Future shift in winter streamflow modulated by the internal variability of climate in southern Ontario
Authors: Champagne Olivier , Arain M. Altaf , Leduc Martin , Coulibaly Paulin , McKenzie Shawn 
Published: June 2020

Abstract. Fluvial systems in southern Ontario are regularly
affected by widespread early-spring flood events primarily caused by
rain-on-snow events. Recent studies have shown an increase in winter floods
in this region due to increasing winter temperature and precipitation.
Streamflow simulations are associated with uncertainties mainly due to the
different scenarios of greenhouse gas emissions, global climate
models (GCMs) or the choice of the hydrological model. The internal
variability of climate, defined as the chaotic variability of atmospheric
circulation due to natural internal processes within the climate system, is
also a source of uncertainties to consider. Uncertainties of internal variability can be assessed using hydrological models fed by downscaled data of a
global climate model large ensemble (GCM-LE), but GCM outputs have too
coarse of a scale to be used in hydrological modeling. The Canadian Regional
Climate Model Large Ensemble (CRCM5-LE), a 50-member ensemble downscaled
from the Canadian Earth System Model version 2 Large Ensemble
(CanESM2-LE), was developed to simulate local climate variability over
northeastern North America under different future climate scenarios. In this
study, CRCM5-LE temperature and precipitation projections under an RCP8.5
scenario were used as input in the Precipitation Runoff Modeling System
(PRMS) to simulate streamflow at a near-future horizon (2026–2055) for four
watersheds in southern Ontario. To investigate the role of the internal
variability of climate in the modulation of streamflow, the 50 members were
first grouped in classes of similar projected change in January–February
streamflow and temperature and precipitation between 1961–1990 and 2026–2055.
Then, the regional change in geopotential height (Z500) from CanESM2-LE was
calculated for each class. Model simulations showed an average
January–February increase in streamflow of 18 % (±8.7) in Big
Creek, 30.5 % (±10.8) in Grand River, 29.8 % (±10.4) in
Thames River and 31.2 % (±13.3) in Credit River. A total of 14 % of all
ensemble members projected positive Z500 anomalies in North America's eastern
coast enhancing rain, snowmelt and streamflow volume in January–February.
For these members the increase of streamflow is expected to be as high as
31.6 % (±8.1) in Big Creek, 48.3 % (±11.1) in Grand River,
47 % (±9.6) in Thames River and 53.7 % (±15) in Credit
River. Conversely, 14 % of the ensemble projected negative Z500 anomalies
in North America's eastern coast and were associated with a much lower increase
in streamflow: 8.3 % (±7.8) in Big Creek, 18.8 % (±5.8) in
Grand River, 17.8 % (±6.4) in Thames River and 18.6 % (±6.5) in Credit River. These results provide important information to
researchers, managers, policymakers and society about the expected ranges
of increase in winter streamflow in a highly populated region of Canada, and they
will help to explain how the internal variability of climate is expected to
modulate the future streamflow in this region.