نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد مهندسی و مدیریت منابع آب، دانشکده عمران، دانشگاه صنعتی شاهرود

2 استادیار گروه مهندسی آب و محیط زیست، دانشکده مهندسی عمران، دانشگاه صنعتی شاهرود

3 استادیار گروه نقشه‌برداری، دانشکده مهندسی عمران، دانشگاه صنعتی شاهرود

4 دانشجوی دکتری مهندسی و مدیریت منابع آب، دانشکده مهندسی عمران، دانشگاه صنعتی شاهرود

چکیده

تخمین بارش در محاسبات بیلان انرژی، مطالعات هیدرولوژیکی، هواشناسی و اهداف کشاورزی، صنعتی، خانگی و آشامیدنی از اهمیت والایی برخوردار است. با توجه به اهمیت داده‌های بارش در علوم مختلف و فقدان شبکه باران‌سنجی گسترده و مناسب به‌­ویژه در حوزه‌های آبخیز کوهستانی، لازم است داده‌های بارش به‌­نحوی برآورد و دقت آن‌ها ارزیابی شود. هدف از این تحقیق، ارزیابی داده‌های بارش سه محصول ماهواره‌ای IMERG از نوع Near Real Time، 3B42RT-7 از نوع Real Time و PERSIANN-CDR از نوع Final Run در بازه زمانی 2000.06.01 تا 2018.09.31 در 41 ایستگاه باران‌سنجی و سه ایستگاه سینوپتیک در داخل و اطراف حوزه آبخیز نیشابور در مقیاس زمانی روزانه و ماهانه است. بررسی شاخص‌های آماری مختلف نشان داد که هیچ‌یک از سه محصول ماهواره‌ای نماینده مناسبی برای داده‌های زمینی در وسعت منطقه‌ای در مقیاس روزانه نیستند. لذا، استفاده از این محصولات در مقیاس روزانه در این حوضه در مدل‌های هیدرولوژیکی توصیه نمی‌شود. از سوی دیگر، مقیاس ماهانه به­‌واسطه تعدیل خطای برآورد بارش‌های روزانه، هر سه محصول بارش ماهواره‌ای عملکرد به­‌مراتب بهتری را نشان دادند. به‌طوری‌که میانگین همبستگی و ضریب نش‌ساتکلیف PERSIANN-CDR با داده‌های بارش ماهانه در سطح حوضه به­‌ترتیب در حدود 90 درصد و 0.75 و ارزیابی این محصول به­‌مراتب بهتر از دو محصول 3B42RT-7 و IMERG است. بر­ این ­اساس، استفاده از محصولات بارش ماهواره‌ای مقیاس ماهانه از نوع Final Run در مطالعات بیلان آب به‌­ویژه در حوضه‌های فاقد آمار، می‌توانند مورد ­توجه قرار گیرند.

کلیدواژه‌ها

عنوان مقاله [English]

Statistical assessment of satellite rainfall products in daily and monthly gauge spatial scales

نویسندگان [English]

  • Zahra Khanmohammadi 1
  • Emad Mahjoobi 2
  • Saeid Gharachelou 3
  • Ashkan Banikhedmat 4

1 MSc Student, Water Resources Engineering and Management, Faculty of Civil Engineering, Shahrood University of Technology

2 Assistant Professor. Department of Water and Environmental Engineering, Faculty of Civil Engineering, Shahrood University of Technology

3 Assistant Professor, Department of Surveying, Faculty of Civil Engineering, Shahrood University of Technology

4 PhD student of Water Resources Engineering and Management, Faculty of Civil Engineering, Shahrood University of Technology

چکیده [English]

Precipitation estimation is of great importance in energy balance calculations, hydrological studies, meteorology and agricultural, industrial, domestic and drinking purposes. Due to the importance of precipitation data in various sciences and the lack of an extensive and appropriate rainfall network, especially in mountainous catchments, it is necessary to estimate precipitation data and evaluate their accuracy. The purpose of this study is to evaluate the precipitation data of three IMERG satellite products of near real-time type, 3B42RT-7 of real-time type and PERSIANN-CDR of final-run type in the period of 06/01/2000 to 09/31/2018 in 41 rain gauge stations and three synoptic stations in and around the Neishabour Catchment area on a daily and monthly time scale. Examination of various statistical indicators showed that none of the three satellite products is a good representative of terrestrial data on a regional and daily scale. Therefore, the use of these products on a daily basis in this basin in hydrological models is not recommended. On the other hand, the monthly scale showed much better performance due to the adjustment of the error of estimating daily precipitation. So that, the correlation coefficient and Nash Sutcliffe coefficient of PERSIANN-CDR with monthly precipitation data in the basin are about 90% and 0.75, respectively, and the evaluation of this product is much better than the two products 3B42RT-7 and IMERG. Accordingly, the use of monthly scale precipitation products of the final-run type in water balance studies, especially in basins without statistics, can be considered.

کلیدواژه‌ها [English]

  • IMERG
  • Neishabour Watershed
  • PERSIANN-CDR
  • Remote sensing
  • TRMM
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