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Abstract In northern regions, river ice‐ jam flooding can be more severe than open‐water flooding causing property and infrastructure damages, loss of human life and adverse impacts on aquatic ecosystems. Very little has been performed to assess the risk induced by ice‐related floods because most risk assessments are limited to open‐water floods. The specific objective of this study is to incorporate ice‐jam numerical modelling tools (e.g. RIVICE, Monte‐Carlo simulation) into flood hazard and risk assessment along the Peace River at the Town of Peace River (TPR) in Alberta, Canada. Adequate historical data for different ice‐jam and open‐water flooding events were available for this study site and were useful in developing ice‐affected stage‐frequency curves. These curves were then applied to calibrate a numerical hydraulic model, which simulated different ice jams and flood scenarios along the Peace River at the TPR. A Monte‐Carlo analysis was then carried out to acquire an ensemble of water level profiles to determine the 1 : 100‐year and 1 : 200‐year annual exceedance probability flood stages for the TPR. These flood stages were then used to map flood hazard and vulnerability of the TPR. Finally, the flood risk for a 200‐year return period was calculated to be an average of $32/m 2 /a ($/m 2 /a corresponds to a unit of annual expected damages or risk). Copyright © 2016 John Wiley & Sons, Ltd.

Gravel-bed rivers are disproportionately important to regional biodiversity, species interactions, connectivity, and conservation. , Gravel-bed river floodplains in mountain landscapes disproportionately concentrate diverse habitats, nutrient cycling, productivity of biota, and species interactions. Although stream ecologists know that river channel and floodplain habitats used by aquatic organisms are maintained by hydrologic regimes that mobilize gravel-bed sediments, terrestrial ecologists have largely been unaware of the importance of floodplain structures and processes to the life requirements of a wide variety of species. We provide insight into gravel-bed rivers as the ecological nexus of glaciated mountain landscapes. We show why gravel-bed river floodplains are the primary arena where interactions take place among aquatic, avian, and terrestrial species from microbes to grizzly bears and provide essential connectivity as corridors for movement for both aquatic and terrestrial species. Paradoxically, gravel-bed river floodplains are also disproportionately unprotected where human developments are concentrated. Structural modifications to floodplains such as roads, railways, and housing and hydrologic-altering hydroelectric or water storage dams have severe impacts to floodplain habitat diversity and productivity, restrict local and regional connectivity, and reduce the resilience of both aquatic and terrestrial species, including adaptation to climate change. To be effective, conservation efforts in glaciated mountain landscapes intended to benefit the widest variety of organisms need a paradigm shift that has gravel-bed rivers and their floodplains as the central focus and that prioritizes the maintenance or restoration of the intact structure and processes of these critically important systems throughout their length and breadth.

The West African monsoon intraseasonal variability has huge socio-economic impacts on local populations but understanding and predicting it still remains a challenge for the weather prediction and climate scientific community. This paper analyses an ensemble of simulations from six regional climate models (RCMs) taking part in the coordinated regional downscaling experiment, the ECMWF ERA-Interim reanalysis (ERAI) and three satellite-based and observationally-constrained daily precipitation datasets, to assess the performance of the RCMs with regard to the intraseasonal variability. A joint analysis of seasonal-mean precipitation and the total column water vapor (also called precipitable water—PW) suggests the existence of important links at different timescales between these two variables over the Sahel and highlights the relevance of using PW to follow the monsoon seasonal cycle. RCMs that fail to represent the seasonal-mean position and amplitude of the meridional gradient of PW show the largest discrepancies with respect to seasonal-mean observed precipitation. For both ERAI and RCMs, spectral decompositions of daily PW as well as rainfall show an overestimation of low-frequency activity (at timescales longer than 10 days) at the expense of the synoptic (timescales shorter than 10 days) activity. Consequently, the effects of the African Easterly Waves and the associated mesoscale convective systems are substantially underestimated, especially over continental regions. Finally, the study investigates the skill of the models with respect to hydro-climatic indices related to the occurrence, intensity and frequency of precipitation events at the intraseasonal scale. Although most of these indices are generally better reproduced with RCMs than reanalysis products, this study indicates that RCMs still need to be improved (especially with respect to their subgrid-scale parameterization schemes) to be able to reproduce the intraseasonal variance spectrum adequately.

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affected by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. These results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.

Abstract Recent flood events in Canada have led to speculation that changes in flood behaviour are occurring; these changes have often been attributed to climate change. This paper examines flood data for a collection of 132 gauging stations in Canada. All of these watersheds are part of the Canadian Reference Hydrometric Basin Network (RHBN), a group of gauging stations specifically assembled to assist in the identification of the impacts of climate change. The RHBN stations are considered to have good quality data and were screened to avoid the influences of regulation, diversions, or land use change. Daily flow data for each watershed are used to derive a peaks over threshold (POT) dataset. Several measures of flood behaviour are examined based on the POT data, which afford a more in‐depth analysis of flood behaviour than can be obtained using annual maxima data. Analysis is conducted for four time periods ranging from 50 to 80 years in duration; the latter period results in a much smaller number of watersheds that have data for the period. The changes in flood responses of the watersheds are summarized by grouping the watersheds by size (small, medium, and large) and also by hydrologic regime (nival, mixed, and pluvial). The results provide important insights into the nature of the changes that are occurring in flood regimes of Canadian rivers, which include more flood exceedances, reduced maximum flood exceedance magnitudes for snowmelt events, and earlier flood events. Copyright © 2016 John Wiley & Sons, Ltd.