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شبیه‌سازی اثر تغییر اقلیم بر عملکرد، بهره‌وری آب و طول دوره رشد چغندرقند در قزوین با استفاده از مدل AquaCrop | ||
| چغندرقند | ||
| مقاله 3، دوره 40، شماره 2، مهر 1403، صفحه 165-184 اصل مقاله (766.02 K) | ||
| نوع مقاله: کامل علمی - پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/jsb.2025.365259.1351 | ||
| نویسندگان | ||
| قاسم مرعی1؛ اصلان اگدرنژاد* 2؛ نیازعلی ابراهیمی پاک3 | ||
| 1دانشجوی کارشناسی ارشد منابع آب، گروه علوم و مهندسی آب، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران. | ||
| 2استادیار، گروه علوم و مهندسی آب، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران. | ||
| 3بخش آبیاری و فیزیک خاک، موسسه تحقیقات خاک و آب، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران | ||
| چکیده | ||
| تغییر اقلیم از عواملی است که می‌تواند در دهه‌های آینده اثرات بسیاری بر رشد و عملکرد گیاهان زراعی داشته باشد. چغندرقند یکی از محصول‌های راهبردی است که رشد و عملکرد آن تحت تأثیر دو تنش آبی و کودی تغییر می‌کند، بنابراین اطلاع از تأثیر این تنش‌ها بر گیاه در مزرعه و تغییر اقلیم برای مدیریت تولید چغندرقند ضروری است. برای دستیابی به این هدف، پژوهش حاضر در ایستگاه تحقیقاتی فیض‌آباد قزوین در طی سه سال زراعی انجام شد. عوامل مورد بررسی شامل مدیریت آبیاری در چهار دور آبیاری (I1، I2، I3 و I4 به ترتیب 6، 9، 12 و 15 روزه) و عامل کودی (از منبع اسید بوریک) در سه سطح (F0: 21، F1: 30 و F2: 39 کیلوگرم در هکتار به ترتیب نشان‌دهنده‌ی سطوح کم، متوسط و زیاد بود. برای شبیه‌سازی اثر تغییر اقلیم، داده‌های هواشناسی بر اساس سناریوهای SSP2-4.5 (حد واسط) و SSP5-8.5 (خیلی بدبینانه) و تحت دو مدل GFDL-ESM4 (مدل G) و MRI_ESM2-0 (مدل M) در طی دوره‌ی 64 ساله، 1404 الی 1468 شبیه‌سازی شدند. برای شبیه‌سازی اثر تغییر اقلیم بر عملکرد و رشد چغندرقند از مدل AquaCrop استفاده شد. نتایج شبیه‌سازی مدل AquaCrop نشان داد که در دوره زمانی آینده نزدیک میانگین عملکرد ریشه در سناریوهای خوش‌بینانه و بدبینانه در مدل G به ترتیب 40746 و 38046 کیلوگرم در هکتار و در مدل M به ترتیب 41546 و 38746 کیلوگرم در هکتار خواهد بود. در دوره زمانی آینده دور، متوسط عملکرد ریشه برای دو سناریوی خوش‌بینانه و بدبینانه در مدل G به ترتیب 52077 و 49377 کیلوگرم در هکتار و در مدل M به ترتیب 52877 و 50077 کیلوگرم در هکتار محاسبه شد، بنابراین، به‌صورت متوسط، در آینده بیش از 40 درصد عملکرد نسبت به شرایط فعلی کاهش می‌یابد. برای جبران این کاهش عملکرد، با در نظر گرفتن شرایط فعلی مدیریت آب و کود در مزرعه، افزایش تراکم بوته توصیه می‌شود. | ||
| کلیدواژه‌ها | ||
| تنش آبی؛ تنش کودی؛ تغییر اقلیم؛ چغندرقند | ||
| عنوان مقاله [English] | ||
| Simulating the effect of climate change on sugar beet yield, water productivity and growing period in Qazvin using the AquaCrop model | ||
| نویسندگان [English] | ||
| Ghasem Marei1؛ Aslan Egdernezhad2؛ niaz ebrahimipak3 | ||
| 1M.Sc. Student of Water Resources, Department of Water Sciences and Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran. | ||
| 2Assistant professor, Department of Water Sciences and Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran. | ||
| 3Department of irrigation and soil physics, Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran. | ||
| چکیده [English] | ||
| Extended Abstract Introduction Global warming has accelerated since the industrial revolution, but due to human activities and environmental degradation, this phenomenon has received increased attention in recent years. Future trends in global warming are expected to be influenced by scenarios projecting continued increases in greenhouse gas emission, particularly carbon dioxide. These scenarios predict varying levels of carbon dioxide production worldwide, which in turn affect climate factors, crop growth, and yield. Changes in climate can significantly impact agricultural production environments. To assess and predict the extent of these impacts on crop growth and yield, crop simulation models are essential tools. Among these, the AquaCrop model is widely used due to its user-friendliness, high accuracy and reliability. This model is capable of simulating variouse field conditions and is applicable to a wide range of agricultural crops, including corn, canola, wheat, saffron, and quinoa.. Sugar beet is considered a strategic crop in Iran, with its yield highly dependent on irrigation water and fertilizer application. Materials and Methods All data were collected from a research field located at the Faizabad research station in Qazvin, Iran, over three agricultural years. The experimental factors included irrigation management at four intervals (I1: 6, I2: 9, I3: 12, and I4: 15 days) and fertilizer application at three levels (F0: 21, F1: 30, and F2: 39 kh ha-1). The LARS-WG model was