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تحلیل پهنه بندی شاخص بهره وری فیزیکی آب در قطب های تولید چغندرقند در ایران | ||
| تحقیقات مهندسی سازه های آبیاری و زهکشی | ||
| دوره 24، شماره 90، خرداد 1402، صفحه 71-90 اصل مقاله (1.22 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/idser.2023.363301.1552 | ||
| نویسندگان | ||
| ادریس تاند1؛ فریبرز عباسی* 2؛ جمال محمد ولی سامانی3 | ||
| 1دانشجوی کارشناسی ارشد رشتة آبیاری و زهکشی، دانشکدة کشاورزی، دانشگاه تربیت مدرس | ||
| 2استاد موسسه تحقیقات فنی و مهندسی کشاورزی، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران | ||
| 3استاد دانشکدة کشاورزی، دانشگاه تربیت مدرس | ||
| چکیده | ||
| برای تامین غذای مورد نیاز جمعیت رو به رشد کشور و با توجه به محدودیت زمین زراعی آبی و کمبود شدید منابع آبی ضرورت دارد تا شاخص بهرهوری آب مورد توجه قرار گیرد. در همین راستا، به‌منظور شناسایی و آگاهی از پتانسیل زراعی اراضی کشاورزی می‌توان از تحلیل، برآورد و تهیه نقشه بهرهوری فیزیکی آب بهره گرفت. هدف اصلی از انجام این تحقیق، ارزیابی روشهای مختلف درونیابی و انتخاب مناسب‌ترین روش به‌منظور برآورد بهرهوری آب محصول زراعی چغندرقند و بررسی الگوی توزیع مکانی در قطب‌های تولید آن در ایران است. بدین منظور برای انجام این پژوهش از 108 داده حاصل از اندازه‌گیری های میدانی در مزارع منتخب چغندرقند کشور برای سال زراعی 1396-1395 استفاده شد. از داده‌های عملکرد محصول، حجم آب آبیاری و میانگین بارش موثر (ده ساله)، شاخص بهرهوری فیزیکی آب چغندرقند برای مزارع منتخب به دست آمد که دامنه آن بین 2/60 تا 13/11 کیلوگرم بر مترمکعب و میانگین آن 6/30 کیلوگرم بر مترمکعب تعیین شد. برای نیل به این هدف ابتدا با استفاده از قابلیت‌های نرم‌افزار SPSS به تحلیل داده‌ها، آنالیز آمار توصیفی و تفکیک مناطق مشابه به گروه‌های مستقل و همگن (ترسیم دندروگرام) و با استفاده از قابلیت‌های نرم‌افزار +GS به تحلیل مکانی داده ها پرداخته شد. در ادامه از روشهای مختلف درونیابی شامل روش های جبری از جمله وزندهی فاصله معکوس، تابع پایه شعاعی، چند جمله‌ای جهانی و چند جمله‌ای محلی و روش زمین‌آمار از جمله کریجینگ معمولی، ساده و عمومی در محیط نرم‌افزار سیستم اطلاعات جغرافیایی برای تهیه نقشه پهنه‌بندی استفاده شد. برای ارزیابی روشهای مختلف درونیابی از روش اعتبارسنجی و مقدار نمایه‌هایی صحت میانگین انحراف خطا (MBE)، میانگین قدر‌مطلق نسبی (MARE)، میانگین مربعات خطا (MSE)، میانگین انحراف مطلق (MAD) و مجذور میانگین مربعات خطا (RMSE) استفاده گردید. نتایج ارزیابی روش های مختلف درونیابی بدین صورت بود که در میان روشهای مورد بررسی، روش تابع پایه شعاع با مدل اسپلاین کاملاً منظم (CRS) بادقت قابل قبول (MBE= 0/009) برای تهیه نقشه پهنه بندی بهره وری فیزیکی آب شرایط مطلوب تری نسبت به سایر روشها داشت. نتایج حاصل از تجزیه خوشه ای برای عوامل تأثیرگذار همچون نوع رقم، شوری خاک، شوری آب آبیاری و بهره وری فیزیکی آب در سطح پنج درصد نشان داد که مناطق مستعد کشت چغندرقند در محدوده مورد مطالعه به 23 گروه مستقل تفکیک و به‌طوری‌که در آن کمترین و بیشترین مقدار بهره وری فیزیکی آب چغندرقند بهترتیب در گروه 11 (اقلید) و 12 (مرودشت) معادل 2/640 کیلوگرم بر مترمکعب و گروه 3 (اسدآباد) معادل 11/025 کیلوگرم بر مترمکعب بود. | ||
| کلیدواژه‌ها | ||
| بهرهوری آب؛ روشهای درونیابی؛ چغندرقند | ||
| عنوان مقاله [English] | ||
| Zoning analysis of physical water productivity index in the hubs of sugar beet production in Iran | ||
| نویسندگان [English] | ||
| Edris Tand1؛ Fariborz Abbasi2؛ Jaman MohammadVali Samani3 | ||
| 1Master's student in the field of irrigation and drainage, Faculty of Agriculture, Tarbiat Modares University | ||
| 2Agricultural Engineering Research Institue, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran | ||
| 3Professor, Faculty of Agriculture, Tarbiat Modares University | ||
| چکیده [English] | ||
