اثر تغییر اقلیم بر تغییرات تبخیر از سطح چاه نیمه های سیستان
محورهای موضوعی :
آب و محیط زیست
حسین بزی
1
,
حسین ابراهیمی
2
,
بابک امین نژاد
3
1 - گروه عمران ، واحد بین المللی کیش، دانشگاه آزاد اسلامی، جزیره کیش، ایران.
2 - دانشیار گروه علوم و مهندسی آب، واحد شهر قدس، دانشگاه آزاد اسلامی، تهران، ایران.*(مسوول مکاتبات)
3 - استادیار،گروه عمران آب، دانشکده فنی و مهندسی، واحد رودهن، دانشگاه آزاد اسلامی، رودهن، ایران.
تاریخ دریافت : 1398/07/22
تاریخ پذیرش : 1398/08/22
تاریخ انتشار : 1400/12/01
کلید واژه:
مدل SDSM,
چاه نیمه های سیستان,
تبخیر,
سناریوهای اقلیمی,
مدل سازی,
چکیده مقاله :
زمینه و هدف : تبخیر یکی از روش های هرز منابع آب در نواحی جغرافیایی است و در مطالعات منابع آب از اهمیت ویژه ای برخوردار است .هدف از این مطالعه ارایه مدل موثر اقلیمی بر نوسانات تبخیر از سطح چاه نیمه های منطقه سیستان طی دهه های آتی در نتیجه تغییر اقلیم می باشد.روش بررسی : در تحقیق حاضر پایگاه داده ها شامل داده های تبخیر سد چاه نیمه و داده های شبکه ای بزرگ مقیاس تهیه شده است. از مدل SDSM برای شبیه سازی تبخیر دهه های آتی تحت سه سناریو RCP2.6 ،RCP4.5 و RCP8.5 استفاده شده است دوره پایه برای مدل سازی از سال 1983 تا 2005 (23 سال) می باشد.یافته ها : مقایسه برآورد تبخیر برای دو دوره زمانی آینده و تحت سناریوهای مختلف نشان داد که برای دوره زمانی 2100-2080 سناریو RCP2.6 و RCP8.5 مقادیر بیشتری برای تبخیر تخمین زدند. بررسی ورودی ها نشان داد که دما هوا، ارتفاع ژئوپتانسیل و شاخص های وزش باد بیشترین تاثیر را در تبخیر چاه نیمه های سیستان دارند.بحث و نتیجه گیری: نتایج این مطالعه نشان داد که میزان تبخیر در دوره 2100-2080 افزایشی، بیش از 300 میلی متر در سال تجربه خواهد کرد. بیشترین افزایش تبخیر در دوره گرم سال خواهد بود.
چکیده انگلیسی:
Background and Objective: Evaporation is one of the wasteful methods of water resources in geographical areas and is of special importance in the study of water resources.Material and Methodology: In the present study, databases including Chah Nimeh dam evaporation data and large-scale network data have been prepared. The SDSM model is used to simulate the evaporation of the coming decades under three scenarios: RCP2.6, RCP4.5 and RCP8.5. The basic modeling period is from 1983 to 2005 (23 years)Findings: Comparison of evaporation estimates for the next two time periods and under different scenarios showed that for the time period 2100-2080 scenarios RCP2.6 and RCP8.5 estimated higher values for evaporation. Examination of inputs showed that air temperature, geopotential height and wind indices have the greatest impact on the evaporation of wells in SistanDiscussion and Conclusion: The results of this study showed that the rate of evaporation in the period of increasing 2100-2080 will experience more than 300 mm per year. The greatest increase in evaporation will be in the warm period of the year.
منابع و مأخذ:
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Wilby, R. L., Wigley, T. M. L., Conway, D., Jones, P. D., Hewitson, B. C., Main, J. and Wilks, D. S., (1998). “Statistical downscaling of general circulation model output: A comparison of methods”. J. Water Resources Research, Vol 34, PP. 2995-3008.
