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تحلیل دوره بازگشتهای توام و شرطی چند مشخصه وابسته آبنمود رواناب با استفاده از توابع مفصل (مطالعه موردی: حوضه آبریز کسیلیان) | ||
تحقیقات آب و خاک ایران | ||
مقاله 17، دوره 49، شماره 2، خرداد و تیر 1397، صفحه 425-437 اصل مقاله (1.42 M) | ||
نوع مقاله: مقاله پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/ijswr.2017.236674.667711 | ||
نویسندگان | ||
سجاد عبداللهی اسدآبادی* 1؛ علی محمد آخوندعلی2؛ رسول میرعباسی نجف آبادی3 | ||
1دانشجوی دکتری مهندسی منابع آب دانشگاه شهید چمران اهواز | ||
2استاد گروه هیدرولوژی و منابع آب دانشگاه شهید چمران اهواز | ||
3دانشگاه شهرکرد | ||
چکیده | ||
اخیراً استفاده از توابع مفصل بهعنوان ابزاری کارآمد و انعطافپذیر برای ایجاد توزیعهای احتمالاتی توام پدیدههای هیدرولوژیکی چند متغیره، از قبیل سیلاب توجه هیدرولوژیستها را به خود جلب کرده است. هدف اصلی از مطالعه حاضر، استخراج و تحلیل دوره بازگشتهای توام و شرطی تعدادی مشخصه وابسته آبنمود رواناب شامل حجم رواناب، دبی بیشینه، زمان پایه و زمان وقوع دبی بیشینه آبنمود میباشد. این مشخصهها از 60 رویداد ثبتشده در ایستگاه آبسنجی ولیکبن واقع در خروجی حوضه آبریز معرف کسیلیان در بازه زمانی 1386-1354 استخراج شده است. از میان سه تابع مفصل در نظر گرفته شده شامل کلایتون، علی- میخائیل- حق و فرانک، برای دو زوج مشخصه وابسته حجم رواناب و دبی بیشینه و حجم رواناب و زمان پایه آبنمود، تابع مفصل فرانک بهعنوان مفصل برتر انتخاب شد. همچنین برای دو مشخصه وابسته دیگر یعنی زمان وقوع دبی بیشینه و زمان پایه آبنمود، تابع مفصل کلایتون بهعنوان مفصل برتر تشخیص داده شد. نهایتاً با ایجاد توزیعهای توام مفصل مبنا اطلاعات ارزشمندی از قبیل توزیعهای احتمالاتی توام، دوره بازگشتهای توام و توام شرطی محاسبه و ترسیم گردید. | ||
کلیدواژهها | ||
آبنمود رواناب؛ مفصل؛ دوره بازگشت توام؛ دوره بازگشت شرطی | ||
عنوان مقاله [English] | ||
Analysis of joint and conditional return periods for several dependent characteristics of runoff hydrograph using copula functions (Case study: Kasiliyan watershed) | ||
نویسندگان [English] | ||
Sajjad Abdollahi Asadabadi1؛ Ali-Mohammad Akhond-Ali2؛ Rasoul Mirabbasi3 | ||
1PhD Student of Water Resources Engineering, Shahid Chamran University of Ahvaz | ||
2Full Proffesor of Hydrology and Water Engineering, Faculty of Water Sciences Engineering, Shahid Chamran University of Ahvaz, Iran. | ||
3Shahrekord University | ||
چکیده [English] | ||
Recently, the use of copula functions as a practical and flexible tool for constructing joint probability distribution of multivariate hydrologic phenomena, such as flood, has attracted great attention of hydrologists. The main objective of this study is to extract and analysis of the joint and conditional return periods of some dependent characteristics of runoff hydrograph, including runoff volume, peak discharge, base time and time to peak discharge. These characteristics extracted from 60 flood events recorded in Valikbon hydrometric station, located in outlet of Kasiliyan reference watershed during 1975-2007. Three copulas, including Clyton, Ali-Mikhail-Haq and Frank were considered for constructing the joint distribution of the paired hydrograph characteristics. The Frank copula was selected as the best copula for constructing the joint distribution from paired characteristics of runoff volume and peak discharge of hydrograph and also runoff volume and base time of hydrograph. While the Clyton copula was recognized as the best copula for other two dependent characteristics, namely time of peak discharge and base time of hydrograph. After constructing joint distributions, several valuable information such as joint probability, joint and conditional return periods were calculated and plotted. | ||