| Extended Abstract Introduction Iran is characterized by a dry and semi-arid climate. The limited irrigated arable land in and the need for increasing food production due to the upward trend in population growth, coupled with water scarcity and Iran's heavy reliance on irrigation, have led to a heightened importance of water productivity in agricultural sector. In this regard, for the purpose of identifying and understanding the agricultural potential of farmlands, the analysis and estimation of physical water productivity can be utilized. The main objective of conducting this research is to evaluate various interpolation methods and to select the most appropriate method for estimating the physical water productivity of the sugar beet. Additionally, the study aims to investigate the spatial distribution pattern of sugar beet production in its major cultivation centers across Iran. Methodology To accomplish this research, 108 field measured data obtained from selected sugar beet farms across Iran for the agricultural year 2016-2017 were used. Data on crop yield, irrigation water, and a ten-year average effective precipitation were collected, and the water productivity index of sugar beet was calculated for the selected farms. To achieve this goal, initially, the data was analyzed using the capabilities of the SPSS software. Descriptive statistical analysis was conducted, and similar regions were classified into independent and homogeneous groups (by drawing a dendrogram). Additionally, the spatial analysis of the data was carried out using the GS+ software. Furthermore, various interpolation methods were employed to create a classification map using the Geographic Information System (GIS) software. These methods encompass algebraic methods, including weighted inverse distance, radial basis function, global polynomial, and local polynomial methods, as well as geostatistical methods like ordinary kriging, simple kriging, and universal kriging. To assess the different interpolation methods, validation methods were employed, and accuracy index values such as Mean Bias Error (MBE), Mean Absolute Relative Error (MARE), Mean Squared Error (MSE), Mean Absolute Deviation (MAD), and Root Mean Square Error (RMSE) were utilized. Results and Discussion The results of the present study revealed that the water productivity index for sugar beet ranged from 2.60 to 13.11 kg/m³, with an average of 6.30 kg/m³. Despite the high standard deviation, the findings indicate a significant potential and high capacity for improving water productivity and crop performance in the sugar beet production hubs in Iran. Among the examined interpolation methods, the Radial Basis Function method with a completely regular spline model (CRS) exhibited acceptable accuracy (MBE=0.009) for generating the water productivity zoning map. The analysis of the generated map suggested that the western regions of the country, especially Kermanshah province, have higher water productivity index values compared to other parts of the country, making them more suitable for sugar beet cultivation. Furthermore, cluster analysis results for influential factors such as variety type, soil salinity, and irrigation water salinity indicated that within the study area, about 5% of the potential sugar beet cultivation areas could be divided into 23 distinct clusters. The minimum and maximum water productivity index were observed in cluster 11 (2.64 kg/m³) and cluster 3 (11.025 kg/m³), respectively. Based on the low level of correlation coefficient according to the results of the Pearson correlation test, the physical productivity of water utilization can be influenced by various factors other than precipitation and climate parameters. These factors include salinity of water, soil salinity, total irrigation water, average effective precipitation (over a ten-year period), and crop yield. It can be concluded that, in addition to precipitation and climatic parameters, other constant factors including management factors have an impact on improving the physical efficiency of water utilization. Conclusions Given the high water consumption in agricultural sector and the need for increased production in cultivated lands, evaluating the water productivity of high-water-demand crops such as sugar beet in Iran is essential. Understanding its current state and obtaining comprehensive