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

Nalley, D.; Adamowski, Jan; Khalil, Bahaa; Biswas, Asim

doi:10.1016/j.jhydrol.2016.02.049

Cited by 66 publications

(51 citation statements)

References 60 publications

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“…The AMO was significantly and positively correlated with precipitation for lags of 1 month for Pearson, Kendall, and Spearman's correlation coefficients in the MHRB. However, when correlations are low, low correlation coefficients with significant p-values may occur due to the large sample size used in this study, which resulted in high degrees of freedom [65]. Furthermore, De Oliveirajunior et al [66] revealed that all tests, regardless of the Standardized Precipitation Index scale, showed low Pearson, Kendall, and Spearman correlation coefficients, while significant for ENSO and PDO in the north and northwest regions of the State of Rio de Janeiro, Brazil.…”

Section: Wavelet Coherence Between the Monthly Precipitation And Largmentioning

confidence: 95%

Relationships between Spatial and Temporal Variations in Precipitation, Climatic Indices, and the Normalized Differential Vegetation Index in the Upper and Middle Reaches of the Heihe River Basin, Northwest China

Zhong

Cheng

2019

Water

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Changes in precipitation are critical indicators of climate change. In this study, the daily precipitation records from 10 meteorological stations in the Heihe River Basin, Northwest China from 1961–2016, precipitation indices, climate indices, and the normalized differential vegetation index (NDVI) were investigated using the Pearson, Kendall, and Spearman correlation coefficients; Theil-Sen Median; Mann–Kendall test; and wavelet coherence. The results indicated that the occurrences (fractional contributions) of 1–2-day wet periods were 81.3% (93.9%) and 55.3% (82.1%) in the upper (UHRB) and middle (MHRB) reaches of the Heihe River Basin, respectively. The spatial distribution of the occurrences (fractional contributions) was almost consistent with non-significant increases/decreases at stations. The ATP, ATD, API, and AMRD increased, while precipitation regimes suggest that dry seasons are getting wetter, and wet seasons are getting drier, although these changes were not significant. Wavelet coherence analyses showed that climate indices influenced precipitation, mainly its concentration, on a 4- to 78.6-month timescale. The Pearson, Kendall, and Spearman correlation coefficients showed weak lagged linkages between precipitation and the North Arctic Oscillation (NAO), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Oscillation (AMO). The NDVI of grasslands, meadows and coniferous forests was significantly and positively correlated with precipitation, while the NDVI of alpine vegetation, swamps and shrubs was negatively and significantly correlated with precipitation in the UHRB. The NDVI of grasslands was significantly and positively correlated, but the NDVI of shrubs, coniferous forests and cultivated vegetation was negatively and significantly correlated with precipitation in the MHRB. The correlation between cultivated vegetation and natural precipitation in the MHRB may have been weakened by human activities.

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Section: Wavelet Coherence Between the Monthly Precipitation And Largmentioning

confidence: 95%

Relationships between Spatial and Temporal Variations in Precipitation, Climatic Indices, and the Normalized Differential Vegetation Index in the Upper and Middle Reaches of the Heihe River Basin, Northwest China

Zhong

Cheng

2019

Water

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“…The mathematical basis and practical explanation for this technique can be found in Torrence and Compo (1998) and Cazelles et al (2008). Other studies employ wavelet analysis for hydrology (Adamowski et al, 2013;Labat, 2008), and/or the closely related cross wavelet analysis to evaluate nonstationary cyclical covariations between hydrological variations and atmospheric circulation indices (Adamowski et al, 2013, Ballesteros-Canovas et al, 2019, Cazelles et al, 2008Keener et al, 2010;Jean et al, 2014;Nalley et al, 2016;Schulte et al, 2016;Torrence and Compo, 1998;Prokoph and Bilali, 2008). Wavelet analysis is performed using R open source statistical programming language (R Core Team, 2016) and the R-package WaveletComp (Roesch and Schmidbauer, 2018).…”

Section: Frequency-domain Analysis Methodsmentioning

confidence: 99%

Hydrological and temperature variations between 1900 and 2016 in the Catskill Mountains, New York, USA

Kelly‐Voicu

Frei

2019

Intl Journal of Climatology

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The Catskill Mountains and surrounding counties in south‐central New York State are home to almost 400,000 residents, and supply drinking water to over 9 million people in New York City and other municipalities. In this study, we identify a set of stations in this region that are appropriate for climatological analysis, and examine variations in precipitation, streamflow, and temperature between 1900 and 2016, extending the time domain of previous studies of the climatology of this region during both the early and recent portions of the record. Temperatures have increased since the mid‐20th century, in particular daily minimum temperatures, at rates that vary with season and elevation. As a result, diurnal temperature ranges have tended to decrease, particularly during the warm season at lower elevations. The most significant hydrological events include the cold drought of the 1960s (a year‐round phenomenon), and the wet period beginning in the late 1990s (primarily a warm season phenomenon). We also find evidence of a particularly wet period at the start of the 20th century. Cyclic behaviour is found in both hydrological and temperature records, with the most prominent cycle in cold season precipitation and streamflow peaking at 28 years.

