Contributions of different time scales to extreme Paraná floods
Contributions of different time scales to extreme Paraná floods
复制标题
不同时间尺度对巴拉那州极端洪水的贡献
作者：
A. Antico;M. E. Torres;H. Diaz
本研究提供了第一个完整的检查如何不同的时间尺度有助于产生四个最大的观测到的巴拉那河洪水（1905年，1983年，1992年和1998年）。这项检查是基于以前的研究结果，其中使用经验方法将1904-2010年巴拉那流量记录（月平均值）分解为几个具有物理意义的振荡，具有独特的时间尺度或周期（几个月到几十年），以及长期增长趋势。我们发现，所有的振荡在很大程度上有助于四个极端的洪水，除了18年的周期，没有贡献于1992年的洪水。年际到年代际（3-85年）周期之间的零星强烈建设性干扰决定了（i）极端洪水发生的有利条件，以及（ii）洪水之间的显着差异。事实上，1983年有记录以来最大的洪水主要是由于3-5年、9年、18年和31-85年周期之间异常强烈的建设性干扰造成的，这些周期分别与厄尔尼诺事件、北大西洋涛动、南大西洋辐合带和太平洋有关。31-85年周期对两次最大洪水（1983年和1992年）的贡献大于长期上升趋势的贡献，表明这种缓慢振荡在洪水形成过程中的重要性。我们的研究结果的理解和预测巴拉那洪水的影响进行了讨论。
The present study provides the first complete examination of how different time scales contributed to generate the four largest observed floods of the Paraná River (1905, 1983, 1992 and 1998). This inspection is based on the results from a previous study where an empirical method was used to decompose a 1904–2010 Paraná flow record (monthly means) into several physically meaningful oscillations with distinctive time scales or periods (few months to decades), and a secular increasing trend. We show that all the oscillations largely contributed to the four extreme floods, except an 18-year cycle that did not contribute to the 1992 flood. Sporadic intense constructive interferences between interannual-to-interdecadal (3–85 years) cycles determined (i) the favorable conditions for extreme-flood occurrence, and (ii) notable differences among floods. Indeed, in 1983, the largest flood ever recorded resulted mainly from an exceptionally strong constructive interference between cycles of 3–5, 9, 18 and 31–85 years, which are related to El Niño events, the North Atlantic Oscillation, the South Atlantic Convergence Zone, and the Pacific Ocean, respectively. Contributions of the 31–85-year cycle to the two biggest floods (1983 and 1992) are larger than the contributions of the secular upward trend, suggesting the importance of this slow oscillation in flood formation processes. The implications of our results for understanding and predicting Paraná floods are discussed.