The main objective of the present study is to propose a method for estimating an optimal temporal storm pattern for urban drainage design in southern Quebec (Canada) in the context of climate change. Following a systematic evaluation of the performance of eight popular design storm models for different typical urban basins, it was found that the Canadian Atmospheric Environment Service (AES) storm pattern and the Desbordes model (with a peak intensity duration of 30 min) were the most accurate for estimating runoff peak flows while the Watt model gave the best estimation of runoff volumes. Based on these analyses, an optimal storm pattern was derived for southern Quebec region. The proposed storm pattern was found to be the most suitable for urban drainage design in southern Quebec since it could provide accurate estimation of both runoff peak flow and volume. Finally, a spatial-temporal downscaling method, based on a combination of the spatial statistical downscaling SDSM technique and the temporal scaling General Extreme Value distribution, was used to assess the climate change impacts on the proposed optimal design storm pattern and the resulting runoff properties.

The potential modification of hydrodynamic factors such as waves is a source of concern for many coastal communities because of its potential impact on shoreline evolution. In the northern Atlantic, swell is created by storm winds that cross the Atlantic following west-east tracks. These tracks are shifted more southward or northward depending on the season and on recurring large scale atmospheric pressure anomalies, also called teleconnection patterns. This study investigates the trends of sea wave patterns in the Bay of Biscay and re lates their interannual variability to teleconnection patterns.

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A vehicle mobility estimator has been developed to produce decision aid maps for projecting civil or military forces on operational theatres. Based on the exploitation of classical geographical sources (e.g. digital elevation models, optical images, and vector databases) and thematic sources (e.g. climate, meteorological, pedological and land cover databases), the system computes speed maps for different kinds of vehicles moving both on‐road and off‐road. Such computations are realized through a ground‐vehicle interaction module that estimates the vehicle performance from experimental results, numerical simulations and empirical relationships. The system's architecture is built using a GIS interface that manages the data, the computation and the presentation layers. An operational version of this tool has been tested and validated on several operational theatres in France and in northern Africa. The results show good agreement between the predicted mobility performance of various vehicles and those observed on the field. A case study is presented to illustrate the mobility maps and demonstrate their relevance in the decision‐making chain depending on different climate contexts. A short application to itinerary optimization is presented as a promising future application.

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