Irrigation
Seyed Abolghasem Haghayeghi Moghaddam; Fariborz Abbasi; Abolfazl Nasseri; Peyman Varjavand; Sayed Ebrahim Dehghanian; Mohammad Mehdi Ghasemi; Saloome Sepehri; Hassan Khosravi; Mohammad Karimi; Farzin Parchami-Araghi; Mustafa Goodarzi; Mokhtar Miranzadeh; Masoud Farzamnia; Afshin Uossef Gomrokchi; Moinedin Rezvani; Ramin Nikanfar; Seyed Hassan Mousavi fazl; Ali Ghadami Firouzabadi
Abstract
Introduction
The basic strategy to mitigate water crisis is to save agricultural water consumption by increasing productivity, which will result in more income for farmers and sustainable production. Due to the economic importance of barley production in the country, it is necessary to study the volume ...
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Introduction
The basic strategy to mitigate water crisis is to save agricultural water consumption by increasing productivity, which will result in more income for farmers and sustainable production. Due to the economic importance of barley production in the country, it is necessary to study the volume of irrigation water and water productivity to produce this strategic product. Based on extensive field research on irrigation water management and application of different irrigation methods in barley farms, the innovations of this research were: a) measuring water consumed and determining water use efficiency in barley production, b) the up-to-date of the measurements and research findings, c) findings applicability for application in agricultural planning at the national and regional levels, d) the ability to development the findings in barley farms at the national level to improve water use efficiency. The hypotheses of this research are: a) barley irrigation water is various in different regions, b) water applied in barley farms is more than the required one, c) the water use efficiency of barley is different in the main production areas, and d) The applied water of barley is not the same in different irrigation methods. Therefore, the main objective of this study is to determine the water consumed and water use efficiency in barley production; to measure the water applied to barley farms in the main production areas; to compare the water measured in the production areas with the net irrigation requirement; and finally to determine water use efficiency of the barley in the main production areas in the Iran.
Materials and Methods
For this purpose, the volume of irrigation water and barley yield in 296 selected farms in 12 provinces (about 75% of the area under cultivation and production of barley in Iran) including Khuzestan, East Azerbaijan, Ardabil, North Khorasan, Fars, Khorasan Razavi, Tehran, Semnan, Markazi, Isfahan, Hamedan and Qazvin were measured directly. Farms in the mentioned provinces were selected to cover various factors such as irrigation method, level of ownership, proper distribution and quality of irrigation water. By carefully monitoring the irrigation program of selected farms during the growing season, the amount of irrigation water for barley during one year was measured. At the end of the season and after determining the average yield of barley during the 2020-2021 year, the values of irrigation water productivity and total water productivity (irrigation+effective rainfall) were determined in selected barley farms in each region. The volume of water supplied was compared with the gross irrigation requirements estimated by the Penman-Monteith method using meteorological data from the last ten years, and compared with the values of the National Water Document. Analysis of variance was used to investigate the possible differences in yield, irrigation water and water productivity in barley production.
Results and Discussion
To assess the reliability of statistical analysis, we evaluated the sufficiency of the number of measurements needed for both the quantity of irrigation water and the ley yield on the farms. Subsequently, we computed statistical indices, such as the mean and standard deviation. The results showed that the number of measurements of irrigation water and barley yield was to be 296 and 283, respectively, which was more than the number of measurements required for irrigation water (41 dataset) and yield (50 dataset). Therefore, the sufficiency of the data for the statistical analysis was reliable. The results showed that the difference in yield, volume of irrigation water and water productivity indices were significant in the mentioned provinces. The volume of barley irrigation water in the studied areas varied from 1900 to 9300 cubic meters per hectare and its average weight was 4875 cubic meters per hectare. The average barley yield in selected farms varied from 1630 to 7050 kg ha-1 and the average was 3985 kg ha-1. Irrigation water productivity in selected provinces ranged from 0.22 to 1.53 and its weight average was 0.90 kg m-3. Average gross irrigation water requirement in the study areas by the Penman-Monteith method using meteorological data of the last ten years and the national water document were 4710 and 4950 cubic meters per hectare, respectively. Irrigation efficiency of barley fields in the country is estimated at 62-65% without deficit irrigation.
Conclusion
In order to reduce water consumption and improve water productivity, it is suggested to manage water delivery to farms during the season and deliver water rights to them according to crops water requirements. To reduce water losses and enhance productivity in the barley farms, it is suggested the application of modern irrigation systems according to the farms conditions with the suitable operation; and modification and improvement of surface and traditional irrigation methods. Note that, water is only one of several necessary and effective inputs in the optimal and economic production of barley. On the other hand, attention should be paid to the optimal application of other inputs including: seeds, fertilizers, equipment and tools etc.
Abolfazl Nasseri
Abstract
Introduction: Due to sensitiveness of flow to roughness coefficient (RC), selection of this coefficient is important in earth canals designing purposes. Precision selection of this coefficient is necessary for design and operation of earthen canals purposes. Overestimation of the actual amount of this ...
