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بررسی اثربخشی راهکارهای مدیریتی کاهش مصرف آب کشاورزی با استفاده از مدل AquaCrop (مطالعه موردی: دشت هشتگرد) | ||
| تحقیقات مهندسی سازه های آبیاری و زهکشی | ||
| دوره 25، پاییز - شماره پیاپی 96، آذر 1403، صفحه 26-1 اصل مقاله (911.56 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/idser.2024.367320.1595 | ||
| نویسندگان | ||
| امید رجا* 1؛ سجاد ویسی2؛ علی برزگر2 | ||
| 1محقق، موسسه تحقیقات فنی و مهندسی کشاورزی، سازمان آموزش و ترویج کشاورزی، کرج، ایران. | ||
| 2کارشناس منابع آب، شرکت آب منطقه ای البرز، کرج، ایران. | ||
| چکیده | ||
| استفادۀ مناسب از منابع آب در بخش کشاورزی نیازمند آگاهی از راهکارهای مدیریتی بهینه و کارآمد آب است. مدیریت وضعیت کنونی دشت هشتگرد در استان البرز حاصل عملکرد مجموعه ای از عوامل انسانی و طبیعی طی دهه های گذشته است و احیا و تعادل بخشی آب زیرزمینی دشت در اولویت قرار دارد. بر اساس آمار درازمدت سطح آب زیرزمینی (99-1370) میزان کسری مخزن در هر سال به طور متوسط برابر با 16/82 میلیون مترمکعب (6/2 درصد) است. در این مطالعه از مدل AquaCrop برای شبیه سازی عملکرد محصولات غالب زراعی و مقدار آب مصرفی در منطقۀ هشتگرد استفاده شد. راهکارهای عملی و کم‌هزینه نیز برای صرفه جویی در مصرف آب با حداقل هزینه مانندبهبود راندمان آبیاری براساس وضع موجود، تغییر تاریخ کاشت و الگوهای مختلف کم آبیاری بررسی شد. واسنجی مدل AquaCrop برای شرایط منطقه‌ای و بر اساس عملکرد محصولات زراعی نشان داد این مدل بهخوبی توانسته است عملکرد محصولات زراعی موردمطالعه را با کمترین خطای نسبی (RE) برای گندم، جو، ذرت علوفه ای و یونجه برای دشت هشتگرد در مرحلۀ واسنجی مدل شبیه سازی کند. بررسی ها نشان داد با توجه به سطوح ارتقای راندمان در مناطق مختلف و برای کشت های مختلف به ترتیب منجر به صرفهجویی به میزان 17/7 میلیون مترمکعب (5/9 درصد) در مصرف آب تخصیصی خواهد شد که می تواند در شرائط کم آبی در تامین آب مورد نیاز راسطح بیشتری از اراضی بدون کاهش عملکرد فراهم کند. نتایج تحقیق نشان داد با انتخاب تاریخ کاشت بهینه (باتوجه به دامنۀ تاریخ کشت متداول در منطقه) برای محصولات غالب محدوده دشت هشتگرد نیاز ناخالص آبیاری به میزان 2/4 میلیون مترمکعب در مصرف آب (0/8 درصد) کاهش می یابد. گزینۀ دیگر مدیریتی، کم آبیاری تحت الگوهای مدیریتی مختلف برای محصولات غالب زراعی، نشان داد با کاهش عمق آب آبیاری و نیز با افزایش دورهای آبیاری، صرفه جویی قابل توجهی در میزان آب مورد نیاز قابل دستیابی است. با کم آبیاری میتوان به میزان 19/3 میلیون مترمکعب (6/0 درصد) در دشت هشتگرد در مصرف آب صرفه جویی کرد. نتایج به دست آمده نشان می دهد در بسیاری از مواقع می توان بدون رفتن زیر بار هزینه های کلان برای تامین امکانات و تجهیزات مدرن، در شرایط مدیریتی برتر موجود در منطقه با اعمال سناریوهای مختلف از جمله بهبود راندمان، تغییر تاریخ کاشت و کم آبیاری در مصرف آب آبیاری مورد نیاز صرفه جویی قابل توجهی کرد. طبیعتاً سهم هر کشت در میزان صرفه جویی متناسب با متوسط آب مصرفی در هکتار و سطح اراضی تحت هر کشت است. | ||
| کلیدواژه‌ها | ||
| استان البرز؛ تاریخ کاشت بهینه؛ صرفه جویی آب؛ راندمان آبیاری؛ کم آبیاری | ||
| عنوان مقاله [English] | ||
| Evaluation the effectiveness of management strategies to reduce agricultural water use by using the AquaCrop model (case study: Hashtgerd plain) | ||
| نویسندگان [English] | ||
| Omid Raja1؛ Sajjad Veysi2؛ Ali Barzegar2 | ||
| 1Researcher, Agricultural Engineering Research Institute (AERI), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran | ||
| 2Water Resources Specialist, Regional Water Company of Alborz, Karaj, Iran | ||
| چکیده [English] | ||
