The Prediction of the Flood Peak Discharge Using a Wavelet Neural Network

Hamidreza Babaali; Reza Dehghani

Volume 4, Issue 11 , September 2017, , Pages 149-168

Abstract
  Introduction Flood is one of the hazardous natural disasters that causes loss of life and financial problems every year. Therefore, scientists have tried to assess the quantitative variability of this phenomenon as much as possible. In this study, the recorded data in Kahman Aleshtar watershed area, ...  Read More

A Comparison of the Performance of Artificial Neural Network, Fuzzy Logic and Adaptive Neuro-Fuzzy Inference Systems Models in the Estimation of Aquifer Hydraulic Conductivity. A Case Study: Maraghe-Bonab Aquifer

Ata Allah Nadiri; Saeed Yousefzadeh

Volume 4, Issue 10 , June 2017, , Pages 21-40

Abstract
  An accurate estimation of the hydrogeological parameters such as hydraulic conductivity, which is essential for careful management and protection of groundwater resources, is an important part of hydrogeological studies. Various field and laboratory methods, generally done using hydrogeological data, ...  Read More

Spatiotemporal Groundwater Level Forecasting in Davarzan Plain

Taher Rajayee; Fatemeh Pouraslan

Volume 2, Issue 4 , January 2017, , Pages 1-19

Abstract
  Taher Rajayee[1]* Fatemeh Pouraslan[2] Abstract In this article, a hybrid, artificial neural network-geostatistics (Kriging) methodology is utilized to predict the spatiotemporal groundwater level in Davarzan plain in Khorasan Razavi province in Iran. The data for the study were the groundwater levels ...  Read More