M. Mohseni Sajadi; M. Afyuni; H. Khademi; Seyed Asadallah Mohseni Movahed; Sh. Ayoubi
Abstract
Abstract
Fluoride (F-) is an essential element for human and some animals. The fluoride concentration in irrigation water is an important index for water quality. The objective of the present study was to determine spatial variability of fluoride in groundwater and soils of some areas in Arak plain. ...
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Abstract
Fluoride (F-) is an essential element for human and some animals. The fluoride concentration in irrigation water is an important index for water quality. The objective of the present study was to determine spatial variability of fluoride in groundwater and soils of some areas in Arak plain. Therefore, during two seasons, autumn (2007) and the end of spring (2008), 87 and 92 water samples were collected from the wells, in the study area, respectively. Furthermore thirty soil samples were taken from the same positions. Fluoride concentrations in groundwater and soil samples around Arak city was measured by Ion Selective Electrode (ISE) method. The results show that the average fluoride of water samples during two seasons ranged from 0.3 to 0.06 mg/L which is below the standard level (1.5). These values were suitable for irrigation. Generally, spatial distribution in groundwater and isopiezometry maps indicated that fluoride increased where groundwater flow lines were centralized. Besides, fluoride concentration has increased in the rural zones and discharge areas. Average concentration of fluoride in agricultural and industrial areas were 1.5 and 7.5 mg/Kg respectively. Maximum concentration of fluoride belonged to industrial areas with 26.5 mg/Kg showing significant difference in 1 % scale in comparison with agricultural zone. There was negative correlation between fluoride with lime values and positive correlation with pH.
Keywords: Fluoride, Spatial variability, Groundwater, Soil, Arak plain
A. Haghverdi; K. Mohammadi; S.A. Mohseni Movahed; B. Ghahraman; M. Afshar
Abstract
Abstract
Soil salinity within plant root zone is one of the most important problems that cause reduction in yield in agricultural lands. In this research, salinity in soil profile was simulated in Tabriz irrigation and drainage network using SaltMod and Artificial Neural Networks (ANNs) models. Based ...
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Abstract
Soil salinity within plant root zone is one of the most important problems that cause reduction in yield in agricultural lands. In this research, salinity in soil profile was simulated in Tabriz irrigation and drainage network using SaltMod and Artificial Neural Networks (ANNs) models. Based on initial spatial distribution of salinity in soil profile, studying area was divided to 4 different soil and water groups and for two seasons in one year salinity was predicted. The SaltMod model was calibrated and then was applied to generate 2400 data sets for training ANN models. Some of the input data of SaltMod were used in ANN models including irrigation water depth, evapotranspiration, water table depth, rainfall, and initial soil salinity. Efficiency of genetic algorithm in training phase of ANNs was analyzed. The mean of correlation coefficient (R2) and root mean square error (RMSE) of estimated salinity in all groups was 0.8 and 0.032 respectively. In conclusion ANNs could perform well in simulation of soil salinity and it could be replaced SaltMod with enough accuracy. The results showed that overall performance of ANN models improve by applying genetic algorithm.
Keywords: Tabriz plain, Soil profile salinity, Genetic Algorithm, Artificial Neural Networks, SaltMod
S.A. Mohseni Movahed; M. Akbari
Abstract
Abstract
Due to limited water resources in agriculture, application of each strategy to economize water use and increase area under cultivation is very important. One such strategy is deficit irrigation. For optimal planning of deficit irrigation, it is necessary to determine different sensitive stages ...
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Abstract
Due to limited water resources in agriculture, application of each strategy to economize water use and increase area under cultivation is very important. One such strategy is deficit irrigation. For optimal planning of deficit irrigation, it is necessary to determine different sensitive stages of plant water shortages. In this study the effect of deficit irrigation on growth and yield of irrigated wheat (Alvand cultivar) in Hamedan area was investigated to determine crop yield response factor to water (Ky) and performance sensitivity coefficient (λi) elimination of irrigation at varios stages were used. Thus the cultivation of winter wheat in Farm of Bu-Ali Sina University was under deficit irrigation using a randomized complete block design with six irrigation treatments and three replication during two consecutive years (2004-2006). Results showed that low irrigation treatments reduced grain yield, dry matter yield and thousand kernel weight. The flowering period (with sensitivity factor of 1.96) was the most sensitive periods toward water deficit irrigation and the elimination of irrigation in this stage will reduce yield more. Elimination of Irrigation in milky doughy stage (with a coefficient of reaction 1.67) showed the most performance reaction to the low irrigation. Reduction of water use efficiency in these stages in comparison with the complete irrigation in this stages indicates irrigation in these stages are necessary. Other results indicate that one irrigation turn may be eliminated in one of the stem elongation or seed hardening stages without any significant decrease in yield and harvest index.
