Evaluation of gene expression programming and Bayesian networks methods in predicting daily air temperature
S.
Mehdizadeh
دانشجوی دکتری آبیاری و زهکشی، گروه مهندسی آب، دانشکده کشاورزی، دانشگاه ارومیه
author
J.
Behmanesh
دانشیار گروه مهندسی آب، دانشکده کشاورزی، دانشگاه ارومیه
author
H.
Saadatnejad Gharahassanlou
دانشآموخته کارشناسی ارشد سازههای هیدرولیکی، دانشگاه آزاد اسلامی، واحد اهر
author
text
article
2016
per
Air temperature is one of the most important variables in estimating crop water requirement and climatic studies. In recent years, several intelligent models such as Gene Expression Programming and Bayesian Networks have been used to estimate air temperature. The purpose of the present research is to evaluate the accuracy of these two approaches in prediction of air temperature in a specific day (t) using data of one to seven days before, i.e. t-1 to t-7. For this purpose, a 25-years dataset of daily temperature of two stations in northwest of Iran, namely Urmia and Tabriz were collected and used for models performance comparison. The results showed that Gen Expression Programming and Bayesian Networks methods were capable to predict the minimum, mean and maximum air temperature with acceptable accuracy. However, the Bayesian networks method showed relatively better performance comparing to the Gene Expression Programming. The findings revealed that in testing stage of Bayesian networks method for Urmia station, the values of determination coefficient (R2) and root mean square error (RMSE) in the best scenario are 0.92 and 2.5 ◦C for minimum temperature, 0.96 and 1.83 ◦C for mean temperature, 0.96 ◦C and 2.3 ◦C for maximum temperature respectively. The corresponding values of statistical indices for Tabriz station in Bayesian networks method were found to be 0.93 and 2.42 ◦C for minimum temperature, 0.97 and 1.90 ◦C for mean temperature and 0.95 and 2.42 ◦C for maximum temperature. In general the mean temperature was predicted more accurately by both approaches in study stations.
Journal of Agricultural Meteorology
Iranian Society of Irrigation and Water Engineering
2345-3419
4
v.
2
no.
2016
https://www.agrimet.ir/article_54970_e5d8d6ae622beb323fe34f8c0dd34a5d.pdf
Assessment of global precipitation datasets and their application in drought monitoring (Case study: Karkhe basin, Iran)
S.M.
Hosseini-Moghari
دانشجوی دکتری مهندسی منابع آب، گروه مهندسی آبیاری و آبادانی، دانشگاه تهران
author
Sh.
Araghinejad
دانشیار گروه مهندسی آبیاری و آبادانی، دانشگاه تهران
author
K.
Ebrahimi
دانشیار گروه مهندسی آبیاری و آبادانی، دانشگاه تهران
author
text
article
2016
per
Lack of reliable long term data of precipitation, required for hydrometeorological studies, is a major challenge in most of weather stations of Iran. The present study aims to analyze the possibility of using global precipitation data as an alternative to the in situ observations. For this purpose, precipitation data collected from three global datasets namelyو APHRODITE, GPCC, and CRU were studied over a period of 30 years (1978-2007) for three synoptic stations located within Karkhe basin; Kermanshah, Khoram-Abad, and Hamedan. In addition to the total amount of precipitation the Standardized Precipitation Index (SPI) was also calculated using data retrieved from these three datasets. The obtained values were compared with observed ones. The obtained results revealed that different global databases perform differently in various climatic regions. However, in general, CRU at Kermanshah station, and APHRODITE at Khoram-Abad and Hamadan station, outperformed the others. For drought monitoring, based on annual SPI index, CRU by 83 percent of correct drought class recognition at Kermanshah station and GPCC by 83 and 70 percent of correct drought class recognition at Khoram-Abad and Hamadan stations, respectively, showed the best performance.
Journal of Agricultural Meteorology
Iranian Society of Irrigation and Water Engineering
2345-3419
4
v.
2
no.
2016
https://www.agrimet.ir/article_54971_996a138bb195b4b1b635ded9add924be.pdf
Assessment of RegCM4 model for estimation of total solar radiation (Case study: Chaharmahal and Bakhtiari province)
M.
