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Climate change forecasting in a mountainous data scarce watershed using CMIP5 models under representative concentration pathways

机译:在有代表性的集中途径下,使用CMIP5模型在山区数据稀缺的分水岭进行气候变化预测

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Hydrology cycle of river basins and available water resources in arid and semi-arid regions are highly affected by climate changes. In recent years, the increment of temperature due to excessive increased emission of greenhouse gases has led to an abnormality in the climate system of the earth. The main objective of this study is to survey the future climate changes in one of the biggest mountainous watersheds in northeast of Iran (i.e., Kashafrood). In this research, by considering the precipitation and temperature as two important climatic parameters in watersheds, 14 models evolved in the general circulation models (GCMs) of the newest generation in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used to forecast the future climate changes in the study area. For the historical period of 1992-2005, four evaluation criteria including Nash-Sutcliffe (NS), percent of bias (PBIAS), coefficient of determination (R (2)) and the ratio of the root-mean-square-error to the standard deviation of measured data (RSR) were used to compare the simulated observed data for assessing goodness-of-fit of the models. In the primary results, four climate models namely GFDL-ESM2G, IPSL-CM5A-MR, MIROC-ESM, and NorESM1-M were selected among the abovementioned 14 models due to their more prediction accuracies to the investigated evaluation criteria. Thereafter, climate changes of the future periods (near-century, 2006-2037; mid-century, 2037-2070; and late-century, 2070-2100) were investigated and compared by four representative concentration pathways (RCPs) of new emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP8.5. In order to assess the trend of annual and seasonal changes of climatic components, Mann-Kendall non-parametric test (MK) was also employed. The results of Mann-Kendall test revealed that the precipitation has significant variable trends of both positive and negative alterations. Furthermore, the mean, maximum, and minimum temperature values had significant positive trends at 90, 99, and 99.9 % confidence level. On the other hand, in all parts of the Kashafrood Watershed (KW), the average temperature of watershed will be increased up to 0.56-3.3 A degrees C and the mean precipitation will be decreased up to 10.7 % by the end of the twenty-first century comparing to the historical baselines. Also, in seasonal scale, the maximum and minimum precipitations will occur in spring and summer, respectively, and the mean temperature is higher than the historical baseline in all seasons. The maximum and minimum values of the mean temperature will occur in summer and winter, respectively, and the amount of seasonal precipitation in these seasons will be reduced.
机译:干旱和半干旱地区的流域水文循环和可用水资源受到气候变化的严重影响。近年来,由于过度增加温室气体的排放而导致的温度升高已导致地球气候系统异常。这项研究的主要目的是调查伊朗东北部最大的山区流域之一(即Kashafrood)的未来气候变化。在这项研究中,通过将流域中的降水和温度作为两个重要的气候参数,在耦合模型比较项目第5阶段(CMIP5)中,采用了最新一代通用循环模型(GCM)演化的14种模型来预测未来研究区域的气候变化。在1992年至2005年的历史时期内,有四个评估标准,包括纳什-萨克克利夫(NS),偏差百分比(PBIAS),确定系数(R(2))和均方根误差与均方根误差之比。测量数据的标准偏差(RSR)用于比较模拟的观测数据,以评估模型的拟合优度。在初步结果中,由于上述14种模型的预测精度相对于所研究的评估标准更高,因此从上述14种模型中选择了四种气候模型,即GFDL-ESM2G,IPSL-CM5A-MR,MIROC-ESM和NorESM1-M。之后,对未来时期(近世纪,2006-2037年;世纪中期,2037-2070年;以及世纪末,2070-2100年)的气候变化进行了调查,并通过新排放情景的四个代表性浓度路径(RCP)进行了比较。 RCP2.6,RCP4.5,RCP6.0和RCP8.5的版本。为了评估气候成分的年度和季节变化趋势,还使用了Mann-Kendall非参数检验(MK)。 Mann-Kendall试验的结果表明,降水量具有正变和负变的显着变化趋势。此外,在90%,99%和99.9%的置信度水平下,平均,最高和最低温度值均具有明显的正趋势。另一方面,到20世纪末,在Kashafrood流域(KW)的所有地区,流域的平均温度将升高至0.56-3.3 A摄氏度,平均降水量将降低至10.7%。一世纪与历史基线相比。同样,在季节尺度上,最大和最小降水分别发生在春季和夏季,并且所有季节的平均温度都高于历史基线。平均温度的最大值和最小值分别发生在夏季和冬季,并且这些季节的季节性降水量将减少。

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