Fluctuations Analysis of Rainfall and Runoff in Aras Border Basin under Climate Change Conditions
Subject Areas : Farm water management with the aim of improving irrigation management indicatorsAmin Sadeqi 1 , Yagob Dinpashoh 2
1 - Department of Water Engineering, Faculty of Agriculture, Tabriz University, Tabriz, Iran
2 - Department of Water Engineering , Faculty of Agriculture, University of Tabriz, Tabriz, Iran
Keywords: Abrupt Change, Simulation, Runoff, Precipitation, GCM,
Abstract :
In this study, rainfall and runoff data recorded of selected stations of Aras Boundary Basin were used to analyze rainfall and runoff fluctuations and they are projected for horizons, 2050. The Pettitt test was used to detect the breakpoint in rainfall and runoff time series. Trends in rainfall and runoff were also calculated using the original and modified Mann-Kendall test. To project the future, general circulation models (GCMs) under two greenhouse gas emission scenarios i.e. RCP4.5 (low emission) and RCP8.5 (high emissions) were used. The Eureqa Formulize tool was used to simulate the rainfall-runoff process. Results showed that most of the abrupt changes have occurred in the second half of the 1990s. 83% of seasonal time series breakpoints were related to runoff. Also, 67% of the abrupt changes have occurred in the winter and spring seasons. The highest increase in annual rainfall (according to RCP4.5 scenario) at Nir station is expected to be 9% and the highest decrease in annual rainfall (according to RCP8.5 scenario) at Khoy station is predicted at 11%. It is also worth mentioning that in the seasonal time scale will have the highest rainfall reduction in summer. The Eureqa Formulize performed very well at all stations with NRMSE of less than 0.5%. The results indicated that the lowest slope of the base period runoff trend line (in seasonal time scale) was -1.3 million m3 in summer at Badalan station. There will be no significant change in the annual flow in the future period.
امانی، ا. و حسینی شمعچی، ع. 1389. بررسی پتانسیل انرژی باد در ایستگاههای حوضه آبریز رودخانه ارس جنوبی. مجله علمی- پژهشی فضای جغرافیایی، سال 10، شماره 29، 26-1.
آذری، م.، مرادی، ح.، ثقفیان، ب. و فرامرزی، م. 1392. ارزیابی اثرات هیدرولوژیکی تغییر اقلیم در حوضه آبخیز گرگانرود. نشریه آب و خاک (علوم و صنایع کشاورزی)، جلد 27، شماره 3، 547-537.
تابان، ح. و ظهرابی، ن. و نیکبخت شهبازی، ع. 1398. شبیهسازی متغیرهای هیدرواقلیمی AOGCMs و بررسی دامنه تغییرات متغیرها تحت تأثیر تغییر اقلیم در حوضه دز علیا. علوم و مهندسی آبیاری، جلد 42، شماره 3، 161-147.
ساری صراف، ب.، قلی نژاد، ن. و کمانی، ا. 1390. بررسی خشکسالی و ترسالی حوضه ارس با استفاده از نمایههای مبتنی بر بارش. فصلنامه جغرافیای طبیعی لار، سال 4، شماره 12، 15-1.
عساکره، ح. و اکبرزداه، ی. 1396. شبیهسازی تغییرات دما و بارش ایستگاه سینوپتیک تبریز طی دوره (2100-2010) با استفاده از ریزمقیاس نمایی آماری (SDSM) و خروجی CanESM2. جغرافیا و مخاطرات محیطی، شماره 21، 174-153.
مرتضوی زاده، ف. و گودرزی، م. 1397. ارزیابی اثرات تغییراقلیم برروی رواناب سطحی و آب زیرزمینی با استفاده از مدل اقلیمی HadGEM2 (مطالعه موردی هشتگرد). نشریه آب و خاک (علوم و صنایع کشاورزی)، جلد 32، شماره 2، 446-433.
Arnell, N.W. and Reynard, N.S. 1996. The effects of climate change due to global warming on river flows in Great Britain. Journal of Hydrology, 183(3-4): 397-424.
Azmi, M., Rüdiger, C. and Walker, J.P. 2016. A data fusion‐based drought index. Water Resources Research, 52(3): 2222-2239.
Demirhan, H. and Atilgan, Y.K. 2015. New horizontal global solar radiation estimation models for Turkey based on robust coplot supported genetic programming technique. Energy Conversion and Management, 106: 1013-1023.
Farsi, N. and Mahjouri, N. 2019. Evaluating the contribution of the climate change and human activities to runoff change under uncertainty. Journal of Hydrology, 574: 872-891.