کلیدواژهها [English] | ||
Runoff hydrograph, Copula, Joint return period, Conditional return period | ||
مراجع | ||
Abbasian, M. and S. Jalali (2015). Multivariate Flood Frequency Analysis Using Copula with Parametric and Nonparametric Marginal Distribution Function. Modares Civil Engineering Journal. 14, 81–92. (In Farsi) Abdul Rauf, U.F. and P. Zeephongsekul (2014). Copula based analysis of rainfall severity and duration: a case study. Theor. Appl. Climatol. 115, 153–166. doi:10.1007/s00704-013-0877-1 Ahmadi, F., Mirabbasi Najafabadi, R. and F. Radmanesh (2015). Application of Joint Deficit Index (JDI) for Analyzing Droughts over the Southern Margin of the Caspian Sea. Iran. J. Soil Water Res. 46, 431–442. doi:10.22059/ijswr.2015.56733 (In Farsi) Azizabadi-Farahani, M., Bakhtiyari, B., Ghaderi, K. and M. Rezapour (2016). The Survey of Climate Change Impact on Drought Severity- Duration- Frequency Curves Using Copulas. Iran. J. Soil Water Res. 47, 743–754. doi:10.22059/ijswr.2016.59981(In Farsi) Bacchi, B., Becciu, G. and Kottegoda (1994). Bivariate exponential model applied to intensities and durations of extreme rainfall. J. Hydrol. 155, 225–236. doi:10.1016/0022-1694(94)90166-X Bahremand, A., Alvandi, E., Bahrami, M. and M. Dashti heravi (2016). Copula functions and their application in stochastic hydrology. Scientific Journal Management System. 4, 1–20. doi:10.22069/ejang.2016.2793 (In Farsi) Bender, J., Wahl, T. and J. Jensen (2014). Multivariate design in the presence of non-stationarity. J. Hydrol. 514, 123–130. doi:10.1016/j.jhydrol.2014.04.017 Chen, L., Singh, V.P., Guo, S., Zhou, J., Zhang, J., (2015). Copula-based method for multisite monthly and daily streamflow simulation. J. Hydrol. 528, 369–384. doi:10.1016/j.jhydrol.2015.05.018 De Michele, C., Salvadori, G., Canossi, M., Petaccia, A. and R. Rosso (2005). Bivariate Statistical Approach to Check Adequacy of Dam Spillway. J. Hydrol. Eng. 10, 50–57. doi:10.1061/(ASCE)1084-0699(2005)10:1(50) Genest, C. and Favre, A., (2007). Everything You Always Wanted to Know about Copula Modeling but Were Afraid to Ask. J. Hydrol. Eng. 12, 347–368. doi:10.1061/(ASCE)1084-0699(2007)12:4(347) Ganjalikhani, M., Zounemat-Kermani, M., Rezapour, M., Rahnama, M.B., (2016). Evaluation of Copula Performance in Groundwater Quality Zoning (Case Study: Kerman and Ravar regions). Iran. J. Soil Water Res. 47, 551–560. doi:10.22059/ijswr.2016.59325 (In Farsi) Joe, H., (1997). Multivariate models and multivariate dependence concepts. CRC Press. Kao, S.-C., Govindaraju, R.S., (2008). Trivariate statistical analysis of extreme rainfall events via the Plackett family of copulas. Water Resour. Res. 44, 1-19. doi:10.1029/2007WR006261 Kao, S.-C., Govindaraju, R.S., (2007). A bivariate frequency analysis of extreme rainfall with implications for design. J. Geophys. Res. Atmospheres. 112, 1-15. doi:10.1029/2007JD008522 Mirabbasi Najafabadi, R., Fakheri-Fard, A., Dinpashoh, Y., Eslamian, S.S., (2014). Longterm Drought Monitoring of Urmia Using Joint Deficit Index (JDI). Water Soil Sci. 23, 87–103. (In Farsi) Mirabbasi, R., Fakheri-Fard, A., Dinpashoh, Y., (2012). Bivariate drought frequency analysis using the copula method. Theor. Appl. Climatol. 