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An objective analysis is one of the main components of data assimilation. By combining observations with the output of a predictive model we combine the best features of each source of information: the complete spatial and temporal coverage provided by models, with a close representation of the truth provided by observations. The process of combining observations with a model output is called an analysis. To produce an analysis requires the knowledge of observation and model errors, as well as its spatial correlation. This paper is devoted to the development of methods of estimation of these error variances and the characteristic length-scale of the model error correlation for its operational use in the Canadian objective analysis system. We first argue in favor of using compact support correlation functions, and then introduce three estimation methods: the Hollingsworth–Lönnberg (HL) method in local and global form, the maximum likelihood method (ML), and thediagnostic method. We perform one-dimensional (1D) simulation studies where the error variance and true correlation length are known, and perform an estimation of both error variances and correlation length where both are non-uniform. We show that a local version of the HL method can capture accurately the error variances and correlation length at each observation site, provided that spatial variability is not too strong. However, the operational objective analysis requires only a single and globally valid correlation length. We examine whether any statistics of the local HL correlation lengths could be a useful estimate, or whether other global estimation methods such as by the global HL, ML, orshould be used. We found in both 1D simulation and using real data that the ML method is able to capture physically significant aspects of the correlation length, while most other estimates give unphysical and larger length-scale values. Implications: This paper describes a proposed improvement of the objective analysis of surface pollutants at Environment and Climate Change Canada (formerly known as Environment Canada). Objective analyses are essentially surface maps of air pollutants that are obtained by combining observations with an air quality model output, and are thought to provide a complete and more accurate representation of the air quality. The highlight of this study is an analysis of methods to estimate the model (or background) error correlation length-scale. The error statistics are an important and critical component to the analysis scheme. [ABSTRACT FROM PUBLISHER]

The paper proceeds with a discussion of the interplay of scale and intensity in determining greenhouse gas emissions. This is followed by the presentation of several macroeconomic scenarios using LowGrow, a simulation model of the Canadian economy. The scenarios considered are ‘business as usual’ which is a projection into the future of past trends, ‘selective growth’ in which differential growth rates are applied to parts of the economy according to their direct and indirect greenhouse gas emissions, and ‘degrowth’ where the average GDP/capita of Canadians is reduced towards a level more consistent with a world economy the size of which respects global environmental limits. The paper ends with a comparison of the scenarios. [Copyright &y& Elsevier]

Abstract: In Part 1 of this paper, a carbonation model was developed and experimentally verified which was able to forecast carbonation depth of a concrete specimen considering varying ambient temperature, humidity and CO2 concentrations. Part 2 of the paper applies the carbonation diffusion/reaction model developed in Part 1 to predict the effects of global climate change on the carbonation of concrete. Climate scenarios were formulated and combined with the model for two major Canadian cities, Toronto and Vancouver. Results show that for undamaged and unstressed concrete, climate change will significantly affect carbonation progress. The model showed that for unloaded, non-pozzolanic concrete, ultimate carbonation depths in Toronto and Vancouver could be up to 45% higher. For in-service structures under load, the rates of deterioration are likely to be even faster. This is a cause for concern, and much further effort must be devoted to fully understand these phenomena. [Copyright &y& Elsevier]

Abstract: Recent advancements in computing and geographic information systems (GIS) have revolutionized the development of planning support systems (PSSs) to study and simulate the future of travel demand in urban areas. While travel demand models have been widely developed and used to inform the urban planning process, very little has been done to explicitly account for demographic changes and the ageing of population within such models. The work in this paper bridges this gap by describing the development and application of IMPACT (integrated model for population ageing consequences on transportation), a GIS-based PSS capable of assessing the ramifications of demographic changes, including population ageing, on the performance and usage of urban transportation systems. Unlike existing operational PSSs, IMPACT possesses unique and novel features that enable it to model demographic changes and urban travel demand for various age cohorts. Through the simulation of scenarios for varying fertility rates, the paper explores and quantifies the impacts of ageing and population age-structure changes on travel patterns in the census metropolitan area (CMA) of Hamilton in Ontario, Canada. The analysis suggests a consistent increase in the number of trips and mobility levels of elderly drivers, as a result of population ageing over time. Furthermore, increases in fertility rates could significantly impact the usage and performance of the transportation system for certain periods of the day, by the year 2031. Results such as these are important to consider when planning the future of cities. The findings in this paper provide new insights into the future of urban travel in the Canadian context. [Copyright &y& Elsevier]