| Extend Abstract Intouduction Many factors have contributed to the drop in the water table of groundwater, including the increase in cultivated area, decrease in rainfall, climate change, and the continuation of drought in recent years, and withdrawing excessive amounts of surface water sources and groundwater from unauthorized wells, which has faced serious challenges in the water sector in Alborz province. The Hashtgerd plain is located in the Alborz province. The current situation of the Hashtgerd plain is the result of a series of human and natural factors over the past few decades, and the restoration and balance of the underground water of the plain is a priority. According to long-term statistics, the groundwater level has decreased by 19.8 m in 29 years (1990-2019) on average, there is a drop in the groundwater level of about 68 cm. per year. The total aquifer deficit is 487.85 million cubic meters, and the average annual amount of the aquifer deficit is 16.82 million cubic meters (6.2%). Given these conditions, it is essential to apply effective solutions for optimal and efficient water management. Methodology The purpose of this study was to provide practical and low-cost solutions to save water consumption in Hashtgerd Plain. There are different solutions with minimal cost, such as improving irrigation efficiency, changing the planting date, and different patterns of deficit irrigation. The approach of this study is to present and examine solutions that do not require changing the irrigation system or even changing the cultivation pattern and also not reducing the cultivated area in the region. It is the examination of the solutions that can be implemented at the lowest possible cost without adversely affecting the livelihood of farmers. The objective of the study was to reduce water consumption or prevent from excessive groundwater of Hashtgerd plain aquifer. The proposed solutions do not require new tools such as precision leveling machines and, so on. Each of the above strategies was evaluated based on the actual conditions in the region. The main objective was to evaluate and estimate the water requirements of the dominant crops in the Hashtgerd Plain, and to present different scenarios for improving irrigation efficiency according to the superior conditions in the region. The feasibility of saving water consumption through strategies to change the planting date and deficit irrigation was evaluated using the AquaCrop 6.0 model. Results and discussion In this study, the AquaCrop model was used to simulate the yield of crops and the amount of water use in the region. The calibration of the AquaCrop model for regional conditions has demonstrated that the AquaCrop model is capable of predicting crop yield with the lowest relative error (RE) for wheat, barley, fodder corn, and alfalfa for the plains during the calibration phase of the simulation model. According to the levels of efficiency improvement in different regions and for different crops, it will lead to savings of 17.7 million cubic meters (5.9%) in the amount of allocated water consumption. This will can provide the possibility of supplying water to a larger area of land without reducing yield under water scarcity conditions. The outcomes of the scenario involving a change in planting date through AquaCrop model simulation demonstrated that this management pattern has the potential to reduce water consumption by 2.4 million cubic meters (0.8%) in the region. In addition, different levels of deficit irrigation can save 19.3 million cubic meters of water consumption. Conclusion The obtained results show that in many cases, it is possible to provide without modern facilities and huge costs, applying different scenarios such as improving efficiency, changing planting dates and deficit irrigation has achieved significant savings in the required irrigation water consumption. Naturally, the share of each crop in the amount of savings is proportional to the average water consumption per hectare and the area of land under each crop. In general, the AcuCrop model can be used as a practical tool for simulating crop yield and evaluating management scenarios. | ||
