected. The long and short antecedent rainfall days were prepared for landslide and non-landslide days simultaneously. First, threshold analysis was conducted by using data obtained from rainfall stations loca...

The relationship between antecedent rainfall and pollutant build-up is difficult to quantify, particularly in arid environments, due to the inherent unpredictability and natural variability in rainfall. To overcome this variability, a rainfall simulator was constructed to mimic storm events under controlled conditions. Simulated storm events at monthly intervals were used to measure increasing ...