Sulis M.,University of Quebec |
Sulis M.,INRS - Institute National de la Recherche Scientifique |
Paniconi C.,University of Quebec |
Paniconi C.,INRS - Institute National de la Recherche Scientifique |
And 3 more authors.
Water Resources Research | Year: 2011
A process-based model that incorporates hydrodynamic feedbacks between the land surface, soil, and groundwater zones is used to assess the sensitivity of the hydrological response (river discharge, aquifer recharge, and soil water storage) to future climate conditions. The analysis is based on the Intergovernmental Panel on Climate Change Special Report on Emissions Scenario A2 and the des Anglais catchment in southwestern Quebec (Canada). Application of the coupled hydrological model (CATHY) to the study basin revealed significant spatiotemporal variations in the river discharge response to climate change owing to a different partitioning between the overland runoff and base flow components of the hydrograph, with the latter alleviating the marked decrease in discharge during the summer period. A spatial analysis of recharge patterns shows that the greatest variations are expected to occur, throughout the year, in the southern portion of the catchment, where the elevations are highest. Compared to river discharge and aquifer recharge, the soil water storage volumes are less sensitive to climate changes. From a spatial analysis of soil moisture variations it was possible to observe organizational patterns that follow the topographic and pedologic characteristics of the catchment. In addition to these analyses, we also compare predictions obtained with the land surface scheme (CLASS) that is coupled to the regional climate model (CRCM) to those from the detailed catchment model for past and future climate change projections. An examination of the runoff revealed that CLASS produces higher estimates than CATHY of surface and subsurface runoff throughout the annual cycle for both past and future projections. For soil water storage, the two models are in general agreement in terms of the intra-annual variability of moisture content at shallower soil layers, whereas a larger difference is found for the deepest layer, with CATHY predicting wetter soil conditions over the entire simulation period and moisture fluctuations of much smaller amplitude. © 2011 by the American Geophysical Union.
Hanesiak J.M.,University of Manitoba |
Stewart R.E.,University of Manitoba |
Bonsal B.R.,Environment Canada |
Harder P.,University of Manitoba |
And 36 more authors.
Atmosphere - Ocean | Year: 2011
Droughts are among the world's most costly natural disasters and collectively affect more people than any other form of natural disaster. The Canadian Prairies are very susceptible to drought and have experienced this phenomenon many times. However, the recent 1999-2005 Prairie drought was one of the worst meteorological, agricultural and hydrologic droughts over the instrumental record. It also had major socio-economic consequences, adding up to losses in the billions of dollars. This recent drought was the focus of the Drought Research Initiative (DRI), the first integrated network focusing on drought in Canada. This article addresses some of the key objectives of DRI by providing a collective summary, understanding and synthesis of the 1999-2005 drought. Bringing together the many datasets used in this study was in itself a major accomplishment. This drought exhibited many important, and sometimes surprising, features. This includes, for example, (1) a non-steady large-scale atmospheric circulation (and sea surface temperature) pattern that mainly resulted in subsidence over the region but also cold and warm periods in its evolution; such features have typically not occurred in previous droughts; (2) large spatial gradients between wet and dry areas that, in some instances, were linked with major precipitation events; and (3) many impacts at and below the earth's surface that occurred with varying temporal lags from the meteorological conditions and, in response, these impacts would have fed back onto the character of the drought (e.g., the surface-convection feedback). The drought's complexity poses enormous challenges for its simulation and prediction at all temporal scales. High-resolution models coupled with the surface are needed to address these and many other issues identified in this article.
Sulis M.,University of Bonn |
Paniconi C.,University of Quebec |
Marrocu M.,Center for Advanced Studies Research and Development in Sardinia 4 |
Huard D.,Ouranos Consortium on Regional Climatology and Adaptation to Climate Change |
Chaumont D.,Ouranos Consortium on Regional Climatology and Adaptation to Climate Change
Water Resources Research | Year: 2012
General circulation models (GCMs) are the primary instruments for obtaining projections of future global climate change. Outputs from GCMs, aided by dynamical and/or statistical downscaling techniques, have long been used to simulate changes in regional climate systems over wide spatiotemporal scales. Numerous studies have acknowledged the disagreements between the various GCMs and between the different downscaling methods designed to compensate for the mismatch between climate model output and the spatial scale at which hydrological models are applied. Very little is known, however, about the importance of these differences once they have been input or assimilated by a nonlinear hydrological model. This issue is investigated here at the catchment scale using a process-based model of integrated surface and subsurface hydrologic response driven by outputs from 12 members of a multimodel climate ensemble. The data set consists of daily values of precipitation and min/max temperatures obtained by combining four regional climate models and five GCMs. The regional scenarios were downscaled using a quantile scaling bias-correction technique. The hydrologic response was simulated for the 690 km2 des Anglais catchment in southwestern Quebec, Canada. The results show that different hydrological components (river discharge, aquifer recharge, and soil moisture storage) respond differently to precipitation and temperature anomalies in the multimodel climate output, with greater variability for annual discharge compared to recharge and soil moisture storage. We also find that runoff generation and extreme event-driven peak hydrograph flows are highly sensitive to any uncertainty in climate data. Finally, the results show the significant impact of changing sequences of rainy days on groundwater recharge fluxes and the influence of longer dry spells in modifying soil moisture spatial variability. © 2012. American Geophysical Union. All Rights Reserved.
Music B.,Ouranos Consortium on Regional Climatology and Adaptation to Climate Change |
Frigon A.,Ouranos Consortium on Regional Climatology and Adaptation to Climate Change |
Lofgren B.,National Oceanic and Atmospheric Administration |
Turcotte R.,Center Dexpertise Hydrique Du Quebec Cehq |
Cyr J.-F.,Center Dexpertise Hydrique Du Quebec Cehq
Climatic Change | Year: 2015
Regional climate modelling represents an appealing approach to projecting Great Lakes water supplies under a changing climate. In this study, we investigate the response of the Great Lakes Basin to increasing greenhouse gas and aerosols emissions using an ensemble of sixteen climate change simulations generated by three different Regional Climate Models (RCMs): CRCM4, HadRM3 and WRFG. Annual and monthly means of simulated hydro-meteorological variables that affect Great Lakes levels are first compared to observation-based estimates. The climate change signal is then assessed by computing differences between simulated future (2041–2070) and present (1971–1999) climates. Finally, an analysis of the annual minima and maxima of the Net Basin Supply (NBS), derived from the simulated NBS components, is conducted using Generalized Extreme Value distribution. Results reveal notable model differences in simulated water budget components throughout the year, especially for the lake evaporation component. These differences are reflected in the resulting NBS. Although uncertainties in observation-based estimates are quite large, our analysis indicates that all three RCMs tend to underestimate NBS in late summer and fall, which is related to biases in simulated runoff, lake evaporation, and over-lake precipitation. The climate change signal derived from the total ensemble mean indicates no change in future mean annual NBS. However, our analysis suggests an amplification of the NBS annual cycle and an intensification of the annual NBS minima in future climate. This emphasizes the need for an adaptive management of water to minimize potential negative implications associated with more severe and frequent NBS minima. © 2015, The Author(s).