Appropriate model for predicting adoption of modern irrigation channels (Case Study: Syakh Darnjan region in Fars province)

Message:
Abstract:

The results of various studies state that a large part of water waste is in the route of water transmission to the fields. Thus, it is essential to optimize the consumption of water by using modern irrigation channels. The purpose of this study is to evaluate predictive models of farmers’ adoption of modern irrigation channels. Therefore diffusion, economic constraints and multidimensional models were examined. The research method was correlative- descriptive and data analysed using discriminant analysis. The study was conducted in Siakh Darenjan region in Fars province. Stratified random sampling was used to collect data from 207 farmers consists of 156 adopters and 51 non-adopters of modern irrigation channel. Data for the study were acquired by the use of questionnaire. A panel of experts confirmed the “Face Validity” of the questionnaire items. A draft questionnaire was pilot-tested using a sample of 28 farmers in a village outside the study area and cronbach’s alpha coefficient for variables was calculated that confirmed the reliability of variables. The results revealed that perceived behavioral control variable in multidimensional and economic constraints models and attitude toward water organization activities in multidimensional and diffusion models are the most important distinctive variables between adopters and non-adopters groups. Also the finding indicated that multidimensional model has a higher ability in classification of adopters and non-adopters of modern irrigation channel. The survey provides multidimensional model for prediction adoption of water irrigation channel. The function obtained from this model, calculates the possibility of adoption of modern channel among farmers. Finally based on the results some practical recommendations have been provided.

Language:
Persian
Published:
Water and Soil Conservation, Volume:20 Issue: 1, 2013
Page:
29
magiran.com/p1121340  
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