توزیع آب در خاک تحت آبیاری قطره‌ای توسط تحلیل گشتاور با کاربرد دبی‌های مختلف

نویسندگان

1 دانشجوی کارشناسی ارشد، گروه مهندسی آب، دانشکده کشاورزی، دانشگاه تبریز، تبریز

2 دانشگاه تبریز

3 عضو هیأت علمی دانشگاه تبریز

4 گروه مهندسی آب، دانشکده کشاورزی، دانشگاه تبریز

چکیده

در طراحی سیستم آبیاری قطره‌ای، تحلیل گشتاور یک روش با کار آمدی بالا، جامع و گسترده برای توصیف توزیع مکانی آب است. در واقع، مقادیر آب موجود در یک سطح معین از خاک تابع مجموعه‌ای از ویژگی‌های فیزیکی خاک است که تخمین آن نیازمند تعیین داده‌های گسترده‌ای می‌باشد که مجموعه این عوامل به صورت کلی می‌تواند با گشتاورهای درجه اول و دوم آب خاک بیان گردد. در این تحقیق، به‌منظور ارزیابی و تعیین قابلیت روش گشتاوردر برآورد مقادیر آب توزیع شده در خاک توسط آبیاری قطره‌ای سطحی، سه دبی خروجی 2 ، 4 و 6 لیتر بر ساعت به‌کار گرفته شد. برای شبیه‌سازی عددی جریان آب در خاک تحت سه دبی مذکور نرم افزار هایدروس دوبعدی اجرا گردید. نتایج حاصل از شبیه‌سازی برای سه دبی با لحاظ زمان‌بندی متناسب با حجم ثابت آب کاربردی 12 لیتر، برای تعیین محدوده و نحوه توزیع رطوبت در خاک به‌کار برده شد. ابتدا صحت‌سنجی‌ مقادیر حاصله بر مبنای مقایسه با آزمایش‌های تجربی انجام شده و محاسبه مقادیر گشتاورهای مربوط به نحوه توزیع آب در خاک در محیط نرم افزار متلب به انجام رسید. نتایج نشان داد که گشتاورها قابلیت بیان موقعیت مرکز جرم آب توزیع شده در خاک و نحوه توزیع آن نسبت به محورهای x و z را دارا می‌باشند. محدوده توسعه رطوبتی خاک با تطبیق بهینه یک بیضی بر مبنای مقادیر گشتاورهای حاصله شبیه‌سازی گردید. در نهایت نتیجه گرفته شد که مدل تحلیل گشتاور روشی مناسب برای مطالعه نحوه توزیع رطوبت آب در خاک تحت آبیاری قطره‌ای است.

کلیدواژه‌ها


عنوان مقاله [English]

Distribution of Water in Soil under Drip Irrigation by Moment Analysis using Different Discharges

نویسندگان [English]

  • Samira Moslemi 1
  • Amirhossein Nazemi 2
  • SEYEDALIASHRAF SADRADDINI 3
  • Saeed Samadianfard 2
  • Fatemeh Mikaeili 4
1 M.Sc., Dept. of Water Eng., Faculty of Agric., University of Tabriz, Iran
2 Tabriz University
3 Prof.,
4 Dept. of Water Eng., Faculty of Agric., University of Tabriz, Iran
چکیده [English]

