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ارزیابی عملکرد جداسازی چند متغیره بارش با استفاده از مدل MuDRain (مطالعه موردی: شمال شرقی استان هرمزگان) | ||
| نشریه مهندسی عمران امیرکبیر | ||
| مقاله 11، دوره 54، شماره 12، اسفند 1401، صفحه 4657-4676 اصل مقاله (2.01 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22060/ceej.2022.21063.7607 | ||
| نویسندگان | ||
| هدی بلوکی؛ مهدی فاضلی* | ||
| دانشکده فنی و مهندسی، دانشگاه یاسوج، یاسوج، ایران | ||
| چکیده | ||
| دادههای بارندگی با وضوح بالای مکانی و زمانی برای مطالعات مهندسی آب، مدلسازی هیدرولوژیکی و ارزیابی خطر سیل، به ویژه در مناطق گرمسیری با الگوهای بارندگی پیچیده ضروری است. نظر به کمبود این دادهها، جداسازی بارش ابزاری مهم است. در این مطالعه به ارزیابی عملکرد تفکیک چند متغیره بارش با استفاده از مدل MuDRain در استان هرمزگان و تأثیر همبستگی ساعتی بین ایستگاهها بر دقت شبیهسازی پرداخته شد. مقایسه سری زمانی ساعتی مشاهداتی و شبیهسازی نشان داد که مدل در حفظ ارتفاع بارش روزانه دقیق است، اما در بیشتر موارد مقادیر شدید بارش را، کمتر از مقدار واقعی شبیهسازی کرده است. همچنین، تعداد وقایع بارشهای شدید را به اندازه کافی تولید نکرده است. مقایسه نتایج تاریخهای منتخب که دارای بیشینه بارش بودهاند نشان داد که ضریب همبستگی (R) و ضریب ناش-ساتکلیف (NSE) به ترتیب بین بازههای0/1898 تا 0/9319 و 0/0319 تا 0/7251 متغیر بودهاند. مقایسه تأثیر همبستگی ساعتی نشان داد که دقت مدل در شبیهسازی بارش ساعتی برای سری زمانی با میانگین همبستگی ساعتی بیشتر، بالاتر است و ضرایب R و NSE در آن به ترتیب برابر0/7816 و 0/5856 بوده در حالی که این ضرایب برای سری زمانی با همبستگی ساعتی کمتر به ترتیب برابر 0/5155 و0/2655 بوده است. در مجموع این مدل میتواند برای مناطق دارای همبستگی ساعتی بسیار بالا با اطمینان بیشتری مورد استفاده قرار بگیرد، در این صورت همبستگی مکانی ایستگاهها به یک مزیت تبدیل میشود، زیرا با بهرهگیری از دادههای بارش ساعتی موجود در ایستگاههای مجاور، امکان ایجاد سری بارشهای ساعتی واقعبینانه در ایستگاه مورد نظر را داراست. | ||
| کلیدواژهها | ||
| بارش ساعتی؛ مدل چندمتغیره؛ MuDRain؛ تفکیک بارش؛ استان هرمزگان | ||
| موضوعات | ||
| هیدرولوژی | ||
| عنوان مقاله [English] | ||
| Evaluation of Multivariate Rainfall Disaggregation Performance Using MuDRain Model (Case Study: North East of Hormozgan Province) | ||
| نویسندگان [English] | ||
| Hoda Bolouki؛ Mehdi Fazeli | ||
| Department of Civil Engineering, Yasouj University | ||
| چکیده [English] | ||
| High-resolution spatial and temporal precipitation data are essential for water engineering studies, hydrological modeling, and flood risk assessment, especially in tropical regions with complex rainfall patterns. Due to the lack of data, rainfall disaggregation is an important tool. In this study, the performance of multivariate rainfall disaggregation using MuDRain model and the effect of hourly correlation among stations on simulation accuracy in Hormozgan province were investigated. Comparison between observed and simulated hourly time series showed that the model evaluates the amount of daily precipitation accurately, but in most cases, it simulated extreme amounts of precipitation less than the actual amounts. Furthermore, the enough number of heavy rainfall events has not been generated. Comparison of the results of selected dates with the highest rainfall showed that the Correlation (R) and Nash–Sutcliffe (NSE) Coefficients ranged from 0.1898 to 0.9319 and 0.0319 to 0.7251 respectively. Comparison of the hourly correlation impact showed that the accuracy of the model in simulating hourly precipitation was higher for time series having higher mean hourly correlation and the coefficients of R and NSE were 0.7816 and 0.5856, respectively, while these coefficients for time series with lower hourly correlation were 0.5155 and 0.2655 respectively. Generally, this model can be used with more confidence for areas with very high hourly correlations, in this case, the spatial correlation of the stations becomes an advantage, because by utilizing the available hourly rainfall data in adjacent stations, it is possible to create a series of realistic hourly rainfall at a desired station. | ||
| کلیدواژهها [English] | ||
| Hourly rainfall, Multivariate model, MuDRain, Rainfall disaggregation, Hormozgan province | ||
| مراجع | ||
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