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ارزیابی عملکرد دادههای بازتحلیل شده Era-Interim در تخمین بارش روزانه و ماهانه | ||
| تحقیقات آب و خاک ایران | ||
| مقاله 2، دوره 50، شماره 4، شهریور 1398، صفحه 777-791 اصل مقاله (1.22 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2018.261613.667962 | ||
| نویسندگان | ||
| اصغر عزیزیان* 1؛ هادی رمضانی اعتدالی2 | ||
| 1استادیار گروه مهندسی آب/ دانشگاه بین المللی امام خمینی قزوین | ||
| 2استادیار گروه مهندسی آب دانشگاه بین المللی امام خمینی قزوین | ||
| چکیده | ||
| تخمین صحیح بارش در شبیهسازی سیلاب، پایش خشکسالی و مدیریت منابع آب امری ضروری و مهم بشمار میآید. در حال حاضر بخشهای عمدهای از جهان، فاقد ایستگاههای اندازهگیری بارش زمینی هستند و حتی در صورت وجود از نظر زمانی و مکانی دارای پوشش مناسبی نیستند و همین مساله مطالعات منابع آب را با چالشی اساسی روبرو مینماید. یکی از مهمترین منابع بارشی موجود، پایگاههای بارشی مدل مبنا میباشد که با تلفیق فنآوریهای ماهوارهای، مدلهای سطح زمین (LSMs) و مدلهای عمومی گردش جو (GCMs) دادههای شبکهبندی شده با توان تفکیک مکانی و زمانی بالا را برای تمامی نقاط دنیا ارائه مینماید. این گزینه میتواند کمبود اطلاعات ایستگاههای زمینی را به ویژه در مناطقی که از این حیث با کمبود مواجه هستند تا حدود زیادی برطرف سازد. در پژوهش حاضر به ارزیابی عملکرد یکی از مهمترین پایگاههای بارشی مدل مبنا به نام پایگاه ECMWF در گامهای زمانی روزانه و ماهانه در سطح حوضه آبریز سفیدرود (در بازه زمانی 2000 تا 2008) پرداخته شده است. همچنین برای ارزیابی هرچه بهتر پایگاه مذکور از دادههای بارش مبتنی بر سنجش از دور TRMM نیز استفاده گردید. نتایج حاصل از ارزیابی عملکرد پایگاه بارش ECMWF در سطح این حوضه در دو مقیاس زمانی روزانه و ماهانه حاکی از آن است که این منبع دارای همبستگی بالایی با ایستگاههای زمینی به ویژه در بخشهای جنوبی، مرکزی و غربی حوضه است. به عنوان مثال در هر دو گام زمانی روزانه و ماهانه، همبستگی بین متوسط دادههای بارشی این منبع با دادههای بارش زمینی به ترتیب در حدود 83/0 و 94/0 برآورد گردید در حالیکه در صورت استفاده از پایگاه TRMM مقادیر مذکور به ترتیب معادل 32/0 و 57/0 بدست آمد. برخلاف پایگاههای بارشی بازتحلیل شده، یکی از نقاط ضعف پایگاههای بارشی همچون TRMM، تخمین ضخامت ابر و میزان آب قابل بارش توسط آن، تنها بر اساس تکنیکهای مبتنی بر سنجش از دور میباشد. همچنین از نظر آمارههای طبقهبندی، پایگاه بارش ECMWF در هر دو گام زمانی روزانه و ماهانه با دارا بودن مقادیر کم شاخص FAR (گزارشهای اشتباه)، مقادیر بالای شاخص Accuracy (صحت پیشبینیهای درست) و نیز مقدار بالا در تشخیص روزهای بارانی (POD) دارای عملکرد بسیار مناسبی میباشد. از آنجائی که حوضه آبریز سفیدرود با توجه به وسعت زیاد دارای تنوع اقلیمی، توپوگرافیکی و پوشش گیاهی متفاوتی است، نتایج بدست آمده در آن میتواند راهنمای مناسبی برای استفاده در حوضههای مشابه مدنظر قرار گیرد. لذا در حوضههای فاقد آمار که امکان دسترسی به دادههای زمینی برای ارزیابی عملکرد پایگاههای بارش مختلف میسر نمیباشد، استفاده از این منبع بارشی ارزشمند میتواند سودمند باشد. | ||
| کلیدواژه‌ها | ||
| داده های باز تحلیل شده؛ ECMWF؛ تخمین بارش؛ سنجش از دور؛ حوضه آبریز سفیدرود | ||
| عنوان مقاله [English] | ||
| Assessing the Accuracy of European Center for Medium Range Weather Forecasts (ECMWF) Reanalysis Datasets for Estimation of Daily and Monthly Precipitation | ||
| نویسندگان [English] | ||
| Asghar Azizian1؛ hadi ramezani etedali2 | ||
| 1Assistant Professor in Water Engineering Department/ Imam Khomeini International University | ||
| 2Assistant Professor in Water Engineering Dept/ IKIU University, Qazvin, Iran | ||
| چکیده [English] | ||
| An accurate estimation of precipitation is important and necessary for flood simulation, drought monitoring and water resources management. Currently, most parts of the world are suffering from the lack of the rain gauge observations and the spatial coverage of ground observations aren’t enough and continues. One of the most important precipitation datasets is the model-based precipitation datasets, by which the satellite techniques, the general circulation models (GCMs) and the land surface models (LSMs) are integrated to provide high temporal and high resolution datasets for all parts of the world. This datasets can compensate the lack of adequate ground observation gauges or can be considered as an alternative for ground observations, especially in ungauged regions. In this research the accuracy of the most important reanalysis datasets, called ECMWF, for estimation of daily and monthly precipitation over the SefidRood watershed for the time period of 2000-2008 was investigated. In addition, for better assessment of the proposed precipitation datasets, TRMM dataset was used. Findings on daily and monthly time scales, show that the correlation coefficient (CC) between observed and ECMWF dataset is so remarkable, especially in south, central and west parts of the study area. For instance, the CC values of the average precipitation of ECMWF data versus gauge datasets in both daily and monthly time steps were estimated to be about 0.83, 0.94, respectively, while the CC values for TRMM dataset versus gauge datasets were estimated to be 0.32 and 0.57, respectively. In contrast to reanalysed datasets, one of the most important weakness of the precipitation datasets such as TRMM is that they estimate the rainfall only based on the cloud thickness and its available water. Moreover, according to the categorical verification statistics in both time spans, ECMWF due to having low value of false alarm ratio (FAR) and high values for accuracy and probability of detection (POD) yields acceptable results over the SefidRood watershed. SefidRood watershed is a large scale region and contains different climate and topographical conditions and hence the results of this research can be used as an appropriate guidance for other similar areas. Based on the findings in this study it’s highly recommended for using this rainfall dataset as one of the best alternatives for ground observations, especially in data sparse regions that accessing to ground datasets is so hard or almost impossible. | ||
| کلیدواژه‌ها [English] | ||
| Reanalysis datasets, ECMWF, Rainfall estimation, remote sensing, SefidRood Catchment | ||
| مراجع | ||
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