Iranian Journal of Irrigation and Drainage
Year:2007 | Volume:1 | Issue:2|Papers Count:10

Proper identification of the unsteady flow in an irrigation network would lead to significant improvement in the network operation. Kinematic diffusive wave model would be considered as a useful means in this regard. However, the diffusive wave equation is a non linear in its nature and could not be solved analytically. The analytical solution of this equation could be attained provided that the equation coefficients are considered constant values. Obviously, the solution accuracy of the model relay on the apt selection of the equations coefficients. In this research the application of the effective hydraulic sensitivity approach for providing proper estimation of the coefficients of the linear diffusive wave equation was presented. The analytical solution of the diffusive wave for a sudden change in the upstream side of a channel reach discharge, which was obtained based on the proposed method, was determined and the results were compared with that of other researchers and with output of a hydrodynamic model. The results indicate that the determination of the diffusive equation coefficient based on the proposed method substantially improved the results of the diffusive equation model.

In order to investigate of water use efficiency irrigation systems study planting of one and two rows and density in Corn (SC 704) in drip irrigation (tape) and furrow, a study was conducted on randomized complete blocks as a strip split plot design with 3 replicates in Esmaeil Abad Research Station of Qazvin in 2006. Four levels of irrigation including: 80, 100 and 120 percent of water requirement with drip irrigation (tape) and 100% water requirement with furrow irrigation as main plots and method of planting (one and two rows) with three levels of crop density including: 75000, 90000 and 105000 as subplots were considered. Results showed that the highest quantity of yield obtained from drip irrigation at level of 120% water requirement in one row planting pattern and crop density equal to 90000 with 16583.52 kg/ha. The maximum of water use efficiency obtained from drip irrigation treatment at level of 80% water requirement in one row planting pattern and crop density equal to 75000 with 3.75 kg/m3. In order to water saving and extension of irrigated lands, the mentioned treatment was recommended.

This study was conducted to investigate the effect of water management on soil moisture and alfalfa (Medicago sativa L.) yield indices distribution in solid-set sprinkler system. Three experimental plots of 25*30 m were selected on a farm located in Varamin irrigation network. Each plot was subdivided into 25 subplots of 5*6 m. Different applied water and sprinkler water uniformity were achieved due to the nozzle pressure scenarios. In each subplot, irrigation depth was measured at 5 points below canopy and mean soil moisture between surface and depth of 40 cm was also monitored at center of the subplot throughout the second cutting period. Also, alfalfa hay yield, crop height, and leaf area index were measured after cutting. The results showed that sprinkler water and soil moisture uniformities varied between 66-77 % and 88-91 %, respectively. The findings revealed that soil moisture uniformity was around 18 % higher than sprinkler water uniformity. The mean range of variations of hay yield, LAI, and crop height for experimental plots were determined 3.167-3.714 t ha-1, 4.41-6.31, and 77.3-80 cm, respectively. Evaluations revealed that alfalfa leaf area index depends on water management more than crop height and hay yield. With respect to the range of variations in both applied water and sprinkler water uniformity in the experimental plots, the range of variations of water use efficiency was estimated 14.29-19.03 kg.ha-1 .mm-1. It indicated that water management has an important effect on both indices of alfalfa hay yield and water productivity.

Hydraulic properties of soils and their applications in water flow models have a marked role in solution of some managemental problems. There are many models to predict soil moisture retention curve. Such a curve was determined for three sites (silt loam, and loam) were determined. Then the performances of four common oversea PTFs (Rawls and Brakensiek, Vereecken et al., Wosten, and Wosten et al.) and four local ones (Ghorbani Dashtaki and Homaee, and Farrokhian Firuzi and Homaee) were traced. Sand table and pressure apparatus were used for soil water content values corresponding to low (0-1 meters) and high suctions (> 1 meter), respectively. All the measurements were done on undisturbed samples. A statistical evaluation test was conducted on measured and predicted water contents. Although the results were not so good, yet Vereecken et al., and Wosten PTFs, among oversea models, were relatively acceptable. The performances of both models of Ghorbani Dashtaki and Homaee, especially at higher suctions, were good. The other local PTFs of Farrokhian Firuzi and Homaee resembled unsatisfactory performance. Therefore, there is a need that suitable PTFs are to be determined for gupsum and carbonated soils corresponding especial features of Iran.

The significance of ground water as an important source of water supply is no doubt to anyone in arid and semiarid areas. Therefore prediction of ground water level fluctuations seems as important parameters for planning conjunctive use in these areas. Neyshabour plain is selected for this research because of presence of 45 pizometerics that most of them have more than 12 years data. Therefore, at first preprocessing job is done on the row data using GIS for editing and generating requirement of data in month scale in 15 selective pisometeric wells and in its thiessen polygon. Then, the performance of different artificial neural networks (ANNs) such as multi layer perceptron (MLP), Generalized Feed Forward (GFF) and Recurrent Neural Network (RNN) in a groundwater level predicting is examined in order to identify an optimal ANN architecture that can simulate the variation of the groundwater level and provide acceptable predictions in during of months ahead. The different experiment results show that GFF neural network trained with the momentum algorithm has the best results for up to 6 months forecasts. The selected performance criteria indicators such as R2=.937 and NRMSE=.378 reveals the relevance of this method

