As climate change intensifies extreme rainfall, traditional design storm methods based on stationary assumptions are increasingly inadequate, often leading to misdesigned drainage infrastructure. To address this and manage projection uncertainties, we developed RiskDRAIN, a web-based application designed for the risk-based adjustment of projected design storms. RiskDRAIN, which stands for Risk-based Design for Resilient Adaptation to Infrastructure Needs, integrates risk analysis with Canadian downscaled CMIP6 projections (CanDCS-M6). The framework incorporates Intensity-Duration-Frequency (IDF) curves derived from the IDF-CC tool, considering two projection techniques (Clausius-Clapeyron scaling and Equidistance Quantile Matching) with GEV and Gumbel distributions, covering a range of emission pathways (SSP2-4.5, SSP5-8.5) and future horizons. Through an interactive interface, users refine design storms by evaluating provincial and site-specific risks derived from hazard exposure and multi-dimensional vulnerability (socio-economic, transportation, and environmental). Validated through a highway drainage case study, RiskDRAIN empowers practitioners with a data-driven platform for cost-effective, climate-resilient infrastructure planning.

This study investigates the influence of climate on the International Roughness Index (IRI) of pavements with varying subgrade types using regression analysis and machine learning (ML) techniques. Pavement subgrade type, a critical geotechnical factor, significantly impacts pavement roughness and performance. Data from the Long-Term Pavement Performance (LTPP) program were analyzed, focusing on IRI values measured along the center lane (CLIRI) and the mean of the left and right wheel paths (MIRI). CLIRI was hypothesized to be primarily influenced by climate due to limited traffic exposure, while MIRI reflects combined effects of traffic and climate. Climate impacts were assessed using the Freezing Index (FI) and precipitation (PPT), while subgrade properties were characterized by the Plasticity Index (PI) and percent fines passing the No. 200 sieve (P200). Advanced ML algorithms, including XGBoost, CatBoost, Random Forest, and LightGBM, outperformed regression models in predicting IRI changes. Results indicate that FI and PPT have stronger correlations with CLIRI than MIRI, highlighting the more significant climatic impact on center lane roughness. Models tailored to subgrade types showed fine subgrade pavements were more accurately predicted and more climate-sensitive compared to coarse subgrades. Climate change analysis revealed that fine subgrade pavements may experience reduced roughness due to decreased FI, whereas coarse subgrades may see increased roughness from higher annual precipitation. These findings emphasize the need for subgrade-specific, climate-sensitive IRI models to enhance predictive accuracy and guide adaptive pavement management strategies, fostering resilient infrastructure under changing climatic conditions.

Throughout their service life, bridges are exposed to ambient actions and environmental influences such as wind, thermal, and snow loads. Bridge design for environmental actions is currently based on observed, historical climate data. However, the effects of climate change have put these guidelines into question due to the ongoing and projected change in climate conditions. Bridge engineers are adapting current guidelines and design provisions to incorporate climate change. The main challenges encountered in this endeavor are the nonavailability of future climate data in the required format and the ability of bridge engineers to access and use these data as needed. The focus of this study is to investigate the effect of climate change on thermal load. The objective is achieved through the development of a methodology that can be used to model future hourly climate data; these may be input as boundary conditions in a thermal finite-element model to determine the thermal load acting on a bridge. To demonstrate the methodology, future climate conditions are projected for two locations across Canada (Toronto and Whitehorse), whereas the resulting thermal loads acting on the bridge are determined during heat waves, cold waves, and periods of high daily temperature variation. The results show that climate change could lead to a significant increase in the magnitude of thermal loads on bridges. It is also shown that the effects of climate change on the thermal load vary significantly depending on the general circulation model used, the emission scenario, and the location.

