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)
Total Dissolved Solids modeling using machine learning algorithms in periods of low and high water (Case study: Khorammabad, Biranshahr and Alashtar watersheds, Lorestan province)

Nasrin Beiranvand; Alireza Sepahvand; Ali Haghizadeh

Volume 76, Issue 3 , November 2023, , Pages 215-236

https://doi.org/10.22059/jrwm.2023.351372.1684

Abstract
  In this study, five soft computing techniques, GP-PUK, GP-RBF, M5P, REEP Tree and RF were used to predict the SL in Cham Anjir, Bahram Joo, Kaka Reza and Sarab Syed Ali hydrometry stations in Khorramabad, Biranshahr and Alashtar sub-watersheds, Lorestan province. Total data set consists of rain, discharge ...  Read More

Application of Geomorphometric attributes in digital soil mapping by using of machine learning and fuzzy logic approaches

Asghar Rahmani; Fereydoon Sarmadian; Sayed Roholla Mousavi; Seyyed Erfan Khamoshi

Volume 73, Issue 1 , June 2020, , Pages 105-124

https://doi.org/10.22059/jrwm.2020.288580.1418

Abstract
  Conventional soil mapping is related to High density sampling, affected by scale and expert knowledge So using of new data mining methods in digital soil properties mapping was the main aim of this study for resolving conventional soil survey problems. In this research, 62 surface soil samples based ...  Read More

The spatial extrapolation of soil great group by application of Random Forest in arid region of central Iran (Faryab-Kahnooj)

Mehrnaz Neyestani; Fereydoon Sarmadian; Azam Jafari; Ali Keshavarzi

Volume 72, Issue 4 , March 2020, , Pages 1147-1166

https://doi.org/10.22059/jrwm.2020.290211.1423

Abstract
  In digital soil mapping, soil characteristic and classes could be extracted truly by numerical and quantitative modelling. Hence, derived rules could be fitted to similar regions for achieving ruled relations on areas without soil information which is called as extrapolation. In the present study, achieving ...  Read More

Groundwater Potential Determination on Yasouj-Sisakht area Using Random Forest and Generalized Linear Statistical Models

Mohammad Taghi avand; Saeed Janizadeh; Mohsen Farzin

Volume 72, Issue 3 , December 2019, , Pages 609-623

https://doi.org/10.22059/jrwm.2019.282912.1392

Abstract
  Increasing population and agricultural development need dramatically water resources groundwater resources, therefore, are increasingly being considered, especially in arid and semi-arid regions. Aim of this research is mapping potential of groundwater resources on Yasouj-Sisakht region using data mining ...  Read More

Groundwater Level Prediction of Boukan Plain using Fuzzy Logic, Random Forest and Neural Network Models

hossein norouzi; ataallah nadiri

Volume 71, Issue 3 , December 2018, , Pages 829-845

https://doi.org/10.22059/jrwm.2018.68924

Abstract
  123 Groundwater system studies to understanding its behavior, requires the exploratory drilling wells, pumping test and geophysical experiments, which can carried out with most cost. For this reason, simulation of groundwater flows by mathematical and computer models, which is an indirect method to ...  Read More