Marie Minville

Structural and Non-Structural Climate Change Adaptation Strategies for the Péribonka Water Resource System

This paper discusses the possibility for a privately managed hydro-power system to adapt to a projected increase in water flow in their central-Québec watersheds by adding power generation potential. Runoffs simulated by a lumped rainfall-runoff model were fed into a stochastic dynamic programming (SDP) routine to generate reservoir operating rules. These rules were optimized for maximum power generation under maximal and minimal reservoir level constraints. With these optimized rules, a power generation simulator was used to predict the amount of generated hydropower. The same steps, excluding calibration, were performed on 60 climate projections (from 23 general circulation models and 3 greenhouse gas emission scenarios) for future horizons 2036–2065 and 2071–2100. Reservoir operation rules were optimized for every climate change projection for the 3 power plants in the system. From these simulations, it was possible to determine hydropower numbers for both horizons. The same steps were performed under a modified system in which an additional turbine was added to each power plant. Results show that both the non-structural (optimizing reservoir rules) and structural (adding turbines) adaptation measures allow for increased power production, but that adapting operating rules is sufficient to reap the most of the benefits of increased water availability.

Improving process representation in conceptual hydrological model calibration using climate simulations

Different sets of calibrated model parameters can yield divergent hydrological simulations which in turn can lead to different operational decisions or scientific conclusions. In order to obtain reliable hydrological results, proper calibration is therefore fundamental. This article proposes a new calibration approach for conceptual hydrological models based on the paradigm that hydrological process representation, along with the reproduction of observed streamflows, need to be taken into account when assessing the performance of a hydrological model. Several studies have shown that complementary data can be used to improve hydrological process representation and make hydrological modeling more robust. In the current study, the process of interest is actual evapotranspiration (AET). In order to obtain a more realistic representation of AET, meteorological variables and the AET mean annual cycle simulated by a regional climate model (RCM) driven by reanalysis are used to impose constraints during the optimization procedure. This calibration strategy is compared to a second strategy which relies on AET derived from reference data and to the classical approach based solely on the reproduction of observed discharges. The different methodologies are applied to calibrate the lumped conceptual model HSAMI, used operationally at Hydro-Quebec, for six Canadian snow-dominated basins with various hydrometeorological and physiographical characteristics.

Can We Adequately Quantify the Increase/Decrease of Flooding Due to Climate Change?

Changes in global climate may have significant impacts on local and regional hydrological regimes. Consequences of these changes may in turn result into potentially significant impacts on flooding occurrence and severity, as well as more or less prolonged droughts. Adaptation strategies, including revisiting engineering design standards and practice, as well as developing innovative water management approaches, will need to be devised to cope with potentially deleterious impacts consequential to shifts in climate. It is therefore imperative to capitalize on the latest and finest tools to quantify impacts of climate change on river flows. A number of studies investigated the potential impacts of climate change on river flooding. Most are directly or indirectly based on linking General Circulation Models (GCM) outputs to hydrological models to generate current and anticipated river flows. The approach suffers from the low spatial and temporal resolution of GCMs which is not suitable for carrying hydrological studies on all but a few watersheds. The number of GCMs and climate scenarios adds to the uncertainty in quantifying watershed hydrological response to climate change. Downscaling techniques, either dynamical or statistical, offer new perspectives for conducting climate change impact studies, as they are used to bridge the spatial and temporal resolution gaps between climate models and what impact assessors need. However, most downscaling methods have problems dealing with the uncertainty linked to models and emission scenarios. This paper presents results from one possible approach and discuss the implications for flood estimation in the snowmelt period and summer/fall season.

A global portrait of hydrological changes at the 2050 horizon for the province of Québec

This paper presents the methodology and results of a vast study on climate change impacts on hydrology for the province of Québec for the 2050 horizon. A climate ensemble was first built with simulations from the World Climate Research Programme (WCRP)s Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset, the North American Regional Climate Change Assessment Program (NARCCAP) and the Canadian Regional Climate Model (CRCM) operational runs. Direct outputs and post-processed data from the climate simulations were used as input to the calibrated HSAMI hydrological model in order to produce a large ensemble of hydrological projections for 305 Québec watersheds. Simulations results indicate that increases in mean annual streamflow are projected for the whole province, with greater changes (up to 14%) in the north. The intra-annual distribution of streamflow also changes, with higher winter flows and lower summer flows as well as apparently earlier spring floods. The maximum height of the snow cover and the number of days with snow on the ground are likely to diminish for the 2050 horizon for the southern half of the province, while the northern half will see more snow, but a shorter snow season as well.