摘要:Study region Athabasca River Basin (ARB) in Alberta, Canada. Study focus Understanding the historical streamflow variability within basins is crucial to reduce the effect of utmost events, such as drought and floods on agriculture, fishery, and other human activities. The Least-Squares Wavelet software (LSWAVE) is applied to estimate the trend and seasonal components of sixty-year-long climate and discharge time series and to study the impact of climate change on streamflow over time. New hydrological insights for the region The seasonal components of the discharge and precipitation time series including annual and semi-annual are coherent with phase discrepancy. The mean temperature has been gradually increasing since 1960, and it is projected to increase by approximately 2 °C during the mid-century which may reduce the snowpack volume during the spring. From the recurring pattern of spectral peaks in the spectrograms and jumps in the trend component of streamflow time series, the blue water is projected to increase during the mid-century, in particular in early 2030s. The results also highlight the potential of LSWAVE in analyzing climate and hydrological time series without any need for interpolation, gap-filling, and de-spiking.
关键词:Climate change ; Coherency analysis ; Data gaps ; Spectral analysis ; Trend analysis ; Water flow analysis