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)
Factor analysis and zoning of qualitative parameters of groundwater resources in Arsanjan Plain, Fars Province

Bahman Kavari; Yahya Esmaeilpour; Ali Akbar Mousavi; Ommolbanin Bazrafshan; Arashk Holisaz

Volume 75, Issue 4 , January 2023, , Pages 607-626

https://doi.org/10.22059/jrwm.2022.346190.1673

Abstract
  The main source of water in the Arsanjan plain is underground water, which has been exploited in the past with Aqueduct and now with numerous wells. For knowing about the quality conditions of these sources; multivariate statistical analysis and interpolation methods were used in three years with different ...  Read More

Assessing the efficiency of SWAT model for runoff simulation in Gamasiyab basin

Shahab oddin Zarezade Mehrizi; Asadollah Khoorani; Javad Bazrafshan; Ommolbanin Bazrafshan

Volume 70, Issue 4 , January 2018, , Pages 881-893

https://doi.org/10.22059/jrwm.2018.243898.1174

Abstract
  Gamasiab River is one of the five main branches of the Karkheh River and plays a basic role in preserving the life and ecosystem of the region. The first step in the adoption of proper and sustainable methods for managing the water resources of the Gamasiyab river is to gain continuous knowledge of the ...  Read More

Comparison of stochastic models and conceptual models in hydrological drought forecast (case study: Karkheh River Basin)

Ommolbanin Bazrafshan; Ali Salajegheh; Ahmad Fatehi; Abolghasem Mahdavi; Javad Bazrafshan; Somayeh Hejabi

Volume 66, Issue 4 , March 2014, , Pages 493-508

https://doi.org/10.22059/jrwm.2014.50026

Abstract
  Drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. This paper presents the performances of autoregressive integrated moving average (ARIMA), Direct multi-step neural network (DMSNN), ...  Read More