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اثر خصوصیات سازۀ الیافی شیشه‌ای حصیری بر دقت حسگر بلوک متخلخل در پایش رطوبت خاک | ||
| تحقیقات مهندسی سازه های آبیاری و زهکشی | ||
| دوره 25، زمستان - شماره پیاپی 97، بهمن 1403، صفحه 50-35 اصل مقاله (1.21 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/idser.2025.368179.1605 | ||
| نویسندگان | ||
| مریم نوابیان* 1؛ مصطفی جمشیدی اوانکی2 | ||
| 1دانشیار گروه مهندسی آب، دانشکده علوم کشاورزی دانشگاه گیلان و عضو وابسته گروه آب و محیط زیست پژوهشکده حوضه آبی دریای خزر دانشگاه گیلان، گیلان، ایران. | ||
| 2استادیار گروه مهندسی نساجی، دانشکده فنی دانشگاه گیلان، گیلان، ایران. | ||
| چکیده | ||
| اطلاع از وضعیت رطوبت خاک می‌تواند تاثیر بسزایی بر برنامه‌ریزی آبیاری و در نتیجه مدیریت آب بخش کشاورزی به عنوان بزرگ‌ترین مصرف‌کننده آب به همراه داشته باشد. اندازه‌گیری رطوبت خاک به روش بلوک متخلخل مبتنی بر مقاومت‌سنجی جریان برق از جمله روش‌های اندازه‌گیری رطوبت است که توسعۀ دانش ساخت آن می‌تواند گام موثری در کاهش هزینه، افزایش دقت و سهولت اندازه‌گیری رطوبت و در نتیجه مدیریت مصرف آب کشاوری باشد. هدف از این پژوهش، بررسی خصوصیات الیاف شیشه‌ای حصیری بر دقت اندازه‌گیری رطوبت خاک به روش بلوک متخلخل است. در این راستا، از دو الیاف P200 و P186 در ساخت بلوک مبتنی بر سازۀ الیافی استفاده گردید و دقت اندازه‌گیری رطوبت توسط آن در 10 بافت خاک در سه تکرار بررسی شد. برای ارزیابی دقت بلوک‌ها، رطوبت اندازه‌گیری شده توسط آن‌ها با روش رطوبت وزنی مقایسه و شاخص‌های آماری R2، RMSE، nRMSE، MAE و D-index محاسبه شدند. نتایج نشان داد که بلوک‌های ساخته شده با هر دو الیاف دقت قابل قبول در اندازه‌گیری رطوبت خاک دارند (R2=0.7-0.98، RMSE=0.05-0.07، nRMSE=16-20%، MAE=0.05-0.06 و D-index=0.94-0.95) اما الیاف P200 با خطای حدود 5 درصد، دقت بیشتری بهدست داده است. این بلوک‌ها در بافت خاک متوسط با حداقل و حداکثر شن بهترتیب 20 و 70 درصد و حداکثر رس 30 درصد، نسبت به سایر بافت‌ها دقت بیشتری (RMSE<0.06) نشان دادند. دقت بلوک‌ها در حد بالای رطوبت خاک کاهش یافت به‌طوری‌که در محدوده دقت 7 درصد قرار نگرفت. بنابراین، استفاده از آن‌ها برای دامنه رطوبت خاک 40-25 درصد وزنی پیشنهاد می‌شود. | ||
| کلیدواژه‌ها | ||
| بافت خاک؛ تراکم الیاف؛ حسگر رطوبتی؛ خیس‌شدگی الیاف | ||
| عنوان مقاله [English] | ||
| Effect of fiber-based Sensors Structure on Block Sensorein soil Moisture monitoring performance | ||
| نویسندگان [English] | ||
| Maryam Navabian1؛ Mostafa Jamshidi Avanaki2 | ||
| 1Associated Prof. of Water Eng. Dep., Agricultural Sciences Faculty, University of Guilan and and Dept. of Water Eng. and Environment, University of Guilan, Rasht, Iran | ||
| 2Assistant Professor of Fibrous Structures and Process Engineering, Faculty of Engineering, University of Guilan, Rasht, Iran | ||
| چکیده [English] | ||
| Extended Abstract Introduction Knowledge of soil moisture status can significantly impact irrigation planning and, consequently, water management in the agricultural sector, which is the most expensive recipient of water resource allocation. Soil moisture measurement using the porous block method, based on electrical resistance measurement, is one of the techniques for assessing moisture levels. Developing an understanding of its construction can effectively reduce costs, increase accuracy, simplify moisture measurement, and achieve these goals. This study aims to enhance the understanding of soil moisture measurement through the development and assessment of porous blocks constructed with glass mat fibers, specifically P200 and P186 types. Materials and Methods In this regard, two types of glass fibers, P200 and P186, were used in the construction of a block with a fibrous structure. The accuracy of moisture measurement was then evaluated in 10 different soil textures. To prepare the soil, it was dried, pounded, and passed through a 2-mm sieve before being placed into a pot. After installing three replicates of each block in the pot, the soil was saturated. At various intervals until the soil dried, the electrical resistance of the block and the soil moisture were measured using the gravimetric method. To assess the accuracy of the blocks, the moisture readings from the blocks were compared with those obtained from the gravimetric method, and statistical indices such as R² (coefficient of determination), RMSE (root mean square error), nRMSE (normalized root mean square error), MAE (mean absolute error), and D-index (index of agreement) were calculated. Results and Discussion The results showed that ELE glass fibers absorbed 2.6 and 0.5 times more water than P200 and P186 fibers, respectively, over 180 seconds. A comparison of the fitting curves for the wicking behavior of the two fibers indicates that the quadratic curve provides a better fit than the linear curve. Additionally, the results showed that solution absorption in P186 decreased earlier than in