نوع مقاله : پژوهشی

نویسندگان

• مهناز کرمی جوزانی ¹
• علیرضا ایلدرمی ²
• حمید نوری ³
• عبدااله پیرنیا ⁴

¹ ـ دانش‌آموخته کارشناسی ارشد آبخیزداری، دانشکده‌ی منابع طبیعی و محیط زیست، دانشگاه ملایر، ایران.

² ـ دانشیار گروه مرتع و آبخیزداری، دانشکده‌ی منابع طبیعی و محیط زیست، دانشگاه ملایر، ایران (نویسنده مسئول).

³ استادیار گروه مرتع و آبخیزداری، دانشکده‌ی منابع طبیعی و محیط زیست، دانشگاه ملایر، ایران.

⁴ دانش‌آموخته کارشناسی ارشد آبخیزداری، دانشکده‌ی منابع طبیعی و کشاورزی، دانشگاه مازندران، ایران.

چکیده

چکیده                                             
 پیش­ بینی­ های اقلیمی نشان می­دهد که افزایش غلظت گازهای گلخانه­ ای سبب تغییر در چرخه­ ی هیدرولوژیکی خواهد شد. هدف از این تحقیق ارزیابی تأثیر تغییر اقلیم بر دبی در حوضه­ ی آبخیز گرگانرود - قره­سو در استان گلستان می­باشد. در این مطالعه از آزمون‌های ناپارامتری جهت آنالیز روند و همبستگی در سری­های زمانی پارامترهای اقلیمی و هیدرولوژیکی در دوره­ی پایه استفاده گردید. سپس داده‌های دو مدل گردش عمومی جو HadCM₃ و ECHAM₄ با به کارگیری مدل LARS-WG طبق سه سناریوی A₂، B₁ و A₁B برای منطقه­ ی مورد مطالعه طی دوره­ی 2030-2011 ریزمقیاس گردید و از مدل شبکه­ ی عصبی پرسپترون چندلایه در مقیاس روزانه برای شبیه­ سازی دوره­ ی پایه­ ی 2008-1987 استفاده شد. دبی خروجی از حوضه برای سه سناریو در دو مدل HadCM₃و ECHAM₄ در دوره­ ی 2030-2011 تولیدگردید. نتایج نشان داد که دبی در دو ایستگاه تمر و اراز کوسه واقع در حوضه­ ی مورد مطالعه کاهش یافته است که در هیچ­کدام از دو ایستگاه این ­کاهش معنی‌دار نیست. ­به­ علاوه تغییرات دمای حداقل و بارش تأثیر بیشتر و معنی‌‌‌داری را بر تغییرات جریان رودخانه­ ی حوضه داشته است.­ نتایج حاصل نشان­دهنده­ ی کاهش دبی در تمام سناریوهای ذکر شده دو مدل گردش عمومی جو در دوره­ی آینده نسبت به دوره­ ی پایه خواهد بود.

تازه های تحقیق

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کلیدواژه‌ها

• کلمات کلیدی: سناریو های اقلیمی
• نوسانات دبی
• شبکه ی عصبی
• حوضه ی گرگانرو

20.1001.1.23833254.1398.6.18.1.0

عنوان مقاله [English]

The Effect of Climate Change on Flood Changes in Gorganrood-Ghareh Sou Watershed Using General Circulation Models

نویسندگان [English]

• Mahnaz Karami Jozani ¹
• Alireza Ildoromi ²
• Hamid Nouri ³
• Abdollah Pernia ⁴

¹ - Graduated from Watershed Master, Faculty of Natural Resources and Environment, Malayer University, Iran.

² Associate Professor of Range and Watershed Management, Faculty of Natural and Environmental Sciences, Malayer University, Iran. (Corresponding Author)

³ Assistant Professor of Rangeland and Watershed Management, Faculty of Natural and Environmental Sciences, Malayer University, Iran.

⁴ Graduated from Watershed Master, Faculty of Agriculture and Natural Resources, Mazandaran University, Iran.