information from fields, as well as monitoring cultivated fields, are necessary for decision-making and macro-level planning to enhance and improve water productivity of sugar beet cultivation in Iran. However, due to the extensive cultivation area, costs, limited resources, and time constraints, this task is challenging and often unfeasible. To address this, the potential of interpolation tools can be utilized. These tools have the capability to extrapolate point-based information to spatial information (area-wide). Results have shown that the highest and lowest error values were associated with the kriging interpolation method and the radial basis function (completely regularized spline) method, respectively, for creating zoning maps. In conclusion, it can be stated that through interpolation, if there is a strong correlation between the data, a better understanding of the spatial distribution of water productivity can be achieved in the study area. | ||
| کلیدواژه‌ها [English] | ||
| Water productivity, Interpolation methods, Sugar beet | ||
| مراجع | ||
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Abbasi, F., Abbasi, N. & Naseri, A. (2019). The technical-economic effects of knowledge and technology on the promotion of water productivity in production areas. Baztab-e-Tat, 2(1), 5-6. (in Persian). Abbasi, F., Abbasi, N. & Tavakoli, A. R. (2017). Water productivity in agriculture; Challenges and prospects. Journal of Water and Sustainable Development, 4(1), 141-144. (in Persian) Abdiaghdam, F., Rasoulzadeh, A., Samadianfard, S., & Navedi, F. (2022). Analysis of water productivity indicators in agricultural lands of Moghan Agro-Industry and Livestock Company. Water and Soil Science, 32(3), 77-90. (in Persian). Baghani, J., Ahmad Ali, J., Eslami, A., Behramlou, R., Ghadami Firouzabadi, A., Akhwan, K., Moiri, M., Karimi, M., Dehghanian, S. A., Islamic, A. R., Abbasi, F., Akbari, M., Abbasi, N., Khosravi, H., Ghafari, Z., Hosseinzadeh, S., Nemati, S., Sepehari, S., Aghaei, M. J. & Nakhjavani Moghadam, M. M. (2018). Determining the Applied Water of sugar beet in Iran. Final Research Report No. 54633. Karaj, Agricultural Engineering and Technical Research Institute. (in Persian). Baghbanyan, M., Emamverdi, G., Ghaderzadeh, H., Damankeshideh, M., & Aminrashti, N. (2020). A survey on virtual water and sustainable productivity indices of agricultural water in major agricultural crops (a case of Saqqez City, Kurdistan province). Iranian Journal of Irrigation & Drainage, 14(3), 1046-1054. (in Persian) Bayat, M.A., & Manshouri, M. (2011). Temporal and spatial study of water use efficiency of strategic crops in regional scale (Case study: Hamadan province). Journal of Water and Soil Resources Conservation, 1(1), 43-51. (in Persian) Choudhury, M. R., Mellor, V., Das, S., Christopher, J., Apan, A., Menzies, N. W., & Dang, Y. P. (2021). Improving estimation of in-season crop water use and health of wheat genotypes on sodic soils using spatial interpolation techniques and multi-component metrics. Agricultural Water Management, 255, 107007. Danesh Azad, M., Yosefi Fard, Y.& Ghorbani, M. (2020). Physical productivity and volume of water calculation used in sugar beet cultivation and its effect on groundwater in drought conditions of Kuhdasht city of Iran. Journal of Water Science and Engineering, 9(26), 57-63. (in Persian). Dehghanisanij, H., Ebrahimi, M., Rezaverdinejad, V., & Taghizadehghasab, A. (2020). Impact of changing irrigation method and planting spacing on water productivity, yield and application efficiency of sugar beet in Miandoab plain. Iranian Journal of Soil and Water Research, 51(8), 2125-2136. (in Persian). Deihimfard, R., Mohammadi-Ahmadmahmoudi, E. & Noori, O. (2019). Assessment of water productivity and supply: demand ratio index in sugar beet (Beta vulgaris L.) in Khorasan Razavi province, Iran using growth simulation models. Iranian Journal of Crop Sciences, 21(3), 268-282. (in Persian). Deutsch, C.V. & Journel, A.G. (1998). Geostatistical Software Library and Users Gulide. 