Keywords: Deficit irrigation, Alvand cultivar wheat, Sensitivity performance coefficient, Reaction performance coefficient, Flowering stage
S.A. Mohseni Movahed; N. Mohseni; S. Norouzpour
Abstract
Abstract
ICSSDOM is a mathematical synthetic model that was written with fortran77 and in which used SA simulation annealing algorithm like an internal loop in basic structure of ICSS hydrodynamic simulation model. This model presented by Mohseni Movahed in 1381. This model is able assess current performance ...
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Abstract
ICSSDOM is a mathematical synthetic model that was written with fortran77 and in which used SA simulation annealing algorithm like an internal loop in basic structure of ICSS hydrodynamic simulation model. This model presented by Mohseni Movahed in 1381. This model is able assess current performance and present optimal operation considering downstream requirement of turnout in real conditions and actual constrains of canal system. For performance optimization of irrigation, canals must be chosen a complete spectrum of indicators and optimized them in an objective function with utilization of optimization method. In this model, necessary actions are considered in order to appoint the relative value of indicators and also is noticed to it’s effectiveness in optimization process with sensitivity analysis. Another problem created after choosing appropriate indicators, is the lack of a standard and quantitative method for appointing their relative value. Using model, Mohseni Movahed (1381), mohseni (1384) and norozpour (1387) have assessed E1R1, E1R5 and E1L4 canals of DEZ networks respectively. In these researches, the most appropriate weighting coefficient of indicators is appointed to performance optimization of irrigation canals and applied method for mentioned coefficient is an origin basic mathematical and logical process, which doesn’t depend on any professional judgment. Although, hydraulic conditions in these canals are different, they show similar results. According to the results in all three cases, while the weighting coefficient of indicators is noticed as a direct proportion of difference between ideal and presented performance, the improvement percent is better than other conditions. The other important and new results of this research are such as: Determination of the suitable composition of SA optimization algorithm parameters and presentation a method and general vision in order to appoint the appropriate extent of Kdiv parameter relative to length of random steps in SA optimization algorithm. These results that earn after different and spreading testes of sensitivity analysis can summarize volume of testes and also can be applied as a confident criterion in future researches.
Keywords: Performance of irrigation canals, SA, ICSSDOM, Weighting factors, Sensitivity analysis
A.A. Sabziparvar; F. Tafazoli; H. Aareabyaneh; M. Mousavi baygi; M. Ghafoori; S.A. Mohseni Movahed; Z. Merianji
Abstract
Abstract
The estimation of reference evapotranspiration (ETo) is of great importance due to its applications in water resource management as well as irrigation scheduling. Difficulties associated with using lysimeters have encouraged researchers to use various ETo models, while the shortage of actual ...
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Abstract
The estimation of reference evapotranspiration (ETo) is of great importance due to its applications in water resource management as well as irrigation scheduling. Difficulties associated with using lysimeters have encouraged researchers to use various ETo models, while the shortage of actual radiation data seems the main obstacle for users of radiation-based models. In this research the output of four radiation-based evapotranspiration models including: Penman-Montieth-FAO56 (PMF56), Penman-Montieth FAO-Irmak (PMFI), modified Jensen-Haise (JH1), and Jensen-Haise (JH2) are evaluated for a cold semi-arid climate. The daily ETo values were generated for 16 different scenarios and the results were compared against a two-year lysimeter data during the growing season (May to November). Deviations of model results were investigated using mean of R2, RMSE, MBE and t-test criteria. The results indicated that the JH2 model which uses radiation model of Daneshyar, can generate the most accurate ETo values (R2>0.85, P
