Investigation of the optimal number of soil moisture based on spatial variation of moisture for irrigation planning and soil and water resources conservation

Subject Areas : Farm water management with the aim of improving irrigation management indicators

mohadese sadat  fakhar ¹ (Dept. Water Sciences and Technology, Imam Khomeini International University, Qazvin, Iran.)
Bijan  Nazari ² (Associated Professor of Water Engineering Department, Faculty of Technical & Engineering, Imam Khomeini International University, Qazvin, Iran.)
Mahmood  Fazeli Sangani ³ (Assistant Professor of Soil Science Department, Faculty of Agriculture Science, University of Guilan, Rasht, Iran.)

Received: 2020-10-05 Accepted : 2021-07-03 Published : 2021-07-23

Keywords: Soil moisture sensors, Spatial Changes, Variogram, Kriging, Cokriging,

Abstract :

The development of an accurate for monitoring the soil moisture is very important step in soil and water conservation activities and studies. The purpose of this study is to provide solutions to optimally determine the number of sensors required to monitor soil moisture bases on geostatistical approaches and intelligent monitoring of the water status in soil. In this research, 87 samples were taken as a regular network from the surface depth (0-30) cm. Three levels of the samples number were considered. By decreasing the samples number, the estimation accuracy decreases and the component effect increases, that indicates an increase in the random and non-structural part of the property. With the high sample number, the fitness of the model was 1.2% and 2.7% more than when the average and the minimum sample number. Reducing the samples has increased the radius of effect and decreased the ratio of structural to non-structural variance of properties. So the radius of effect of field capacity when the sensors number is at its maximum level is 36.8% and 38.4% less than the other two levels, respectively. As the samples number decreases, the estimation error increases sharply. Based on the findings, the use of between 20 and 30 sensors per 100 hectares produced the best results. The kriging method was an excellent estimator for moisture mediation. The proposed method can be used in determining the optimal sensors number for irrigation planning.

References:

انصاری، ح و حسن پور، م. 1394. طراحی و ساخت REC-P55 برای خواندن رطوبت خاک، دما و شوری. مجله آبیاری و زهکشی ایران. 9 (1): 32-43.

تافته. الف.، امداد م. غالبی. س. 1396 تعیین مناسبترین شرایط آبیاری نواری به‌منظور افزایش راندمان کاربرد آب با استفاده از مدل SRFR مجله مهندسی آبیاری و زهکشی. 8 (30): 200-210.

دوستی. م. 1386. مدیریت آبیاری گلخانه با استفاده از روش­های جدید اندازه گیری رطوبت خاک. اولین کارگاه بهبود بهره­وری استفاده از آب در گلخانه، 18 مهر ، کرج ، ایران ، 18 ص.

روغنی. م. امام جمعه. ر و کمالی. ک. 1391. بررسی و ساخت سنسورهای دفن شده TDR و ارزیابی عملکرد آن در کاهش رطوبت خاک. مجله علوم و مهندسی آبخیزداری ایران. (17): 53-62

زارع ابیانه. ح.، خسرایی. الف، ابراهیمی پاک. ن. الف.، تافته. الف. و جوزی. م. 1398. انتخاب مدل بهینه نفوذ آب به خاک (مطالعه موردی: سرزمین های جهاد نصر استان خوزستان). مدیریت آب و آبیاری. 9 (2): 291-304.

شاهرخ-نیا، م. 1395. اصول و ابزار برنامه ریزی آبیاری برای مزارع و باغات. شورای تحقیقات و تحقیقات مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی فارس. 25 (4): 35-47.

قائمی الف. الف، و رحمانی ثقیه. ج 1393. بررسی عملکرد سنسورهای هوشمند به عنوان یک رویکرد جدید برای تعیین میزان رطوبت خاک. مجله آبیاری و زهکشی ایران. 8 (1): 16-25.

نامدار خجسته، د.، شرفا، م.، اسکندری، ز. و فاضلی سنگانی، م. 1390. اثرات رس و شوری بر مقدار حجم حجمی آب با استفاده از بازتاب سنجی حوزه زمانی. مجله تحقیقات خاک ایران (علوم خاک و آب سابق). 25 (2): 103-112.