Background and Objectives: Water shortage and the need for its optimal use in arid and semi-arid regions, including Iran, has led water officials and farmers to use modern irrigation systems, such as drip irrigation with the aim of making optimal use of water resources. Drip irrigation has been welcomed in most parts of the world due to its high efficiency and the possibility of irrigation in different environmental conditions. The most important reason for the superiority of drip irrigation over other irrigation methods is the controllable amount of water for each plant. Drip irrigation is a method in which water is poured out of the net at low pressure through an orifice or device called an emitter and dripped into the bottom of the plant. This irrigation system, like other methods, requires accurate knowledge of the parameters affecting it to achieve the desired efficiency. One of the most important parameters for the irrigation system is the distribution of moisture in the soil and in fact the shape of the moist bulb. Therefore, knowledge of how to distribute water in the soil is essential for the proper design and management of subsurface drip irrigation systems. Since testing is very difficult and time consuming to detect the shape of moisture distribution in the soil, the use of numerical and analytical simulation can be an effective and efficient way to design these systems.
Methodology: In order to determine the progress of the moisture front in drip irrigation, first the soil texture type and physical properties of the soil were determined. It should be noted that the emitter flow rate was measured and adjusted in volume at the beginning of the test to minimize the difference between the emitter flows along the three side tubes. Evaluation experiments were performed with three outflows of 2, 4 and 6 liters per hour. With the start of the system, the progress of the moisture front at different times was measured by digging a trench using a scale. Numerical simulation of moisture front progress was performed using HYDRUS model based on Richard equation and analytical simulation was performed using Moment Analysis. HYDRUS software was used to numerically simulate the progress of the moisture front. The simulation range was considered to be 100 cm by 100 cm on the two-dimensional plane. In these simulations, 3956 nodes are used to represent the entire simulation range and also, relevant equations were used to calculate the two-dimensional spatial Moment of the wetting pattern.
Findings: The simulations show that the initial volumetric moisture content is 0.11 and the saturation volumetric moisture content is 0.380 and the water dispersion rate increases over time on the x and z axes. With increasing flow, the maximum dispersion is in the x-axis, which occurs in flow of 6 liters per hour. The result for flow of 6 liters per hour based on the data used is slightly higher than the desired value. The reason why the value of M00 in the flow rate of 6 liters per hour is higher than expected, is that in the simulation flow rate of 6 liters per hour change in the size of the inlet diameter and the amount of flux changes the amount of water entering the soil and moistens a large volume of soil. Due to the different amount of moisture applied to the area at different times, the value of z_c,σ_x^2,σ_z^2 is different and has caused a change in the size of the oval in different flows. The increase in the size of the ovals indicates the high dispersion of water in that area. The results showed that the Moment analysis was able to express the position of the center of mass of water distributed in the soil with correlation coefficient of 0.986 in linear mode and 0.982 in logarithmic mode. By comparing the values of diameter and depth obtained from the HYDRUS and the drawn ovals, it can be concluded that both methods provide close results. The accuracy of the Moment analysis method in simulating different types of moisture patterns resulting from drip irrigation under different flows with the use of different volumes of water is similar to the HYDRUS model and therefore it is possible to use this feature to predict the pattern of moisture from a certain flow using a specific volume of water.
Conclusion: In this study, the accuracy of Moment analysis in simulating various moisture patterns resulting from drip irrigation under different flows with the use of different volumes of water was investigated and the possibility of using this feature to predict the pattern of moisture from a given flow using a specific volume of water checked. In order to investigate the Moment of the amount of water distributed in the soil by subsurface drip irrigation, simulation was performed by two-dimensional HYDRUS software for three discharges of 2, 4 and 6 liters per hour with an inlet water volume of 12 liters. Then, using the results of simulation of moisture distribution range by a programming language including MATLAB software, and by calculating the Moments, it was determined that the Moments are able to express the position of the center of mass of water distributed in the soil and how it is distributed relative to x and z axes. The increase in the size of the ovals indicates that more water is distributed in that area. Comparing the diameters and depths of the moisture front between the simulated HYDRUS model and the Moment analysis model, it was found that the Moment analysis is an efficient way to study the distribution of water moisture by drip irrigation and this method can be used as an alternative input to estimate parameters.

کلیدواژه‌ها [English]

