Surface water quality prediction using decision tree method

Document Type : Original Article

Authors

1 Assistant Professor, Department of Water Engineering, University of Tabriz, Tabriz, Iran.

2 MSc student of Civil Engineering, Islamic Azad University of Maragheh, Maragheh, Iran.

3 Assistant Professor, Department of Water Engineering, ShahrekordUniversity, Shahrekord. Iran.

Abstract

Consideration of water quality and implementation of appropriate actions for preventing of water resources pollution is a very important issue in Iran because of surface water deficit. Sustainable development of agriculture is impossible without considering of surface water quality. Water quality control is a noteworthy issue in irrigation scheduling program of agricultural land. Since surface water quality monitoring and assessment is very expensive and time consuming. Thus, finding a cheap, simple and relatively exact method which can predict the water quality class base on minimum hydro chemical parameters would be very useful. Decision tree as one of the data mining techniques classify data sets based on a tree structure and uses for prediction base on extracting the exiting patterns and roles among data sets. In this study, the decision tree method was used to classify water quality in some hydrometrics stations located at southern side of Sahand Mountain, including Chekan, Girmizigol, Shishovan, Tazekand and Moghanjig. The water quality classes were defined based on if-then rules. The results showed that the decision tree method is able to predict the water quality classes based on small number of hydro chemical parameters with high accuracy

Keywords

References

 
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