Inter-annual to inter-decadal streamflow variability in Quebec and Ontario in relation to dominant large-scale climate indices

被引:60
作者
Nalley, D. [1 ]
Adamowski, J. [1 ]
Khalil, B. [1 ,2 ]
Biswas, A. [3 ]
机构
[1] McGill Univ, Dept Bioresource Engn, Ste Anne De Bellevue, PQ H9X 3V9, Canada
[2] Helwan Univ, Dept Civil Engn, Cairo, Egypt
[3] McGill Univ, Dept Nat Resource Sci, Ste Anne De Bellevue, PQ H9X 3V9, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Streamflow variability; NAO; PDO; ENSO; Continuous wavelet transform; Wavelet coherence; WAVELET TRANSFORM; TIME-SERIES; NORTH-ATLANTIC; ENSO INFLUENCES; PRECIPITATION; OSCILLATION; TRENDS; TEMPERATURE; MANAGEMENT; RAINFALL;
D O I
10.1016/j.jhydrol.2016.02.049
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The impacts of large-scale climate oscillations on hydrological systems and their variability have been documented in different parts of the world. Since hydroclimatic data are known to exhibit non stationary characteristics, spectral analyses such as wavelet transforms are very useful in extracting time-frequency information from such data. As Canadian studies, particularly those of regions east of the Prairies, using wavelet transform-based methods to draw links between relevant climate indices [e.g., the El Nino Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Pacific Decadal Oscillation (PDO)] and streamflow variability are not common, this study aims to analyze such relationships for the southern regions of Quebec and Ontario. Monthly and annual streamflow data with a record length of 55 years were used to capture streamflow variability at intra-annual, inter-annual and inter-decadal scales. The continuous wavelet transform spectra of monthly streamflow data revealed consistent significant 6- and 12-month periodicities, which are likely associated with strong seasonality factors. Its annual counterparts showed four different significant periodicities: up to 4 years, 4-6 years, 6-8 years, and greater than 8 years - all of which occurred after the late 1960s/early 1970s. Wavelet coherence analyses show that the influence of ENSO and NAO at the inter-annual scale occurs at 2-6 year periodicities, and the influence of PDO occur at periodicities up to 8 years and exceeding 16 years. Correlations between these climate indices and streamflow were computed to determine the time delay of streamflow response to the influence of ENSO, NAO, and PDO. The lag times ranged from 6-48 months (for monthly data) and 1-4 years (for annual data). This research contributes to our understanding of streamflow variability over the southern parts of Quebec and Ontario, and the role of ENSO, NAO, and PDO phenomena on this variability. These relationships can be also used to improve hydrological forecasting and water resources management in Ontario and Quebec. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:426 / 446
页数:21
相关论文
共 69 条
[1]   Influence of Trend on Short Duration Design Storms [J].
Adamowski, Jan ;
Adamowski, Kaz ;
Bougadis, John .
WATER RESOURCES MANAGEMENT, 2010, 24 (03) :401-+
[2]  
Anctil F, 2004, J CLIMATE, V17, P163, DOI 10.1175/1520-0442(2004)017<0163:WAOTIV>2.0.CO
[3]  
2
[4]   Using wavelet transforms to estimate surface temperature trends and dominant periodicities in Iran based on gridded reanalysis data [J].
Araghi, A. ;
Baygi, M. Mousavi ;
Adamowski, J. ;
Malard, J. ;
Nalley, D. ;
Hasheminia, S. M. .
ATMOSPHERIC RESEARCH, 2015, 155 :52-72
[5]   Long-term SPI drought forecasting in the Awash River Basin in Ethiopia using wavelet neural network and wavelet support vector regression models [J].
Belayneh, A. ;
Adamowski, J. ;
Khalil, B. ;
Ozga-Zielinski, B. .
JOURNAL OF HYDROLOGY, 2014, 508 :418-429
[6]   Application of Continuous Wavelet Transform in Examining Soil Spatial Variation: A Review [J].
Biswas, Asim ;
Si, Bing Cheng .
MATHEMATICAL GEOSCIENCES, 2011, 43 (03) :379-396
[7]  
Brown RD, 1996, J CLIMATE, V9, P1299, DOI 10.1175/1520-0442(1996)009<1299:IVIRCS>2.0.CO
[8]  
2
[9]   Detection of hydrologic trends and variability [J].
Burn, DH ;
Elnur, MAH .
JOURNAL OF HYDROLOGY, 2002, 255 (1-4) :107-122
[10]   Forecasting Urban Water Demand Via Wavelet-Denoising and Neural Network Models. Case Study: City of Syracuse, Italy [J].
Campisi-Pinto, Salvatore ;
Adamowski, Jan ;
Oron, Gideon .
WATER RESOURCES MANAGEMENT, 2012, 26 (12) :3539-3558