توسعه يك مدل پيش بيني ريسك خشكسالي هوا شناسي (مطالعه موردي: زيرحوضه آبريز افين)

(Development of Weather Meteorological Drought Forecast Model (Case Study: Sub-basin Afin Watershed

خشكسالي به عنوان پيچيده ­ترين، اما كمتر شناخته شده­ ترين خطر در ميان تمام خطرات طبيعي است كه نسبت به هر خطر طبيعي ديگر، درصد بيشتري از مردم را تحت تأثير قرار مي‌دهد. خشكسالي يكي از پديده­ هاي طبيعي و مكرر اقليمي است؛ تجزيه و تحليل ريسك خشكسالي تركيبي از تجزيه و تحليل خطر خشكسالي و تجزيه و تحليل آسيب­پذيري خشكسالي است. در اين مطالعه سعي شده است چشم ­انداري از تغييرات ريسك خشكسالي هواشناسي در آينده نشان داده شود. مطالعه به­ صورت موردي براي زيرحوضه افين (واقع در استان خراسان جنوبي) انجام شده است. دوره آماري استفاده شده براي دوره پايه 33 سال (2015-1983) مي ­باشد. داده هاي آينده براساس سه مدل از پروژه CORDEX بدست آمده است. دوره آتي، به سه دوره 27 ساله شامل، آينده نزديك (2046-2020)، آينده مياني (2073-2047) و آينده دور (2100-2074) تقسيم شده است. به منظور محاسبه ريسك خشكسالي، مخاطره خشكسالي براساس سه شاخص خشكسالي SPI، SPEI و eRDI براي دوره پايه و دوره ­هاي آتي و پس از آن آسيب­پذيري تعيين شد. افزايش شدت خشكسالي­ها در دوره­هاي آتي از ديگر نتايج حاصل از اين مطالعه است. خروجي­ هاي ريسك بدست آمده از روش مستقيم محاسبه ريسك كه با داده ­هاي CORDEX و نيز روش استفاده از مدل پيش­بيني ريسك كه در اين مطالعه بدست آمد، نشان از افزايش تعداد وقايع خشكسالي و بدنبال آن افزايش وقايع ريسك خشكسالي در منطقه دارد. همچنين، مشاهده شد شدت ريسك خشكسالي­ ها براساس سناريوي انتشار RCP8.5 بيشتر از RCP4.5 مي­ باشد

Introduction: Drought is the most complex, but less well-known risk among all natural hazards, which affects more people than any other natural hazard. Meteorological and seasonal hydrological drought is a common phenomenon in subtropical countries and is expected to increase further in the future. Drought is one of the natural and frequent climate phenomena. Drought risk analysis is a combination of drought risk and drought vulnerability analysis. Drought risk assessment can be estimated either by remote sensing or by statistical methods or by a combination of both previous methods. Drought risk assessment shows a more suitable and accurate view of the drought. Drought risk in addition to drought severity is simultaneously includes the probability of occurrence of drought and the impact this phenomenon on the environment and the region. This study has been made to illustrate the visionary of changes in future meteorological drought risk. Materials and Methods: The study was conducted as a case study for the Afin sub-basin. In this research the average of minimum average of maximum temperature, the average temperature at 2 meters above ground level and rainfall data have been used. The statistical period used for the base period is 33 years (1983-2015). Future data is derived from three models of the cordex project. The upcoming period is divided into three 27-year periods including the near future (2020-2046), the middle term (2047-2073) and the distant future (2074-2100). In order to investigate the drought in future, a combined model of three climatic models using the Bayesian method. Then, the future values of the meteorological parameters were calculated. Drought risk for the upcoming periods was calculated by the direct method and modeling method. Finally, a comparison was made between the two methods in order to determine the appropriateness of the predicted model. Results and Discussion: In the survey of the intensity of SPI and SPEI drought indices during the base time period for time scales studied, the SPEI and SPI drought indices showed that both, drought events were the same during the studied period, while the SPEI shows more mild and moderate droughts, and the SPI index has shown intense intensity on some scales. In future periods, according to the RCP8.5 scenario, the number of drought events in each period does not differ from the RCP4.5 scenario, but the intensities are higher than RCP4.5. By completing the questionnaire and using exploratory and confirmatory factor analysis methods, the drought vulnerability was determinated 53%. ARIMA (0, 0, 0), the appropriate time series model was used to predict the level of risk. In the drought risk prediction section, the results showed that according to the SPI drought index in the upcoming periods, the number of drought events relative to the base period is relatively higher, thus the number of drought events (including four drought conditions) will increase in the far future than the two upcoming middle and nearer periods. According to prediction of models of risk, rainfall parameter for all time scales of SPI index and for four-time scales of spring, autumn, winter and annual drought index SPEI, is an effective parameter in drought estimation and effect on drought occurrence in the study area. Conclusion: The results of this study indicate an increase in temperature in future periods based on both RCP emission scenarios. Increasing the severity of droughts in future is another result of this study. The risk outcomes obtained from the direct risk-measurement method, which was obtained with CORDEX data as well as the method of using the risk-predictive model obtained in this study, showed strong correlation and no significant difference in mean, which indicates the model's appropriateness for risk prediction (hazard and after that risk) for the future. Also, the risk outcomes obtained from the direct risk calculation method, which is based on CORDEX data with the method of using the risk prediction model obtained in this study, indicates an increase in the number of drought events followed by an increase in drought risk events in the region. Also, it was observed that the severity of drought risk according to the RCP8.5 release scenario is higher than RCP4.5. It is suggested that a number of models (more than three models) being used from the sixth report of the Intergovernmental Panel on Climate Change.