Soil is a dynamic environment which continuously affected by physicochemical and biological changes. Therefore, it is obvious that application of municipal wastewater may influence different properties of soil, especially it(s chemical characteristics. Thus, to evaluate the impact of waste water type and it's mode of application on some chemical properties of soil at different depths, an experiment was performed using polyethylene cylinders (11 cm diameter and 150 cm height) in a factorial statistical design with three replications. Raw sewage and treated effluent (from Parkandabad Treatment Plant in Mashhad) were added to the columns filled with sandy loam soils under continuously and intermittent flood conditions in 7 periods of 15 days. At the end of experiment, soil samples were taken from 0-25, 25-50, and 50-100 cm depths. The results showed that parameters such as soil Salinity, Sodium Adsorption Ratio (SAR), Nitrogen (NO-3) and Phosphorus (PO-24) Total Organic Carbon (TOC) and two heavy metals (Nickel and Cadmium) increased due to application of raw sewage and treated effluent, although pH decreased in the soil solution. The experiment showed that average soil Salinity, SAR, NO-3 PO-24 and Ni were significantly higher in raw sewage as compared to treated effluent. There was not a clear difference between pH, TOC and Cd among wastewaters used. Mode of wastewater application had significant effect on soil Salinity, PO-24 and Cd. The average amounts of these parameters were higher in continuously compared to intermittent application. Based on the above results, wastewater application needs special management whatever the objective might be. So that by sound usage of wastewater, environmental impact risks are reducing to the lowest levels in soil, plant as well as surface and ground water resources.

Estimating of crop water requirement (ET) is one of the important parameters in the designation process of irrigation systems. If in this process, mean amounts of the evapotranspiration for a several years period are being used based on the meteorological data, then the occurrence probability of that will be 50%, while it is possible that the plant will face a water challenge (stress). Therefore, in order to prevent such a problems, it has been suggested to estimate the evapotranspiration rate with different probabilities so that based on the plant geaus and agricultural management, the ET with the paper occurrence probability can be chosen and then used in the designation process of the irrigation systems. In this paper, using data from Hashem-Abad Synoptic station, Gorgan, ETo and ETp of the main agricultural products of the region for every julian day of the year in the long-term has been computed. Then, through the moving average method, the beginning and the final data of water requirement maximum circles (1 to 30 days) were been defined and Log-Normal distribution, ETo and ETp with different probabilities for these circles, were estimated. Analysing ETo and ETp amounts with different probabilities revealed that by increasing the irrigation circle the mean daily evapotranspiration decreases. Also for a specific circle by increasing the probability level, the mean daily evapotranspiration increased.

The use of treated wastewater (effluent) in irrigation of agricultural crops has become a point of attention in many arid and semi-arid regions of the world. To reduce the risk of public health issues, as well as, to increase the irrigation efficiency, the use if drip irrigation system is also advised. However, the potential for clogging of irrigation system especially those related to the drippers is increased in this practice and can become a significant economical and mangemental burden. In this research the effect of water quality management on clogging of different drippers was investigated. For this purpose, five different irrigation schemes and three types of drippers were used. The irrigation schemes included use of water, effluent, diluted effluent (50% each water and wastewater), water alternating by effluent, and effluent followed by washing the system. The drippers Types included; vortex, long path and micro-flopper. The experiment was conducted at a small-scale level at a research greenhouse located at College of Agriculutre, Ferdowsi University of Mashad. On the basis of the results, the slops of the lines showing the change in drippers? Flows versus time, were - 4.86, -5.23, and -5.87 for the treatments using diluted effluent, alternating water and effluent, and effluent followed by washing, respectively. The correlation coefficients obtained for these treatments were 0.62, 0.65, and 0.73, respectively. The results of this research showed that all the irrigation schemes included water and effluent, had a significant (p ? 0.05) impact on reduction of drippers? Clogging and as a result on increasing the flow, as compared to the irrigation scheme used effluent alone. However, the differences observed between the schemes using both water and effluent were not significant. In regard to the effect of dripper types on clogging, although micro-flopper showed a better performance, the differences observed between different types were not significant.

A field experiment was conducted during 2007 growing season at the khorassanAgl1cultural Research Center (Torogh Station). In order to achieve different water and salinity gradient in the field, two perpendicular laterals (Line Sources) were used. On lateral applied non? Saline water (1dS/m) and the other one applied saline water (6dS/m) with 3 sprinklers on each lateral. A total of 196 catch cans were placed in the center of 2x2 plots. After each irrigation the amount of water and its salinity were measured. The model simulated the maximum yield when 950 mm water was applied. This was verified by field results.However, the model in general simulated yield 10% less than what was obtained under field conditions (RMSE =10ton/ha). The Hest also showed that there is not a significant difference between sugar beet yield and the one predicted by the model.Analysis of yield data also indicated that the production of sugar beet is not influenced by water or soil salinity. The results of SWAP model showed the same trend. In general, SWAP model was found to be a useful tool in predicting yield under different irrigation regimes.