| کلیدواژه‌ها [English] | ||
| Alborz Province, Irrigation Efficiency, Deficit Irrigation, Optimal Planting Date, Water Saving | ||
| مراجع | ||
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Abedinpour, M., Sarangi, A., Rajput, T. B. S., Singh, M., Pathak, H., & Ahmad, T. (2012). Performance evaluation of AquaCrop model for maize crop in a semi-arid environment. Agricultural Water Management, 110: 55-66. Agricultural Jihad. (2021). Alborz province agricultural statistics in the hydrological year 2019-2020, 84 pp. Alborz Regional Water Organization. (2020). Investigating the state of water resources and annual consumption of Alborz province in the hydrological year 2019-2020. Iran Water Resources Management Company, Water Resources Basic Studies Office. 37 pp. Alizadeh, H.A., Nazari, B., Parsinejad, M., Ramezani, Eetedali, H., & Janbaz, H.R. (2011). Evaluation of AquaCrop Model on Wheat Deficit Irrigation in Karaj area. Iranian Journal of Irrigation & Drainage, 4(2), 273. (In persian) Allen, R.G., Pereira, L.S., Raes, D., & Smith M. (1998). FAO Irrigation and drainage paper No. 56. Rome: Food and Agriculture Organization of the United Nations 56: 97-156. Amiri, E., & Khorsand, A. (2018). Evaluation of Aquacrop model to predict maize total biomass and grain yield under different water regimes and fertilizer. Plant Ecophysiology, 10(33), 174-185. (In persian) Amiri, E., Bahrani, A., Khorsand, A., & Haghjoo, M. (2016). Evaluating AquaCrop Model Performance to Predict Grain Yield and Wheat Biomass, Under Water Stress. Water and Soil Science, 25(4/2), 217-229. (In persian) Amiri, E., Khorsand, A., Daneshian, J., & Yousefi, M. (2018). Predicting biomass and grain yield in canola under different water regimes and fertilizers using AquaCrop model. Irrigation Sciences and Engineering, 41(1), 57-72. (In persian) Andarzian, B., Bannayan, M., Steduto, P., Mazraeh, H., Barati, M. E., Barati, M. A., & Rahnama. A. (2011). Validation and testing of the AquaCrop model under full and deficit irrigated wheat production in Iran. Agriculture Water Management, 100 (1), 1-8. Consulting engineers for water and sustainable development. (2009). Studies on the updating of the balance of water resources, the study areas of the Salt Lake watershed, water balance report, sustainable water and development consulting engineers. Appendix No. 5, 79 pp. (In persian) Djaman, K. (2011). Crop evapotranspiration, crop coefficients, plant growth and yield parameters, and nutrient uptake dynamics of maize (Zea mays L.) under full and limited irrigation. The University of Nebraska-Lincoln. Doorenbos, J., & Kassam, A. H. (1979). Yield response to water. Irrigation and drainage paper, 33, 257. Droogers, P., Immerzeel, W.W., & Lorite, I. J. (2010). Estimating actual irrigation application by remotely sensed evapotranspiration observations. Agriculture Water Management, 97, 1351–1359. Eskandaripour, R., Khorsand, A., Rezaverdinejad, V., Zeinalzadeh, K., & Norjoo, A. (2020). Investigation of Polyethylene Mulch on Improvement of Tomato Water Use Efficiency using AquaCrop Model. Journal of Plant Ecophysiology, 11(39), 71-85. (In persian) Esmaili Falak, A., & Abbasi, F. (2024). Introduction and Analysis of Effective Megatrends in Water, Soil and Agriculture in the World and Iran Until 2050. Irrigation and Drainage Structures Engineering Research, 24(93), 101-118. doi: 10.22092/idser.2024.365754.1581 (In persian) Farahani, H. J., Steduto, P., & Oweis, T. Y. (2009). Parameterization and evaluation of AquaCrop for full and deficit irrigated cotton. Agronmi Journal, 101, 469-476. Frank, A. & Bauer, A. (1995). Phyllochron difference in