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River basin planning in Alberta has relied on the use of computer modeling since the early 1980s. Typical modeling studies rely on a single time step operational framework, where water allocation d...

As Canadian crude bitumen production from oil sands has increased in recent decades, the nation’s oil and gas industry has become a significant contributor to national greenhouse gas emissions. Canada has developed carbon emission reduction targets to meet its Nationally Determined Contributions and Mid-Century Strategy goals. A detailed profile of energy consumption pathways in the oil sands industry is necessary to identify potential areas of improvement and to monitor progress toward meeting emissions reduction targets. Much of the existing literature for oil sands modeling provides input assumptions with different technological boundaries. For a set of oil sands extraction and upgrading technologies, this study first reviews the literature and then quantifies energy input requirements, CO2 emissions, and operating costs for a set of consistent technological boundaries and energy units. Summary results refer to requirements and costs at the production facility, excluding transportation and blending costs. An energy system diagram of oil sands production that matches these boundaries is provided, which can be used by integrated assessment models, oil sands companies, and government ministries to evaluate the present and future energy consumption and emissions pathways of the oil sands industry.

Municipal sewage contains significant embedded resources in the form of chemical and thermal energy. Recent developments in sustainable technology have pushed for the integration of resource recovery from household wastewater to achieve net zero energy consumption and carbon-neutral communities. Sewage heat recovery and fit-for-purpose water reuse are options to optimize the resource recovery potential of municipal wastewater. This study presents a comparative life cycle assessment (LCA) focused on global warming potential (GWP), eutrophication potential (EUP), and human health carcinogenic potential (HHCP) of an integrated sewage heat recovery and water reuse system for a hypothetical community of 30,000 people. Conventional space and water heating components generally demonstrated the highest GWP contribution between the different system components evaluated. Sewage-heat-recovery-based district heating offered better environmental performance overall. Lower impact contributions were demonstrated by scenarios with a membrane bioreactor (MBR) and chlorination prior to water reuse applications compared to scenarios that use more traditional water and wastewater treatment technologies and discharge. The LCA findings show that integrating MBR wastewater treatment and water reuse into a district heating schema could provide additional environmental savings at a community scale.

Monochloramine (NH2Cl), as the dominant disinfectant in drinking water chloramination, can provide long-term disinfection in distribution systems. However, NH2Cl can also be discharged into storm sewer systems and cause stormwater contamination through outdoor tap water uses. In storm sewer systems, NH2Cl dissipation can occur by three pathways: (i) auto-decomposition, (ii) chemical reaction with stormwater components, and (iii) biological dissipation. In this research, a field NH2Cl dissipation test was conducted with continuous tap water discharge into a storm sewer. The results showed a fast decrease of NH2Cl concentration from the discharge point to the sampling point at the beginning of the discharge period, while the rate of decrease decreased as time passed. Based on the various pathways involved in NH2Cl decay and the field testing results, a kinetic model was developed. To describe the variation of the NH2Cl dissipation rates during the field testing, a time coefficient fT was introduced, and the relationship between fT and time was determined. After calibration through the fT coefficient, the kinetic model described the field NH2Cl dissipation process well. The model developed in this research can assist in the regulation of tap water outdoor discharge and contribute to the protection of the aquatic environment.

This paper describes a new approach to fill missing data in hydrologic series. Based on a multiple-order autoregressive model, our algorithm represents the random term with an empirical distribution function that includes different parameters for the low, medium and high ranges of the modelled hydrologic variable. The algorithm involves a corrective mechanism that preserves the original statistical distribution of the series that are filled, while also eliminating the possibility of obtaining negative values for low flows. The algorithm requires multiple correlated hydrologic time series with sufficient data to permit accurate calculation of their statistical properties. It ensures that both the original statistical dependence among the data series and the statistical distribution functions will be preserved after the missing data had been filled. The model has been tested using 15 streamflow series in the Upper Bow River watershed in Alberta, Canada.

This study introduces an end-use-based system dynamics model to support municipal water planning and management over the medium-to long-term. The Calgary Water Management Model (CWMM) simulates water demand and use to 2040 at a weekly time step for ten municipal end-uses, as well as the effects of population growth, climate change, and various water management policies, and includes policy implementation costs for assessment of conservation versus economic trade-offs. The model was validated against historical water demand data for Calgary, Alberta. A series of scenario simulations showed (1) potentially large changes to both seasonal and non-seasonal water demands with climate change and population growth, (2) a need to enhance historical water management policies with new policies such as xeriscaping and greywater reuse to achieve water management goals, and (3) the value of an end-use based model in simulating management policy effects on municipal water demand and use.