Gebremicael, T. G., Mohamed, Y. A., Betrie, G. D., van der Zaag, P. and Teferi, E. 2013. Trend analysis of runoff and sediment fluxes in the Upper Blue Nile basin: A combined analysis of statistical tests, physically-based models and landuse maps. Journal of Hydrology, 482: 57-68.
Hamed, K.H. and Rao, A.R. 1998. A modified Mann-Kendall trend test for autocorrelated data. Journal of Hydrology, 204(1–4):182–196.
Huntington, T. G. 2003. Climate warming could reduce runoff significantly in New England, USA. Agricultural and Forest Meteorology, 117(3-4): 193-201.
IPCC 2013. Climate Change: The Physical Science Basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press.
Kendall, MG. 1975. Rank correlation methods. Charles Griffin, London 35.
Li, B., Su, H., Chen, F., Li, H., Zhang, R., Tian, J., Chen, Sh., Yang, Y. and Rong, Y. 2013. Separation of the impact of climate change and human activity on streamflow in the upper and middle reaches of the Taoer River, Northeastern China. Theoretical and Applied Climatology, 118(1-2): 271-283.
Liu, J., Chen, J., Xu, J., Lin, Y., Yuan, Z. and Zhou, M. 2019. Attribution of runoff variation in the headwaters of the Yangtze River Based on the Budyko Hypothesis. International Journal of Environmental Research and Public Health, 16(14): 2506.
Liu, N., Harper, R. J., Smettem, K. R. J., Dell, B. and Liu, S. 2019. Responses of streamflow to vegetation and climate change in southwestern Australia. Journal of Hydrology, 572: 761-770.
Liu, Y., Hu, X., Wu, F., Chen, B., Liu, Y., Yang, S. and Weng, Z. 2019. Quantitative analysis of climate change impact on Zhangye City’s economy based on the perspective of surface runoff. Ecological Indicators, 105: 645-654.
Mallakpour, I., Sadegh, M. and AghaKouchak, A. 2018. A new normal for streamflow in California in a warming climate: Wetter wet seasons and drier dry seasons. Journal of Hydrology, 567: 203-211.
Mann, H.B. 1945. Nonparametric tests against trend. Journal of the Econometric Society, 13(3):245–259.
Młyński, D., Cebulska, M. and Wałęga, A. 2018. Trends, variability, and seasonality of maximum annual daily precipitation in the upper Vistula basin, Poland. Atmosphere, 9(8): 313.
Pettitt, A. N. 1979. A non‐parametric approach to the change-point problem. Journal of the Royal Statistical Society: Series C (Applied Statistics), 28(2): 126-135.
Radchenko, I., Dernedde, Y. Mannig, B. Frede, H. G. and Breuer, L. 2017. Climate change impacts on runoff in the Ferghana Valley (Central Asia). Water Resources, 44(5): 707-730.
Reshmidevi, T.V., Kumar, D.N., Mehrotra, R. and Sharma, A. 2018. Estimation of the climate change impact on a catchment water balance using an ensemble of GCMs. Journal of Hydrology, 556: 1192-1204.
Schmidt, M. and Lipson, H. 2009. Distilling free-form natural laws from experimental data. Science, 324(5923): 81-85.
Sen, P. K. 1968. Estimates of the regression coefficient based on Kendall's tau. Journal of the American Statistical Association, 63(324): 1379-1389.
Sfyrakis, C. 2010. Runoff prediction from a hydrological spatio-temporal database. M.Sc. Thesis, Artificial Intelligence, School of Informatics, University of Edinburgh, (1-90).
Teng, J., Chiew, F. H. S., Timbal, B., Wang, Y., Vaze, J. and Wang, B. 2012. Assessment of an analogue downscaling method for modelling climate change impacts on runoff. Journal of Hydrology, 472: 111-125.
Xie, P., Wu, Z., Sang, Y. F., Gu, H., Zhao, Y. and Singh, V. P. 2018. Evaluation of the significance of abrupt changes in precipitation and runoff process in China. Journal of Hydrology, 560: 451-460.
Xu, J., Wang, J., Wei, Q. and Wang, Y. 2016. Symbolic regression equations for calculating daily reference evapotranspiration with the same input to Hargreaves-Samani in arid China. Water Resources Management, 30(6): 2055-2073.
Yang, W., Long, D. and Bai, P. 2019. Impacts of future land cover and climate changes on runoff in the mostly afforested river basin in North China. Journal of Hydrology, 570: 201-219.
Zheng, H., Chiew, F. H., Charles, S. and Podger, G. 2018. Future climate and runoff projections across South Asia from CMIP5 global climate models and hydrological modelling. Journal of Hydrology: Regional Studies, 18: 92-109.
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