P200. Therefore, it appears that P200 fibers are more effective at absorbing the solution and, subsequently, the water from the soil environment. The results also indicated that ELE and P200 fibers exhibited a similar decreasing trend in moisture over the first 15 minutes; however, after that point, the moisture reduction rate in P200 continued at a lower slope. P200 fibers demonstrated behavior more akin to ELE fibers during both moisture reduction and solution absorption. The findings reveal that the porous blocks constructed with P200 fibers achieved superior accuracy in measuring soil moisture, yielding an error margin of approximately 5%. Notably, the findings indicate that the P186 and P200 fibers exhibit optimal accuracy in medium soil textures, outperforming their performance in other soil types. Specifically, the P186 fibers achieve their highest accuracy in soil textures characterized by a sand content between 50-70% and clay content below 35%. Similarly, the P200 fibers also demonstrate robust accuracy within the same sand and clay content ranges, but they extend their effectiveness to include soils with sand content ranging from 20-50% and clay content around 28%. Conversely, the results suggest that both P200 and P186 fibers struggle with accuracy in soil textures that exhibit either high clay or high sand content. This highlights the importance of soil composition in the performance of these fibers for measuring soil moisture, indicating that they are less reliable in extreme soil conditions. Furthermore, the study highlighted a decline in measurement accuracy at elevated soil moisture levels, indicating that these blocks are most effective within a soil moisture range of 25-40% by weight. Conclusion In conclusion, this research underscores the potential of utilizing glass mat fibers in the construction of porous blocks to improve soil moisture measurement accuracy. By refining this methodology, the findings contribute valuable insights toward optimizing irrigation practices and advancing water management strategies in agriculture. Enhanced accuracy in moisture readings not only promotes efficient water usage but also supports sustainable agricultural practices, ultimately benefiting food production and environmental conservation efforts. | ||
| کلیدواژه‌ها [English] | ||
| Fiber Density, Moisture Sensor, Soil Texture, Wetting of Fiber | ||
| مراجع | ||
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Abbasi, F., & Abbasi, N. (2024). An analysis of irrigation efficiencies over time in Iran. Iranian Journal of Irrigation and Drainage. 6(17): 1025-1033. (In Persian) Ansari, H., & Hassanpour, M. (2015). Design and construction of REC-P55 for reading of soil moisture, temperature and salinity. Iranian Journal of Irrigation and Drainage. 1(9): 32-43. (In Persian) Aram, M., & Meysami, H. (2010). Concrete with fiber, a method for producing high strength concrete shell. Concrete Research. 3(1): 51-59. (In Persian) Bai, W., Kong, L., & GuoState, L. (2013). Effects of physical properties on electrical conductivity of compacted lateritic soil. Journal of Rock Mechanics and Geotechnical Engineering. 5: 406–411. Bannayan, M., & Hoogenboom, G. (2009). Using pattern recognition for estimating cultivar coefficients of a crop simulation model. Field crops research. 111(3): 290-302. Bouyoucos, G.J, & Mick, A.H. (1940). An electrical resistance method for the continuous measurement of soil moisture under field conditions. Bull. 172. Michigan Agric. Exp. Stn., East Lansing. Physical and mineralogical methods. 2nd ed. SSSA Book Ser. 5. SSSA, Madison, WI. Campbell, G.S., & Mulla, D.J. (1990). Measurement of soil water content and potential. Chapter 6 In Stewart B.A. and Nielsen D.R. (co-editors). Irrigation of Agricultural Crops. American Society of Agronomy. Madison, USA. 127-142. Charlesworth, P. (2005). Soil Water Monitoring, Irrigation Insights No. 1, Second Edition. Coelho E.F. and D. Or. 1996. Flow and uptake patterns affecting soil water sensor placement for drip irrigation management. Transactions of the American Society of Agricultural Engineers. 39(6): 2007-2016. Coleman, E.A., & Hendrix, T.M. (1949). The fiberglass electrical soil- moisture instrument. Soil Science. 67: 425–438. Esmaeilzadeh, M., & Nayshapori, M. R. (2001). Design, manufacture and increase the efficiency of gypsum blocks for determining soil moisture. Agricultural Sciences and Natural Resources. 8(3): 3-11. (In Persian) Ezekiel, O., Danbaki, B.A., & Fabumi, G.T. (2021). Performance evaluation of gypsum block, tensiometer and moisture sensor for soil moisture content determination. Journal of Agricultural Engineering and Technology. 