The coefficient of thermal expansion (CTE) is typically assumed to be constant in RC bridge design. In fact, under freezing temperatures, the CTE of concrete exhibits hysteretic nonlinear response, which, however, is rarely considered in design and analysis. A review of the literature indicates that the temperature dependence of the CTE of concrete materials can induce significant length changes to the structural components, leading to cracking and delamination, significant internal stresses if restrained, and a gradual deterioration in cold regions that experience repeated frost events. Contrary to contraction under low temperatures, which is expected in isotropic elastic materials, the length change is expansive when the concrete material is saturated or partially saturated, the amount of expansion being a function of the w/c ratio of the paste and the aggregate characteristics. The experimental study presented in this paper aims to investigate and quantify the effect of freezing temperature on the thermal expansion of concrete, considering mixes with different compositions and degrees of saturation. Freezing-thawing cycles to temperatures of -40 degrees C are applied to test specimens of the various concrete materials in order to collect data regarding the resulting thermal strain. The effect of the number of consecutive freezing-thawing cycles on the accumulation of the resulting residual strain is also investigated. The test data illustrate the effect of the w/c ratio on expansion under freezing conditions, provided that the degree of saturation exceeds a critical limit in the range between 80% and 90%. It was also determined that aggregate size affects the thermal behavior of concrete under low temperatures, but the residual length change converges to a limiting value after repeated cycles of thermal loading, therefore, the residual strain increments decrease with the increase in number of freezing and thawing cycles.

This study explores the influence of spatial variability in soil strength and hydraulic parameters on slope stability under extreme rainfall conditions. A probabilistic framework is implemented to assess failure probability by integrating the Hydraulic Statistics-Random Limit Equilibrium Method (HS-RLEM) with finite element seepage analysis. The results reveal that variability in strength parameters is the primary factor controlling slope stability, while hydraulic variability plays a secondary role by influencing pore pressure distribution and suction recovery. The findings underscore the limitations of traditional deterministic methods in capturing transient hydrological effects and highlight the necessity of probabilistic approaches in landslide risk assessment. By accounting for spatially correlated soil properties, this study provides a more accurate representation of failure risk, contributing to improved slope stability evaluations and more effective geotechnical mitigation strategies for rainfall-induced landslides.

Previous studies have extensively applied the generalized consolidation theory, which incorporates a two-stress state variable framework, to predict the volumetric behavior of unsaturated expansive soils under varying mechanical stress and matric suction. A key requirement for this approach is a constitutive surface that links the soil void ratio to both net stress and matric suction. A large number of fitting parameters are typically needed to accurately fit a two-variable void ratio surface equation to laboratory test data. In this study, a single-stress state variable framework was adopted to describe the void ratio as a function of effective stress for unsaturated soils. The proposed approach was applied to fit void ratio–effective stress constitutive curves to laboratory test data for two different expansive clays. Additionally, a finite element model coupling variably saturated flow and stress–strain analysis was developed to simulate the volume change behavior of expansive clay subjected to moisture fluctuations. The model utilizes suction stress to compute the effective stress field and incorporates the dependency of soil modulus on volumetric water content based on the proposed void ratio–effective stress relationship. The developed numerical model was validated against a benchmark problem in which a layer of Regina expansive clay was subjected to a constant infiltration rate. The results demonstrate the effectiveness of the proposed model in simulating expansive soil deformations under varying moisture conditions over time.

Climate change is amplifying extreme precipitation events in many regions and imposes substantial challenges for the resilience of road drainage infrastructure. Conventional design storm methodologies, which rely on historical trends of rainfall data under a stationarity assumption, may not adequately account for future climate change and variability. This study introduces a risk-based framework for determining climate-informed design storms tailored to road drainage systems. The proposed framework integrates climate model projections with risk assessment to quantify the potential impacts of future extreme rainfall on drainage performance and adjust the future design storm, with a focus on the province of Ontario, Canada. Projected precipitation changes for mid- and late-century time horizons are quantified using statistically downscaled CMIP6 General Circulation Models (GCMs). The risk level is defined as a function of hazard and vulnerability, where hazard combines both physiographic and meteorological factors. Vulnerability is composed of socioeconomic, transportation, and environmental considerations. To systematically integrate these components, a weighting scheme is developed based on a sensitivity analysis of the criteria, which provides flexibility in assigning relative importance to each factor. The estimated risk level is then applied to adjust projected design storm accordingly. The proposed workflow is demonstrated through both province-wide and site-specific applications across Ontario's road network to better highlight its scalability and adaptability. The findings signify the necessity of shifting from static, stationarity-based design methodologies to dynamic, risk-informed approaches that enhance the long-term resilience of transportation networks.