Heidary Beni
دانشجوی دکتری آب و هواشناسی، گروه جغرافیای طبیعی، دانشکده علوم جغرافیایی و برنامهریزی، دانشگاه اصفهان
author
text
article
2016
per
The amount of energy received from the sun on the ground needed to estimate crop water use, use of clean energy and issues related to climatic factors. In this study, the ability of two estimation methods based on statistical and dynamic methods were evaluated. Angstrom, as a widely accepted statistical model, and Regional Climate Model (RegCM version 4.0) were chosen to obtain radiation estimations. To perform this study, meteorological data of 6 IRIMO’s automatic weather stations located in Chaharmahal and Bakhtiari province, west of Iran, were used. RegCM4 model was run considering initial values and boundary conditions of NNRP1 ,at 18 sigmoid levels, with spatial resolution of 30 km and temporal resolution of 150 minutes, in the period of 2010 to 2014. Results showed the RegCM4 model output has the minimum Root mean square error (RMSE) of 10 W m-2 in warm months (June to September) and highest RMSE of 408 W m-2 in February. The lowest RMSE was obtained in September in Borujen station and the highest value was recorded in month of February in Ardal. The average value of overall RMSE in the region was 175 W m-2. Monthly values of Angstrom model was calibrated for study stations. The highest correlation coefficient and lowest RMSE and MBE were obtained for September. The maximum value of RMS was 321 W m-2 in April. Angstrom model showed an underestimation in 73% of the cases while RegCM showed an overestimation 93 % of the cases. These results tend to confirm the need for post-processing of the climate model outputs.
Journal of Agricultural Meteorology
Iranian Society of Irrigation and Water Engineering
2345-3419
4
v.
2
no.
2016
https://www.agrimet.ir/article_54972_be9cd9815036969492f25e5b55ca080a.pdf
Quantitative projection of the probable impacts of climate change on date and damage risk of late spring frost during 21st century over Iran
A.
Khalili
استاد گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران
author
J.
Rahimi
دانش آموخته دکتری هواشناسی کشاورزی، گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران
author
J.
Bazrafshan
دانشیار گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران
author
text
article
2016
per
The late spring frost (LSF), as one of the main climatic disasters, has significant negative impacts on agricultural and horticultural crops production. It is expected that the features of its occurrence will be altered by climate change and global warming. Hence, the present study was performed to quantify these changes under two scenarios of A2 and A1B using CGCM3 general circulation model outputs, downscaled by ANN technique. For this purpose, daily minimum temperature data of 50 weather stations for the period of 1961-2010, representing different climatic regions of Iran, were collected and quality-controlled. Trend analysis of the regional mean of annual minimum temperature showed a significant (p
Journal of Agricultural Meteorology
Iranian Society of Irrigation and Water Engineering
2345-3419
4
v.
2
no.
2016
https://www.agrimet.ir/article_54973_5c9e6423a84bcecf0418e33f689e4188.pdf
Comparison of SDSM and LARS-WG models for simulation of meteorological variables in Northwest of Iran
B.
Sobhani
دانشیار، گروه جغرافیا، دانشکده ادبیات و علوم انسانی، دانشگاه محقق اردبیلی
author
M.
Eslahi
دانشجوی دکترای آب و هواشناسی، گروه جغرافیا، دانشکده ادبیات و علوم انسانی، دانشگاه محقق اردبیلی
author
Y.
Akbar Zadeh
دانشجوی دکتری آب و هواشناسی، دانشکده علوم انسانی، دانشگاه زنجان
author
text
article
2016
per
In this study, the performance of two statistical weather generators the Statistical Downscaling Model (SDSM) and LARS-WG in simulating daily values of rainfall, maximum and minimum temperatures in northwest of Iran is compared. The study network was consisting 12 weather stations with minuim 40 years of daily temperature and precipitation data. The 1961-1990 period was used the baseline for models evaluation. In this study, two non-parametric tests of correlation and Mann-Whitney were used in monthly basis for comparisons.Root mean square error (RMSE) was used to compare the accuracy of two models. The results showed that the skill of both model in simulating minimum and maximum temperature data is similar, but the number of month with higher correlation was more in case of using SDSM.For precipitation data, the mean RMSE values of SDSM and LARS-WG models simulations were 26.5 and 0.32 mm, respectively which indicates higher accuracy SDSM.No significant differences between the observed and simulated data were found using the Mann-Whitney nonparametric test.The number of month with significance correlation with slightly more in SDSM comparing the other model.
Journal of Agricultural Meteorology
Iranian Society of Irrigation and Water Engineering
2345-3419
4
v.
2
no.
2016
https://www.agrimet.ir/article_54974_51f22e3e9e38718640a6e0990d9ba2f6.pdf
Evaluation of economical vulnerability to climatic fluctuations (Case study: Khorasan Razavi province)
H.
Hatef
دانشجوی دکتری اقتصاد کشاورزی، گروه اقتصاد کشاورزی، دانشکده کشاورزی، دانشگاه فردوسی مشهد
author
M.
Kohansal
استاد گروه اقتصاد کشاورزی، دانشکده کشاورزی، دانشگاه فردوسی مشهد
author
M.
Bannayan
استاد گروه زراعت و اصاح نباتات، دانشکده کشاورزی، دانشگاه فردوسی مشهد
author
N.