For more than a century, planted shelterbelts in Saskatchewan, Canada have protected farmyards from the elements, decreased soil erosion, sequestered atmospheric carbon, as well as provided many other ecological functions. It is estimated that there are >60,000 km of planted shelterbelts throughout the province, and considerably more in all of the Canadian Prairies. This paper details the overall process of quantifying and mapping the carbon stocks in white spruce ( Picea glauca ) shelterbelts planted in Saskatchewan. Shelterbelt data collected from field sampling sites, which were identified by a unique site selection approach, were used to parameterize two models for use in shelterbelt systems; an independent data set was used to validate model predictions. Shelterbelt tree growth was modeled with the Physiological Principles in Predicting Growth (3PG) model, and carbon flux and stocks in shelterbelts were modeled with the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3). Annual total ecosystem carbon (TEC) flux in white spruce shelterbelts increased one order of magnitude, from −0.33 to 4.4 Mg C km −1 yr −1 , for age 1–25 years, and reached a peak of 5.5 Mg C km −1 yr −1 (age 39 years). An initial soil carbon loss from the shelterbelt, caused by the land-use change, was offset in full by tree growth by age 17, 18, and 21 years for trees planted at 2.0, 3.5, and 5.0 m spacing within a row, respectively. Increase in carbon stocks, after 60 years of growth, was predicted in the litter layer (21.8 Mg C km −1 ), belowground biomass (26.1 Mg C km −1 ), and aboveground biomass (117.6 Mg C km −1 ). Across all the different provincial soils, carbon additions were 106–195 Mg C km −1 in 60-yr-old white spruce shelterbelts. Cumulatively, accounting for eight decades of white spruce shelterbelt planting and tree growth, carbon additions totaled 50,440 Mg C province-wide in 991 km of white spruce shelterbelts. The C additions represented 38% of the province-wide TEC stocks, which totaled 131,750 Mg C. The cumulative carbon storage in all components of planted white spruce shelterbelts far exceeded the initial carbon levels present at the time of shelterbelt planting. [ABSTRACT FROM AUTHOR]

The Canadian Space Agency (CSA), through its Analogue Missions program, supported a microrover-based analogue mission designed to simulate a Mars rover mission geared toward identifying and characterizing methane emissions on Mars. The analogue mission included two, progressively more complex, deployments in open-pit asbestos mines where methane can be generated from the weathering of olivine into serpentine: the Jeffrey mine deployment (June 2011) and the Norbestos mine deployment (June 2012). At the Jeffrey Mine, testing was conducted over 4 days using a modified off-the-shelf Pioneer rover and scientific instruments including Raman spectrometer, Picarro methane detector, hyperspectral point spectrometer and electromagnetic induction sounder for testing rock and gas samples. At the Norbestos Mine, we used the research Kapvik microrover which features enhanced autonomous navigation capabilities and a wider array of scientific instruments. This paper describes the rover operations in terms of planning, deployment, communication and equipment setup, rover path parameters and instrument performance. Overall, the deployments suggest that a search strategy of “follow the methane” is not practical given the mechanisms of methane dispersion. Rather, identification of features related to methane sources based on image tone/color and texture from panoramic imagery is more profitable. [ABSTRACT FROM AUTHOR]

The first objective of this paper is to demonstrate how mathematical models simulating the structural state of sewer pipes can help to assess the financial resources required for the preservation of sewer networks. The second objective is to assess and compare the annual replacement rate that should be applied to four different Canadian sewer networks to stabilize their global structural state for the long term. The required annual replacement rates are similar for the four studied networks, even if their global structural states were different prior to replacement. Results also show that the required annual replacement rate is three times less if the deterioration states of all pipes in the network are known, as opposed to the case where the structural states are unknown. This demonstrates the importance of sewer pipe inspection for the planning of sewer pipe renewal. [ABSTRACT FROM AUTHOR]

