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Bakhtiar Karimi

Bakhtiar Karimi

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId: 994
Faculty: Faculty of Agriculture
Address: Dept. of Water Science and Engineering,Faculty of Agriculture University of Kurdistan. Sanandaj. Iran.
Phone: 087-33627721 (3212)

Research

Title
Determining suitable probability distribution for estimating wetting front in surface and subsurface Drip Irrigation
Type
JournalPaper
Keywords
Subsurface drip irrigation,Wetting bulb,Frequency distribution, Relative Residual Square Mean,Irrigation management.
Year
2012
Journal Journal of Elixir Agriculture
DOI
Researchers Bakhtiar Karimi ، Teymour Sohrabi ، Farhad Mirzaei

Abstract

Drip irrigation systems have a preference in selecting a suitable irrigation method in arid and semi-arid regions because of its high potential in uniform applying water in through a field. A proper management of drip irrigation system is, to some extent, dependent upon accurate understanding of wetting patterns distributions in soil under different combinations of soil type and emitter discharge rate. Using statistical distribution to estimate wetting front pattern in drip irrigation systems can improve their performance in different conditions. In this paper, the wetting area and water distribution on light, medium and heavy texture homogeneous soils in subsurface drip irrigation (SDI) and surface irrigation (DI) were evaluated. Experimental tests were carried out in a plexiglass lysimeter container with transparent walls. Emitters were buried at 15, 30 and 45 cm depths and discharge rates of 2.4, 4 and 6 L/h were applied. In this research, data of water front was divided into tree hourly periodic lengths of 2, 4 and 6. Then, with analysis of data in time series according to HYFA software output and goodness fit of Relative Residual Square Mean, suitable frequency distribution function for different conditions was evaluated. Based on relative frequency, the best fitted distribution for DI and SDI was found to be Normal and Pearson type III distribution (Moment method) and Normal distribution (maximum likelihood (method