Temperature fluctuations within a bridge deck during a cold wave event can cause severe continuity stresses in structures where movement is restrained. Thermal loads are accounted for using thermal gradients that vary depending on bridge location and cross-sectional geometry. However, the effect of temperature change on material properties, particularly on the coefficient of thermal expansion (CTE) is rarely accounted for in the analysis and design. A review of the literature indicates that the CTE of concrete materials can vary significantly with changes in temperature, especially under freezing conditions, whereas saturated or partly saturated concrete exhibits nonlinear expansion at temperatures below freezing, resulting from effective reversal of the CTE sign. This effect has not been considered in the literature, when investigating thermal actions on bridge decks in cold temperatures. The aim of this study is to analyze, using an advanced nonlinear F.E. platform, the structural response of a prestressed concrete box bridge structure subjected to cold wave events, when considering the effect of temperature on the nonlinearity, the magnitude and the sign of the CTE of concrete. Meteorological data from three historical cold events of different intensity is input in the thermal models to simulate the temperature distribution in the bridge deck; the estimated temperature field was then used in a structural model to determine the resulting thermal stresses. The temperature-dependence and nonlinearity of the CTE is modeled after calibration of the mathematical relationships against published data. The results indicate that this behavior has a significant influence on structural response, highlighting the need for pertinent consideration of its effect in the relevant sections of the bridge codes.

Global climate change is expected to alter climate patterns this century, significantly affecting soil behavior through soil-atmosphere interactions. This study employs numerical simulations to examine the impact of climate change on the deformation of Regina clay in Regina, Canada. A key innovation is the development of a coupled hydro-mechanical model that integrates a soil-atmosphere boundary to simulate moisture dynamics using a single stress state framework for unsaturated soils. This approach simplifies analysis by incorporating suction stress and aligns with classical soil mechanics principles, enhancing model accuracy and predictability. Climate projections from the latest CMIP6 data were utilized, incorporating 26 general circulation models (GCMs) and three shared socioeconomic pathways (SSPs). By using climate data from multiple GCMs and SSPs, the study captures a wide range of potential outcomes, increasing the reliability of predictions. A novel structured approach was applied to select critical future climate scenarios, enabling a comprehensive analysis of soil deformation under historical and future climatic conditions. Results indicate a shift from historical shrinkage behavior to swelling dominance in expansive soils, with the maximum yearly ground movement projected to be 59 mm in 2063, surpassing the historical peak of 44 mm in 1998. Ground movement (heave) is anticipated to exceed historical levels by more than 20

Low-Impact Developments (LIDs), like green roofs and bioretention cells, are vital for managing stormwater and reducing pollution. Amidst climate change, assessing both current and future LID systems is crucial. This study utilizes variably saturated flow modeling with the HYDRUS software (version 4.17) to analyze ten locations in Ontario, Canada, focusing on Toronto. Historical and projected climate data are used in flow modeling to assess long-term impacts. Future predicted storms, representing extreme precipitation events, derived from a regional climate model, were also used in the flow modeling. This enabled a comprehensive evaluation of LID performance under an evolving climate. A robust methodology is developed to analyze LID designs, exploring parameters like water inflow volumes, peak intensity, time delays, runoff dynamics, and ponding patterns. The findings indicate potential declines in LID performance attributed to rising water volumes, resulting in notable changes in infiltration for green roofs (100%) and bioretention facilities (50%) compared to historical conditions. Future climate predicted storms indicate reduced peak reductions and shorter time delays for green roofs, posing risks of flooding and erosion. Anticipated extreme precipitation is projected to increase ponding depths in bioretention facilities, resulting in untreated stormwater overflow and prolonged ponding times exceeding baseline conditions by up to 13 h at numerous Ontario locations.