Abstract: Municipal wastewater treatment plants (WWTPs) dispose of numerous trace organic contaminants in the receiving waters that can impact biological function in aquatic organisms. However, the complex nature of WWTP effluent mixtures and a wide variety of potential mechanisms that can alter physiological and reproductive development of aquatic organisms make it difficult to assess the linkages and severity of the effects associated with trace organic contaminants. This paper describes a surface water quality modeling exercise that was performed to understand the relevant contaminant fate and transport processes necessary to accurately predict the concentrations of trace organic compounds present in the aquatic environment. The target compounds modeled include a known antiandrogenic personal care product (triclosan) and selected pharmaceuticals (venlafaxine, naproxen, and carbamazepine). The WASP 7.5 model was adapted and calibrated to reflect approximately ten kilometers of reach of the Grand River watershed that is highly influenced by a major urban WWTP. Simulation of the fate and transport of the target compounds revealed that flow-driven transport processes (advection and dispersion) greatly influenced the behavior of the target contaminants in the aquatic environment. However, fate mechanisms such as photolysis and biodegradation can play an important role in the attenuation of some compounds. The exception was carbamazepine where it was shown to act as a conservative tracer compound for wastewater specific contaminants in the water phase. The calibrated water quality model can now be employed in a number of future applications. Prediction of fate and transport of other trace organic contaminants across the watershed and assessment of the performance of WWTP infrastructure upgrades in the removal of these compounds are just a few examples. [Copyright &y& Elsevier]

Abstract: Image composites are often used for earth surface phenomena studies at regional or national level. The compromise between residual clouds and the length of compositing period is a necessary corollary to the choice of satellite optical data for monitoring earth surface phenomena dynamics. This paper introduced a methodology for estimating availability of cloud-free image composites for optical sensors with various revisiting intervals, using MODIS MOD06 L2 cloud fraction product in the period of 2000–2008. The methodology starts with downscaling of the cloud fraction product to 1km×1km cloud cover binary images. The binary images are then used for the exploration of spatial and temporal characteristics of cloud dynamics, and subsequently for the simulation of cloud-free composite availability with various revisiting intervals of optical sensors. Using Canada''s southern provinces as an application case, the study explored several factors important for the design of environmental monitoring system using optical sensors of earth observation, in particular, cloud dynamics and its inter-annual variability, sensors’ revisiting intervals, and cloud-free threshold for targeting composites. While the cloud images used in the analysis are at 1km×1km resolution, our analysis suggests that the simulated availabilities of cloud-free image composites may also provide reasonable estimates for optical sensors with higher than 1km×1km resolution, though the closer to 1km×1km resolution the optical sensor, the more pertinent the application. Also, the methodology can be parameterised to different temporal period and different spatial region, depending on applications. [Copyright &y& Elsevier]

In this paper, an integrated simulation—optimization approach is proposed for annual planning of power restoration workforce related to an electricity distribution company in a province of Canada. Internal and external workforces are employed to perform maintenance actions and restore power after interruptions throughout the province. According to the electricity distribution network, the province is divided into a number of work locations (WL), each having local crews to perform maintenance actions and fix power interruptions. However, determining the size of the crew in each WL over the year is challenging because of high fluctuation in interruption frequency and consequently in projected demand during the year. The frequency of interruptions is affected by various factors such as geographical location, time calendar, and particularly weather conditions. The objective is to determine the optimal combination of internal and external workforce over the year to cover the interruptions across the province with minimum cost and minimum customer interruption duration. [ABSTRACT FROM PUBLISHER]