چکیده [English]

Introduction
The Climate forecasts show that climate change will change the hydrological cycle. The purpose of this study was to assess the effect of climate change on the Gorganrood- Ghareh Sou watershed in Golestan province using two generic oocytes of HadCM₃ and ECHAM₄ and the LARS-WG model according to the three scenarios of A₂, B₁ and A₁B for the period of 2011-2030. The results showed that discharge has insignificantly decreased in two stations of Tamar and Arazkooseh in the studied watershed. In addition, changes in the minimum temperature and rainfall have a more significant effect on river discharge changes in the watershed. The results also indicated a decrease in the discharge rate in all scenarios of two models of general circulation of the atmosphere in the future period relative to the base period.Many of the environmental problems of our age, including floods, storms, droughts, and the like are all rooted in global climate change.

 

The study of the effects of climate change on water resources is an important issue that has been considered in recent years. For example, Kling et al. (2012) examined variations in runoff in the Danube watershed under the influence of changing scenarios. The results showed that most models predicted precipitation increase and runoff reduction for future years. Rajabi (2013) investigated the effect of changes on Ghareh Sou runoff in Kermanshah province in the coming decades and its results showed that in the coming periods, the average rainfall of the watershed reduced. Singh et al. (2013) evaluated the performance of artificial neural network in a small watershed in India based on RMSE and R criteria. The results showed that the neural network model had an acceptable performance in the study of climate change in the region.
Methodology
Gorganrood watershed-Ghareh Sou is in the southeastern part of the Caspian Sea with an area of 13061 km². The average annual rainfall is about 300 mm to 1000 mm, and the annual average temperature varies from about 7.5 to 17 ° C. In this study, the seasonal and annual data series of minimum and maximum parameters of temperature, precipitation and annual discharge of the year and non-parametric tests were used to determine the trend direction and correlation of the studied parameters. In order to investigate the effect of variation on discharge, the data from B₁, A₂ and A₁B scenarios of the HadCM₃ model and B₁, A₂ and A₁B scenarios of ECHAM₄ model were used.  In addition, Lars statistical model was used for calibration of the data, after calibrating and validating it for the simulation of rainfall-runoff, The output of the Lars statistical model was introduced into the neural network model and the changes in the discharge rate were investigated in the course of 2030-2011 (near future). In order to evaluate the performance of the model, the statistical index of the coefficient of explanation and the mean squared error were used.



Results
The annual variations in discharge at two stations of Tamar and Arazkooseh showed that precipitation on both stations of Arazkooseh and Tamar was significant at 99% probability level. But it had less effect on rainfall than river discharge.  The studies showed that during the last 30 years in the study area, the maximum temperatures and precipitation, had insignificantly increased. The minimum temperature had a significant increase in most of the studied time series. Also, the climatic parameters had a more significant effect on rainfall than the minimum temperature.The results of the climate simulation showed that the average temperature for the HadCM₃ for 2011-2030 period would increase with all scenarios. The results of the HadCM₃ model showed that precipitation is rising in all scenarios. But in the ECHAM₄ model, the precipitation in the A₂, B₁ scenarios will decrease, but in A₁B scenario it will increase. In HadCM₃ and ECHAM₄ models, the highest precipitation rates are respectively for A₂ and A₁B scenarios.
Discussion and Conclusion
The results of the two HadCM₃ and ECHAM₄ models indicated an increase in precipitation (except for scenario A₂ and B₁ in the ECHAM₄ model) and increase in temperature in the Gorganrood-Ghareh Sou watershed. Moreover, the changes in minimum temperature will be higher than maximum temperature. Discharge will decrease in both climatic models. The results showed that the greatest decrease in the amount of discharge in both climates models and in all three scenarios was in September. The results of the changes in the discharge rate at the two hydrometric stations of Tamar and Arazkooseh indicated that although the changes were not significant in any one, the decrease in discharge rate during the period at the Tamar station was more pronounced than that of the Arazkooseh station. The results showed that the LARS meteorological model had a high potential for generating daily data.

کلیدواژه‌ها [English]

• Keywords: Climate scenarios
• Neural network
• Gorganrood Watershed