108, 191–206. doi:10.1007/s00704-011-0524-7 Nelsen, R.B., (2006). An Introduction to Copulas. Springer Science & Business Media. Rahimi, L., Dehghani, A., Abdolhosseini, M., Ghorbani, K., (2014). Flood Frequency Analysis Using Archimedean Copula Functions Based on Annual Maximum Series (Case Study:Arazkuseh Hydrometric Station in Golestan Province). Iranian Journal of Irrigation and Drainage. 8, 353–365. (In Farsi) Requena, A.I., Chebana, F., Mediero, L., (2016). A complete procedure for multivariate index-flood model application. J. Hydrol. 535, 559–580. doi:10.1016/j.jhydrol.2016.02.004 Salari, M., AkhoundAli, A.M., Adib, A., Daneshkhah, A.R., (2015). Bivariate Flood Frequency Analysis Using the Copula Functions. Journal of Irrigation Science and Engineering. 37, 29–38. (In Farsi) Salvadori, G., De Michele, C., (2004). Frequency analysis via copulas: Theoretical aspects and applications to hydrological events. Water Resour. Res. 40, 1-7. doi:10.1029/2004WR003133 Salvadori, G., Michele, C.D., Kottegoda, N.T., Rosso, R., (2007). Extremes in Nature: An Approach Using Copulas. Springer Science & Business Media. Sanikhani, H., Mirabbasi Najafabadi, R., Dinpashoh, Y., (2014). Modeling of Temperature and Rainfall of Tabriz Using Copulas. Irrigation and Water Engineering. 123–133. (In Farsi) Serinaldi, F., Kilsby, C.G., (2013). The intrinsic dependence structure of peak, volume, duration, and average intensity of hyetographs and hydrographs. Water Resour. Res. 49, 3423–3442. doi:10.1002/wrcr.20221 Shiau, J.T., Feng, S., Nadarajah, S., (2007). Assessment of hydrological droughts for the Yellow River, China, using copulas. Hydrol. Process. 21, 2157–2163. Shiau, J.T., (2006). Fitting Drought Duration and Severity with Two-Dimensional Copulas. Water Resour. Manag. 20, 795–815. doi:10.1007/s11269-005-9008-9 Shiau, J.T., (2003a). Return period of bivariate distributed extreme hydrological events. Stoch. Environ. Res. Risk Assess. 17, 42–57. doi:10.1007/s00477-003-0125-9 Shiau, J.T., (2003b). Return period of bivariate distributed extreme hydrological events. Stoch. Environ. Res. Risk Assess. 17, 42–57. doi:10.1007/s00477-003-0125-9 Shiau, J.T., Modarres, R., (2009). Copula-based drought severity-duration-frequency analysis in Iran. Meteorol. Appl. 16, 481–489. doi:10.1002/met.145 Snyder, W.M., (1962). Some possibilities for multivariate analysis in hydrologic studies. J. Geophys. Res. 67, 721–729. doi:10.1029/JZ067i002p00721 Vandenberghe, S., Verhoest, N.E.C., Onof, C., De Baets, B., (2011). A comparative copula-based bivariate frequency analysis of observed and simulated storm events: A case study on Bartlett-Lewis modeled rainfall. Water Resour. Res. 47, 1-16. doi:10.1029/2009WR008388 Water Resources Researches Centre of Iran (TAMAB), (2009). Hydrological and Meteorological Reports of Kasilian Watershed for the Period of 1991-92 to 2008-09. (In Farsi) Wong, S.T., (1963). A multivariate statistical model for predicting mean annual flood in new england. Ann. Assoc. Am. Geogr. 53, 298–311. doi:10.1111/j.1467-8306.1963.tb00451.x Yue, S., Rasmussen, P., (2002). Bivariate frequency analysis: discussion of some useful concepts in hydrological application. Hydrol. Process. 16, 2881–2898. doi:10.1002/hyp.1185 Zhang, L., Singh, V.P., (2006). Bivariate Flood Frequency Analysis Using the Copula Method. J. Hydrol. Eng. 11, 150–164. doi:10.1061/(ASCE)1084-0699(2006)11:2(150)
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