Abstract: We describe a decision support system that has been developed to inform management and planning in a portion of the St. Lawrence Estuary in Canada (covering the Saguenay-St. Lawrence Marine Park and the proposed St. Lawrence Estuary Marine Protected Area). The system is composed of a spatiotemporal, georeferenced database, a simulator (3MTSim) that reproduces the spatiotemporal movement of marine mammals and maritime traffic in the estuary, and data post-processing tools that can be used to analyse the output of 3MTSim. 3MTSim allows users to test different management scenarios for maritime traffic (e.g., area closures, speed limits, regulations concerning the observation of marine mammals) in order to assess their effects on navigational patterns which may influence marine mammal exposure to vessels. 3MTSim includes an individual-based model of marine mammal movement patterns that has been elaborated based on existing telemetry data on fin, blue, and beluga whales as well as on land-based theodolite tracking of humpback and minke whales. Observations recorded aboard research and whale-watching vessels have provided the spatial data necessary to estimate species’ abundances and distribution maps that are used to initialise the whale model. Different types of vessels, including cargo ships and commercial whale-watching boats are also modelled individually, using an agent-based approach. The boat model represents the decision-making process of boat captains as a function of environmental conditions, the contextual setting, and their respective goals. An extensive database of real-time tracking data available for the different types of vessels, coupled with observations and interviews, has served in the elaboration of the boat model. In this paper, an overview of the entire system is presented and its effectiveness as a decision support tool is demonstrated via the results from a sample of scenario-based simulations. [Copyright &y& Elsevier]

Abstract: To interpret the snowpack evolution, and in particular to estimate snow water equivalent (SWE), passive microwave remote sensing has proved to be a useful tool given its sensitivity to snow properties. However, the main uncertainties using existing SWE algorithms arise from snow metamorphism which evolves during the winter season, and changes the snow emissivity. To consider the evolution in snow emissivity a coupled snow evolution–emission model can be used to simulate the brightness temperature (TB) of the snowpack. During a dedicated campaign in the winter season, from November to April, of 2007–2008 two surface-based radiometers operating at 19GHz and 37GHz continuously measured the passive microwave radiation emitted through a seasonal snowpack in southern Quebec (Canada). This paper aims at modeling and interpreting this time series of TB over the whole season, with an hourly step, using a coupled multi-layer snow evolution–emission model. The thermodynamic snow evolution model, referred as to Crocus, was driven by local meteorological measurements. Results from this model provided, in turn, the input variables to run the Microwave Emission Model of Layered Snowpacks (MEMLS) in order to predict TB at 19GHz and 37GHz for both vertical (V) and horizontal (H) polarizations. The accuracy of TB predicted by the Crocus–MEMLS coupled model was evaluated using continuous measurements from the surface-based radiometers. The weather conditions observed during the winter season were diverse, including several warm periods with melting snow and rain-on-snow events, producing very complex variations in the time series of TB. To aid our analysis, we identified days with melting snow versus days with dry snow. The Crocus–MEMLS coupled model was able to accurately predict melt events with a success rate of 86%. The residual error was due to an overestimation of the duration of several melt events simulated by Crocus. This problem was explained by 1) a limitation of percolation, and 2) a very long-acting melt of lower layers due to geothermal flux. When the snowpack was completely dry, the global trend of TB during the season was characterized by a decrease of TB due to growth in the snow grain size. During most of the season, Crocus–MEMLS correctly predicted the evolution of TB resulting from temperature gradient metamorphism; the root mean square errors ranged between 2.8K for the 19GHz vertical polarization (19V) and 6.9K for the 37GHz horizontal polarization (37H). However, during dry periods near the end of the season, the values of TB were strongly overestimated. This overestimation was mainly due to a limitation of the growth of large snow grains in the wet snowpack simulated by Crocus. This effect was confirmed by estimating snow grain sizes from the observed TB and the coupled model. The estimated snow grain sizes were larger and more realistic than those initially predicted by the Crocus model. [Copyright &y& Elsevier]

Abstract: CANDU-SCWR (Supercritical Water-Cooled Reactor) is one type of Generation IV reactors being developed in Canada. Its dynamic characteristics are different from existing CANDU reactors due to the supercritical conditions of the coolant. To study the behaviours of such reactors under disturbances and to design adequate control systems, it is essential to have an accurate dynamic model to describe such a reactor. One dynamic model is developed for CANDU-SCWR in this paper. In the model construction process, three regions have been considered: Liquid Region I, Liquid Region II and Vapour Region, depending on bulk and wall temperatures being higher or lower the pseudo-critical temperature. A moving boundary method is used to describe the movement of boundaries across these regions. Some benefits of adopting moving boundary method are illustrated by comparing with the fixed boundary method. The results of the steady-state simulation based on the developed model agree well with the design parameters. The transient simulations demonstrate that the model can predict the dynamic behaviours of CANDU-SCWR. Furthermore, to investigate the responses of the reactor to small amplitude perturbations and to facilitate control system designs, a least-square based system identification technique is used to obtain a set of linear dynamic models around the design point. The responses based on the linear dynamic models are validated with simulation results from nonlinear CANDU-SCWR dynamic model. [Copyright &y& Elsevier]