2nd Ed. Oxford University Press. New York. Ehsani, M. & Khalidi, H. (2003). Water Productivity in Agricultural . Tehran. National Irrigation and Drainage Committee of Iran. (in Persian) Ghorbanpour, A. K., Kisekka, I., Afshar, A., Hessels, T., Taraghi, M., Hessari, B., & Duan, Z. (2022). Crop water productivity mapping and benchmarking using remote sensing and google earth engine cloud computing. Remote Sensing, 14(19), 4934. Habibzadeh, Y., Abdi, S., & Abedi, R. (2020). Zoning of sugar beet cultivation in West Azarbaijan province based on cultivation and irrigation systems in GIS. Journal of Crops Improvement, 22(4), 601-615. (in Persian). Hassani Pak, A. A. (1998). Geostatistics. Tehran. Tehran University Press. (in Persian) Hassanli, A. M., Ahmadirad, S., & Beecham, S. (2010). Evaluation of the influence of irrigation methods and water quality on sugar beet yield and water use efficiency. Agricultural Water Management, 97(2), 357-362. Jamali, R., Besharat, S., Yasi, M. & Amirpour Deylami, A. (2018). Assessment of the application efficiency, water use efficiency and productivity of irrigated water in the Urmia lake basin (Case Study: Zarineh Rood irrigation and drainage network). Journal of Water and Soil Science; 22(3):117-130. (In Persian).
Kamali, M. E., Faridhosseini, A., Ansari, H., & Gholami Sefidkouhi, M. A. (2017). Preparation of water requirement maps of maize by comparing geostatistical and deterministic methods. Iranian Journal of Irrigation & Drainage, 11(5), 708-721. (in Persian). Kaveh, F. & Hosseini Abri, S. A. (2010). Increasing water productivity in irrigated agriculture. 12th Seminar of Iranian National Committee on Irrigation and Drainage. Feb. 5. Tehran, Iran. (in Persian). Khalili, A. (2005). Attempt to develop a new climatic classification system based on environmental heating-cooling requirements and its application for Iran. Geographical Research, 19(75), 5-14. (In Persian). Li, X., Tong, L., Niu, J., Kang, S., Du, T., Li, S., & Ding, R. (2017). Spatio-temporal distribution of irrigation water productivity and its driving factors for cereal crops in Hexi Corridor, Northwest China. Agricultural Water Management, 179, 55-63.
Mohammadi, J. (2006). Pedometry: Spatial Statistics (Geostatistics). Tehran. Plek Publications. (In Persian). Naseri, A., Abbasi, F., & Akbari, M. (2017). Estimating agricultural water consumption by analyzing water balance. Irrigation and Drainage Structures Engineering Research, 18(68), 17-32. (In Persian). Piri, H., & Mobaraki, M. (2021). Investigating water footprints and water consumption efficiency of crops of potatoes, sugar beets, tomatoes and forage corn in different climates of Iran. Journal of Water and Soil Conservation, 27(6), 103-120. (in Persian). Robinson, T. P., & Metternicht, G. (2006). Testing the performance of spatial interpolation techniques for mapping soil properties. Computers and electronics in agriculture, 50(2), 97-108. Saini, K. S., & Brar, N. S. (2018). Crop and water productivity of sugar beet (Beta vulgaris) under different planting methods and irrigation schedules. Agricultural Research, 7, 93-97. Seydan, S. M., & Mansouri, H. (2019). Water productivity in sugar beet cultivation under classical and furrow irrigation system in Hamedan province. Journal of Agroecology, 11(2), 673-686. (In Persian). Soltani, G., Akbari, M. & Mohammadi, H. (2010). Investigating water productivity in dry areas (case study of Marvdasht - Karbal Plain). 06th National Conference of Agricultural Economics. Feb. 3. Karaj, Iran. (In Persian). Taheri, M., Rezaverdinejad, V., Behmanesh, J., Abbasi, F., & Baghani, J. (2020). Spatial analysis of water productivity index at major wheat production centers of IRAN. Journal of Water Research in Agriculture, 34(2), 217-227. (in Persian).
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