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Climate change will have a significant impact on the hydrological cycle. This paper presents the results of a pilot project for the Yamaska River in Québec. The objective of this project is to evaluate the river's vulnerability to low flows attributable to climate change and to analyze a no-regrets adaptation strategy at locations identified as vulnerable. The vulnerability was evaluated using statistical indicators (low flow indices) based on long-term observations at four locations in the basin. A distributed physically-based hydrological model in use in Québec was calibrated and validated against observed streamflow data to properly represent low flows. Hydrological simulations used seven climate projections provided by the north american regional climate change assessment program (NARCCAP) s project. Also, five members of the canadian regional climate model (CRCM), nested with the coupled global climate model (CGCM) under the special report on emission scenarios (SRES) A2 emission scenario, were run for a reference (1971-2000) period and a future (2041-2070) period. Streamflow simulations indicate a degradation of future low flow conditions, particularly in June and August, when compared to the reference period. In addition, the 7-day low flow value with a 2-year return period (7Q2) and the 7-day low flow value with a 10-year return period (7Q10) decrease by 16-64% and 18-45% respectively. A no-regrets adaptation strategy allowing stakeholders to reduce withdrawal according to alert levels was implemented. Simulations of the application of the no-regrets adaptation strategy reduced the number of days where streamflows are below the Crisis level in the future period by at least 20%. [ABSTRACT FROM AUTHOR]

A procedure is proposed that enables the estimation of natural baseflow in a gauged watershed through analyses of recession curves and stream hydrographs. The analysis results in a surrogate for the recovery level of a watershed after a prolonged drought and allows the medium term prediction of runoff behaviour for water resources management. The method has been applied for the Upper Battle River Watershed in the northern Prairies of Alberta, Canada. Results show that baseflow is extremely low after a multi-year drought (2001 to 2003). The recession index indicates that one year after the climatological end of the drought the integrated watershed storage that usually sustains the baseflow is abnormally low, with associated negative impacts on available water resources. This paper describes the derivation, classification and application of a watershed specific recession index. Results show that the described procedure is relatively simple, reliable and efficient. [ABSTRACT FROM AUTHOR]

Summary: In recent years, climate change impacts on water resources sectors have been extensively documented. Anticipated changes range from more severe storms to more frequent floods and drought at regional scale. Pressure on water resources and hence on the environment will probably increase with the need of quality data for sustainable design of water resources projects. Therefore, for an optimal network design, hydrometric networks are to be reviewed periodically based on the information needs of the various end users and the perspective for future water resources development. This paper evaluates hydrometric networks to identify essential streamflow stations and critical areas (highly poor network density) within major watersheds across the different provinces of Canada using entropy theory. The method is applied to daily streamflow data and information coefficients such as marginal entropy, joint entropy and transinformation index are used for the identification of important stations as well as critical areas in the basin. The analysis results show that almost all Canadian main watersheds contain deficient hydrometric networks. The most deficient streamflow networks are identified in Alberta (North Saskatchewan, Oldman, and Red Deer basins), Northern Ontario (Hudson Bay basin), and the Northwest Territories. The information might prove to be helpful for decision makers to undertake cost-benefit analyses for hydrometric network updating in each region. [Copyright &y& Elsevier]

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It is a common practice to employ hydrologic models for assessing alterations to streamflow as a result of anthropogenically driven changes, such as riverine, land use, and climate change. However, the ability of the models to replicate different components of the hydrograph simultaneously is not clear. Hence, this study evaluates the ability of a standard hydrologic model set-up: Variable Infiltration Capacity (VIC) hydrologic model for two headwater sub-basins in the Fraser River (Salmon and Willow), British Columbia, Canada, with climate inputs derived from observations and statistically downscaled global climate models (GCMs); to simulate six general water resource indicators (WRIs) and 32 ecologically relevant indicators of hydrologic alterations (IHA). The results show a generally good skill of the observation-driven VIC model in replicating most of the WRIs and IHAs. Although the WRIs, including annual volume, centre of timing, and seasonal flows, and the IHAs, including maximum and minimum flows, were reasonably well replicated, statistically significant differences in some of the monthly flows, number and duration of flow pulses, rise and fall rates, and reversals were noted. In the case of GCM-driven results, additional monthly, maximum, and minimum flow indicators produced statistically significant differences. A number of issues with the model input/output data, hydrologic model parametrization and structure as well as downscaling methods were identified, which lead to such discrepancies. Therefore, there is a need to exercise caution in the use of model-simulated indicators. Overall, the WRIs and IHAs can be useful tools for evaluating changes in an altered hydrologic system, provided the skill and limitations of the model in replicating these indicators are understood. © 2013 Her Majesty the Queen in Right of Canada. Hydrological Processes © 2013 John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