Abstract: The algorithms designed to estimate snow water equivalent (SWE) using passive microwave measurements falter in lake-rich high-latitude environments due to the emission properties of ice covered lakes on low frequency measurements. Microwave emission models have been used to simulate brightness temperatures (Tbs) for snowpack characteristics in terrestrial environments but cannot be applied to snow on lakes because of the differing subsurface emissivities and scattering matrices present in ice. This paper examines the performance of a modified version of the Helsinki University of Technology (HUT) snow emission model that incorporates microwave emission from lake ice and sub-ice water. Inputs to the HUT model include measurements collected over brackish and freshwater lakes north of Inuvik, Northwest Territories, Canada in April 2008, consisting of snowpack (depth, density, and snow water equivalent) and lake ice (thickness and ice type). Coincident airborne radiometer measurements at a resolution of 80×100m were used as ground-truth to evaluate the simulations. The results indicate that subsurface media are simulated best when utilizing a modeled effective grain size and a 1mm RMS surface roughness at the ice/water interface compared to using measured grain size and a flat Fresnel reflective surface as input. Simulations at 37GHz (vertical polarization) produce the best results compared to airborne Tbs, with a Root Mean Square Error (RMSE) of 6.2K and 7.9K, as well as Mean Bias Errors (MBEs) of −8.4K and −8.8K for brackish and freshwater sites respectively. Freshwater simulations at 6.9 and 19GHz H exhibited low RMSE (10.53 and 6.15K respectively) and MBE (−5.37 and 8.36K respectively) but did not accurately simulate Tb variability (R=−0.15 and 0.01 respectively). Over brackish water, 6.9GHz simulations had poor agreement with airborne Tbs, while 19GHz V exhibited a low RMSE (6.15K), MBE (−4.52K) and improved relative agreement to airborne measurements (R=0.47). Salinity considerations reduced 6.9GHz errors substantially, with a drop in RMSE from 51.48K and 57.18K for H and V polarizations respectively, to 26.2K and 31.6K, although Tb variability was not well simulated. With best results at 37GHz, HUT simulations exhibit the potential to track Tb evolution, and therefore SWE through the winter season. [Copyright &y& Elsevier]

Abstract: In 1988, Dr. Kyoji Sassa proposed a geotechnical model [Sassa, K., 1988. Geotechnical model for the motion of landslides. In: Proceedings, 5th International Symposium on Landslides, vol. 1, pp. 37–56] to simulate landslide motion and to establish a theoretical framework for landslide simulation. In 2002, based on the experimental results of using a ring-shear apparatus for simulation of landslide motion, Wang and Sassa proposed a model for apparent friction coefficient change (which is a key parameter of landslide motion) that can be combined with Sassa’s original geotechnical model. As presented in the model for apparent friction coefficient change, a landslide is considered as a two-layer structure, i.e., a debris layer and a sliding zone. During landsliding, the thickness of the debris layer changes, while shear resistance changes in the sliding zone. In this paper, after a brief introduction of the two models, a parametric study is presented to show the differing importance of each parameter. Also included is a presentation of three case studies: The 1995 Fei Tsui Road landslide, and the 1995 Shum Wan landslide, both in Hong Kong, and the 1903 Frank slide in Alberta, Canada to show the advantage of combining the two models. [Copyright &y& Elsevier]

