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Water quality variations in different climates of Iran: toward modeling total dissolved solid using soft computing techniques

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Abstract

In present paper, wavelet analysis of total dissolved solid that monitored at Nazlu Chay (northwest of Iran), Tajan (north of Iran), Zayandeh Rud (central of Iran) and Helleh (south of Iran) basins with various climatic conditions, have been studied. Daubechies wavelet at suitable level (db4) has been calculated for TDS of each selected basins. The performance of artificial neural networks (ANN), two different adaptive-neurofuzzy inference system (ANFIS) including ANFIS with grid partition (ANFIS-GP) and ANFIS with subtractive clustering (ANFIS-SC), gene expression programming (GEP), wavelet-ANN, wavelet-ANFIS and wavelet-GEP in predicting TDS of mentioned basins were assessed over a period of 20 years at twelve different hydrometric stations. EC (μmhos/cm), Na (meq L−1) and Cl (meq L−1) parameters were selected (based on Pearson correlation) as input variables to forecast amount of TDS in four studied basins. To develop hybrid wavelet-AI models, the original observed data series was decomposed into sub-time series using Daubechies wavelets at suitable level for each basin. Based on the statistical criteria of correlation coefficient (R), root mean square error (RMSE) and mean absolute error (MAE), the hybrid wavelet-AI models performance were better than single AI models in all basins. A comparison was made between these artificial intelligence approaches which emphasized the superiority of wavelet-GEP over the other intelligent models with amount of RMSE 18.978, 6.774, 9.639 and 318.363 mg/l, in Nazlu Chay, Tajan, Zayandeh Rud and Helleh basins, respectively.

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Authors and Affiliations

  1. Water Engineering Department, Faculty of Agriculture, Urmia University, Urmia, Iran

    Majid Montaseri & Sarvin Zaman Zad Ghavidel

  2. Water Engineering Department, Faculty of Agriculture, University of Kurdistan, Sanandaj, Iran

    Hadi Sanikhani

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  1. Majid Montaseri
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  2. Sarvin Zaman Zad Ghavidel
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Correspondence to Sarvin Zaman Zad Ghavidel.

Appendix

Appendix

See Tables 10, 11, 12.

Table 10 Main characteristic of the Köppen climate major groups and sub-types (Chen and Chen 2013)
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Table 11 1D Daubechies wavelet values of TDS variable
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Table 12 Equations of optimal single GEP models in studied basins
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Montaseri, M., Zaman Zad Ghavidel, S. & Sanikhani, H. Water quality variations in different climates of Iran: toward modeling total dissolved solid using soft computing techniques. Stoch Environ Res Risk Assess 32, 2253–2273 (2018). https://doi.org/10.1007/s00477-018-1554-9

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