wheat, barley and forage grasses. Crop Science, 35: 19-23. Garcia-Vila, M., Fereres, E. Mateos, L., Orgaz, F., & Steduto, P. (2009). Deficit irrigation optimization of cotton with AquaCrop. Agronmi Journal 101: 477- 487. Ghorbanian Kurdabadi, M., Liaghat, A.M, Vatankhah, E., & Noori, H. (2013). Simulation of yield and evapotranpiration of forage maize using AquaCrop model. Journal of Soil and Water Resources Conservation, 4(1), 48-64. (In persian) Heng, L.K., Evett, S.R., Howell, T.A., & Hsiao, T.C. (2009). Calibration and testing of FAO AquaCrop model for maize in several locations. Agronmi Journal, 101: 488-498. Jafari, H., & Abbasi, F. (2024). Evaluation of wheat water irrigation management in Iran with the approach of reducing the area under cultivation and improving water productivity. Iranian Journal of Soil and Water Research. doi: 10.22059/ijswr.2024.380800.669778 (In persian) Karimi Organi, H., Rahimi Khoob, A. & Nazari Fard, M.H. (2016). Calibration and validation of Aquacrop model for berlay in Pakdasht region. Iranain Water and Soil Research, (3) 47, 539-549. (In persian) Khorsand, A., Dehghanisanij, H., Heris, A.M., Asgarzadeh, H., & Rezaverdinejad, V. (2024). Calibration and evaluation of the FAO AquaCrop model for canola (Brassica napus) under full and deficit irrigation in a semi-arid region. Applied Water Science, 14(3), 56. Khorsand, A., Verdinejad, V.R., & Shahidi, A. (2014). Performance evaluation of AquaCrop model to predict yield production of wheat, soil water and solute transport under water and salinity stresses. Water and Irrigation Management, 4(1), 89-104. (In persian) Li, W., Song, R., Awais, M., Ji, L., Li, S., Liu, M., ... & Qi, H. (2024). Global Sensitivity Analysis of Crop Parameters Based on AquaCrop Model. Water Resources Management, 38(6), 2039-2058. Liaghat, A. M., Mokari Ghahroodi, E., Noory, H., & Sotoudenia, A. (2015). Evaluation of Qazvin Plain Irrigation Systems Through an Assessment of Classical vs Neoclassical Irrigation Efficiencies. Iranian Journal of Soil and Water Research, 46(2), 343-351. doi: 10.22059/ijswr.2015.55938 (In persian) Lu, Y., Wei, C., McCabe, M. F., & Sheffield, J. (2022). Multi-variable assimilation into a modified AquaCrop model for improved maize simulation without management or crop phenology information. Agricultural Water Management, 266, 107576. McMaster, G.L., Wilhelm, W., & Morgan J. (1994). Simulating winter wheat shoot apex phenology. The journal of agricultural science. 119, 1-12. Niamnsi, Y.N., & Mbue, I.N. (2009). Estimation for ground water balance based on recharge and discharge: a tool for sustainable ground water management. Zhonghu County Alluvial Plain Journal American Science, 5 (2), 40-83. Nikbakht, J., & Najib, Z. (2015). Effect of irrigation efficiency increasing on groundwater level fluctuations (Cast study: Ajab-Shir Plain, East Azarbaijan). Water and Irrigation Management, 5(1), 115-127. (In persian) Parsinejad, M., Raja, O., & Chehrenegar, B. (2022). Practical analysis of remote sensing estimations of water use for major crops throughout the Urmia Lake basin. Agricultural water management, 260, 107232. Raes, D., Steduto, P., Hsiao, T., & Fereres, E. (2016). Refrence Manual Aquacrop Version 5.0 Food and Agriculture Organization of the United Nations, Rome, Italy. Raes, D., Steduto, P., Hsiao, T.C. & Freres, E. (2012). Refrence Manual Aquacrop, FAO, Land and Water Division, Rome Italy. Raes, D., Steduto, P., Hsiao, T.C., & Fereres. E. (2009). AquaCrop-The FAO crop model for predicting yield response to water: II. Main algorithms and software description. Agron. J. 101, 438–447. Raja, O., & Parsinejad, M. (2023). Cost-effective strategies to improve crop water productivity—case