بررسی عملکرد دو پایگاه داده هواشناسی در تخمین ردپای آب گیاه ذرت، مطالعه موردی: دشت قزوین

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی آب دانشکده کشاورزی و منابع طبیعی دانشگاه بین المللی امام خمینی(ره)

2 دانشجوی دکتری سازه های آبی، دانشگاه تهران، تهران، ایران

3 دانشجوی دکتری آبیاری و زهکشی دانشگاه تهران، تهران، ایران

چکیده

از آنجایی که دسترسی به ایستگاه‌های سینوپتیک در همه مناطق وجود ندارد، یا ساخت و تجهیز آن‌ها به تعداد بالا ممکن است مقرون‌به‌صرفه نباشد، و یا احتمال غلط بودن داده‌های آن‌ها به‌علت خطای اندازه‌گیری یا واسنجی‌نشدن ابزارها وجود دارد، بهتر است به دنبال یافتن ابزارهای جایگزین بود که پایگاه‌های داده هواشناسی یکی از این روش‌های مناسب می‌باشند. در این مطالعه، به ارزیابی دو پایگاه داده GPCC و AgMERRA پرداخته شد. هدف از این مطالعه، بررسی دقت این دو پایگاه در محاسبه ردپای آب بود که برای یک محصول و در یک منطقه خاص به‌عنوان مطالعه موردی مورد ارزیابی قرار گرفت. به-منظور مقایسه بهتر تخمین‌ها، از میانگین تخمین، R2، RMSE و ME (حداکثر خطا) استفاده شد. نتایج نشان داد که پایگاه داده GPCC عملکرد بسیار بالاتری نسبت به پایگاه داده AgMERRA دارد. میانگین ردپای آب آبی، سبز و ردپای کل آب برای گیاه ذرت در این استان به ترتیب برابر با 58/242، 47/149 و 05/392 مترمکعب بر تند بود که این مقادیر در پایگاه GPCC برابر بود با 58/207، 78/143 و 35/351 مترمکعب بر تن و برای پایگاه AgMERRA برابر بود با 06/149، 58/110 و 64/259 مترمکعب بر تن. بر اساس نتایج، هر دو پایگاه در تخمین ردپای آب سبز، عملکرد بهتری نسبت به ردپای آب آبی داشتند. این مطالعه نشان می‌دهد که پایگاه‌های داده، می‌توانند ابزارهای مناسبی در مطالعات هواشناسی در کشاورزی باشند و در صورت صحت‌سنجی و واسنجی آن‌ها می‌توانند در مطالعات مختلف مدیریت آبی، نظیر مدیریت آبیاری، مدیریت منابع آب و مدیریت کشاورزی مورد استفاده قرار گیرند.

کلیدواژه‌ها


عنوان مقاله [English]

Study of the performance of two meteorological datasets in estimating the maize water footprint, a case study: Qazvin Plain

نویسندگان [English]

  • Hadi Ramezani Etedali 1
  • Faraz Gorgin 2
  • Parisa Kakvand 3
1 Dept. of Water Sciences and Engineering, Imam Khomeini International University
2 Ph. D Student, Department of Water Structures, University of Tehran, Tehran, Iran
3 Ph. D Student, Department of Irrigation and Drainage Engineering, University of Tehran, Tehran, Iran
چکیده [English]

Due to the lack of availability of synoptic stations, the high costs of their construction, or the possibility of the inaccuracy of their data or inaccurate calibration, it is better to find alternative tools, which meteorological datasets are one of these suitable devices. In this study, two datasets, GPCC and AgMERRA, were evaluated. The purpose of this study is to investigate the accuracy of these two datasets in calculating the water footprint of maize for a specific crop in a specific region as case studies. For comparison of the estimations, the average estimation, R2, RMSE, and maximum error (ME) were used. The results showed that GPCC is more efficient than AgMERRA in estimating the water footprint of maize. The average blue, green, and the total water footprint of maize in this province were 242/58, 149/47, and 392/05 m3/ton which was 207/58, 143/78, and 351/35 m3/ton for GPCC and 149/06, 110.58, and 259/64 m3/ton, respectively. According to the results, both datasets were more efficient in estimating the green water footprint than the blue water footprint. This study shows that datasets can be suitable tools in meteorological studies in agriculture, and if they are validated and calibrated, they can be used in various water management, such as irrigation management, water resources management, and agriculture management.

کلیدواژه‌ها [English]

  • Green Water footprint
  • Blue Water Footprint
  • synoptic station
  • GPCC
  • AgMERRA
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