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Introduction: Due to sensitiveness of flow to roughness coefficient (RC), selection of this coefficient is important in earth canals designing purposes. Precision selection of this coefficient is necessary for design and operation of earthen canals purposes. Overestimation of the actual amount of this coefficient will cause an underestimation for flow velocity. Accordingly, sedimentation in the earth canals will reduce canals’ capacitances. Adversely, underestimation of this coefficient will cause an overestimation for flow velocity and water flux in the earth canals. It will also increase the risk of soil erosion in the channels. This coefficient is expressed by Manning, Chezy and Darcy Weisbach equations. While, hydraulic engineers have selected Manning equation to estimate the flow rate in open channels due to ease of use and acceptable precision in the application of this equation. Water for crop production in Moghan, as one of the most important agricultural centers in Iran, is supplied from Moghan-Meel diversion dam via main canal of irrigation and drainage network with a capacity of 80 m3 s-1 with a length of 116 km. All of the branched 63-channel from the main channel are earthen. Continual sedimentation in the earth canals reduced the capacity of them and re-estimation the capacity of this canals needs to the precise quantities of variables such as roughness coefficient. Because the overestimation of the actual value of the coefficient would reduce the canals’ capacity and underestimation of the coefficient increase the risk of erosion in earth canals. The analysis of the correlation among variables, regression, analysis of statistical distribution of variables, analysis of variance of variables and the analysis of the events probabilities for stochastic variables can be made by statistical methods. Therefore, these methods were applied to analysis of roughness coefficient in the earth canals. Also, due to the importance of roughness coefficient and significant sensitivity of the capacity to this coefficient, the current study was conducted to statistically analyze and to evaluate roughness coefficients in non-vegetated canals for irrigation and drainage network of Moghan (in North-west of Iran). The results of the research may be applied in the design, evaluation and utilization of networks, especially in the irrigation and drainage network of Moghan.
Materials and Methods: Experimental area was Moghan plain located at the north-west of Iran with latitude from 39º 22’ to 39º 45’ N, longitude from 47º 22’ to 47º 45’ E and sea level of 32.0 m. The annual averages air temperature, relative humidity and pan evaporation are 14.5º C, 72% and 111 mm month-1, respectively. Annual rainfall in this plain is 332 mm. In the network of Moghan, 50 sections were selected to measure water flow velocity (with a flow meter) and canals cross sections (with profilimetery devices). The selected sections were in earth canals located at the farms of Agro-Industrial Company of Moghan, farmers’ farms, Pirayvatlu’s farms, Iranabad, Hajhazar, Farms of Agricultural Education Center and Agricultural Research Center. A flowmeter (type AOTT) made by Iranian Water Resources Engineering Company was applied to measure flow velocity in different sections of the channel. Resistance coefficient were determined by the following equation according to the dimensions and the velocity of the water flow in the earth canals
(1)
Where R is the hydraulic radius (m), V is velocity (m/s) and S is channel slope (m/m).
In this study, the Reynolds number was applied to determine the flow regime in the channel. The partial correlation coefficient was used to determine the effective variables in the roughness coefficient in canals without vegetation. The application of the coefficient of correlation is that the dependent variable (multiple independent variables) and independent stay in the form of fixed values of other independent variables. The software’s of SPSS and Minitab were used in statistical analysis.
Results and Discussion: Roughness coefficients averaged 0.06. Results revealed that RC varied from 0.014 to 0.050 (and more than) for 90 to 40% probabilities in non-vegetated canals. Also, flow velocity, hydraulic radius, cross section area, wetted perimeter and roughness coefficient were lognormal in distributions.
Results also showed that flow regimes were turbulent and with increase in Reynolds numbers, roughness coefficients decrease. Sensitivity analysis of flow rate to roughness coefficient showed that with increase as 200 and 300 percent in roughness coefficients, flow rates were 0.50 and 0.33 of flow rate from average roughness coefficient. Moreover,
A simple regression model was developed based on effective variables (viz. flow velocity and canal slope) on roughness coefficient by omitting non-effective variables in non-vegetated canals. Developed model was as follows:
(2) R2=0.99
The variables of the model were previously introduced earlier. The coefficient of determination (R2) shows that more than 99% variations in RC could be explained by flow velocity and canal slope.
Conclusion: Roughness coefficient in the earth non-vegetated canals was successfully and precisely evaluated for irrigation and drainage network of Moghan (in North-west of Iran) by statistical methods. Roughness coefficients averaged 0.06. The sensitivity of canal discharge to roughness coefficient was significant. It is recommended to select and apply actual values of this coefficient in engineering or computing purposes. By omitting non-effective variables in roughness coefficient in non-vegetated canals, a simple regression model with R2 of 0.99 was developed based on effective variables. In this study, the role of vegetation in channel for roughness coefficient was not evaluated. Therefore, it is recommended that the effect of different vegetation on roughness coefficient tobe evaluated with models such as hydrodynamic and zero-inertia.
