JWSS - Journal of Water and Soil Science

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Poor performance of irrigation canals and its effect on decreasing of Agricultural water productivity require attention for their improvement. In this paper a new mathematical model is introduced which could present optimal operation considering downstream requirements of turnouts, canal inlet flow, actual constraints and real conditions of canal system. Four performance indicators of delivery including efficiency, adequacy, equity and stability are considered as an objective function in the process of optimization. Since this objective function is an implicit function of decision variables (regulation of turnouts and control structures) and hydraulic parameters, it is necessary to implement hydrodynamic model, using numerical optimization methods. SA (Simulated Annealing) technique is a numerical meta – heuristic intelligent search method which is used in combination with a hydrodynamic model (ICSS) (Irrigation Conveyance System Simulation.) for performance optimization of canal system. Theoretically it is proven that SA technique is capable of tending towards global optimum solution asymtotically. Taking short random steps in SA algorithm guarantees avoiding instability in hydrodynamic model. The developed model has been applied on E1R1 Distributary canal of Dez irrigation network for ten days. The results indicated that optimal performance improved very well in comparison with the present situation.In this model the weighting coefficients of indicators are determined using sensitivity analysis in optimization process. Consistency test on the derived coefficients shows that proposed method is appropriate. Applying weighting coefficients for performance indicators in the processes of optimization has resulted in 7 to 21 percent improvement compared to the case of equall weighting coefficients. Also, the results indicate that the developed model (ICSS-DOM) (ICSS-Delivery Optimization Model) is an efficient tool for the evaluation and optimization of irrigation canal performance, producing good and valid results in a relatively short and suitable time.

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Kernel hardness is one of the most important characterizations on end-use quality of bread wheat and also used for their marketing classification. Kernel texture, mainly controlled by one major locus (Ha) located on the short arm of chromosome 5D. Two tightly linked genes as puroindolin a , and b covered by this major locus and designed as Pina and Pinb respectively. When both puroindolines are in their ‘functional’ wild state, grain texture is soft. When either of the puroindoline alleles is absent or alter by mutation, then the result is hard texture. In this study, 61 Iranian commercial cultivars and 92 landraces were investigated for their kernel hardness and puroindoline alleles using SKCS and, PCR and cleaved amplified polymorphic sequences (CAPS) techniques respectively. Specific primers were used to amplify Pina and Pinb. The results indicated that frequency of hard, mixed and soft genotypes were 65.6, 19.6 and 14.8% respectively, in commercial cultivars and 58.7, 13 and 28.3% in landraces varieties. Among hard type of commercial cultivars, 18 and 5, genotypes have identified as Pina-D1b and Pinb-D1b respectively. Kavir was only cultivar with Pinb-D1e allele. Pinb-D1b allele was identified in two hard types of landrace varieties. Surprisingly, Pinb-D1c was not found in any varieties. Influence of the above proindoline alleles on kernel hardness showed that the SKCS hardness index of Pina-D1b was significantly higher than that of Pinb-D1b. Our knowledge about the genetic basis of kernel hardness could provide useful information in breeding programs of bread wheat.

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Because of the fact that alternative agricultural policies cannot be examined in a laboratory, the potential effects of policies must be analyzed before policy setting, and during or after the policy implementation using mathematical programming (MP) models. In this context, the consequences of increasing the acreage of colza at representative farm (RF) level of Namdan plain were analyzed using positive mathematical programming (PMP), which were improved to overcome normative character of optimization models. The main aim of PMP is to give as true a picture as possible of the situation and then simulate the behavior of farmers as parameters in which the object of agricultural policy intervention is shifted. Based on the results of this study, reduction in the acreage of wheat and bean and increase in the expected profit of RFs are the consequences of increasing acreage of colza. But, as variance of profit increases, the net impact of policy on the expected utility of RFs is not perfectly known. The results also indicated that the use of pesticide increases through introducing colza into a cropping pattern. The effect of policy on water use is different among RFs and they can't take this policy as a water demand management policy.

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As pressurized irrigation is not possible for all circumstances, the use of modern techniques in surface irrigation is essential. In this paper, BISEDOM, a new mathematical model for evaluation, design and optimization of border irrigation is introduced. The effects of weighting coefficients of indicators are investigated based on the potential to improve and the most appropriate weighting scheme in optimization process is presented. In this model, volume balance equations for hydrodynamic simulation and SA method for optimization steps are used. Due to the nature of the SA, its parameters are determined by the method of sensitivity analysis. In this model, evaluation of different combinations of decision variables (inlet flow, length, width and slope of the strip) and consequently the performance of irrigation efficiencies reagent strip in an objective function is possible. Finally, the results indicate that the proposed method for weighted indicators has significant effects on improving performance of border irrigation. Model validation results in three parts of design, evaluation and optimization in comparison with SIRMOD and asymptote method showed that the results are very close to each other. The results also indicate that the proposed model has a good efficiency in comparison with other existing models especially for optimization purposes.

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In the ICSSDOM simulation-optimization model, simulated annealing algorithm is combined with a hydrodynamic simulation model named ICSS. In this model the ability of weighting of indicators is also considered. In this study, using this model the performance of the S-L-R5 canal in the DEZ irrigation network was evaluated in a period of 10 days. With presenting a proposed method for weighting the indicators and its various options, using parametric sensitivity analysis, optimal adjustment of intake and check structures was obtained. It was found if the coefficient of each index is selected as a direct ratio of the ideal improvement potential of the indicator, the percentage of the improvement is more than the other investigated options. In addition, due to the interaction of the indicators in the multi-objective functions, the consistency of the weighting method with the nature of the optimization problem in this study has been shown. Statistically, the adequacy of the 10-day period of study was confirmed. The model validation with mathematical asymptote method shows 6% error which indicates the model is valid. For example, on the first day, based on the option three (The optimal option), the optimal gate opening for 5 intakes and one check control was between 3.9 to 14.7 Cm. In this condition optimal delivery was between 46 to 178 liters per second.

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