Stream Flow Prediction in Flood Plain by Using Artificial Neural Network (Case Study: Sepidroud Watershed)

author

  • A.R Mardookhpour Assistant Professor, Department of civil engineering, Islamic Azad University, Lahijan, Iran
Abstract:

In order to determine hydrological behavior and water management of Sepidroud River (North of Iran-Guilan) the present study has focused on stream flow prediction by using artificial neural network. Ten years observed inflow data (2000-2009) of Sepidroud River were selected; then these data have been forecasted by using neural network. Finally, predicted results are compared to the observed data. Results showed that neural network could predict stream flow with high precision and the maximum error percentage in data prediction was about 3.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

stream flow prediction in flood plain by using artificial neural network (case study: sepidroud watershed)

in order to determine hydrological behavior and water management of sepidroud river (north of iran-guilan) the present study has focused on stream flow prediction by using artificial neural network. ten years observed inflow data (2000-2009) of sepidroud river were selected; then these data have been forecasted by using neural network. finally, predicted results are compared to the observed dat...

full text

Groundwater quality assessment using artificial neural network: A case study of Bahabad plain, Yazd, Iran

Groundwater quality management is the most important issue in many arid and semi-arid countries, including Iran.Artificial neural network (ANN) has an extensive range of applications in water resources management. In this study,artificial neural network was developed using MATLAB R2013 software package, and Cl, EC, SO4 and NO3 qualitativeparameters were estimated and compared with the measured ...

full text

The Economic Evaluation of Optimal Water Allocation Using Artificial Neural Network (Case Study: Moghan Plain)

recipitation shortage and the consequent loss of several water resources, as well as the population growth, are the most important problems in arid and semi-arid regions like Iran. The providence of basic tools for optimal water resources management is considered as one of the main solutions to this problem. Since the agricultural sector is the main user of water resources, the present study pr...

full text

Prediction of monthly rainfall using artificial neural network mixture approach, Case Study: Torbat-e Heydariyeh

Rainfall is one of the most important elements of water cycle used in evaluating climate conditions of each region. Long-term forecast of rainfall for arid and semi-arid regions is very important for managing and planning of water resources. To forecast appropriately, accurate data regarding humidity, temperature, pressure, wind speed etc. is required.This article is analytical and its database...

full text

flood forecasting using artificial neural networks and nonlinear multivariate regression (case study: taleghan watershed)

it is necessary to use empirical models for estimating of instantaneous peak discharge because of deficit of gauging stations in the country. hence, at present study, two models including artificial neural networks and nonlinear multivariate regression were used to predict peak discharge in taleghan watershed. maximum daily mean discharge and corresponding daily rainfall, one day antecedent and...

full text

Prediction and modeling of fluoride concentrations in groundwater resources using an artificial neural network: a case study in Khaf

 Background: One issue of concern in water supply is the quality of water. Measuring the qualitative parameters of water is time-consuming and costly. Predicting these parameters using various models leads to a reduction in related expenses and the presentation of overall and comprehensive statistics for water resource management. Methods: The present study used an artificial neural...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 4  issue 1

pages  71- 77

publication date 2012-12-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023