اثرات تغییر اقلیم برحجم منابع آب و انتقال آب بین حوضه ای

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشیار آب و هواشناسی، دانشکده علوم جغرافیایی و برنامه ریزی، دانشگاه اصفهان

2 دانشجوی دکتری آب و هواشناسی، دانشکده علوم جغرافیایی و برنامه ریزی، دانشگاه اصفهان

چکیده

تغییراقلیم با تاثیرگذاری بر چرخه­آب در تشدید ­مخاطرات هیدرواقلیمی نقش دارد. حوضه سراب به دلیل تامین بیش از 70 درصد  آب رودخانه بهشت­آباد (انتقال آب حوضه­کارون به حوضه­زاینده­رود)جایگاه مناسبی در برنامه ریزی منابع­آب  دارد.حجم آب قابل  انتقال از چالش­های بزرگ این پروژه است در این پژوهش تلاش برآن است که با کمک سناریوهای تغییر اقلیم به میزان درستی از آن دست یابیم برای بررسی اثرات تغییراقلیم بر منابع آب حوضه از داده­های هیدرومتری و کلیماتولوژی دوره 1392-1366 استفاده گردید. آزمون ناپارامتری من-کندال برای تعیین روند استفاده و به کمک مدلHADCM3 پیش­بینی متغیرهای اقلیمی انجام شد. همچنین با درنظرگرفتن سناریوهای تغییراقلیم برآورد منابع آب در افق 1415-1385انجام گردید. نتایج آزمون نشان­دهنده روند معنی­دار افزایشی­دما، تبخیر و تغییرات بدون­ روند بارش در سطح 95درصد است. نتایج مدل و روندیابی، نشان دهنده کاهش متوسط دبی سالانه حوضه از 1/11متر مکعب به 9/5 مترمکعب است. کاهش 53درصدی دبی به دلیل اجرای طرح های توسعه منابع آب ،برداشت آب از حوضه ،افزایش دما و تبخیر، منجر به کاهش 4/184 میلیون­مترمکعب حجم رواناب خواهد شد. ازاین مقدار 5/30 درصد ناشی از افزایش دما و تبخیر و 5/69 درصد ناشی از اجرای برنامه­های توسعه­ و برداشت منابع آبی  در­سطح حوضه می­باشد.  بنابراین تغییر اقلیم و آنترپوسن راهبرد های مبتنی بر انتقال آب را با چالش روبرو خواهد کرد. لذا بیشتر بر راهبرد اصلاح الگوی مصرف در حوضه مقصد تاکید نمود.

کلیدواژه‌ها


عنوان مقاله [English]

The Effect of Climate Change on Volume of Water Resources and Transfer of Inter-Basin Water

نویسندگان [English]

  • Daryoodh Rahimi 1
  • Farahnaz Zarei 2
1 Associate Professor, Department of Physical Geography, University of Isfahan, Iran.
2 Ph.D. Student, Department of Physical Geography, University of Isfahan, Iran.
چکیده [English]

Climate change is a serious challenge to human interest by its adverse effect on various sectors, such as water sources, agriculture, and energy. According to IPCC report, the average annual temperature of the earth has been raised between 0.3 to 0.6º because of the spread of the greenhouse gases, and this report predicts this amount will increase between 1 to 3.5º until 2100(Boberg et al ,2010).
To study the effect of greenhouse gases in the atmosphere and the oceanic-atmospheric, general circulation model in regional scale is the most efficient vehicle. These models have been developed to simulate the current climate. They also performed well in predicting future changes in the climate and simulating interactions of soil, atmosphere, and oceans (IPCC, 2007). The effect of climate change on water sources is assessed using rainfall-runoff models by simulating hydrological processes. Studying future climate change and its likely events will help planners and water sources administrators to cope with the future challenge. Considering these likely changes will contribute to objective planning toward optional operations. Predicting future runoff value is one of the most important factors about dam construction, water transferring, agricultural growth and industrial activities.
 Semenov (2008) assessed LARS-WG performance by data from 20 representative stations. Babaeian  et al, (2004) and Khaliliaqdam, et al( 2013), studied the effect of climate change on the hydroelectric reservoir of Jor Dam by the microclimate model LARS-WG and scenarios B1, B2, and A1B. Output results of the model showed that Tmin and Tmax will increase to the amount of o.3-0.6 degrees. As a result, available water reservoirs of behind the dams for hydroelectric generation are affected by the decreased rainfall. BaniHabib et al, (2016), simulated the input flow of Shahcheraghi Dam using the generator LARS-WG, data downscaling, and the function of artificial neural networks on output of LARS. They found that nightly and daily temperatures rise 1.1 and 1.2 degrees from 2015 to 2040, and rainfall will decrease by 9% during January. By simulating artificial neural networks, it was determined that the input flow will experience 2.4-4.1 % decrease based on different scenarios.

کلیدواژه‌ها [English]

  • climate change
  • Water resources
  • HadCM3
  • Sarab basin

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