The artificial neural networks (ANNs) have been applied to various hydrologic problems recently. This research demonstrates static neural approach by applying Modular feedforward neural network to rainfall-runoff modeling for the upper area of Wardha River in India. The model is developed by processing online data over time using static modular neural network modeling. Methodologies and techniq...

Watershed models such as SWAT (Soil and Water Assessment Tool) simulate water quality impacts of land and water resource management alternatives. To simulate these impacts, long-term daily rainfall data are necessary. In the absence of measured rainfall data, watershed models use weather generators to simulate rainfall events. The objective of this study is to examine several daily precipitatio...

This paper presents the combination of different precipitation data sets and the distributed hydrological model, in order to examine the flood runoff reproductivity of scattered observation catchments. The precipitation data sets were obtained from observation using rain-gages, satellite based estimate (TRMM), and numerical weather prediction model (NWP), then were coupled with the super tank m...

As a result of quick progression in computer and information technologies, computer modeling has become a vital tool in watershed research and management practices. Stanford Watershed Model (SWM) is an integrated physically based Watershed model that can be used to simulate water flow stream/canal network and overland runoff, interflow and evaporation by considering the interaction between surf...

abstract this papare is resaults of analysing the data which reported from a harvesting project. the site for collecting data is buildings' roofs of azad islamic university of mashhad. a rain gauge and a small reservoir (capacity is 4 cubic meters) were set at this site. then the amount of precipitation and its runoff were measured during two years (from 1386, dey, 23 to 1388, tir, 3).the sampl...

this study aims to evaluate effects of two downscaling methods; change-factor and statistical downscaling on therunoff of the azam-harat river located at yazd province (with an arid climate) of iran, under the a2 emission scenariofor the period of 2010-2039. for this purpose, cgcm3-ar4 model; a rainfall-runoff conceptual model, ihacres; twodownscaling models, change factor and lars-wg were appl...

the discharge or runoff which ousts from a watershed is important. because its deficiency leads to financial losses and its excesses cause damage in lives and property as flood. in this research using artificial neural network multi-layer perceptron (mlp (and adaptive neuro-fuzzy interface system (anfis) and multiple regression method simulated rainfall- runoff process on daily basis in the kho...

Darrin J. Greenstein, Liesl L.Tiefenthaler, and Steven M. Bay ABSTRACT Stormwater runoff is an important source of toxic substances to the marine environment, but the effects of antecedent dry period, rainfall intensity, and duration on the toxicity of runoff are not well understood. In this study, simulated rainfall was applied to parking lots to examine the toxicity of runoff while controllin...

[1] The key question that is asked in this study is ‘‘how are the three independent bias components of satellite rainfall estimation, comprising hit bias, missed, and false precipitation, physically related to the estimation uncertainty of soil moisture and runoff for a physically based hydrologic model?’’ The study also investigated the performance of different satellite rainfall products as a...

the wepp physically model is able to dynamically simulate runoff and soil erosion using physical concepts of erosion and hydraulic of overland flow science considering plant growth, residue decomposition, winter process. determination of the capability of this model in runoff and erosion estimation in different range type with investigation the effects of management were the main objectives of ...