Recently, numerous studies have highlighted that the climate worldwide is changing rapidly due to increased greenhouse gas (GHG) emissions. The average ambient temperatures across Canada are rising approximately twice as fast as the rest of the world. The projected change in climate may increase the air and surface temperature indices, thus affecting the duration of spring load restrictions (SLRs) on roads, which may potentially impact the trucking industry and economy. Therefore, the best practices must be adjusted when identifying the optimal SLR periods that consider climate change. In Ontario, Canada, the SLR periods are imposed based on subsurface temperature data that is obtained from the road weather information system (RWIS) and spring load adjustment (SLA) stations in conjunction with visual observations. In this study, different methods of determining SLR periods were investigated. Then, new models were developed to correlate the surface cumulative thawing index (CTI) and thawing depth (TD) of a site. These models were developed utilizing atmospheric, surface, and subsurface data that was collected from different SLA and RWIS weather stations at various locations across Ontario, Canada. Finally, the developed models were utilized to predict the SLR periods for future scenarios using data from different global circulation models (GCM) and representative concentration pathways (RCPs). This study concludes that the SLR periods are expected to shrink across Ontario, Canada, by 2100. The results of this study might help different road authorities and trucking agencies maximize the life of the road structure and minimize the economic hardships that are faced during SLR periods.

Bridge codes tend to provide general guidance on the thermal gradients acting on bridge decks based on data from historical extreme events that have occurred within a country, without considering the location of the bridge itself. However, the thermal gradient is a function of the climate conditions that occur locally, in the vicinity of the bridge. Thus, a significant number of bridge decks are designed for climate conditions that might not be representative of their locations. The aim of this research is to optimize current guidelines to ensure that thermal gradients are derived based on bridge location. This objective is achieved through the investigation of the relationship that occurs between climate parameters and the resulting thermal extremes. An advanced finite-element platform was used to model the thermal performance of a concrete box girder. Several sets of meteorological data from 18 locations across Canada (representative of different Canadian climate types) were used as input in the thermal models to simulate the temperature distribution within the bridge deck. Upon analysis of the results, it was determined that a correlation exists between the direct normal irradiance (DNI) at a certain location and the resulting thermal differential that occurs between the top and the interior of the cross section. Four categories were defined, with each category representing a range of DNI values and a resulting range of thermal differentials between the top and the interior. To demonstrate the applicability of the established relationship, a case study was performed in which the maximum limit provided by the Canadian Highway Bridge Design Code was investigated across several provinces in Canada.

To counter the impacts of climate change and urbanization, engineers have developed ingenious solutions to reduce flooding and capture stormwater contaminants through the use of Low Impact Developments (LIDs). The soil is generally considered to be completely saturated when designing for the LIDs. However, this may not always be an accurate or realistic approach, as the soil could be variably unsaturated leading to inaccurate designs. To analyse the flow under variably unsaturated conditions, Richards’ equation can be used. To solve the Richards’ equation, two nonlinear hydraulic properties, namely soil water characteristic curve (SWCC) and the unsaturated hydraulic conductivity function are required. Laboratory and field measurements of unsaturated hydraulic properties are cumbersome, expensive and time- consuming. Pedotransfer functions (PTFs) estimate soil hydraulic properties using routinely measured soil properties. This paper presents a comparison between the direct measurement obtained through experimental procedures and the use of PTFs to estimate soil hydraulic properties for two green roof and three bioretention soil medias. Comparison between the measured and estimated soil hydraulic properties was accomplished using two different approaches. Statistical analyses and visual comparisons were used to compare the measured and estimated soil hydraulic properties. Additionally, numerical modelling to predict the water balance at the ground surface was conducted using the measured and estimated soil hydraulic properties. In some instances, the use of predicted hydraulic properties resulted in overestimation of the cumulative net infiltration of as much as 60 % for the green roof substrate, but was considered negligible for the bioretention substrate. Design performance criteria for green roof and bioretention facilities were examined using the measured and estimated soil hydraulic properties under extreme precipitation analysis. Results indicate that there is a high level of uncertainty when using PTFs for LID materials. A percent difference between the measured and predicted properties for the green roof peak time delay under a 2-year storm can be as much as 300%. For the bioretention design criteria of a 25-year storm, the surface runoff was overestimated by 14.7 cm and by 100% for the ponding time percent difference.

