Wavelet transform for medium-range streamflows projections in national interconnected system

Carlos Eduardo Sousa Lima; Marx Vinicius Maciel da Silva; Cleiton da Silva Silveira; Francisco das Chagas Vasconcelos Junior

doi:10.5327/Z217694781048

Authors

Carlos Eduardo Sousa Lima Federal University of Ceará (UFC) - Brazil https://orcid.org/0000-0003-2199-3382
Marx Vinicius Maciel da Silva Federal University of Ceará (UFC) - Brazil https://orcid.org/0000-0001-9435-1001
Cleiton da Silva Silveira Federal University of Ceará (UFC) - Brazil https://orcid.org/0000-0003-3303-5157
Francisco das Chagas Vasconcelos Junior Fundação Cearense de Meteorologia e Recursos Hídricos - Brazil https://orcid.org/0000-0002-1558-8383

DOI:

https://doi.org/10.5327/Z217694781048

Keywords:

autoregressive wavelets; National Interconnected System; climate variability; streamflow projection.

Abstract

This study aimed to analyze the variability of average annual streamflow time series of the National Interconnected System (NIS) (Brazil) and create a projection model of future streamflow scenarios from 3 to 10 years using wavelet transform (WT). The streamflow time series were used and divided into two periods, namely, 1931–2005 and 2006–2017, for calibration and verification, respectively. The annual series was standardized, and by the WT, it was decomposed into two bands plus the residue for each base posts (BP) for later reconstruction. Then, an autoregressive (AR) model per band and residue was made. The projection was obtained by adding the AR models. For performance evaluation, a qualitative analysis of the cumulative probability distribution of the projected years and an analysis of the likelihood were performed. The model identified the probability distribution function of the projected years and obtained a likelihood ratio of > 1 in most SIN regions, indicating that this methodology can capture the mediumrange variability.

Downloads

Download data is not yet available.

References

Alves, B.C.C.; Souza Filho, F.A.; Silveira, C.S., 2013. Análise de tendência e Padrões de Variação das séries históricas de vazões do Operador Nacional de Sistemas (ONS). Revista Brasileira de Recursos Hídricos, v. 18, (4), 19-34. http://dx.doi.org/10.21168/rbrh.v18n4.p19-34.

Costa, F.S.; Maceira, M.E.P.; Damázio, J.M., 2007. Modelos de previsão hidrológica aplicados ao planejamento da operação do sistema elétrico brasileiro. Revista Brasileira de Recursos Hídricos, v. 12, (3), 21-30. http://dx.doi.org/10.21168/rbrh.v12n3.p21-30.

Grimm, A.M.; Almeida, A.S.; Beneti, C.A.A.; Leite, E.A., 2020. The combined effect of climate oscillations in producing extremes: the 2020 drought in southern Brazil. Revista Brasileira de Recursos Hídricos, v. 25, e48. https://doi.org/10.1590/2318-0331.252020200116.

Grimm, A.M.; Saboia, J.P.J., 2015. Interdecadal variability of the south american precipitation in the monsoon season. Journal of Climate, v. 28, (2), 755-775. http://dx.doi.org/10.1175/JCLI-D-14-00046.1.

International Energy Agency – IEA, 2020. World Energy Balances 2020 edition. International Energy Agency (Accessed August 25, 2021) at: https://www.iea.org/countries/brazil.

Jesus, E.M.; Rocha, R.P.; Reboita, M.S.; Llopart, M.; Dutra, L.M.M.; Remedio, A.R.C., 2016. Contribution of cold fronts to seasonal rainfall in simulations over the southern La Plata Basin. Climate Research, v. 68, (2-3), 243-255. http://dx.doi.org/10.3354/cr01358.

Kayano, M.T.; Andreoli, R.V.; Garcia, S.R.; Souza, R.A.F., 2018. How the two nodes of the tropical Atlantic sea surface temperature dipole relate the climate of the surrounding regions during austral autumn. International Journal of Climatology, v. 38, (10), 3927-3941. http://dx.doi.org/10.1002/joc.5545.

