Assessing the accuracy of station precipitation data and reanalysis for runoff simulation (case study: Shapur watershed)

Document Type : Original Article

Authors

1 Imam Khomeini International University, Qazvin, Iran

2 Tarbiat Modares University, Tehran, Iran

10.22034/rsgi.2024.60988.1068

Abstract

The current research was conducted to evaluate the effectiveness of the reanalysis data of Era-interim, Agera5, and station data to simulate runoff using the Sacramento model in the Shapur watershed. Focusing on an innovative approach, this study provides solutions for integrating reanalysis data into runoff modeling that can improve the flexibility and accuracy of hydrological models. The research data were analyzed by statistically comparing the simulated discharge with the observed discharge at the watershed outlet on a daily time scale. The results showed that the discharge simulated by the station precipitation data with a correlation coefficient of 0.93 with the observed discharge performs better than the discharge simulated by the reanalysis data. Also, among the reanalysis data, the Agera5 data with a correlation coefficient of 0.82 performs better than the Era-interim data. The results of Era-interim data show an underestimation in the amount of precipitation, which is because it is located in the Shapur watershed (the coastline bordering the Oman Sea and the Persian Gulf). Also, in the review of the long-term monthly data, the reanalysis data in the hot months of Dubai has not been correctly simulated, which is due to the durability and low thickness of the clouds, and this has caused a decrease in the accuracy of the amount of precipitation. Finally, due to the proper distribution of rain gauge stations in this basin, the results obtained from the station data are better than the reanalysis data.

Keywords

Main Subjects

پژوهش حاضر به‌منظور ارزیابی کارایی داده‌های بازتحلیل پایگاه‌های Era-interim، Agera5 و داده‌های ایستگاهی جهت شبیه‌سازی رواناب با استفاده از مدل Sacramento در حوضه آبخیز شاپور انجام شده است. با تمرکز بر رویکردی نوآورانه، این مطالعه راهکارهایی برای ادغام داده‌های بازتحلیل در مدل‌سازی رواناب ارائه می‌دهد که می‌تواند انعطاف‌پذیری و دقت مدل‌های هیدرولوژیکی را ارتقا ‌بخشد. داده‌های پژوهش از طریق ارزیابی آماری دبی شبیه‌سازی‌شده با دبی مشاهداتی در خروجی حوضه در مقیاس زمانی روزانه مورد تجزیه‌وتحلیل قرار گرفتند. نتایج نشان داد دبی شبیه‌سازی‌شده توسط داده‌های بارندگی ایستگاهی با ضریب همبستگی 93/0 با دبی مشاهداتی عملکرد بهتری نسبت به دبی شبیه‌سازی‌شده توسط داده‌های بازتحلیل­ دارد. هم‌چنین در میان داده‌های بازتحلیل­، داده Agera5 با ضریب همبستگی 82/0 دارای عملکرد بهتری نسبت به داده Era-interim می‌باشد. نتایج داده Era-interim کم برآوردی در مقادیر بارش را نشان می‌دهد که علت این امر واقع‌شدن در حوضه آبخیز شاپور (خط ساحلی هم‌مرز دریای عمان و خلیج‌فارس) می‌باشد. هم‌چنین در بررسی صورت گرفته در داده‌های بلندمدت ماهانه، داده‌های بازتحلیل­ در ماه‌های گرم سال دبی را به‌درستی شبیه‌سازی نکرده است که علت این امر دوام و ضخامت کم ابرها می‌باشد و این مسئله باعث کاهش دقت در مقدار بارش شده است. درنهایت به دلیل پراکندگی مناسب ایستگاه‌های باران‌سنجی در این حوضه نتایج حاصل از داده‌های ایستگاهی بهتر از داده‌های بازتحلیل‌ می‌باشد.

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Volume 4, Issue 10
April 2024
Pages 147-123
  • Receive Date: 25 March 2024
  • Revise Date: 05 July 2024
  • Accept Date: 18 April 2024