Wilby, R. L., & Harris, I. (2006). A framework for assessing uncertainties in climate change impacts: Low‐flow scenarios for the River Thames, UK. Water Resources Research, 42(2).pp18-25.
Stephen, P., Charles, B. C., and Bates James, P. H., (2004). Statistical Downscaling of Daily precipitation from observation and Model Atmospheric Field, Hydrological Processes, Vol. 18, pp. 1373-1394.
Wilby Robert L. and Christian W. Dawson (2004), Using SDSM Version 3.1 - A decision support tool for the assessment of regional climate change impacts, A Consortium for the Application of Climate Impact Assessments, Environment Agency of England and Wales.
Martynov, A., Laprise, R., Sushama, L., Winger, K., separovic, L., & Dugas, B. (2013). Reanalysis-driven climate simulation over cordex North America domain using the Canadian Regional Climate Model. Version 5: model performance evaluation. Climate Dynamics, 41(11-12), PP. 2973-3005.
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Herath, S., and Ratnayake, U., (2004), Monitoring rainfall trends, to predict adverse impacts-a case study from Sri Lanka 1964-1993. Global Environ. Change, Vol. 14, pp. 71-79.
Easterling, D. R., Horton, B., Jones, P. D., Peterson, T. C., Karl, T. R., Parker, D. E., and Folland, C. K., (1997). Maximum and minimum temperature trends for the globe. Science, Vol. 277, No. 5324, pp. 364-367.
IPCC, (2007). Climate Change: The physical science basis. In: Solomon, S., Qin, D, Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor, M., Miller H.L. (Eds), Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge.
Deryng D, Conway D, Ramankutty N, Price J, Warren R. (2014). Global crop yield response to extreme heat stress under multiple climate change futures Environmental, Research Letters, Vol.9,pp.340-345
Mishra, A K., Ines, A. V., Singh, V. P., and Hansen, j. w., (2013). Extraction of information content from stochastic disaggregation and bias corrected downscaled precipitation variables for crop simulation and Stochastic Environmental Research and Risk Assessment, vol. 27, No. 2, pp. 449-457.
Chu, J. T., Xia, J., Xu, C. Y., & Singh, V. P. (2010). Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River, China. Theoretical and Applied Climatology, 99(1-2), pp.149-161.
Fowler H. J., and Wilby R. L., (2007). Beyond the downscaling comparison study. International Journal of Climatology. Vol. 27, pp. 1543-1545.
Wang Y. Q. Leung L. R. McGregor J. L. Wang W. C. Ding Y. H. Kimura F. (2004). Regional climate modeling: progress, challenges, and prospects. Journal of the Meteorological Society of Japan. 82(6) ,pp.1599-1628.
Mpelasoka F. Hennessy K. Jones R. and Bates B. (2008). Comparison of suitable drought indices for climate change impacts assessment over Australia towards resource management. International Journal of Climatology. Vol 28,pp.1283- 1292.
Loukas A., Vasiliades L., and Tzabiras J. (2008). Climate change effects on drought severity. Advances in Geosciences, Vol.17,pp.23–29.
Yu pao-shan, Y. Tao-Chang and W. chih-Kang. (2002). Impact of climate change on water resources in southern Taiwan, J. Hydrol. Vol 260, PP.161-175.
Tang Runsheng, Y. Etzion (2004), Comparative studies on the water evaporation rate from a wetted surface and that from a free water surface, Elsevier BV, 39, 1.
Lenters D., J., K. Kratz, T. & J. Bowser, C., 2005. Effects of climate variability on lake evaporation: Results from a long-term energy budget study of Sparkling Lake, northern Wisconsin (USA), 308,PP.168–195.
Dankers, R. & Christensen, O. B., (2005), climate change impact on snow coverage, evaporation and river discharge in the sub-arctic tana basin, northern Fennoscandia, 69,PP.367–392.
Yaning. chen, (2007). Effect of climate change on water resources in Tarim river basin, northwest , j.e.s. 19, PP.488-493.
