Two important applications of rainfall-runoff models are forecasting and simulation. At present, rainfall-runoff models based on artificial intelligence methods are built basically for short-term forecasting purposes and these models are not very effective for simulation purposes. This study explores the applicability and effectiveness of adaptive neuro-fuzzy-system-based rainfall-runoff models...

Integrated river-basin management for the Volga river requires understanding and modelling of the flow process in its macro-scale tributary catchments. At the example of the Kostroma catchment (16 000 km2), a method combining existing hydrologic simulation tools was developed that allows operational modelling even when data are scarce. Emphasis was placed on simulation of three processes: snow ...

Snow covered area is an important variable in snowmelt runoff modelling. SAR can supply information on this parameter by detecting the decrease in the backscattering coefficient which occurs when the snowpack becomes wet. However, the method is subject to several geometric, geophysical and logistical constraints which limit its general applicability. These include missing coverage due to relief...

In recent years, artificial neural networks (ANNs) have become one of the most promising tools in order to model complex hydrological processes such as the rainfall-runoff process. In many studies, ANNs have demonstrated superior results compared to alternative methods. ANNs are able to map underlying relationship between input and output data without prior understanding of the process under in...

Erosive runoff is a recurring problem and is a source of sometimes deadly muddy floods in the Pays de Caux (France). The risk results from a conjunction of natural factors and human activity. Efficient actions against runoff in agricultural watersheds are well known. However they are still difficult to implement as they require co-operation between stakeholders. Local actors thus need tools to ...

Earlier analyses of valley networks on Mars often concluded that they were poorly integrated, immature drainage systems. Consequently, surface runoff from precipitation was generally thought to be an unimportant geomorphic process. Combination of Mars Global Surveyor (MGS) imaging and altimetry data sets, however, provides a vast improvement in image clarity and resolution. Although we have use...

in recent years, artificial neural networks (anns) have become one of the most promising tools in order to model complex hydrological processes such as the rainfall-runoff process. in many studies, anns have demonstrated superior results compared to alternative methods. anns are able to map underlying relationship between input and output data without prior understanding of the process under in...

A 64-year data set of daily rainfall and runoff, and average monthly potential evapotranspiration (PET) was split into subsets of 2, 5, 10, 20 and 30 years. Each subset was used to calibrate the AWBM daily rainfall-runoff model. Each subset calibration was then used to estimate runoff from the 64 years of rainfall and PET data. The ratios of calculated to actual total runoff were used to determ...