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“…For Moldova, identified two broad categories of stream flow periodicities namely 1-16.5 and 27.8-55.6 years with the associated correlation matrix of the global wavelet spectrum suggesting that the North Atlantic Oscillation (NAO), East Atlantic/West Russia Oscillation (EAWRO), Pacific Decadal Oscillation (PDO), are the main drivers of stream flow periodicities. Using annual flow data Nalley et al, (2016) revealed significant periodicities in stream flow for Quebec rivers at 4, 4-6, 6-8 and greater than 8 years with wavelet coherence analyses demonstrating ENSO and NAO effects at the inter-annual scale at periodicities of 2-6 years, whereas the influence of the PDO revealed itself at periodicities up to 8 and exceeding 16 years. Interestingly, Nalley et al (2016) also uncovered lag effects between teleconnection patterns and stream flow response with time delays to ENSO, NAO, and PDO of 1-4 years.…”

Section: Stream Flowmentioning

confidence: 99%

“…Using annual flow data Nalley et al, (2016) revealed significant periodicities in stream flow for Quebec rivers at 4, 4-6, 6-8 and greater than 8 years with wavelet coherence analyses demonstrating ENSO and NAO effects at the inter-annual scale at periodicities of 2-6 years, whereas the influence of the PDO revealed itself at periodicities up to 8 and exceeding 16 years. Interestingly, Nalley et al (2016) also uncovered lag effects between teleconnection patterns and stream flow response with time delays to ENSO, NAO, and PDO of 1-4 years. For north-east Brazil, Genz and Tanajura (2013) found, using spectral analysis, inter-annual modes of stream flow variability at 2-3, 3-4, 7-8 and 11-12 years noting, without offering explanations of the linking mechanisms, that the decadal frequency is consistent with SST related South Atlantic and ENSO indices.…”

Section: Stream Flowmentioning

confidence: 99%

Hydroclimatology, modes of climatic variability and stream flow, lake and groundwater level variability

McGregor

2017

Progress in Physical Geography: Earth and Environment

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(2017) 'Hydroclimatology, modes of climatic variability and stream ow, lake and groundwater level variability.', Progress in physical geography., 41 (4). pp. 496-512. Further information on publisher's website:https://doi.org/10.1177/0309133317726537Publisher's copyright statement:Additional information: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Hydroclimatology is an expansive discipline largely concerned with understanding the workings of the hydrological cycle in a climate context. Acknowledging this, and given the burgeoning interest in the relation between climate and water in the context of working towards an improved understanding of the impacts of climatic variability on water resources this progress report turns its attention to the connection between large scale modes of climatic variability and hydrological variability in streams, lakes and groundwater. A survey of the recent literature finds a plethora of teleconnection indices have been employed in the analysis of hydrological variability. Indices representing modes of climatic variability such as El Nino Southern Oscillation, the North Atlantic Oscillation, the Pacific North America pattern, the Pacific Decadal Oscillation and Atlantic Meridional Oscillation dominate the literature on climatic and hydrological variability. While examples of discernible signals of modes of climatic variability in stream flow and lake and groundwater level time series abound, the associations between periodic to quasi-period oscillations in atmospheric/ocean circulation patterns and variability within the terrestrial branch of the hydrological are far from simple being both monotonic (linear and non-linear) and non-monotonic and also conditional on period of analysis, season and geographic region. While there has been considerable progress over the last five years in revealing the climate mechanisms that underlie the links between climatic and hydrological variability a bothering feature of the literature is how climatic and hydrological variability is often viewed through a purely statistical lens with little attention given to diagnosing the relationship in terms of atmosphere and ocean physics and dynamics. Consequently significant progress remains to be made in obtaining a satisfactory hydroclimatological understanding of stream flow, lake and groundwater variability especially, if hydroclimatological knowledge is to be fully integrated into water resource management and planning.3

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

Cited by 66 publications

References 60 publications

Relationships between Spatial and Temporal Variations in Precipitation, Climatic Indices, and the Normalized Differential Vegetation Index in the Upper and Middle Reaches of the Heihe River Basin, Northwest China

Relationships between Spatial and Temporal Variations in Precipitation, Climatic Indices, and the Normalized Differential Vegetation Index in the Upper and Middle Reaches of the Heihe River Basin, Northwest China

Hydrological and temperature variations between 1900 and 2016 in the Catskill Mountains, New York, USA

Hydroclimatology, modes of climatic variability and stream flow, lake and groundwater level variability

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