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Roostai, M., Sohrabi, T., Mesah, A., Ahadi, M. (2013). Risk Analysis of Maize Biomass under Climate Change Impacts(Case tudy: Pakdasht). , 26(4), 425-438. doi: 10.22092/jwra.2013.131420
Maryam Roostai; Teymour Sohrabi; Alireza Mesah; Mohammadsadegh Ahadi. "Risk Analysis of Maize Biomass under Climate Change Impacts(Case tudy: Pakdasht)". , 26, 4, 2013, 425-438. doi: 10.22092/jwra.2013.131420
Roostai, M., Sohrabi, T., Mesah, A., Ahadi, M. (2013). 'Risk Analysis of Maize Biomass under Climate Change Impacts(Case tudy: Pakdasht)', , 26(4), pp. 425-438. doi: 10.22092/jwra.2013.131420
Roostai, M., Sohrabi, T., Mesah, A., Ahadi, M. Risk Analysis of Maize Biomass under Climate Change Impacts(Case tudy: Pakdasht). , 2013; 26(4): 425-438. doi: 10.22092/jwra.2013.131420

Risk Analysis of Maize Biomass under Climate Change Impacts(Case tudy: Pakdasht)

پژوهش آب در کشاورزی
Volume 26, Issue 4, June 2013, Pages 425-438    PDF (422.8 K)
Document Type: Research Paper
DOI: 10.22092/jwra.2013.131420
Authors
Maryam Roostai* 1; Teymour Sohrabi2; Alireza Mesah3; Mohammadsadegh Ahadi4
1MSc student, Irrigation and Reclamation Engineering Dept., University of Tehran
2Professor of Irrigation and Reclamation Engineering Dept., University of Tehran
3Assistant Professor of Irrigation Engineering Dept., College of Abureihan, University of Tehran
4Project Assistant for Climate Change Enabling Activity (UNDP-GEF), Department of Environment, National Climate Change Office
Abstract
A variety of factors contributing to food insecurity should be evaluated precisely. Among these factors, climate change has the major influence. This study evaluates risk analysis of maize biomass under climate change in the period of 2010-2039, in a maize field in Pakdasht (east of Tehran, Iran) using AOGCM uncertainties. Climate Change scenarios were derived from 9 climate experiments (9 AOGCMs under A2 emission scenario) for two time periods (1971-2000 and 2010-2039). Beta probability density function (pdf) was fitted to these scenarios and 2000 samples of temperature and rainfall of climate change scenarios were produced. Also, their cumulative distribution functions (cdf) were depicted and changes of temperature and rainfall at 25%, 50%, and 75% risk levels were extracted. LARS-WG model was used for statistical downscaling of data and AquaCrop model was employed in simulation of maize biomass for future period (2010-2039).Descending trend was detected from biomass simulation in future period. At 50 % risk level, decreasing biomass was 1.21 ton per hectare in full irrigation treatment and 1.42 ton per hectare in deficit irrigation treatment. Risk analysis results showed that difference between 25% and 75% risk’s biomass amount in full and deficit irrigation were 0.7 and 0.5 ton per hectare, respectively.
Keywords
AOGCM uncertainties; LARS-WG model; AquaCrop; Simulation of biomassi
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