Modelling Nitrate Prediction of Groundwater and Surface Water Using Artificial Neural Networks

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Benzer S., Benzer R.

JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI, cilt.21, sa.2, ss.321-325, 2018 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 21 Sayı: 2
  • Basım Tarihi: 2018
  • Doi Numarası: 10.2339/politeknik.385434
  • Dergi Adı: JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.321-325
  • Gazi Üniversitesi Adresli: Evet

Özet

This study aims to estimate the changes in the amount of nitrate in Yesilirmak Watershed using surface water and underground water of the nitrate content determined by General Directorate of State Hydraulic Works using Artificial Neural Networks (ANNs). This study was conducted in 2010 at 30 stations (9 groundwater, 18 surface water and 3 closed water source) in Yesilirmak Watershed. Nitrate ranged from 0.341 to 77.700 mg/L, with an average value of 17.870 mg/L. In this study, changes in the amount of nitrate in Amasya using groundwater and surface water in the basin of the nitrate content determined by the Provincial Directorate of Agriculture modeling was presented with an approach based on Artificial Neural Networks (ANNs) and predict the nitrate value for the year of 2020 and 2030. Thus, the nitrate levels of water samples obtained from 30 stations water supplies found to be under the limits of Turkish and international codex of drinking water intended for human consumption.