Application of a data mining approach to derive operating rules for the Eleviyan irrigation reservoir

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Date

2012-01-01

Author

Sattari, M. Taghi
APAYDIN, HALİT
ÖZTÜRK, FAZLI
Baykal, Nazife

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Optimum irrigation reservoir operation is a significant issue for water management decision makers. In this study, we used 4 different datasets of monthly amounts of water to be released from the Eleviyan irrigation reservoir in Iran as inputs in a data mining model; "if-conditional" operating rules were determined as outputs. Operating rules derived from data mining and rules obtained from an optimization model were in high concordance, especially between the 2 datasets from the preconstruction period, with differences in only 12 of 252 instances (252 months) used to compare the 2 methods. Operating rules determined for the preconstruction period using the data mining method were also consistent with optimum operating rules determined either by optimization or Monte Carlo simulation. Thus, we concluded that the decision tree subtechnique of data mining is an appropriate method for determining meaningful operating rules for the reservoir.

Subject Keywords

Water resource management, Optimization, Operational research, Operating rules, Monte Carlo simulation, Decision tree, Data mining

URI

https://hdl.handle.net/11511/32164

Journal

LAKE AND RESERVOIR MANAGEMENT

DOI

https://doi.org/10.1080/07438141.2012.678927

Collections

Graduate School of Informatics, Article

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Citation Formats

M. T. Sattari, H. APAYDIN, F. ÖZTÜRK, and N. Baykal, “Application of a data mining approach to derive operating rules for the Eleviyan irrigation reservoir,” LAKE AND RESERVOIR MANAGEMENT, pp. 142–152, 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32164.