Burgess, T.M., and Webster, R. 1980. Optimal interpolation., and isarithmic mapping of soil properties. European Journal of Soil Science. 31 (2): 315-331.

     Dursun, M. and Semih, O. 2011. A wireless application of drip irrigation automation supported by soil    moisture sensors. Academic Journals. 6 (7): 1573-1582.

Duan, F.; Liu, J.; Fan, Y.; Chen, Z.; Han, Q. and Cao, H. 2017. Influential Factor Analysis of Spraying E_ect of Light Hose-Fed Traveling Sprinkling System. The Journal of Irrigation and Drainage Engineering. 35: 541–546.

Ganjegunte, G.K, Sheng, Z. and Clark, J. 2012. Evaluating the accuracy of soil water sensors for irrigation scheduling to conserve freshwater. Applied Water Science. 2: 119-125.

El Marazky, M.S, Fawzi, S.M. andAl-Ghobari, H. 2011. Evaluation of soil moisture sensors under intelligent irrigation systems for economical crops in arid regions. American Journal of Agricultural and Biological Sciences. 6 (2): 287-300.

Frueh, W.T. and Hopmans, J.W. 1977. Soilmoisture calibration of a TDR multilevel probe ingravely soils. Soil Science. 162: 554-565.

Goovaerts, P. 1999 .Geostatistics in soil science: state-of-the-art and perspectives. Geoderma. 89 (1-2): 1-45.

Heaton, K. 2007. Soil moisture management with water mark sensors. Utah State University Extension, Kane and Garfield County Agent, February 6-7.

Hanson, R.B., Orloff,S. and Pters, D. 2000. Monitoring soil moisture helps refine irrigation management. California Agriculture. 54, 38-42.

Irrometer. 2010. Watermark Soil Moisture Sensor – Model 200SS. Specification Document. Irrometer company, Inc. P. O. Box 2424, Riverside, CA 92516. http://www. irrometer.com.

Khorami, M. Alizadeh, A. and Ansari. H. 2013. Simulation of water movement and moisture redistribution under drip irrigation systems using hydrus 2D/3D. Journal of. Water and Soil. 27 (4): 692-702.

Larson, G.F. 1985. Electrical sensor for measuring moisture in landscape and agricultural soils. U. S. Patent 4,531,087. Date of Patent: July 23.

Mahmut, C. and Cevat, K. 2003. Spatial and temporal changes of soil salinity in a cotton field irrigated with low-quality water. Hydrology. 272: 238-249.

Nazari, B., Liaghat, A., Akbari, M.R. and Keshavarz, M., 2018. Irrigation water management in Iran: Implications for water use efficiency improvement. Agricultural water management, 208, pp.7-18.

Nolz, R., Kammerer, G. and Cepuder,P. 2012. Calibrating soil water potential sensors integrated into a wireless monitoring network. Agricultural Water Management. 116: 12– 20.

Osroosh, Y., Peters, R.T., Campbell, C.S. and Zhang, Q. 2016. Comparison of Irrigation Automation Algorithms for Drip-Irrigated Apple Trees. Computersand Electronics in Agriculture. 128: 87–99.

Thompson, R.B., Gallardo, M., Aguera, T., Valdez, L.C. and Fernandez, M D. 2006. Evaluation of the watermark sensor for use with drip irrigated vegetable crops. Irriggation Science Journal. 24: 185–202.

Western, A.W., Zhou, S.-L., Grayson, R.B ,.McMahon, T.A., Blöschl, G. and Wilson, D.J. 2004. Spatial correlation of soil moisture in small catchments and its relationship to dominant spatial hydrological processes. Journal of Hydrology. 286 (1-4): 113-134.

Winter. C., Soylemez. N., Trivedi. j., Pickens. N., Craig. C. and Vaidyanathan. V. 2006. Design of a sensor based smart sprinkler system. Proceedings of the international journal management engineering - intertech conference, Kean university, New jersey, October 19-21.