study: Bakhtegan and Maharloo, Iran. International Journal of Environmental Science and Technology, 20(1), 883-894. Raja, O., Parsinejad, M., & Sohrabi, T. (2019). Evaluation of managment strategies to reduce water use in Marvdasht-Kharameh study area, Journal of Soil and Water Resources Conservation, 8(4), 67-86. (In persian) Raja, O., Parsinejad, M., Sohrabi, T., & Ahmadaali, Kh. (2019). Status Investigation of the Marvdasht- Kharameh water resources using sustainability analysis indicators, Iranian Journal of Soil and Water Research, 50(4), 897-909. (In persian) Ramezani Etedali, H., Liaghat, A., Parsinejad, M., & Tavakkoli, A. (2016). AquaCrop Model Calibration and Evaluation in Irrigation Management for Main Grains. Iranian Journal of Irrigation & Drainage, 10(3), 389-397. (In persian) Ramezani, F., Kaviani, A., & Ramezani Etedali, H. (2017). Evaluation of AquaCrop Model for different Harvesting time of Alfalfa in Ardestan. Water and Soil, 31(3), 738-753. (In persian) Ramezani, M., Babazadeh, H., & Sarai Tabrizi, M. (2018). Simulating Barley Yield under Different Irrigation Levels by using AquaCrop Model. Irrigation Sciences and Engineering, 41(4), 161-172. (In persian) Rasaei, A. H., Sharafati, A., & Kardan Moghaddam, H. (2020). Analysis of Groundwater Uncertainty in Climate Change (Case study: Hashtgerd Plain). Iranian journal of Ecohydrology, 7(3), 815-827. (In persian) Rezaverdinejad, V., Khorsand, A., & Shahidi, A. (2014). Evaluation and comparison of AquaCrop and FAO models for yield prediction of winter wheat under environmental stresses. J. Biodivers. Environ. Sci, 4(6), 438-449. Salemi, H.R., Mohd Soom, M.A., Lee, T.S., Mousavi, S.F., Ganji, A., & Yusoff, M.K. (2011). Application of AquaCrop model in deficit irrigation management of winter wheat in arid region. African Journal of Agricultural Research, 610, 2204-2215. Schiermeier, Q. 2014. Water risk as world warms. Nature, 505, 10–11. Shirazi, M., & Nateghi, S. (2020). Determination of the Relationships Between the Meteorological and Hydrological Droughts in the Hashtgerd Plain. Watershed Management Research, 33(1), 72-87. (In persian) Steduto, P., Hsiao, T.C., Fereres E., & Raes, D. (2012). Crop yield response to water. FAO Roma. Steduto, P., Hsiao, T.C., Raes, D. & Fereres, E. (2009). AquaCrop-The FAO crop model to simulate yield response to water: I. Concepts and underlying principles. Agron. J. 101: 426– 437. Taheri Tizro, A., Nozari, H., & Alikhani, H. (2016). Spatio-Temporal Water Levels Forecasting by Time Series-Geostatistics as a Hybrid Model in Hashtgerd Plain-Alborz Province. Journal of Water and Soil Science, 20 (76), 99-113. (In persian) Tavakoli, A.R., Moghadam M.M. & Sepaskhah, A.R. (2015). Evaluation of the AquaCrop model for barley production under deficit irrigation and rainfed condition in Iran. Agricultural Water Management, 161: 136-146. UNESCO. (2010). science report 2010, The Current Status of Science around the World, pp.542. Wali, U.S., Walia, S.S., Sidhu, A.S., & Nayyar, S. (2014). Productivity of direct seeded rice in relation to different dates of sowing and varieties in central Punjab. Journal of Crop and Weed, 10 (1): 126-129. Xie, Z., Kong, J., Tang, M., Luo, Z., Li, D., Liu, R., ... & Zhang, C. (2023). Modelling winter rapeseed (Brassica napus L.) growth and yield under different sowing dates and densities using AquaCrop model. Agronomy, 13(2), 367. Zhang, C., Kong, J., Tang, M., Lin, W., Ding, D., & Feng, H. (2023). Improving maize growth and development simulation by integrating temperature compensatory effect under plastic film mulching into the AquaCrop model. The Crop Journal, 11(5), 1559-1568. | ||
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