Volume 76 (2023)
Volume 75 (2022)
Volume 74 (2021)
Volume 73 (2020)
Volume 72 (2019)
Volume 71 (2018)
Volume 70 (2017)
Volume 69 (2016)
Volume 68 (2015)
Volume 67 (2014)
Volume 66 (2013)
Volume 65 (2012)
Volume 63 (2010)
Volume 62 (2009)
Modeling of daily soil temperature using synoptic data and neural network

TAYYEBEH MESBAHZADEH; ali azareh; Elham Rafiiei sardooi; Fateme FarzanePei

Volume 71, Issue 1 , June 2018, , Pages 285-295


  Soil moisture, as the soil hydrologic parameters, can be affected by soil temperature and controls various hydrological processes. Given the importance of this issue, in this study, the efficiency of artificial neural network was studied to simulate soil temperature at 5- 100 cm depth. Recorded meteorological ...  Read More

Reconstruction of Daily Discharge using Artificial Neural Network and Neuro-Fuzzy Methods (Case Study: Upstream of Karoun Watershed)

Mojtaba Nassaji zavareh; Bagher Ghermezcheshmeh; Fatemeh Rahimzadeh

Volume 69, Issue 2 , July 2016, , Pages 503-514


  Daily constant discharges are needed estimating daily discharge in the hydrological model. The different number of statistical years, statistical deficiencies, and measurement error leads to the formation of time series with an uncommon time base. Hence the reconstruction of daily discharge data is of ...  Read More

Artificial Neural Network (ANN) Model for Ground Water Quality Simulation (Case study: Kashan aquifer)

mohammad mirzavand; Hoda ghasemieh; mahmud akbari; seyed javad sadatinejad

Volume 68, Issue 1 , June 2015, , Pages 159-171


  Kashan aquifer is adjacent to Salt Lake. Because of this adjacency, the saline water of the lake has moved to the aquifer. In this study groundwater quality of the aquifer was simulated using Artificial Neural Network (ANN) model. For this purpose, the dominant ion of water was first determined by Piper ...  Read More

Forecasting of runoff and sediment using neural network and multi regression in Aghajari Marls

Mahadi Vatakhah; Hamzeh Saidian

Volume 67, Issue 3 , December 2014, , Pages 487-499


  Erosion and sediment movement phenomena are one of the most complex issues in management of rivers drainage areas that in water projects are very important. That its measurement wants high time and cost. Issue of surface runoff in river basin is a complex issue that human knowledge and understanding ...  Read More

Application of Artificial Neural Networks in Simulating and Forecasting of Meteorological Drought Decile Percentage Index (Case study: Sistan & Balouchestan Province)

Arash Malekian; Mahrou Dehbozorgi; Amir Houshang Ehsani; Amir Reza Keshtkar

Volume 67, Issue 1 , May 2014, , Pages 127-139


  Consecutive droughts in Sistan and Baloochestan province cause water resources restriction and this isa very significant problem for this region. In this study, in order to forecast the drought cycle in 9climatological stations in the province, we used Artificial Neural Networks. The input data wereaverage ...  Read More

Assessment of the Effect of Input Factors Number in Accuracy of Artificial Neural Network for Landslide Hazard Zonation (Case study: Haraz Watershed)

Hamidreza Moradi; Alireza Sepahvand; Parviz Abdolmaleki

Volume 65, Issue 2 , September 2012, , Pages 231-243


  More than 30% of Iran's land is formed from mountainous areas. So each year, landslides cause damages to structures, residential areas and forests, creating sedimentation, muddy floods and finally deposit the sediments in reservoir dams. Therefore, for preventing of this damages and expressing the sensitivity ...  Read More

Estimation of the suspended sediment loud of Karaj River using fuzzy logic and neural networks

A. Salajegheh; A. Fathabadi

Volume 62, Issue 2 , October 2009, , Pages 271-282

  Correct estimation of suspended sediment transported by a river is an important practice in water structure design, environmental problems and water quality issues. Conventionally, sediment rating curve used for suspended sediment estimation in rivers. In this method discharge and sediment discharge ...  Read More