DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION

Year 2016, Volume: 8 Issue: 3, 19 - 26, 01.12.2016

Özlem Terzi Tahsin Baykal

Abstract

The accurate estimation of the amount of suspended sediment of rivers is important in water resources
engineering because sediment in rivers can also shorten the lifespan of dams and reservoirs. For this purpose, the
models are developed to estimate suspended sediment of Kızılırmak River using the data mining process. The
river flow values are used as input parameter by developing sediment models. The most appropriate model is
obtained by the M5’Rules algorithm. The determination coefficient of the model is obtained as 0.66 and it is
observed that the data mining process can be used to estimate suspended sediment of rivers in hydrology field.

Keywords

sediment, data mining process, M5'Rules, Kızılırmak River

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