Volume 78 (2025)
Volume 77 (2024)
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)
Digital mapping of soil texture components in the Sirjan region using machine learning models

Elham Mehrabi Gohari; Roghaye Shahriyaripour; Ahmad Tagabadipoor; Seyed Roohollah Mousavi

Volume 78, Issue 2 , June 2025, , Pages 265-288

https://doi.org/10.22059/jrwm.2024.375890.1760

Abstract
  This study aims to evaluate and compare the efficiency of Artificial Neural Network (ANN), Regression Tree (RT) and Neuro-Fuzzy (ANFIS) models using a digital soil mapping framework to predict soil texture in a part of Sirjan province. Sampling was carried out at 84 observation points with a regular ...  Read More

Modeling the Effect of Environmental Factors on the Diversity of Vegetation in Central Alborz Protected Area

Hannaneh Sadat Sadat Mousavi; Afshin Danehkar; Ali Jahani; Vahid Etemad; Farnoush Attar Sahragard

Volume 76, Issue 1 , June 2023, , Pages 29-44

https://doi.org/10.22059/jrwm.2023.351879.1688

Abstract
  Different forms of land use development and human activities in protected areas are considered to be the main drivers of change, which have many effects on habitats, habitats, diversity and richness of species. The purpose of this research is to model the effect of human activities on the diversity of ...  Read More

Modeling of land subsidence in Abarkouh plain using Synthetic aperture radar method and artificial intelligence

Zahra Khosravani; Mohammad Akhavan Ghalibaf; Maryam Dehghani; Vali Derhami; Mustafa Bolca

Volume 75, Issue 3 , December 2022, , Pages 429-448

https://doi.org/10.22059/jrwm.2022.340930.1652

Abstract
  The aim of this study was to model the subsidence of Abarkouh plain using inSAR and artificial intelligence techniques. At first, the subsidence map was prepared using the 46 Sentinel - 1 radar images (2014 – 2018) and radar interferometry techniques. Then, the Feedforward artificial neural network ...  Read More

Evaluation of the Effect of Probability Distributions on Suspended Sediment Prediction Accuracy using ANN and ANFIS Models (Case Study: Dez Basin)

Hamide Afkhami; mohammad dastorani; farzaneh fotouhi firuzabadi

Volume 69, Issue 2 , July 2016, , Pages 323-338

https://doi.org/10.22059/jrwm.2016.61686

Abstract
  Due to the nature of the sediment data, selection of appropriate methods for processing the data before entering them to the artificial intelligence models can enhance the reliability of simulations results. In this study, the effects of sediment data processing procedures on ANN and ANFIS models outputs ...  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

https://doi.org/10.22059/jrwm.2012.30014

Abstract
  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

Abstract
  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