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基于 PERSIANN-CDR 估计降水数据的印度奥里萨邦地理空间干旱严重度分析(1983-2018 年)。

Geospatial drought severity analysis based on PERSIANN-CDR-estimated rainfall data for Odisha state in India (1983-2018).

机构信息

Department of Civil and Environmental Engineering, Federal University of Paraíba, João Pessoa, PB 58051-900, Brazil.

Department of Civil and Environmental Engineering, Federal University of Paraíba, João Pessoa, PB 58051-900, Brazil.

出版信息

Sci Total Environ. 2021 Jan 1;750:141258. doi: 10.1016/j.scitotenv.2020.141258. Epub 2020 Aug 5.

Abstract

Studying the behavior of drought and its short-, medium- and long-term features throughout a region is very important for the creation of adequate public policies and actions aimed at the economic and social development of the region. Furthermore, the frequency and intensity of weather-related natural hazards (rainfall, heatwaves and droughts) are increasing every year, and these extreme weather-related events are potent threats worldwide, particularly in developing countries, such as India. Thus, this paper aims to evaluate the drought behavior in the Odisha region of India (1983-2018) by using the standardized precipitation index (SPI) and the new drought severity classification (DS). PERSIANN-CDR-estimated rainfall data were used to provide 271 time series, which were equally spaced at intervals of 0.25°, over Odisha state. The accuracy of these time series was evaluated with rain gauge-measured data at multiple time scales, and it was observed that the PERSIANN-CDR-estimated rainfall data effectively captured the pattern of rainfall over Odisha state. It was noted that almost half of the mean annual rainfall was concentrated in July and August. On addition, northeastern Odisha and areas near the coast were the rainiest regions. Furthermore, the drought pattern was evaluated based on nine distinct four-year periods (SPI-48), and the results indicated that there was high spatiotemporal variability in drought occurrence among those periods; e.g., in the last four years, extreme drought events occurred throughout the state. For the DS severity index analysis, it was noted that the values tended to be more significant with the increase in the drought time scale. For short-term droughts, DS values were less significant throughout the region, whereas for the medium-term droughts, there was an increase in the DS values in all regions of Odisha, especially in the north-central region. For long-term droughts, the values were more significant throughout the region, especially in the areas with the highest rainfall levels. Finally, the PERSIANN-CDR data should also be analyzed in other regions of India, and the obtained results are useful for the identification of droughts throughout the region and for the management of water resources and can be replicated in any part of the world.

摘要

研究一个地区的干旱及其短期、中期和长期特征的行为对于制定适当的公共政策和行动以促进该地区的经济和社会发展非常重要。此外,与天气有关的自然灾害(降雨、热浪和干旱)的频率和强度每年都在增加,这些与极端天气有关的事件是全世界的严重威胁,特别是在印度等发展中国家。因此,本文旨在通过使用标准化降水指数(SPI)和新的干旱严重程度分类(DS)来评估印度奥里萨邦(1983-2018 年)的干旱行为。使用 PERSIANN-CDR 估算的降雨数据提供了 271 个时间序列,这些时间序列在奥里萨邦以 0.25°的间隔等距分布。在多个时间尺度上使用雨量计测量数据对这些时间序列的准确性进行了评估,结果表明 PERSIANN-CDR 估算的降雨数据有效地捕捉了奥里萨邦的降雨模式。结果发现,几乎一半的年平均降雨量集中在 7 月和 8 月。此外,奥里萨邦东北部和沿海地区是降雨量最大的地区。此外,根据九个不同的四年期(SPI-48)评估干旱模式,结果表明,这些时期的干旱发生具有高度的时空变异性;例如,在过去的四年中,整个州都发生了极端干旱事件。对于 DS 严重程度指数分析,随着干旱时间尺度的增加,DS 值趋于更显著。对于短期干旱,整个地区的 DS 值都不太显著,而对于中期干旱,奥里萨邦所有地区的 DS 值都有所增加,特别是在中北部地区。对于长期干旱,整个地区的 DS 值都更为显著,特别是在降雨量最高的地区。最后,还应该在印度的其他地区分析 PERSIANN-CDR 数据,并且获得的结果对于识别整个地区的干旱以及水资源管理非常有用,并且可以在世界任何地方复制。

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