Abstract: This paper will discuss TRIPLEX-Flux, a process-based model that estimates net ecosystem production (NEP) as well as analyzing the level of sensitivity of the model''s response by simulating CO2 flux in an existing old black spruce BOREAS site in central Canada. The research objectives were: (1) to test the TRIPLEX-Flux model simulations against flux tower measurements; and (2) to examine parameter and input variable effects on model response via sensitivity analysis. Validation of NEP data at 30min intervals derived from tower and chamber measurements showed that the NEP data from the model corresponded well with the measured NEP from the BOREAS site (R 2 >0.65). Sensitivity analysis demonstrated different levels of sensitivity between morning and noon periods and from the current to doubled atmospheric CO2 concentrations. Additionally, the comparison of different algorithms to calculate stomatal conductance showed that the NEP predicted by the model using the iteration algorithm was consistent with the results using a constant C i/C a of 0.74 for current and 0.81 for doubled CO2 concentrations. Varying parameter and input variable values by ±10% resulted in a similar model response between morning and noon periods (less than or equal to 27.6% and 27.4%, respectively). Most parameters were more sensitive at noon than they were in the morning except for those that were correlated with air temperature, suggesting that air temperature has considerable influence over model sensitivity for these parameters/variables. Air temperature effect was greater under doubled than it was under current atmospheric CO2 concentrations. In contrast, model sensitivity to CO2 decreased under doubled CO2 concentrations. [Copyright &y& Elsevier]

An emerging environmental issue in Canada is how to quantify the contribution of agricultural soil emissions of ammonia (NH3) to environmental pollution. Emission inventories are essential to predict these emissions and their subsequent atmospheric transportation, transformation, and deposition. Due to the high spatial and temporal variability associated with NH3 emissions, emission inventories based on measurements become expensive and emission factors lose accuracy. Process-based models are capable of accounting for the complex soil interactions, but current models lack temporal refinement and few models consider NH3 emissions. This paper presents the development of a one-dimensional (vertical), time-dependent model capable of predicting NH3 emissions from a slurry applied to a bare soil. The model is based on chemical, physical and biological relationships that govern soil heat, moisture, and nitrogen movement. Processes considered include convection, diffusion, decomposition, nitrification, denitrification, and surface to atmosphere transport. The model is tested with experimental data from Agriculture and Agri-Food Canada which conducted NH3 measurements following application of dairy cattle slurry to a bare field. An investigation into the sensitivity of emissions to pH and slurry infiltration rate is conducted and model predictions are best fit to measurements based on this investigation. Testing demonstrated the model''s ability to predict the large NH3 emissions immediately following application and subsequent emission trends associated with diurnal patterns that emission factors cannot capture. Results showed that model performance could benefit from a more in depth measurement program and empirical or process models of surface pH. Potential exists for the model to become a useful tool in predicting emissions on local, regional, or national scales. [Copyright &y& Elsevier]

Abstract: A new technique for climate simulations and projections has emerged over the past 15 years that allows to reach unprecedented spatial resolution at an affordable computing cost: regional climate modelling. The technique has matured and several groups around the world are participating in model intercomparison projects and collaborating in coordinated endeavour to produce ensemble climate-change projections at regional scales. The paper describes the formulation of a specific regional climate model (RCM), the Canadian RCM, commenting on the formulation choices and experience gained during the development and validation process of this model. Current issues in regional climate modelling are also reviewed and discussed. [Copyright &y& Elsevier]

Abstract: A dome-covered house is an example of designing sustainable buildings by learning from the optimized biological forms from the nature. The paper presents a 3-D thermal and air flow (3D-TAF) model that estimates the energy needs of a dome-covered house. The model is verified with CFD simulations under the COMSOL Multiphysics environment, experimental measurements and simulation results from similar structures published by other researchers. The use of the dome is expected to reduce the annual heating load of the house by 62.6%, compared with that of an isolated house located in Montreal at latitude. [Copyright &y& Elsevier]

This paper uses a cultural model approach to interpret and analyse the impact of an interactive computer simulation tool (GB-Quest) on the possibility of fostering dialogue about sustainability in southwestern British Columbia, Canada. We define cultural models theory, compare cultural models to mental models and illustrate some basic features of cultural models. We then describe the research process in which participants engaged in conversation, guided and facilitated by GB-Quest, about sustainability. Findings suggest that the use of cultural models frameworks reinforces participants' understanding of sustainability. In reflecting on their prior models of sustainability, we argue that study participants can elucidate how cognitive conceptual resources reflect publicly shared knowledge (Turner, 2004). [ABSTRACT FROM AUTHOR]

