Analysis Water Quality by Artificial Neural Network in Bazoft River (Iran)

Dariush Rahimi and Sadat Hashe

Abstract

Water quality assessment provides a scientific basis for water resources development and management .Climate change is changing our assumptions about water resources. We used to of samples 372 in Bazoft river that they collected by CBRW in 1975-2012. In this article, we did analysis relation discharge and %NA, SAR, TDS and EC in Bazoft River. We used to use of ANN model for the analysis effected discharge on amount concentration in this basin. The results shown that correlation rate are between discharge to EC (0.62) and TDS (0.75).So they are between discharge to %NA (0.59) and SAR (0.45).According it minimum epoch is for TDS (21) and maximum epoch is for %NA (420). The analysis effect discharge on %NA and SAR at months( Mar, April ,May, June and July) that discharge decreasing has amount concentration is decreasing. Furthermore the analysis effect discharge on %NA and SAR in annually shown that if discharge is creasing then amount value %NA and SAR is creasing too. But about TDS and EC this relation is reversed. These changes are forming soil and geology formation erosion and salt dome.