印度季节性干旱和年代际干旱的长期时空变化

Pavan Kumar B, B. Pinjarla, P. Joshi, P. Roy
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引用次数: 1

摘要

对印度全国范围内的气候数据(1958-2018)进行了全面分析,以评估干旱的时空变化。利用联合国环境规划署(UNEP)干旱指数(AI),即降水量(P)与潜在蒸散量(PET)之比,对干旱进行分析。免费提供的Terra-Climate数据库,P和PET变量,为监测AI和干旱指数异常(AIA)的季节和年代际变化提供了前所未有的机会。该研究还评估了P和AI异常与植被异常的长期模式。结果表明,最干旱的显著聚集区位于印度中西部的马哈拉施特拉邦。总体而言,60 a期间干旱区面积呈逐渐增加的趋势,空间上干旱区面积百分比变化幅度最大。印度人工智能的变化模式在很大程度上是由降水模式的变化驱动的。1972-1992年降水减少对AIA影响最大的季节频繁出现在哈里夫季节,每4-5年出现一次。最近几年(2013年至2018年)重复的模式是,降水减少导致干旱加剧。该研究还显示,从2014年到2018年,灌溉水源的可用性和使用量有所增加。因此,尽管降水较少,但在这一时期产生了积极的植被。这些发现对于理解气候变化对土地利用模式以及土地和水资源管理的影响具有重要意义。
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Long Term Spatio-temporal Variations of Seasonal and Decadal Aridity in India
A comprehensive analysis of climate data (1958-2018) is carried out at the national scale in India to assess spatiotemporal variation in aridity. The aridity is analyzed using UNEP (United Nations Environment Programme) Aridity Index (AI), which is the ratio between Precipitation (P) and Potential Evapotranspiration (PET). Freely available Terra-Climate database, P and PET variables, offered an unprecedented opportunity for monitoring variations in AI and aridity index anomalies (AIA) at interseasonal and inter-decadal basis. The study also assesses longer term patterns of P and AI anomalies with vegetation anomalies. The results indicate that significant clustered areas with maximum dryness are located at west-central part of India, the state of Maharashtra. Overall, there is a gradual increase in the extent of arid zone during 60-year period and spatially maximum extent of percentage change in aridity area is observed. The change patterns of AI in India are largely driven by the changing patterns of precipitation. The maximum impact of decline in precipitation on AIA was observed during Kharif season frequently, for every 4-5 years during 1972-1992. The pattern repeated in the last few recent years (2013- 2018), the decline in precipitation resulted increased aridity. The study also reveals that the availability and usage of irrigation sources have increased from 2014 to 2018. Thus, despite of less precipitation positive vegetation has been resulted in this period. The findings are important to understand the impacts of climate change on land use pattern, and land and water resource management.
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