Surfactants (i.e., solutes that reduce the surface tension of water) exist in the subsurface either naturally or are introduced to the subsurface due to anthropogenic activities (e.g., agricultural purposes, environmental remediation strategies). Surfactant-induced changes in surface tension, contact angle, density, and viscosity alter the water retention and conduction properties of the vadose zone. This research numerically investigates the effects of surfactants in the vadose zone by comparing the flow and transport of three different surfactant solutions, namely butanol, ethanol, and Triton X-100. For each surfactant case, surfactant-specific concentration-dependent surface tension, contact angle, density, and viscosity relationships were incorporated by modifying a finite element unsaturated flow and transport code. The modified code was used to simulate surfactant infiltration in the vadose zone at residual state under intermittent boundary conditions. The modelling results show that all three surfactant solutions led to unique and noteworthy differences in comparison to the infiltration of pure water containing a conservative tracer. Results indicate that surfactant infiltrations led to complex patterns with reduced vertical movement and enhanced horizontal spreading, which are a function of concentration-dependent surface tension, density, contact angle, viscosity and sorption characteristics. The findings of this research will help understanding the effects of surfactant presence in the subsurface on unsaturated flow and its possible links to future environmental problems.

The climate across the world and especially across Canada is becoming warmer. Recent research suggests that, on average, past and projected warming in Canada are about twice those of global values. As part of the Superpave Mix design system, Performance Grade (PG) of the asphalt binder is selected based on historical climatic conditions in relation to the expected in-service temperature spectrum of the pavement surface. Given the effects of climate change, it is important to ascertain how projected ambient conditions may impact pavement surface temperatures and therefore the suitable PG towards more durable and resilient pavement construction in the future. In this study, new regression models, to predict pavement surface temperatures, were developed using air temperatures and latitude of a site. These models were developed to determine the relationships between asphalt pavement surface temperature and ambient weather data from weather stations within the Ontario Ministry of Transportation's Road Weather Information System (RWIS). The developed models were used to predict the pavement temperatures for future climate data from different Global Circulation Models (GCMs) and Representative Concentration Pathways (RCPs), and the results were compared with that of latest Long-Term Pavement Performance (LTPP) models. According to the results of this study, based on the scale of the expected warming, changes in the asphalt binder grades across Ontario are expected in the future. The results of this study also suggest that different types of PGs including 52–34, 58–28, 64–28and 70–22 may need to be adopted by the end-century. This study provides practical recommendations that road authorities and planners may use to adapt paving materials to changing temperature conditions.

Abstract As the frequency of thermal extremes gradually increases owing to climate change, the role of thermal loads on bridge performance increasingly becomes a concern. The purpose of this study is to investigate the suitability of AASHTO Bridge Design Specifications in quantifying with confidence the design thermal gradients that account for cold wave events. An advanced finite element platform was used to model the thermal performance of a prestressed concrete box girder and to analyse the thermal gradients that occur during cold wave events. Meteorological data on four historical cold wave events in Ontario, Canada, were used as input in the thermal models to simulate the temperature distribution within the bridge deck. The temperature–time history distributions obtained were then used as boundary conditions in a structural finite element model to simulate the structural response. The thermal results indicate that the AASHTO recommended gradients failed to capture the true thermal load distribution within the superstructure, which led to an underestimation of the resulting structural implications.

