چکیده:
در این پژوهش، به منظور ارزیابی ویژگی‌های آتی خشکسالی ابتدا میزان توانمندی سه مدل اقلیمی در شبیه‌سازی دما و بارش برای دوره پایه (2005-1976) برای چهار نمونه اقلیمی ایران (اهواز، بندر انزلی، شهر کرد و کرمان) بررسی شد و در ادامه رویدادهای حدی خشکسالی (SPEI≤-1) از سری ماهانه برای دو دوره پایه و 2050-2021 تحت سناریوهای خط سیر گازهای گلخانه‌ای (RCP)، شناسایی و ویژگی‌های شدت، سختی و مدت استخراج شد. نتایج نشان داد مدل‌های اقلیمی بجز بندر انزلی، در سایر ایستگاه‌ها، از مهارت مناسبی در شبیه‌سازی متغیرهای دما، بارش، فراوانی طبقات SPEI-1 برخوردار هستند. بر اساس پیش‌نگری انجام شده، در اهواز تحت سناریوی RCP4.5، فراوانی طبقه متوسط (64 رویداد) و تحت سناریوی RCP8.5، فراوانی طبقه شدید SPEI-1(3 رویداد) بیش از دوره پایه (به ترتیب 58 و 1 رویداد) خواهد بود. به ازای دوره‌های بازگشت یکسان، مقادیر شدت خشکسالی‌های حدی تحت سناریویRCP8.5 با دوره پایه تفاوت قابل ملاحظه‌ای خواهد داشت. برای دوره بازگشت 50 سال، شدت این بلیه تحت سناریوی RCP8.5، 4/3 خواهد بود در حالیکه دوره پایه دارای شدت 6/2 می‌باشد. تحت سناریوی RCP4.5، شدت (4/2 برای دوره بازگشت 50 سال) نسبت به دوره پایه اندکی کاهش نشان می‌دهد. برای شهرکرد، فراوانی طبقه متوسط نمایه خشکسالی تحت دو سناریو نسبت به دوره پایه کاهش و در مقابل فراوانی انواع شدید آن افزایش نشان می‌دهد. با بررسی تغییرات تابع چگالی احتمال (PDF) توزیع مقادیر حدی تعمیم یافته (GEV) برای ایستگاه شهرکرد نشان داده شد که میانگین و تغییرپذیری شدت مقادیر حدی این پدیده تحت دو سناریوی افزایش می‌یابد. در ایستگاه کرمان، فراوانی مقادیر شدید SPEI-1 تحت سناریوی RCP4.5 نسبت به دوره پایه افزایش نشان داد. تحت سناریوی RCP8.5، به ازای دوره‌های بازگشت یکسان، انتظار بروز خشکسالی‌های حدی ضعیف‌تر نسبت به دوره پایه وجود دارد.
Introduction
The Intergovernmental Panel on Climate Change (IPCC) fifth assessment report has pointed out that global warming is intensifying, and the frequency and intensity of extreme climate events such as high temperature and heavy rainfall will increase significantly (IPCC 2013). The weather and climate disasters have also increased and had a very serious impact on social stability, economic development and people’s lives . Probabilistic analysis of drought events plays an important role for an appropriate planning and management of water resources systems, especially in arid or semi-arid regions characterized by low annual or seasonal precipitation. In particular, estimation of drought return periods can provide useful information for a proper water use under drought conditions. As the changes in the frequency and intensity of extreme drought events bring great threats to natural and social systems, studies on the drought events, especially on the analysis of statistical characteristics of extreme drought events, have attracted the attention of an increasing number of scholars in the recent decades.
This study aimed to project future SPEI using RCP8.5 and RCP4.5 projection data. The drought characteristics by the threshold level to the projected SPEI were identified. This study also projected the drought risk of each station (representing four climate zones of Iran) in the 21st century by fitting the drought characteristics to the Generalized Extreme Value (GEV) distribution.
In this study, the analysis of extreme values of standardized precipitation-evapotranspiration index (SPEI) was performed to evaluate the potential future changes in drought characteristics in Keramn, Sharekord, Ahvaz and Bandar Anzali stations which are representing the warm and arid, cold and semi-arid, warm and semi-arid and humid climate respectively. The capability of three global climate models in simulating temperature and precipitation during the base period (1976-2005) for four climate zones of Iran (Ahvaz, Bandar Anzali, Shahrekord and Kerman) was investigated. Drought extreme events (SPEI≤-1) were identified from the monthly series for the base period and the period 2021-2051 under the RCP scenarios, and the characteristics of intensity, severity and duration were extracted.
Materials and methods
As it is difficult to define when the drought started and ended, previous researches assessed the risk of drought in an indirect way by conducting the frequency analysis of the drought indexes.
SPEI can reflect the effect of not only the variability in precipitation but also the variability of evapotranspiration. Thus, this study used SPEI. SPEI is the difference between the random month 𝑖 and PET obtained by using the precipitation and the Hargreaves & Samani (1982) equation, as shown in
D= P_i- 〖PET〗_i (1)
Which is synthesized in each time scale like
D_n^k=∑_(i=0)^(k-1)▒〖P_(n-i)-〖PET〗_(n-i) 〗 (2)
Here, 𝑘 is the time scale of synthesis, and 𝑛 is the month used for calculation.
The severity and duration and drought intensity were calculated using SPEI. Negative SPEIs mean the dry condition; a drought event is defined when the SPEI is continuously negative and reaches a value of “−1.0” or less. Thus, it is assumed that “−1.0” is the threshold level and that the drought starts in the level lower than “−1.0” in monthly SPEI. The aggregate of SPEI while one drought event lasts was defined as the severity of drought.
Results
The results showed that GCMs in the stations under study (except Bandar Anzali), have good skill in simulating the variables of temperature, precipitation, frequency and drought classes. In Ahvaz under RCP4.5 scenario, the frequency of moderate events and under RCP8.5 scenario, the frequency of severe class will likely be more than the base period. For the same return periods, the extreme drought intensity values under RCP8.5 scenario with the base period will be significantly different. Under the opposite scenario, the intensity decreases slightly compared to the baseline period. For Shahrekord, the frequency of the middle class of this phenomenon under two scenarios projected to decrease compared to the 1975-2005 priod and in contrast to the frequency of severe types projected to increase. Changes in Probability Density Function (PDF) of GEV for Shahrekord station showed that the mean and variability of the intensity of extreme values of this phenomenon will likely increase under two scenarios. At Kerman station, the frequency of severe drought under RCP4.5 scenario increase compared to the base period. Under the RCP8.5 scenario, droughts projected to be reduced.
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