A multiplicative relationship, drought magnitude ( M) = drought intensity ( I) × drought duration or length ( L) is used as a basis for predicting the largest expected value of hydrological drought magnitude, E( M) over a period of T-year (or month). The prediction of E( M) is carried out in terms of the SHI (standardized hydrological index, tantamount to standard normal variate) sequences of the annual and monthly streamflow time series. The probability distribution function (pdf) of I (drought intensity) was assumed to follow a truncated normal. The drought length ( L) was taken as some characteristic duration of the drought period, which is expressible as a linear combination of the expected longest (extreme) duration, E( L) and the mean duration, L of droughts and is estimated involving a parameter ø (range 0 to 1). The drought magnitude (deficit-sum, M) has been assumed to follow a gamma pdf, in view of the observed behavior of M. The model M = I × L has been invoked via two approximations, viz. Type-1 involves only mean of I and Type-2 involves both mean and variance of I through the theorem of extremes of random numbers of random variables. The E( L) were obtained using the Markov chain (MC) model of an appropriate order, which turned out to be zero order Markov chain (MC-0) at the annual time scale. At the monthly time scale, the E( L) was best represented by MC-0 for SHI sequences with low value of lag-1 autocorrelation ( ρ < 0.3) and first order Markov chain (MC-1) for SHI sequences with ρ > 0.3. At low cutoff levels ( q ≤ 0.2), the trivial relationship E( M) = E( I) × E( L) i.e. without considerations of the extreme number theorem and the pdf of M yielded satisfactory results. [ABSTRACT FROM AUTHOR]

Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the Qbic³ project (Quábec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e., lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in Southern Quábec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by global climate models over a reference (1971-2000) and a future (2041-2070) period. The results show that, for our hydrological model ensemble, the choice of model strongly affects the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model. [ABSTRACT FROM AUTHOR]

Simulation of surface water flow and temperature under a non-stationary, anthropogenically impacted climate is critical for water resource decision makers, especially in the context of environmental flow determination. Two climate change scenarios were employed to predict streamflow and temperature: RCP 8.5, the most pessimistic with regards to climate change, and RCP 4.5, a more optimistic scenario where greenhouse gas emissions peak in 2040. Two periods, 2018–2050 and 2051–2100, were also evaluated. In Canada, a number of modelling studies have shown that many regions will likely be faced with higher winter flow and lower summer flows. The CEQUEAU hydrological and water temperature model was calibrated and validated for the Wilmot River, Canada, using historic data for flow and temperature. Total annual precipitation in the region was found to remain stable under RCP 4.5 and increase over time under RCP 8.5. Median stream flow was expected to increase over present levels in the low flow months of August and September. However, increased climate variability led to higher numbers of periodic extreme low flow events and little change to the frequency of extreme high flow events. The effective increase in water temperature was four-fold greater in winter with an approximate mean difference of 4 °C, while the change was only 1 °C in summer. Overall implications for native coldwater fishes and water abstraction are not severe, except for the potential for more variability, and hence periodic extreme low flow/high temperature events. [ABSTRACT FROM AUTHOR]

For effective planning, design, and management of water resources engineering, the probability distribution of annual streamflow is necessary. The method of L-moments is applied to identify the probability distribution type of annual streamflow in different climatic regions of Canada. In the Pacific and southern British Columbia mountains (regions 1 and 2), the generalized extreme value (GEV) distribution fits the observations best with the 3-parameter lognormal (LN3) and log Pearson type III (LP3) as potential candidates. In Yukon and northern British Columbia (region 3), the LN3 distribution corresponds to observations best with the LP3 and P3 as potential candidates. In the northwestern forest (region 5), the LP3 distribution matches observations best with the P3 and GEV as potential candidates. In Arctic Tundra (region 10), the 3-parameter Weibull (W3) is the best one with the LN3 and P3 as potential candidates. The P3 distribution provides a best-fit to observations in the Prairies (region 4), northeastern forest (region 6), great Lakes and St. Lawrence (region 7), Atlantic (region 8), and Mackenzie (region 9) with the LN3, LP3, and GEV as potential candidates. [ABSTRACT FROM AUTHOR]