بررسی و پیش‌بینی جریانات سطحی استان خوزستان با استفاده از مدل‌های سری زمانی
محورهای موضوعی :
آب و محیط زیست
علیرضا انتظاری
1
,
رسول سروستان
2
1 - دانشیار اقلیم‌شناسی، دانشکده جغرافیا و علوم محیطی، دانشگاه حکیم سبزواری، سبزوار، ایران.
2 - دانشجوی دکترای در رشته آب و هواشناسی شهری، دانشکده جغرافیا و علوم محیطی، دانشگاه حکیم سبزواری، سبزوار، ایران.*(مسوول مکاتبات)
تاریخ دریافت : 1396/05/27
تاریخ پذیرش : 1397/11/15
تاریخ انتشار : 1400/02/01
کلید واژه:
سری زمانی,
جریانات سطحی,
فصلی- ضربی,
خوزستان,
پیش‌بینی,
چکیده مقاله :
زمینه و هدف: پژوهش حاضر به مطالعه و بررسی جریانات سطحی استان خوزستان و پیش‌بینی آن برای دوره 1398 تا 1407 با استفاده از مدل‌های سری زمانی است.روش بررسی: پژوهش حاضر در 9 ایستگاه منتخب از استان خوزستان به منظور مقایسه دقت مدل سری‌های زمانی و پیش‌بینی مقدار جریانات سطحی انجام‌شده است. برای این منظور از داده‌های دبی ماهانه ایستگاه هیدرومتری به مدت 22 سال (1370-1392) استفاده شده است. از مدل سری زمانی فصلی ضربی جریانات سطحی بررسی و بهترین مدل برازش داده شد، صحت و دقت مدل‌ها به کمک نرمال بودن توزیع باقی‌مانده‌ها، فرض ثابت بودن واریانس، نمودارهای مربوط به باقی‌مانده‌ها در طول زمان، تائید گردید.یافته‌ها: یافته‌های این مطالعه نشان داد، بهترین مدل‌های برازش شده در ایستگاه‌های اهواز (1,1,1)(1,0,1) SARIMA، بامدژ(1,1,0)(1,0,1) SARIMA، تله زنگ (1,0,1)(1,1,1) SARIMA، حرمله(1,0,1)(1,1,1) SARIMA، دزفول (2,0,1)(1,1,1) SARIMA، دشت بزرگ (2,0,2)(1,1,1) SARIMA، دوکوهه (2,2,0)(1,1,1) SARIMA، گتوند (2,1,1)(1,0,1) SARIMA و فارسیاب(2,1,1)(1,1,2) SARIMA می‌باشند؛ که این مدل‌ها از دقت خوبی برای پیش‌بینی جریانات سطحی برخوردار بودند.بحث و نتیجه‌گیری: نتایج جریانات سطحی برای سال‌های 1398 تا 1407 نشان داد که جریانات سطحی در تمام ایستگاه‌های منتخب کاهش می‌یابد و این کاهش در ایستگاه اهواز به بیش‌ترین و ایستگاه دوکوهه به کمترین مقدار به ترتیب با 78/9 و 58/0 می‌رسد. همچنین نتایج پیش‌بینی ماهانه نشان داد که بیش‌ترین و کمترین مقدار کاهش جریانات سطحی به ترتیب در آذر ماه با 98/6 و شهریور با 67/1 خواهد رسید.