Abstract: Quantification of the magnitude of net terrestrial carbon (C) uptake, and how it varies inter-annually, is an important question with future potential sequestration influenced by both increased atmospheric CO2 and changing climate. However the assessment of differences in measured and modeled C accumulation is a challenging task due to the significant fine scale variation occurring in terrestrial productivity due to soil, climate and vegetation characteristics as well as difficulties in measuring carbon accumulation over large spatial areas. The Moderate Resolution Imaging Spectroradiometer (MODIS) offers a means of monitoring gross primary production (GPP), both spatially and temporally, routinely from space. However it is critical to compare and contrast the temporal dynamics of the C and water fluxes with those measured from ground-based networks, or estimated using physiological models. In this paper, using a number of approaches, our objective is to determine if any systematic biases exists in either the MODIS, or the modeled estimates of fluxes, relative to the measurements made over an evergreen, needleleaf temperate rainforest on Vancouver Island, Canada. Results indicate that 8-day GPP as predicted with a simple physiological model (3PGS), forced using local meteorology and canopy characteristics, matched measured fluxes very well (r 2 =0.86, p <0.001) with no significant difference between eddy covariance (EC) and modeled GPP (p <0.001). In addition, modeled water supply closely matched measured relative available soil water content at the site. Using canopy characteristics from the MODIS fraction of photosynthetically active radiation (fPAR) algorithm, slightly reduced the correspondence of the predictions due to a large number of unsuccessful retrievals (83%) due to sun angle, snow and cloud. Predictions of GPP based on the MODIS GPP algorithm, forced using local meteorology and canopy characteristics, were also highly correlated with EC measurements (r 2 =0.89, p <0.001) however these estimates were biased under predicting GPP. Estimates of GPP based on the most recent MODIS reprocessing (collection 4.5) remained highly correlated (r 2 =0.88, p <0.001) yet were also the most biased with the estimates being 30% less than the EC-measured GPP. Most of the variance in GPP at the site was explained by the absorbed photosynthetically active radiation. We also compared the nighttime respiration as measured over 2 years at the site with the minimum 8-day MODIS land surface temperature and found a significant relationship (r 2 =0.57), similar to other studies. [Copyright &y& Elsevier]

Abstract: Evolutionary simulation-optimization (ESO) techniques can be adapted to model a wide variety of problem types in which system components are stochastic. Grey programming (GP) methods have been previously applied to numerous environmental planning problems containing uncertain information. In this paper, ESO is combined with GP for policy planning to create a hybrid solution approach named GESO. It can be shown that multiple policy alternatives meeting required system criteria, or modelling-to-generate-alternatives (MGA), can be quickly and efficiently created by applying GESO to this case data. The efficacy of GESO is illustrated using a municipal solid waste management case taken from the regional municipality of Hamilton-Wentworth in the Province of Ontario, Canada. The MGA capability of GESO is especially meaningful for large-scale real-world planning problems and the practicality of this procedure can easily be extended from MSW systems to many other planning applications containing significant sources of uncertainty. [Copyright &y& Elsevier]

Currently, a model (referred to as a monthly model) employing monthly temperature and precipitation data is used by the Canadian Wheat Board to estimate spring wheat yields for the Canadian Prairies. The model uses a cumulative moisture index as an explanatory variable. In this paper, the performance of the monthly model was improved by first developing a daily model by employing daily, instead of monthly, data for the 1975-1996 period and then by developing a hybrid model which incorporated into the daily model an additional variable derived from the National Oceanic and Atmospheric Administration (NOAA)/Advanced Very High Resolution Radiometer (AVHRR)-based composited Normalized Difference Vegetation Index (NDVI) data for the 1987-1996 period. Out of the seven variables derived, two variables - the average NDVI during the heading phenological-phase and the average NDVI during the entire growing season - were found to be the best. The start and the end of the heading phase were estimated using a biometeorological time scale model. The performance of models was tested on five crop districts (1b, 3bn, 4b, 6a, and 9a) of Saskatchewan on the basis of coefficient of determination, R[sup 2]. While using 1975-1996 data, the values for R[sup 2] were 0.43, 0.82, 0.73, 0.71 and 0.00 in the case of the daily model as opposed to 0.20, 0.71, 0.57, 0.58, and 0.00 in the case of the monthly model for districts 1b, 3bn, 4b, 6a, and 9a, respectively. While using 1987-1996 data, the values of R[sup 2] were 0.79, 0.96, 0.83, 0.95, and 0.39 in the case of the hybrid model as opposed to 0.13, 0.70, 0.75, 0.50, and 0.00 in the case of the monthly model for districts 1b, 3bn, 4b, 6a, and 9a, respectively. For district 9a, which experiences an adequate supply of soil moisture, the concept of cumulative soil moisture index was not found to hold well for yield estimation. [ABSTRACT FROM AUTHOR]

