Santos Celso Augusto Guimarães, Brasil Neto Reginaldo Moura, Passos Jacqueline Sobral de Araújo, da Silva Richarde Marques
Department of Civil and Environmental Engineering, Federal University of Paraíba, João Pessoa, PB, 58051-900, Brazil.
Department of Geosciences, Federal University of Paraíba, João Pessoa, PB, 58051-900, Brazil.
Environ Monit Assess. 2017 Jun;189(6):250. doi: 10.1007/s10661-017-5948-9. Epub 2017 May 3.
In this work, the use of Tropical Rainfall Measuring Mission (TRMM) rainfall data and the Standardized Precipitation Index (SPI) for monitoring spatial and temporal drought variabilities in the Upper São Francisco River basin is investigated. Thus, the spatiotemporal behavior of droughts and cluster regions with similar behaviors is identified. As a result, the joint analysis of clusters, dendrograms, and the spatial distribution of SPI values proved to be a powerful tool in identifying homogeneous regions. The results showed that the northeast region of the basin has the lowest rainfall indices and the southwest region has the highest rainfall depths, and that the region has well-defined dry and rainy seasons from June to August and November to January, respectively. An analysis of the drought and rain conditions showed that the studied region was homogeneous and well-distributed; however, the quantity of extreme and severe drought events in short-, medium- and long-term analysis was higher than that expected in regions with high rainfall depths, particularly in the south/southwest and southeast areas. Thus, an alternative classification is proposed to characterize the drought, which spatially categorizes the drought type (short-, medium-, and long-term) according to the analyzed drought event type (extreme, severe, moderate, and mild).
在这项工作中，研究了利用热带降雨测量任务（TRMM）降雨数据和标准化降水指数（SPI）来监测圣弗朗西斯科河上游流域干旱的时空变化。因此，确定了干旱的时空行为以及具有相似行为的聚类区域。结果表明，聚类、树形图和SPI值的空间分布的联合分析是识别同质区域的有力工具。结果显示，该流域的东北地区降雨指数最低，西南地区降雨深度最高，且该地区分别在6月至8月和11月至1月有明确的旱季和雨季。对干旱和降雨状况的分析表明，研究区域是同质且分布良好的；然而，在短期、中期和长期分析中，极端和严重干旱事件的数量高于降雨深度高的地区预期的数量，特别是在南部/西南部和东南部地区。因此，提出了一种替代分类方法来表征干旱，该方法根据分析的干旱事件类型（极端、严重、中度和轻度）在空间上对干旱类型（短期、中期和长期）进行分类。