26 (2): 103-111. Food and Agriculture Organization of the United Nations (FAO). (2017). Water for Sustainable Food and Agriculture. A report produced for the G20 Presidency of Germany. Food and Agriculture Organization of the United Nations, 33 pages. Food and Agriculture Organization of the United Nations (FAO). (2017a). Water Scarcity – One of the Greatest Challenges of Our Time. Food and Agriculture Organization of the United Nations. (Accessed 15 March 2023). Ghaemi, A.A. & Rahmani Soghayeh, J. (2014). Investigation the Performance of Smart Sensors as a New Approach to Determine Soil Moisture Content. Iranian Journal of lrrigation and Drainage. 1(8): 16-25. (In Persian) Ghanadzadeh, M. A. Davari, K. & Ghahraman, B. (2009). Evaluation of some different types of gypsum blocks for determination of soil moisture. Journal of Iranian Water Research. 2 (2): 23-32. (In Persian) Jamieson, P.D., Porter, J.R., & Wilson, D.R. (1991). A test of the computer simulation model ARCWHEAT1 on wheat crops grown in New Zealand. Field Crops Research. 27 (4): 337-350. Keyhani, A. (2001). Development of Mini-Gypsum Blocks for Soil Moisture Measurement and their Calibration to Compensate for Temperature. Journal of Agricultural Science Technology. 3: 141-145. Leib, B.G. (1998). The 1998 survey of irrigation scheduling providers. The Washington Irrigator News Letter. Washington State University. Prosser, WA. Leib, B.G., Hattendorf, M., Elliott, T. & Matthews, G. (2002). Adoption and of 1998. Agric. Water Manage.55:105–120.Adaptation of Scientific Irrigation Scheduling: Trend from Washington, USA as of 1998. Agriculture Water Management. 55: 105–120. Lewis, C. D. (1982). Industrial and business forecasting methods, London: Butterworths. McCann, I.R., Kincaid, D.C & Wang, D. (1992) Operational characteristics of the Watermark model 200 soil water potential sensor for irrigation management. Applied Engineering in Agriculture. 8 (5): 605- 609. Moravejalahkami, B. & Baghshahi, M. (2020). Feasibility study of the construction and evaluation of a soil moisture sensor in different soil textures. Iran-Water Resources Research. 16(1): 135-145. (In Persian) Nandi, R., & Shrestha, D. (2024). Assessment of Low-Cost and Higher-End Soil Moisture Sensors across Various Moisture Ranges and Soil Textures. Sensors. 24 (5886): 1-13. Ozili, P.K. (2023). The acceptable R-square in empirical modelling for social science research. MPRA Paper No. 115769. Online at https://mpra.ub.uni-muenchen.de/115769/ Prichard, T., Hanson, B., Schwankl, L., Verdegaal, P., & Smith, R. (2004). Deficit irrigation of quality wine grapes using micro-irrigation techniques. University of California Cooperative Extension, PP. 91. Rafiei-Sardooi, E., Azareh, A., Joorabian Shooshtari, S., & Parteli, E.J.R. (2022). Long-term assessment of land-use and climate change on water scarcity in an arid basin in Iran Ecol. Model. 467, Article 109934. Raja, O. Parsinejad, M. & Sohrabi, T. (2019). Evaluation of management strategies to reduce water use in Marvdasht-Kharameh study area. Journal of Water and Soil Recourses Conservation. 8 (4): 67-85. (In Persian) Rasheed, M.W., Tang, J., Sarwar, A., Shah, S., Saddique, N., Khan, M. U., Imran Khan, M., Nawaz, S., Shamshiri, R. R., Aziz, M., & Sultan. M. (2022) .Soil Moisture Measuring Techniques and Factors Affecting the Moisture Dynamics: A Comprehensive Review. Sustainability. 14 (1153): 1-23. Rudnick, D. R., Djaman, K., & Irmak, S. (2015). Performance analysis of capacitance and electrical resistance type soil moisture sensors in a silt loam soil. American Society of Agricultural and Biological Engineers. 58 (3): 649-665. Savage, M. J. (1993). Statistical aspects of model validation. In a workshop on the field water balance in the modeling of cropping systems. University of Pretoria, South Africa. Spaans, E.J.A., & Baker, J.M. (1992). Calibration of Watermark soil moisture sensors for soil matric potential and temperature. Plant and Soil. 143: 213-217. Wang, H. (2019). Irrigation efficiency and water withdrawal in US agriculture. Water Policy. 21: 768–786. Werner, H. (2002). Irrigation Management: using electrical resistance blocks to measure soil moisture. College of Agriculture & Biological Sciences publications page, which is at http://agbiopubs.sdstate.edu/articles/FS899.pdf. Willmott, C. J. (1982). Some comments on the evaluation of model performance. Bulletin of the American Meteorological Society. 63 (11): 1309-1313. Yazdani Kachouei, M. (1996). Comparison of methods for measuring soil moisture in the field. (M. Sc. Thesis), Faculty of Agriculture, Department of Water Engineering and Management, Tarbiat Modares University, Tehran, Iran. (In Persian)
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