پیوندهای مفید
آمار
| تعداد نشریات | 8 |
| تعداد شماره‌ها | 427 |
| تعداد مقالات | 5,578 |
| تعداد مشاهده مقاله | 6,830,261 |
| تعداد دریافت فایل اصل مقاله | 5,799,891 |
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 | ||
|
[1] P. Fytilas, Multivariate rainfall disaggregation at a fine time scale, Graduate thesis, University of Rome "La Sapienza", Rome, (2002). [2] D. Martins, M.L.T. Gandini, N.S. Kruk, P.I.B. Queiroz, Disaggregation of daily rainfall data for the Caraguatatuba city, in São Paulo State, Brazil, RBRH, 24 (2019). [3] D.M. Knoesen, The development and assessment of techniques for daily rainfall disaggregation in South Africa, MSc Dissertation, University of KwaZula-Natal, Pietermaritzburg, South Africa, (2005). [4] I.S. Hanaish, Multivariate Rainfall Disaggregation Using MuDRain Model: Malaysia Experience, International Journal of Civil, Mechanical Energy Science, 2(2) (2016). [5] A. Shrestha, Impact of climate change on urban flooding in Sukhumvit area of Bangkok, Master of Science Thesis, Asian Institute of Technology UNESCO–IHE, Thailand, (2013). [6] M. Safeeq, A. Fares, Accuracy evaluation of ClimGen weather generator and daily to hourly disaggregation methods in tropical conditions, Theoretical applied climatology, 106(3) (2011) 321-341. [7] Y. Lu, Statistical downscaling and disaggregation for supporting regional climate change impact studies, Doctoral thesis, Nanyang Technological University, Singapore, 2015. [8] E. Dodangeh, K. Shahedi, K. Solaimani, Effect of Weather Station Selection on Parameterization of Modified Bartlett-Lewis Rectangular Pulse (BLRPM) and HSPF Models, Journal of water and soil, 31(3) (2017) 754-771. [9] M. Alavinia, F. Nasiri Saleh, Evaluation of Applicability of HSPF Model to Estimate Runoff and Sediment in Abaru Watershed in Hamedan Province, Modares Civil Engineering journal, 13(4) (2013) 61-70. [10] J. Dastorani, M. Mahdavi, A. Salajegheh, A.F. Fard, Simulation of Daily Stream Flows in Semi-Arid Mountainous Watersheds using Hydrological Simulation FORTRAN Program (HSPF), Journal of Range and Watershed Management, 70(1) (2017) 87-100. [11] M. Ivković, A. Todorović, J. Plavšić, Improved input to distributed hydrologic model in areas with sparse subdaily rainfall data using multivariate daily rainfall disaggregation, Journal of Hydroinformatics, 20(4) (2018) 784-797. [12] U. Petry, Y. Hundecha, M. Pahlow, A. Schumann, Generation of severe flood scenarios by stochastic rainfall in combination with a rainfall runoff model, in: RIMAX Contributions at the 4th International Symposium on Flood Defence (ISFD4), Deutsches GeoForschungsZentrum GFZ, (2009). [13] D. Nijssen, A. Schumann, M. Pahlow, B. Klein, Planning of technical flood retention measures in large river basins under consideration of imprecise probabilities of multivariate hydrological loads, Natural Hazards Earth System Sciences, 9(4) (2009) 1349-1363. [14] S. Aswathy, N. Sajikumar, M. Mehsa, Watershed Modelling Using Control System Concept, Procedia Technology, 24 (2016) 39-46. [15] M.A.J. Bakhshi, Firas, Disaggregation the Daily Rainfall Dataset into Sub-Daily Resolution in the Temperate Oceanic Climate Region, International Journal of Marine Environmental Sciences, 13(1) (2019) 11-16. [16] I.S. Hanaish, K. Ibrahim, A.A. Jemain, Daily rainfall disaggregation using HYETOS model for Peninsular Malaysia, matrix, 2 (2011) 1. [17] D.S. Knoesen, The development and assessment of a regionalised daily rainfall disaggregation model for South Africa, Water SA, 34(3) (2008) 323-330. [18] V.R. Dorneles, R.d.C. Damé, C.F. Teixeira-Gandra, L.B. Méllo, M.A. Ramirez, E.B. Manke, Intensity-duration-frequency relationships of rainfall through the technique of disaggregation of daily rainfall, Revista Brasileira de Engenharia Agrícola e Ambiental, 23 (2019) 506-510. [19] H. Park, G. Chung, A Nonparametric Stochastic Approach for Disaggregation of Daily to Hourly Rainfall Using 3-Day Rainfall Patterns, Water, 12(8) (2020) 2306. [20] T.D. Beyene, M.A. Moges, S. Tilahun, Development of Rainfall Disaggregation Model in the Awash River Basin, Ethiopia, in: 6th EAI International Conference, ICAST 2018, Bahir Dar, Ethiopia, October 5-7, (2018). [21] D. Koutsoyiannis, C. Onof, H.S. Wheater, Multivariate rainfall disaggregation at a fine timescale, Water Resources Research, 39(7) (2003). [22] D. Koutsoyiannis, Rainfall disaggregation methods: Theory and applications, in: Workshop on Statistical and Mathematical Methods for Hydrological Analysis, Rome, (2003), pp. 1-23. [23] B. Debele, R. Srinivasan, J.Y. Parlange, Accuracy evaluation of weather data generation and disaggregation methods at finer timescales, Advances in water resources, 30(5) (2007) 1286-1300. [24] P. Fytilas, D. Koutsoyiannis, F. Napolitano, A case study of spatial-temporal rainfall disaggregation at the Tiber river basin, Italy, in: EGS-AGU-EUG Joint Assembly, (2003), pp. 2748. [25] H.R. Safavi, Engineering hydrology, fourth edition, Arkane Danesh Publication, Isfahan, (2014). (in Persian) [26] A. Alizadeh, The Principles of Applied Hydrology, Imam Reza (AS) University, Mashhad, (2013). (in Persian) [27] Y. Lu, X. Qin, Multisite rainfall downscaling and disaggregation in a tropical urban area, Journal of Hydrology, 509 (2014) 55-65. [28] H. Bolouki, M. Fazeli, H. Sharifzade, Prediction of Climate Change Affects on Sistan and Baluchestan Province with Emphasis on Precipitation and Temperature Variables, in: 2nd International and 5th National Conference on the Conservation of Natural Resources and Environment, (2021). (in Persian) [29] H. Bolouki, Climate Change Detection and Extraction of Intensity-Duration-Frequency Curves Using Fractal Theory for Three South Coast Provinces of Iran, Yasouj University, Yasouj, (2021). (in Persian). | ||
|
آمار تعداد مشاهده مقاله: 630 تعداد دریافت فایل اصل مقاله: 763 |
||