چکیده انگلیسی:
The purpose of this study was to study the surface currents of Khuzestan province and its prediction for the period (2019Background and Objective: The present study is to evaluate the surface currents of Khuzestan province and its forecast for the period 2019 to 2021 using time series models.Material & Methodlogy: The present study was conducted in 9 selected stations from Khuzestan province in order to compare the accuracy of the time series model and predict the amount of surface currents. For this purpose, the monthly flow data of the hydrometric station for 22 years (1391-2014) has been used. The multiplicative seasonal time series model of surface currents was investigated and the best model was fitted. Findings: The results of these studies show that the best models fitted in SARIMA (1,1,1) (1,0,1), SARIMA, SARIMA (0,1,1) (1,0,1), telephoto SARIMA, Primate (1,0,1) (1,1,1) SARIMA, Dezful (1,0,2) (1,1,1) SARIMA, Plain SARIMA, Dokehe (0,2,2) (1,1,1) SARIMA, Gotvand (1,1,2) (1,0,1) SARIMA (1,1,1) And SARAB (1.1.2) (2.1.1), which had good accuracy to predict surface currents.Discussion and Conclusion: Surveying the annual prediction of surface currents for 2019 to 2029 showed that surface currents in all selected stations decreased and this decrease in Ahwaz station to the highest and the two-hill station to the lowest values reaches to 9.78 and 0/58 respectively; also, the monthly forecast showed that in December, with 6/98 and 1/67, the highest and lowest decreases would occur.
منابع و مأخذ:
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Manzafari, G, Urban Hydrology, 2010, Yazd University Press Center, 1st edition. (In Persian)
Asakereh, H, Modeling of Arima for annual average temperature of Tabriz city, 2010, Geography Research Quarterly, 756.15622-15601. (In Persian)
Niromand, H; and Bzorg Nia A, Time Series, 2008, Payame Noor University Press. (In Persian)
Komornık, J. Komornıkova, M. Mesiar, R. Szokeova, and J. Szolgay 2006. Comparison of forecasting performance of nonlinear models of hydrological time series.Physics and Chemistry of the Earth, 31: 1127–1145.
Burlando P. Montana A. and Raze R. 1996. Forecasting of storm rainfall by combined use of radar, rain gages and linear models, Atmospheric Research, 42: 199-216.
Durdu, o. f. 2010. A hybrid neural network and Arima model for water quality time series prediction. Engineering Applications of Artificial Intelligence. 23: 586-594.
Damle, C. and A. Yalcin. 2007. Flood prediction using time series data mining. Journal of Hydrology. 333, (2-4): 305-316.
Quimpo, R. 1971. Structure relation between parametric and stochastic hydrology International symposium on mathematical models in hydrology. Int. Assoc. of hydrology.Sci. Warasaw: 140-150.
Karvonen T., Koivusalo H., Jauhiainen M., Palko J. and Weppling K. 1999. A hydrological model for predicting runoff from different land use areas, Journal of Hydrology, 217: 253-265.
Spolia, S.K. and S. Chander. 1970. Modeling of surface runoff systems by an ARIMA J. Hydrology, 22: 317-332.
Chow, V. T., Maidment, D. R. and Mays, L.W. 1988. Applied Hydrology, New York, Mc Graw Hill Pub. p. 572
Ashgar Tosi, S. The prediction of the occurrence of drought in Khorasan province and optimization of the pattern of cultivation for adaptation to it, 2003, Master's degree in irrigation and drainage engineering, Ferdowsi University of Mashhad. (In Persian)
Bashiri, M. Watankha, M. Comparison of Different Time Series Analysis Methods in Monthly Dubai Monthly Forecast Estimation of Karkheh Basin, 2010, Water Management and Irrigation Journal,2. (In Persian)
Sharifan, H and Ghahraman, B, Estimation of Rain Forecasting Using ARIMA Technique in Golestan Province, 2007 Journal of Agricultural Science and Natural Resources, 3 (14). (In Persian)
Ghahraman, N and Gharakhani, A, Evaluation of time series models for estimation of evaporation from the case of case study: Shiraz Station", 2011, Journal of Water Research in Agriculture, C: (1) 81-75. (In Persian)
Statistical Calendar of Khuzestan Province, 2017. (In Persian)
Cohen, S. A. Ianetz and G. Stanhill. 2002. Evaporative climate changes at Bet Dagan, 1964-1998. Agricultural and Forest Meteorol. 111(2): 83-91.
Rahimzadeh, F, Statistical Methods in Meteorological and Climatological Studies. Seyed Bagher Hosseini Publishing House, 2011, Tehran, 463. (In Persian)
Khorrami, Mostafa, Bzorg Nia, A, Analyzing Time Series Models with Minifry Software 14. Spokesperson's Publishing House, Mashhad, 1386, 336. (In Persian)
