Using CART algorithm in predicting groundwater table fluctuations inside and outside of an irrigation system (case study: irrigating area of Qazvin)

Document Type : Research Paper


1 University of Zabol

2 Dept. of Water Engineering, Faculty of Water and Soil, University of Zabol.

3 Associate Professor, Dept. of Irrigation and Drainage, Faculty of Agriculture and Natural Resources, University of Tehran

4 Assistant Professor, Dept. of Water Engineering, Faculty of Agriculture, University of Zanjan


Due to importance of predicting groundwater table fluctuations as an important and key factor in agricultural activities, the main aim of this study is finding the model and effective factors in predicting groundwater table fluctuations by using CART tree algorithm in data mining package of "SPSS modeler 18.0 IBM", in Qazvin irrigating area during 15 years from 2001 to 2015. Input variables to the model were the degree of effectiveness of each piezometer, net water requirements, the amount of consumption in each piezometer, rainfall depth, inflow and outflow from Taleghan reservoir, cropping area, and inflow to the irrigation system, the model output as objective function is groundwater table fluctuations. The predictability of the model was determined by the criteria such as correlation coefficient and mean absolute error. The results showed that the performance of the CART algorithm in predicting water table fluctuations inside the irrigation system is better than the outside of it. Furthermore, the results show that the most important parameter effective in predicting groundwater table fluctuations inside of the irrigation system is inflow to reservoir.


Main Subjects

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