Surface-active solutes that exist in the subsurface either naturally (humic acid) or as a result of anthropogenic activities (alcohols, surfactants, PFAS) alter the hydraulic and geotechnical properties of the unsaturated porous media. The alteration of properties is the result of concentration-dependent surface tension, and/or density, and the contact angle effects. These effects are manifested in the form of changes in water retention and conduction and changes in the suction component of the shear strength. Differences in the spatial distribution of these solutes in the subsurface result in capillary pressure gradients causing flow perturbations. Conceptual and numerical models to understand the effects of these solutes require concentration-dependent consideration of surface tension, density, and the contact angle effects on hydraulic and geotechnical properties of porous media. Capillary rise experiments have been carried out to either quantify the effect of surface-active solutes on the height of capillary rise or to determine the concentration-dependent contact angle changes due to salinity of the pore water. This paper provides a comprehensive review of the literature on capillary rise experiments and how they can potentially be used to characterize the hydraulic and geotechnical properties of unsaturated porous media affected by surface-active solutes.

Location-specific climate datasets are required for the design and evaluation of a number of civil engineering projects. It requires huge effort to compile a multi-year quality-controlled climate dataset. In this paper, a method of generating simulated daily climate variables of interest from readily available climate normal using the general-purpose weather generator SIMETAW is presented. The accuracy of this method is assessed by comparing the climate datasets generated using SIMETAW with the recorded historical climate datasets for nine different sites across Canada with climates ranging from semi-arid to pre-humid. This comparison was done using visual presentations as well as statistical analyses of the two datasets. It was found that the multi-year daily climate datasets generated by SIMETAW using just 12 monthly climate normal values are fairly similar to the recorded historical climate datasets. The usefulness of SIMETAW-generated climate datasets was demonstrated by using them in numerical simulations of three different design problems, namely, infiltration into soils, swelling potential of an expansive soil, and soil cover design. From the results of these numerical simulations, it is concluded that the SIMETAW-generated multi-year daily climate datasets are satisfactory for use in the geotechnical and geoenvironmental problems of the kind simulated herein.

The climate in Canada has warmed and will continue to warm faster in the future, which will result in more intense and frequent temperature variations. Asphalt binder selection based on the Superpave performance grade (PG) system relies on historic climatic conditions in relation to the expected in-service temperature range of the flexible pavement. In view of climate change, it is crucial to investigate the extent to which pavement surface temperatures will be affected by ambient conditions of the future in order to assess the relative impact on the appropriate PG for more durable and resilient pavement construction. In this study, the latest long-term pavement performance (LTPP) model was used to determine the asphalt pavement surface temperatures. For different representative concentration pathways (RCP), the relative impact of climate change on pavement temperature extremes and thereby appropriate PG to meet projected pavement temperatures was assessed using the LTPP models. The results of this study indicate that in the future, climate variations will cause changes to asphalt binder grades across the examined locations in Ontario, which depend on the severity of the projected warming. This research offers useful suggestions that can be incorporated by the road agencies and designers towards adaptation of pavement construction materials suitable to the changing climate.

The purpose of this study is to investigate the impact of climate change on the thermal and structural response of concrete box girders. An advanced finite element platform was used to model a concrete box girder and analyze the additional thermal stresses that result from climate change. Meteorological data for future climate scenarios in Toronto, Canada was used as input in a thermal model to simulate the temperature distribution within the bridge deck. The temperature distribution was then used as input in a structural model of the bridge, to determine the resulting thermal stresses. The results show increases in tensile and compressive stresses as well as increased bridge movements. This study highlights the importance of explicitly considering climate change to achieve more robust bridge codes, particularly when it comes to thermal effects.