used to simulate meteorological data for Qazvin under two climate change scenarios: an optimistic scenario (SSP2-4.5) and a pessimistic scenario (SSP5-8.5). These simulations were performed using two atmospheric general circulation models, GFDL-ESM4 (G model) and MRI_ESM2-0 (M model), across two future periods: 2026-2045 (near-future) and 2046-2099 (-uture). The AquaCrop model was then used to simulate sugar beet yield and water productivity based on these climate projections. Some statistical criteria were applied to evaluate the performance and accuracy of both the LARS-WG and AquaCrop models.. Results and Discussion During the calibration stage, the RMSE statistics for the AquaCrop model showed a yield prediction error of 3511 kg ha-1, placing its accuracy in the excellent category (NRMSE<0.1). For water productivity, the model’s error was 1.2 kg m-3, with accuracy evaluated as good (0.1<NRMSE<0.2). In the validation stage, the AquaCrop model showed some errors and underestimations in simulating yield and water productivity, as indicated by the mean bias error (MBE) exceeding acceptable thresholds. The RMSE for yield during validation was 2797 kg ha-1. The LARS-WG model was evaluated using observed and simulated climate data for the baseline period (1950-2014). While slight underestimation of temperature and overestimation of some parameters were observed, the RMSE values were small enough to be considered negligible. The NRMSE values for all three variables studied were below 0.1, indicating high model accuracy. Furthermore, the efficiency coefficient (EF) and the index of agreement (d) were both greater than 0.8, demonstrating strong model performance. The coefficient of determination (R²) exceeded 0.9, indicating that the LARS-WG model explained over 90% of the variance in the observed data. Comparing rainfall between models, the baseline rainfall predicted by model G was lower than that of model M. Future projections revealed that under the optimistic scenario, rainfall is expected to increase compared with the current conditions, while the pessimistic scenario predicts a slight decrease. Minimum temperature changes were less consistent; the pessimistic scenario showed minimal increases, whereas the optimistic scenario exhibited more variability. Model M predicted the lowest minimum temperature, while model G predicted an increase. These climatic changes imply an increase in evapotranspiration, which, along with effects on crop growth duration, can alter the length of growing period. Since increases in evapotranspiration surpass increases in minimum temperature, the overall length of the growing period is expected to decrease. Rainfall is projected to increase by approximately 6 mm in the near-future and 8 mm in the far-future. Correspondingly, the sugar beet growing period (time from planting to harvest) is predicted to shorten comapred with the baseline period. The average growth period was 160 days during the baseline period, decreasing to 154 days in the near-future and 153 days in the far-future. Simulations using models G and M for the near future under optimistic and pessimistic scenarios yielded growth periods of 156 and 152 days, respectively. For the far future, these values were 155 and 150 days, respectively. These findings indicate that, under climate change, the growth and development phases of many crops will shorten, with the magnitude depending on crop type and climatic severity. Yield changes under water and fertilizer stress mirrored observed treatments, suggesting similar trends will continue in coming decades. In model G, the average sugar beet yield for the near future under optimistic and pessimistic scenarios were 40746 and 38046 kg.m-3, respectively representing decreases of 40 and 44% compared with current conditions. Furthermore, yield reductions are projected to be more severe in the far-future than in the near-future. Conclusion Based on climate change scenarios and growth simulations using the Aquacrop model, the results showed a yield gap of approximately 40 and 70% between potential and actual sugar beet yield. To address this issue, it is recommended to increase the planting density compared with current practices. By reducing the difference between potential and actual evapotranspiration, this strategy may help narrow the yield gap and improve overall productivity under changing climatic conditions. | ||
| کلیدواژه‌ها [English] | ||
| Climate Change, Fertilizer Stress, Sugarbeet, Water Stress | ||
| مراجع | ||
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