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مقایسه دو مجموعه داده بارش شبکه‌بندی شده با وضوح بالا در بالادست سد مارون در ایران | ||
| تحقیقات آب و خاک ایران | ||
| مقاله 2، دوره 50، شماره 3، مرداد 1398، صفحه 527-541 اصل مقاله (1.65 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2018.269435.668058 | ||
| نویسندگان | ||
| علی گرجی زاده* 1؛ علی محمد آخوندعلی2؛ علی شهبازی3؛ علی مریدی4 | ||
| 1دانشجوی دکترا، گروه هیدرولوژی و منابع آب، دانشکده مهندسی علوم آب، دانشگاه شهید چمران اهواز ، اهواز، ایران | ||
| 2استاد گروه هیدرولوژی و منابع آب دانشگاه شهید چمران اهواز | ||
| 3سازمان آب و برق خوزستان، اهواز، ایران | ||
| 4استادیار دانشکده عمران، آب و محیط زیست دانشگاه شهید بهشتی تهران، تهران، ایران | ||
| چکیده | ||
| برآورد ماهواره‌ای بارش مهم و ضروری است چرا که برای جبران اندازه‌گیری‌های محدود بارش باران در مناطقی که نظارت مستمر و پیوسته بارشها با توجه به پراکندگی شبکه‌های باران‌سنجی وجود ندارد، کاربرد دارند. سیستم‌های برآورد بارش ماهواره‌ای می‌توانند اطلاعات را در مناطقی که اطلاعات باران‌سنجی در دسترس نیست ارائه دهند. لذا بررسی دقت این نوع داده‌ها از اهمیت بالایی برخوردار است. در این مطالعه از داده‌های باران دو مجموعه داده بارش ماهواره‌ای PERSIANN-CDR و PERSIANN-CCS در بالا دست سد مارون (ایستگاه‌های باران‌سنجی دهنو، قلعهرییسی، ایدنک، مارگون) در سال‌های 2003 تا 2014 استفاده گردید و ارزیابی در مقیاس‌های روزانه، ماهانه، فصلی و سالانه انجام گرفت. نتایج نشان میدهد که بارش سالانه در هر دو مجموعه داده در تمامی ایستگاه‌ها کمبرآورد میشوند ولی مدل PERSIANN-CCS نسبت به PERSIANN-CDR تناسب نزدیک‌تری با داده‌های مشاهداتی دارد. در برآورد بارش فصلی، نتایج نشان دهنده مناسب‌تر بودن مدل PERSIANN-CCS در تخمین بارش و تشخیص وقایع بارش نسبت به مدل دیگر می‌باشد. در برآورد بارش ماهانه و روزانه نتایج نشان‌دهنده مناسب‌تر بودن داده‌های PERSIANN-CDR نسبت به مجموعه داده دیگر می‌باشد. همچنین با توجه به مقادیر POD (احتمال آشکارسازی) و FAR (شاخص هشدار اشتباه) برآورد شده مشخص گردید که از لحاظ شاخص POD، داده‌های روزانه بارش مدل PERSIANN-CCS و طبق شاخص FAR داده‌های بارش روزانه مدل PERSIANN-CDR عملکرد بهتری در آشکارسازی روزهای بارانی و غیر بارانی دارند. | ||
| کلیدواژه‌ها | ||
| تخمین بارندگی؛ داده های شبکه بندی شده؛ شاخص‌های ارزیابی؛ منطقه‌ایدنک | ||
| عنوان مقاله [English] | ||
| Comparison of two high-resolution gridded precipitation data sets at the upstream of the Maroun dam in Iran | ||
| نویسندگان [English] | ||
| Ali Gorjizade1؛ Alimohammad Akhoond-Ali2؛ Ali Shahbazi3؛ Ali Moridi4 | ||
| 1PhD Candidate, Department of Hydrology and Water Resources, Faculty of Water Engineering, Shahid Chamran University of Ahvaz, Ahwaz, Iran | ||
| 2Professor, Department of Hydrology and Water Resources, Faculty of Water Engineering, Shahid Chamran University of Ahvaz, Ahwaz, Iran | ||
| 3Khuzestan Water and Power Organization, Ahwaz, Iran | ||
| 4Assistant professor, Faculty of Civil, Water and Environmental Sciences, Shahid Beheshti University of Tehran, Tehran, Iran | ||
| چکیده [English] | ||
| Satellite-based precipitation estimations are important and necessary because they are used to compensate the limited rain measurements in areas where there is no continuous monitoring of rainfall due to the dispersion of rain ague networks. Satellite-based precipitation estimation systems can provide information in areas where rainfall data are not available. Therefore, the accuracy of this type of data is very important. In this study, rainfall data of two long-term satellite data sets (FARSI-CDR and PERSIANN-CCS) at the upstream of Maroun Dam (Dehno, Ghale-Raeesi, Idenak, Margoon stations) during 2003-2014 were used and evaluated on daily, monthly, seasonally and annually basis. The results show that the annual precipitation of each dataset is underestimated in all stations, but the PERSIANN-CCS model compare to the PERSIANN-CDR has better estimations for annual observations. For estimation of seasonal precipitation, the results indicate that the PERSIANN-CCS model is better than the other one for rainfall estimation and rainfall detection. For estimation of monthly and daily precipitation, the results indicate that PERSIANN-CDR data are more appropriate than the other data set. Also, regarding to POD (probability of detection) and FAR (False alarm rate) estimated data, It was found that according to POD index, PERSIANN-CCS precipitation daily data and according to FAR, daily precipitation data of PERSIANN-CDR model have better performance in detecting rainy and non-rainy days. | ||
| کلیدواژه‌ها [English] | ||
| Rainfall estimation, gridded dataset, Evaluation indicators, Idenak region | ||
| مراجع | ||
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