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Agricultural Water Foot Print and Virtual Water Budget in Iran Related to the Consumption of Crop Products by Conserving Irrigation Efficiency

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Journal of Water Resource and Protection 2012年第5期4卷 318-324页

作者： Azam Arabi Amin Alizadeh Yaser Vahab Rajaee Kazem Jam naser niknia Ferdowsi University of Mashhad Mashhad Iran Regional Water Authority Company of Razavi Khorasan Mashhad Iran Water Engineering Department Azad University of Ferdows Iran Water Engineering Department Shiraz University Shiraz Iran

In this study we estimate agricultural water footprint and its components from consumption perspective in arid and semi-arid region like Iran. This study is based on blue water consumption in irrigated land. Iran has imported net virtual water about 11.64 billion cubic meters (bcm) as international crop trade in 2005-2006. Therefore, Iran has depended on virtual water imports. By conserving about 60% irrigation efficiency, the total water requirement to produce imported crops in Iran is nearly 20.78 billion cubic meters. It is nearly 9 percent of renewable water resources and 12.65% agricultural appropriated water which has added to internal water resources. Agricultural virtual water budget is about 112.78 Gm3/yr. Agricultural water footprint is 110.2 Gm3/yr. About 12.83% of agricultural water footprint of Iran is related to external water resources on the country boundaries. It means external water footprint. Water dependency, water self-sufficiency and water scarcity indexes in agricultural sector of Iran, are estimated 10.1%, 89.9% and 70.8%, respectively.

关键词： Water Footprint Virtual Water Trade Blue Water Resource Water Budget

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Application of Gamma Test and Neuro-Fuzzy Models in Uncertainty Analysis for Prediction of Pipeline Scouring Depth

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Journal of Water Resource and Protection 2014年第5期6卷 514-525页

作者： naser niknia Hossein Kardan Moghaddam S. M. Banaei Hassan Torabi Podeh Fereydoon Omidinasab Azam Arabi Yazdi Agricultural Meteorology Department of Water Engineering Ferdowsi University of Mashad Mashhad Iran Agriculture Faculty Lorestan University Khoramabad Iran Department of Water Engineering Lorestan University Khoramabad Iran Faculty Member of Birjand University of Technology Birjand Iran Faculty Member of Birjand University Birjand Iran Structural Eng. Lorestan University Khoramabad Iran

The process involved in the local scour below pipelines is so complex as to make it difficult to establish a general empirical model to provide accurate estimation for scour. This paper describes the use of an adaptive neuro-fuzzy inference system (ANFIS) and a Gamma Test (GT) to estimate the submerged pipeline scour depth. The data sets of laboratory measurements were collected from published literature and used to train the network or evolve the program. The developed networks were validated by using the observations that were not involved in training. The performance of ANFIS was found to be more effective when compared with the results of regression equations and GT Network modelling in predicting the scour depth of pipelines.

关键词： Pipelines Local Scour Gamma Test ANFIS

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