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Rating Irrigation Canals Using Cognitive Indexes

  • Mrinmoy MajumderEmail author
Chapter

Abstract

The main objective of this investigation was to identify an optimal configuration to enable irrigation canals to withstand future uncertainties from climate change and uncontrolled urbanization. To accomplish this objective, a set of factors was selected based on their influence on the stability and functionality of irrigation canals. The selected factors were of two types: conducive, which increase the efficiency of irrigation canals, and deductive, which decrease it. All the variables were rated with respect to their capacity to increase efficiency on a scale of one to nine, where nine is assigned for efficiency-increasing ability and one is assigned to efficiency-decreasing abilities. All possible combinations one the nine-point scale rating of the factors were created to make a combinatorial data matrix that represents every possible situation that might arise in an irrigation canal. The data set was then clusterized with the help of guided neuroclustering methods (GNCM) and an agglomerative decision tree algorithm (DTA). According to the clusterization and comparison of the two methods, the sample with the optimal configuration that both clustering algorithms had selected within their optimal clusters was identified. The selected combination was recommended in the construction of new canals to increase the canals’ longevity. According to the clusterization method, flow volume in the canal can be semihigh, but variation in the flow must be very low. Channel loss and demand from farmers must be semi and extremely low, respectively, and there should be as many buffer ponds as possible and the contribution from groundwater must be maximized. The amount of sedimentation must be minimized. That is, an irrigation canal must be developed in such a way that demand from farmers is highly regulated. A large number of buffer ponds must be created in and around the canal. Preventive measures must be strictly imposed to control inflow volume, channel loss, flow turbulence, and sedimentation. Infrastructure to store excess water must be available so that excess water from extreme events can be stored for use in times of high demand. Only canals with the above recommended configurations will be able to withstand the vulnerabilities that will arise in the near future from abrupt changes in climate and uncontrolled growth in urban populations.

Keywords

Irrigation canals Decision tree algorithms Neuro-clustering 

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.School of Hydro-Informatics EngineeringNational Institute of Technology Agartala, BarjalaJiraniaIndia

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