Departamento de Estatística e Informática, Universidade Federal Rural de Pernambuco, Av. Manoel Medeiros S/N, Dois Irmãos, Recife 52171-900, PE, Brazil.
Departamento de Energia Nuclear, Universidade Federal de Pernambuco, Moraes Rego 1235, Cidade Universitária, Recife 50670-901, PE, Brazil.
Chaos. 2023 Feb;33(2):023115. doi: 10.1063/5.0135352.
We investigated the influence of the construction of cascade dams and reservoirs on the predictability and complexity of the streamflow of the São Francisco River, Brazil, by using complexity entropy causality plane (CECP) in its standard and weighted form. We analyzed daily streamflow time series recorded in three fluviometric stations: São Francisco (upstream of cascade dams), Juazeiro (downstream of Sobradinho dam), and Pão de Açúcar station (downstream of Sobradinho and Xingó dams). By comparing the values of CECP information quantifiers (permutation entropy and statistical complexity) for the periods before and after the construction of Sobradinho (1979) and Xingó (1994) dams, we found that the reservoirs' operations changed the temporal variability of streamflow series toward the less predictable regime as indicated by higher entropy (lower complexity) values. Weighted CECP provides some finer details in the predictability of streamflow due to the inclusion of amplitude information in the probability distribution of ordinal patterns. The time evolution of streamflow predictability was analyzed by applying CECP in 2 year sliding windows that revealed the influence of the Paulo Alfonso complex (located between Sobradinho and Xingó dams), construction of which started in the 1950s and was identified through the increased streamflow entropy in the downstream Pão de Açúcar station. The other streamflow alteration unrelated to the construction of the two largest dams was identified in the upstream unimpacted São Francisco station, as an increase in the entropy around 1960s, indicating that some natural factors could also play a role in the decreased predictability of streamflow dynamics.
我们研究了梯级大坝和水库的建设对巴西圣弗朗西斯科河流量的可预测性和复杂性的影响，使用了标准形式和加权形式的复杂性熵因果平面（CECP）。我们分析了三个流量站记录的日流量时间序列：圣弗朗西斯科（梯级大坝上游）、若阿泽伊鲁（索布拉迪诺大坝下游）和糖面包山站（索布拉迪诺和兴古大坝下游）。通过比较 Sobradinho（1979 年）和 Xingó（1994 年）大坝建设前后 CECP 信息量化器（排列熵和统计复杂性）的值，我们发现水库运行使流量系列的时间变异性向可预测性较低的方向变化，表现为熵值较高（复杂性较低）。加权 CECP 通过在有序模式的概率分布中包含幅度信息，为流量的可预测性提供了一些更精细的细节。通过在 2 年滑动窗口中应用 CECP 分析了流量可预测性的时间演化，该窗口揭示了 Paulo Alfonso 综合体（位于 Sobradinho 和 Xingó 大坝之间）的影响，该综合体始建于 20 世纪 50 年代，其特征是下游糖面包山站的流量熵增加。在上游未受影响的圣弗朗西斯科站，还发现了与建设两座最大大坝无关的其他流量变化，即 20 世纪 60 年代左右熵的增加，表明一些自然因素也可能在流量动态的可预测性降低方面发挥作用。