Kayano, M.T.; Andreoli, R.V.; Souza, R.A F., 2019. El Niño–Southern oscillation related teleconnections over South America under distinct Atlantic multidecadal oscillation and Pacific interdecadal oscillation backgrounds: La Niña. International Journal of Climatology, v. 39, (3), 1359-1372. http://dx.doi.org/10.1002/joc.5886.

Mantua, N.J.; Hare, S.R.; Zhang, Y.; Wallace, J.M.; Francis, R.C., 1997. A Pacific Interdecadal climate oscillation with impacts on salmon production. Bulletin of American Meteorology Society, v. 78, (6), 1069-1980. https://doi.org/10.1175/1520-0477(1997)078%3C1069:APICOW%3E2.0.CO;2.

Moreira, J.G.V.; Naghettini, M., 2016. Detecção de tendências monotônicas temporais e relação com erros dos tipos I e II: estudo de caso em séries de precipitações diárias máximas anuais do estado do Acre. Revista Brasileira de Meteorologia, v. 31, (4), 394-402. https://doi.org/10.1590/0102-778631231420140155.

Morettin, P.A., 1999. Ondas e ondaletas: da análise de Fourier à análise de ondaletas. Edusp, São Paulo.

Operador Nacional do Sistema – ONS, 2010a. Critérios para estudos hidrológicos – Submódulo 23.5. Procedimentos de Rede. Operador Nacional do Sistema, Brasília, 11 pp.

Operador Nacional do Sistema – ONS, 2010b. Operação do Sistema Interligado Nacional – Relatório Anual de Avaliação das Previsões de Vazões. Operador Nacional do Sistema, Brasília, 230 pp.

Operador Nacional do Sistema – ONS, 2016. O que é o SIN (Sistema Interligado Nacional). Operador Nacional do Sistema, Rio de Janeiro (Accessed Novemer 25, 2021) at: http://www.ons.org.br/paginas/sobre-o-sin/o-que-e-o-sin.

Rocha, R.V.; Souza Filho, F.A., 2020. Mapping abrupt streamflow shift in an abrupt climate shift through multiple change point methodologies: Brazil case study. Hydrological Sciences Journal, v. 65, (16), 2783-2796. https://doi.org/10.1080/02626667.2020.1843657.

Terrier, M.; Perrin, C.; Lavenne, A.; Andréassian, V.; Lerat, J.; Vaze, J., 2021. Streamflow naturalization methods: a review. Hydrological Sciences Journal, v. 66, (1), 12-36. https://doi.org/10.1080/02626667.2020.1839080.

Torrence, C., Compo, G.P., 1998. A practical guide to wavelet analysis. Bulletin of American Meteorology Society, v. 79, 61-78. https://doi.org/10.1175/1520-0477(1998)079%3C0061:APGTWA%3E2.0.CO;2.

Wang, Y.L.; Hsu, Y.C.; Lee, C.P.; Wu, C.R., 2019. Coupling influences of ENSO and PDO on the inter-decadal SST variability of the ACC around the Western South Atlantic. Sustainability, v. 11, (18), 4853. https://doi.org/10.3390/su11184853.

Wang, H.; Kumar, A.; Wang, W.; Xue, Y., 2012. Influence of ENSO on Pacific decadal variability: an analysis based on the NCEP Climate Forecast System. Journal of Climate, v. 25, 6136-6151. https://doi.org/10.1175/JCLI-D-11-00573.1.

Zhang, R.; Delworth, T.L., 2006. Impact of Atlantic multidecadal oscillations on India/Sahel rainfall and Atlantic hurricanes. Geophysical Research Letters, v. 33, (17). https://doi.org/10.1029/2006GL026267.

Zhang, Y.; Wallace, J.M.; Battisti, D., 1997. ENSO-like interdecadal variability: 1900-93. Journal of Climate, v. 10, 1004-1020. https://doi.org/10.1175/1520-0442(1997)010%3C1004:ELIV%3E2.0.CO;2.