Shahnoushi Foroshani
استاد گروه اقتصاد کشاورزی، دانشکده کشاورزی، دانشگاه فردوسی مشهد
author
text
article
2016
per
Climatic changes have severe effects on water and soil sources in any given region. To study the resulting fluctuations of climatic factors in different regions for possible adaptation policies to new climate events is of great importance. A possible approach to study the damage on economic activities caused by climatic fluctuations is to calculate vulnerability index. To achieve this goal, Vulnerability Index (VI) in the period of 1994-2014 has been calculated for 11 regions of Khorasan Razavi province. The components of climatic fluctuations vulnerability index included two types of shocks (permanent shocks and recurrent shocks). The shocks included temperature fluctuations, precipitation, floods and increasing aridity. The results of the index suggest that in Khorasan Razavi province in the period of study, Torbat heydarieh had the highest and Chenaran had the lowest economic damage from climate change. The average index of vulnerability to fluctuations in the climate Khorasan Razavi province is 47.04 (above-average vulnerability of the developing countries). It is suggested that different agencies for planning and allocating funds for negative impacts of changing climatic factors may find these indices results quite useful and beneficial for further studies.
Journal of Agricultural Meteorology
Iranian Society of Irrigation and Water Engineering
2345-3419
4
v.
2
no.
2016
https://www.agrimet.ir/article_54975_1a69e77e9e183ba5392231b262202678.pdf
Estimation of actual evapotranspiration in Qazvin plain using satellite Images and METRIC algorithm
R.
Nazari
دانشآموخته کارشناسی ارشد آبیاری و زهکشی، گروه مهندسی آب، دانشکده فنی و مهندسی، دانشگاه بینالمللی امام خمینی (ره)
author
A.
Kaviani
استادیار گروه مهندسی آب، دانشکده فنی و مهندسی، دانشگاه بینالمللی امام خمینی (ره)
author
text
article
2016
per
Proper estimation of crop water requirement is vitally important to maintain sustain crop production in arid regions, where water shortage is challenging. The aim of this study was to estimate actual evapotranspiration (ETa) of crops in Qazvin plain, Iran using satellite images and METRIC algorithm. In this regard,the obtained values of ETa by METRIC algorithm using the images of Terra satellite MODIS sensor and Landsat 7 satellite ETM+ sensor, were compared with lysimeteric measurements Results of the statistical comparisons showed that Landsat 7 ETM+ sensor with correlation coefficient of r=1.00, RMSE=0.91 mm day-1 and MAE=0.10 mm day-1 and Standard Error (SE) =0.09 mm day-1 had more acceptable agreement with measured data comparing with those obtained from MODIS sensor and can be recommended as the preferred option in the region.
Journal of Agricultural Meteorology
Iranian Society of Irrigation and Water Engineering
2345-3419
4
v.
2
no.
2016
https://www.agrimet.ir/article_54976_8b162d2a89d74d7171cbdc7ce6dc008b.pdf
Evaluation of reference evapotranspiration calculation methods and determination of Pistachio evapotranspiration in Rafsanjan
H.
Noory
استادیار گروه آبیاری و آبادانی، دانشکده مهندسی و فناوری کشاورزی، دانشگاه تهران
author
A.
Badiehneshin
دانشجوی دکتری آبیاری و زهکشی، دانشکده مهندسی و فناوری کشاورزی، دانشگاه تهران
author
A.
Mohammadi Mohammad Abadi
عضو هیأت علمی پژوهشکده پسته، موسسه تحقیقات علوم باغبانی، سازمان تحقیقات، آموزش و ترویج کشاورزی، رفسنجان
author
text
article
2016
per
The aim of this study was determination of Pestachio evapotrspitaion in Rafsanjan plain, south of Iran. For this purpose, the results of the six reference evapotranspiration (ETo) estimation equations was compared by ETo grass lysimetric measurements. Among the selected methods, Penman-Monteith FAO was found to be the best one with root mean square error (RMSE) of 1.3 mm.mm-1 and percent absolute error (PAE) equals to 17%, Kimberly-Penman, radiation and Blaney-Criddle methods were ranked next to PM equation with acceptable accuracy. Hargreaves and modified Penman method showed poor performance. Pistachio crop evapotranspiration (ETc) was determined using pistachio crop coefficients and 4 years average of lysimeteric values ETo. Based on the results, the mean Pistachio ETc was 9600 cubic meters per hectare during April to November during. Maximum of ETo and ETc occurred in July. More than 50% of ETc was observed in June, July and August which confirms the importance of maintaining sufficient water for irrigation during this period.
Journal of Agricultural Meteorology
Iranian Society of Irrigation and Water Engineering
2345-3419
4
v.
2
no.
2016
https://www.agrimet.ir/article_54977_17c9aabc9ced618a90d9716aaabfd63b.pdf