Gianniou, S. K. & Antonopoulos, V. Z., (2007). Evaporation and energy budget in Lake Vegoritis,. Journal of Hydrology, (345).PP. 212– 223.
Armstrong, R. N., Pomeroy, J. W. & Martz, L. W., (2008). Evaluation of three evaporation estimation methods in a Canadian prairie landscape. Hydrological processes (15) PP.2801–2815.
Yao, H., (2009). Long-Term Study of Lake Evaporation and Evaluation of Seven Estimation Methods: Results from Dickie Lake, South-Central Ontario, Canada. Water Resource and Protection, (2) , PP. 59-77.
Donohue J., R., R. McVicar, T. & L. Roderick, M., 2010. Assessing the ability of potential evaporation formulations to capture the dynamics in evaporative demand within a changing climate, 386 186–197(186–197).
Van Vliet T.H., M., 2013. Global river discharge and water temperature under climate change. Global Environmental Change, PP. 450–464.
Song, L. & Zhang, J., (2012). Hydrological response to climate change in Beijiang River Basin Based on the SWAT Model, J. Procedia Engineering., 28, PP. 241 – 245.
Helfer, F., Lemckert, C. & Zhang, H., 2012. Impacts of climate change on temperature and evaporation from a large reservoir in Australia. Journal of Hydrology, PP. 365–378.
Benzaghta Ali, M., Ahmed Mohammed, T. & Ibrahim Ekhmaj, A., (2012). Prediction of Evaporation from Algardabiya Reservoir. Libyan Agriculture Research Center Journal International, (3): PP.120-128.(in persian)
Yang, H. & Yang, D., 2012. Climatic factors influencing changing pan evaporation across China. 414–415(184–193).
Bozkurt, D. & Lutfi Sen, O., 2013. Climate change impacts in the Euphrates–Tigris Basin based on different model and scenario simulations. Journal of Hydrology, pp. 149-161.
Tabari, H., Marofi, S., Aeini, A., Talaee, P.H. and K. Mohammadi. (2014). Sensitivity of evapotranspiration to climatic change in different climates. Global and Planetary Change, 115,PP.16–23.( Persian)
Tanasijevic, L., Todorovic, M., Pereira, L.S., Pizzigalli, C. and P. Lionello. (2014). Impacts of climate change on olive crop evapotranspiration and irrigation requirements in the Mediterranean region. Agricultural Water Management 144, PP. 54–68.
Tao X, Chena H, Xua C, Houa Y, Jiea M. (2015). Analysis and prediction of reference evapotranspiration with climate change in Xiangjiang River Basin China, Water Science and Engineering, 8(4), PP. 273- 281.
Wilby, R. L., Wigley, T. M. L., Conway, D., Jones, P. D., Hewitson, B. C., Main, J. and Wilks, D. S., (1998). “Statistical downscaling of general circulation model output: A comparison of methods”. J. Water Resources Research, Vol 34, PP. 2995-3008.
Wilby, R. L., & Harris, I. (2006). A framework for assessing uncertainties in climate change impacts: Low‐flow scenarios for the River Thames, UK. Water Resources Research, 42(2).pp18-25.
Stephen, P., Charles, B. C., and Bates James, P. H., (2004). Statistical Downscaling of Daily precipitation from observation and Model Atmospheric Field, Hydrological Processes, Vol. 18, pp. 1373-1394.
Wilby Robert L. and Christian W. Dawson (2004), Using SDSM Version 3.1 - A decision support tool for the assessment of regional climate change impacts, A Consortium for the Application of Climate Impact Assessments, Environment Agency of England and Wales.
Martynov, A., Laprise, R., Sushama, L., Winger, K., separovic, L., & Dugas, B. (2013). Reanalysis-driven climate simulation over cordex North America domain using the Canadian Regional Climate Model. Version 5: model performance evaluation. Climate Dynamics, 41(11-12), PP. 2973-3005.
