Performance Assessment of Some Irrigation Networks in the World Using Benchmarking and Data mining Techniques

Document Type : Research Article

Authors

1 Department of Irrigation and Drainage Engineering, Campus of Abouriahan, University of Tehran

2 College of Aboureyhan, University of Tehran

Abstract

Abstract
The objective of the present study is to assess the performance of 18 irrigation districts from ten countries in the world using the Benchmarking method and data mining analysis (cluster analysis). Irrigation networks of Dez, Sefidrood, Tajan and Voshmgir from Iran have been compared with 14 irrigation districts from nine other countries. The k- means algorithm was used to analyze the performance indicators, thereby enabling irrigation districts to be classified into seven statistically homogeneous groups. The results showed that the irrigation districts without any canal coverage and irrigation districts with 100% of concrete coverage in the main canal and 50% in the secondary canals may be classified into a homogeneous group due to drainage water recycling system. In other words, canal coverage and drainage water recycling may prepare an appropriate water delivery condition. Land-leveling plays an important role to improve yield production in the irrigation districts. Increasing 1.5 to 2 t ha-1 in yield production for Bani amir district of Morocco and Office du niger of Mali due to the implementation of land-leveling has been experimented. The evaluation indicated that water user association (WUA) is another factor to improve the management process of the irrigation districts. The economic indicators in Voshmgir area have a high value because of the WUAs and managing around 70% of the irrigated areas by them. Lack of these organizations in the Dez irrigation district, increased the amount of annual relative irrigation supply indicator to 3.08. This indicator in Office du niger district with the WUAs is just 0.12. Benchmarking and data analysis techniques are powerful tools to evaluate efficiency in irrigation districts.

Keywords: Benchmarking, Cluster analysis, Data mining, Irrigation district, Performance assessment

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