  • Drip Irrigation
  • Emitter
  • HYDRUS
  • Moment Analysis
  • Wetting Front
Alizadeh A,1998. Principles and Operation of Drip Irrigation.  Astan Quds Razavi, Mashhad. (In Persian with English abstract)
Farajzadeh K, 2014. Simulation of pulsed drip irrigation and determination of wet diameter and depth and the most appropriate cut-off ratio. MSc Thesis, University of Tabriz. (In Persian with English abstract)
Gee GW and Bauder JW, 1986. Particle-size analysis. Pp.383-411. In: Klute A, (Ed.) Methods of Soil Analysis. Part 1. 2nd Ed., Agron. Monogr. 9. ASA-SSSA, Madison, WI.
Kandelous M and Simunek J, 2010. Numerical simulations of water movement in a subsurface drip irrigation system under field and laboratory conditions using HYDRUS-2D. Agricultural Water Management 97:1070-1076.
Karimi B, Sohrabi T, Mirzaei F and Ababaei B, 2015. Developing equations to predict the pattern of soils moisture redistribution in surface and subsurface drip irrigation systems using dimension analysis. Journal of Water and Soil Conservation, 21(6): 223-237.
Karimi B, Mohammadi P, Sanikhani H, Salih SQ and Yaseen ZM, 2020. Modeling wetted areas of moisture bulb for drip irrigation systems: An enhanced empirical model and artificial neural network. Computers and Electronics in Agriculture, 178, 105767.
Karimi B, Karimi N, Shiri J and Sanikhani H, 2022. Modeling moisture redistribution of drip irrigation systems by soil and system parameters: regression-based approaches. Stochastic Environmental Research and Risk Assessment 36(1):157-172.
Kazemi H, Sadraddini AA, Nazemi AH and Sanchez C, 2021. A moment analysis for modeling soil water distribution in furrow irrigation: variable vs. constant ponding depths. Water 13, 1415. https://doi.org/10.3390/w13101415
Kisi O, Khosravinia  P, Heddam S, Karimi B and Karimi N, 2021. Modeling wetting front redistribution of drip irrigation systems using a new machine learning method: Adaptive neuro-fuzzy system improved by hybrid particle swarm optimization–Gravity search algorithm. Agricultural Water Management 256, 107067.
Lazarovitch N, Warrick AW, Furman A and Simunek J, 2007. Subsurface water distribution from drip irrigation described by moment analyses. Vadose Zone Journal 6:116–123.
Lazarovitch  N,  Warrick, AW,  Furman A and Zerihun D, 2009. Subsurface water distribution from furrows described by moment analyses. Journal of Irrigation and Drainage Engineering 135:7–12.
Radcliffe D and Šimunek J, 2010. Soil Physics with HYDRUS: Modeling and Applications, CRC Press, Taylor and Francis Group: Boca Raton, FL, USA.
 
Samadianfard S, 2009. Numerical and analytical simulation of moisture front progress in drip irrigation. MSc Thesis, University of Tabriz. (In Persian with English abstract)
Samadianfard S, Sadraddini AA and Nazemi AH, 2011. Numerical and analytical simulation of moisture front progress in drip irrigation. Soil and Water Science 22(3): 1-16. (In Persian with English abstract)
Samadianfard S, Nazemi AH and Sadraddini AA, 2014.  M5 model tree and gene expression programming based modeling of sandy soil water movement under surface drip irrigation. Agriculture Science Development 3:178-190. (In Persian with English abstract)
Shiri J, Karimi B, Karimi N, Kazemi MH and Karimi S, 2020. Simulating wetting front dimensions of drip irrigation systems: Multi criteria assessment of soft computing models. Journal of Hydrology, 585, 124792.
Solat S, Alinazari F, Maroufpoor E, Shiri J and Karimi B, 2021. Modeling moisture bulb distribution on sloping lands: Numerical and regression-based approaches. Journal of Hydrology 601, 126835.
Sperling O and Lazarovitch N, 2010. Characterization of water infiltration and redistribution for two-dimensional soil profiles by moment analyses. Vadose Zone Journal 9: 438–444.
Xiong Y, Furman A and Wallach R, 2011.  Moment analysis description of wetting and redistribution plumes in wettable and water-repellent soils. Journal of Hydrology 423: 30- 42.
Yeh TCJ, Ye M and Khaleel R, 2005. Estimation of effective unsaturated hydraulic conductivity tensor using spa al moments of observed moisture plume. Water Resource Research 41, doi:10.1029/2004WR003736.
Zdankhah P and Khaledian MR, 2013. Improving model efficiency of HYDRUS-2D by considering temporal variability in soil hydraulic properties. Soil and Water Science 26(6): 1440-1449. (In Persian with English abstract)
Zhenjie Q, Jiusheng L and Weixia Z, 2017. Effects of lateral depth and irrigation level on nitrate and Escherichia coli leaching in the North China Plain for subsurface drip irrigation applying sewage effluent. Irrigation Science 35(6): 469-482