Background: As population health needs become more complex, addressing those needs increasingly requires the knowledge, skills, and judgment of multiple types of human resources for health (HRH) working interdependently. A growing emphasis on team-delivered health care is evident in several jurisdictions, including those in Canada. However, the most commonly used HRH planning models across Canada and other countries lack the capacity to plan for more than one type of HRH in an integrated manner. The purpose of this paper is to present a dynamic, multi-professional, needs-based simulation model to inform HRH planning and demonstrate the importance of two of its parameters-division of work and clinical focus-which have received comparatively little attention in HRH research to date.Methods: The model estimates HRH requirements by combining features of two previously published needs-based approaches to HRH planning-a dynamic approach designed to plan for a single type of HRH at a time and a multi-professional approach designed to compare HRH supply with requirements at a single point in time. The supplies of different types of HRH are estimated using a stock-and-flow approach.Results: The model makes explicit two planning parameters-the division of work across different types of HRH, and the degree of clinical focus among individual types of HRH-which have previously received little attention in the HRH literature. Examples of the impacts of these parameters on HRH planning scenarios are provided to illustrate how failure to account for them may over- or under-estimate the size of any gaps between the supply of and requirements for HRH.Conclusion: This paper presents a dynamic, multi-professional, needs-based simulation model which can be used to inform HRH planning in different contexts. To facilitate its application by readers, this includes the definition of each parameter and specification of the mathematical relationships between them. [ABSTRACT FROM AUTHOR]

The work of theorists such as Foucault and Baudrillard has posed a significant challenge to more conventional sociological frameworks for dealing with issues of state power and political economy. Yet empirical work on the state-political economy relationship in Canada has, so far, made little use of these theoretical insights. In contrast, the specific aim of this paper is to display the usefulness of Foucault's concern with surveillance and Baudrillard's concern with codification so as to better understand the constitutive features and the mundane practices of Canadian workers' compensation boards. [ABSTRACT FROM AUTHOR]

• A Multi-Dimensional Hypothetical Fuzzy Risk Simulation model is developed. • Decision-makers' preference is reflected to develop the optimized policies. • Multi-dimensional risks in 2030 of various policy options are revealed. • A special case study of the Province of Saskatchewan, Canada, is conducted. • Hypothetical Extraction Method is used to estimate the comprehensive performances. Changing climate is one of the most challenging environment issues worldwide. The objective of this paper is to develop a Multi-Dimensional Hypothetical Fuzzy Risk Simulation Model to facilitate the Greenhouse Gases mitigation policy development and multi-dimensional risk simulation. In detail, the comprehensive performances of various industries are evaluated and analyzed through Hypothetical Extraction Method. The preferences of decision-makers are considered through Analytic Hierarchy Process and Fuzzy Technique for Order Preference by Similarities to Ideal Solution method to develop the optimized Greenhouse Gases mitigation policies. The multi-dimensional risks of optimized Greenhouse Gases mitigation policies are simulated through RAS method. A detailed case study of the Province of Saskatchewan, Canada, is conducted to illustrate the potential benefits of the proposed model and support the Greenhouse Gases mitigation policy development. It is found that Electric power generation, transmission and distribution sector is the key industry in Saskatchewan. The government supports are suggested to be allocated to the Electric power generation, transmission and distribution sector, since it will benefit the province from environmental, economic, and urban metabolic perspectives. [ABSTRACT FROM AUTHOR]