Multivariate Regression Method and Artificial Neural Network (ANN) in Modeling Ground Water Salinity in the Coastal Areas of Mazandaran Province, Iran

Document Type : Research Paper

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Abstract

Scarcity of water resources in spite of burgeoning population makes them important and necessitates optimum use of these resources. Shallow groundwater is a resource that has been ignored in irrigation management, while it is an available free source of water which can provide at least part of plants water requirement. Therefore, a two-year experiment was conducted in 2009-2011 to find the effect of shallow groundwater tables, at 60, 80, and 110 cm depth, on water requirement, water use efficiency (WUE) and yield of three wheat cultivars, namely, W33g, Cross Alborz,  and  Bahar. Experiments were performed at RaziUniversity lysimeter research station No1 as a randomized complete block factorial experiment with three replications. In these experiments, 45 tubular poly ethylene lysimeters with 1.20m height and 0.30m diameter were fixed in the ground with 1m distance from each other. The highest utilization of groundwater was found for the water table depth of 60 cm and the lowest was found for the 110 cm depth. The 2-year average contribution to different cultivars by groundwater in depths of 60, 80, and 110 cm was 63%, 55% and 45%, respectively. The results for Cross Alborz cultivar showed no significant difference (P<0.01) in WUE between the three water table depth treatments. Overall, the optimum WUE and yield was found at water table depth of 80 cm.

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Journal of Water Research in Agriculture
Volume 26, Issue 3
May 2012
Pages 355-365

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