Investigation of Ability of KNN and M5 Trees Models in River Flow Modeling: Case Study Sarmo Stations

Prediction of the flow discharge accurately is a key point in the optimum planning and management of water resources. The Ghorghanrood watershed is one of the watersheds in the north of Iran that it is located in Gholestan Province. The impact of drought and rain on basic fluctuations and overall flow of the river plays a major role in planning of implementation of watershed resources. In this research, the KNN model and M5 decision tree were used as one of the methods of data-mining for estimating the flow discharge of Ghorghanrood River that it is located in Sarmo Station. In this regard, the raining and flow discharge data of Sarmo Station (in Mohammadabad) under five various scenarios by applying transfer functions on the data. The results showed that M5 decision tree has mostly superiority over KNN model and reaches more accurate prediction. Also, in the defined scenarios, the b and c models which respectively include all data and daily raining data, last day raining and two days before raining, result the most accurate estimation. These two scenarios are under the transfer function, the five-day moving mean and have R2 standard of 0.999 and MAE and RMSE standards of 0.001.