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Investigation of Multi-model Spatiotemporal Mesoscale Drought Projections over India under Climate Change Scenario
Journal of Hydrology ( IF 6.4 ) Pub Date : 2018-12-01 , DOI: 10.1016/j.jhydrol.2018.10.012
Vivek Gupta , Manoj Kumar Jain

Abstract Projected droughts for 21st century over India have been analysed using precipitation and temperature data obtained from Regional Climate Models (RCMs) under Representative Concentration Pathways (RCPs) 4.5 and 8.5. Standardized Precipitation Index (SPI), Standardized effective Precipitation Evapo-Transpiration Index (SP*ETI) and Standardized Precipitation-Evapotranspiration Index (SPEI) at the timescale of 12-months have been used for drought characterization. The K-means clustering algorithm has been utilized to delineate distinct drought homogeneous regions in India. Trends and periodicities in drought characteristics have also been analysed. The results of this study reveal that increase in evapotranspiration due to projected rise in temperature would play a major role in affecting future drought dynamics in most parts of India. Analysis indicates that computed magnitude of drought intensity, duration and frequency depends on the choice of drought indicator. SPEI drought index has been found to project highest drought risk as compared to other two indices used in this study. North India is more vulnerable to increase in drought severity and frequency in near future. However in far future, most parts of the country, except few southeastern states, are likely to face an escalation in drought severity and frequency. A shift in drought hazard from central India toward southeast-central India is likely to happen with increase in greenhouse gas (GHG) concentration. The areal extent of droughts has been found to be increasing historically which is expected to increase further in future for most parts of the country. Historically, drought dynamics were more influenced by decrease in precipitation. However, in future, the drought dynamics will be significantly influenced by increased evapotranspiration resulting from increase in temperature in spite of likely increase in precipitation. The periodicity analysis indicates inter-annual periodicities influencing monsoon months to be distributed uniformly across all clusters of the Indian subcontinent with dominant cycles of 2–3.6 years. Further, change in periodic cycles of drought due to climate change is found to be insignificant.

中文翻译:

气候变化情景下印度多模式时空中尺度干旱预测研究

摘要 使用从区域气候模型 (RCM) 获得的降水和温度数据,在代表性浓度路径 (RCP) 4.5 和 8.5 下,分析了印度 21 世纪预计的干旱。12 个月时间尺度的标准化降水指数 (SPI)、标准化有效降水蒸散指数 (SP*ETI) 和标准化降水蒸散指数 (SPEI) 已被用于干旱表征。K-means 聚类算法已被用于描绘印度不同的干旱均质区域。还分析了干旱特征的趋势和周期性。这项研究的结果表明,由于预计温度升高而导致的蒸散量增加将在影响印度大部分地区未来的干旱动态方面发挥重要作用。分析表明,干旱强度、持续时间和频率的计算幅度取决于干旱指标的选择。与本研究中使用的其他两个指数相比,已发现 SPEI 干旱指数预测的干旱风险最高。在不久的将来,印度北部更容易受到干旱严重程度和频率增加的影响。然而,在遥远的未来,除少数东南部州外,该国大部分地区可能面临干旱严重程度和频率的升级。随着温室气体 (GHG) 浓度的增加,干旱危害可能会从印度中部向印度中东南部转移。历史上已经发现干旱的面积范围在增加,预计未来该国大部分地区还会进一步增加。从历史上看,干旱动态更多地受到降水减少的影响。然而,在未来,尽管降水可能增加,但由于温度升高导致蒸散量增加,干旱动态将受到显着影响。周期性分析表明影响季风月份的年际周期性均匀分布在印度次大陆的所有集群中,主导周期为 2-3.6 年。此外,由于气候变化导致的干旱周期性变化被认为是微不足道的。周期性分析表明影响季风月份的年际周期性均匀分布在印度次大陆的所有集群中,主导周期为 2-3.6 年。此外,由于气候变化导致的干旱周期性变化被认为是微不足道的。周期性分析表明影响季风月份的年际周期性均匀分布在印度次大陆的所有集群中,主导周期为 2-3.6 年。此外,由于气候变化导致的干旱周期性变化被认为是微不足道的。
更新日期:2018-12-01
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