Bacteriological contamination of drinking water wells poses a challenge to many rural areas of First Nations communities in Alberta that rely on wells as the primary drinking water source for large proportions of their populations. Here we reviewed available historical data for the Samson Cree Nation near Maskwacis, Alberta (formerly Hobbema), to identify linkages between various environmental and historical factors and the risk of contamination by Escherichia coli and total coliform bacteria. Increased bacterial counts were found to be associated with a peak in total precipitation and surface water flow following a two to four month lag period. Wells installed by contractors operating at an earlier period in time were also found to be at greater risk than more recent installations. These findings can be used to better characterize the risk of contamination, which will assist in tailoring remedial actions to address chronic or recurring bacteriological presence in wells.

Chloramination has been widely applied for drinking water disinfection, with monochloramine (NH2Cl) the dominant chloramine species. However, under neutral pH, NH2Cl can autodecompose and react with chemical components in drinking water, thus decreasing disinfection efficiency. In tap water, the NH2Cl loss rate can be influenced by temperature, pH, Cl/N molar ratio, the initial NH2Cl concentration, and the natural organic matter (NOM) concentration. A good prediction of NH2Cl loss can assist in the operation of drinking water treatment plants. In this research, a kinetic rate constantinline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="01999-ilm01.gif"/)and a reactive site fraction (S = 0.43 ± 0.06) for the reaction between free chlorine released from NH2Cl autodecoposition and tap water NOM were derived from a kinetic model to predict the NH2Cl loss under various conditions. A temperature-dependent model was also developed. The model predictions match well with the experimental results, which demonstrates the validity of the model and provides a convenient and accurate method for NH2Cl loss calculations.

Water stressed regions rely heavily on the import of water-intensive goods to offset insufficient food production driven by socioeconomic and environmental factors. The water embedded in these traded commodities, virtual water, has received increasing interest in the scientific community. However, comprehensive future projections of virtual water trading remain absent. Here we show, for the first time, changes over the 21st century in the amount of various water types required to meet international agricultural demands. Accounting for evolution in socioeconomic and climatic conditions, we estimate future interregional virtual water trading and find trading of renewable water sources may triple by 2100 while nonrenewable groundwater trading may at least double. Basins in North America, and the La Plata and Nile Rivers are found to contribute extensively to virtual water exports, while much of Africa, India, and the Middle East relies heavily on virtual water imports by the end of the century., Assessments of future virtual water trading are still lacking. Here the authors estimated the global virtual water trade throughout the century and found that virtual green water exports and virtual blue water exports at least triple to more than 3200 bcm and 170 bcm, respectively, by the end of the century.

Data-driven modeling with machine learning (ML) algorithms in hydrologic modeling and forecasting suffers a number of pitfalls and challenges, including variable selection bias, resubstitution validation, inconsistent validation processes for different algorithms and model selection using the test set. They lead to incorrect model development and biased, overly optimistic performance estimates – and thus, unreliable models. This study presents a novel model building and testing workflow that addresses common machine learning (ML) challenges and pitfalls. The presented workflow incorporates optional variable transformation and preprocessing techniques, and applies to various ML model types, variable selection algorithms and resampling techniques. We demonstrate its performance through streamflow forecasting for the Bow River Basin, Alberta, Canada, using four conventional ML algorithms (ANN, SVM, ELM and RBF networks) driven by local hydrometeorological conditions and large-scale climate indices. Using the cross-validation average out-of-sample results and a separate test set, the prediction accuracy estimate bias (the relative difference between the model performance estimated using the validation sets and a separate test set) was empirically estimated to be 5.6%, 4.4%, 2.5% and 3.0% for the Seasonal, May, June and July models, respectively. In addition, the streamflow forecasting models had an average coefficient of determination of 0.85. Preprocessing and dimensionality reduction through principal component analysis (PCA) was detrimental to prediction accuracy. Snow water equivalent from individual snow courses proved the most important predictor for Bow River streamflow, while global climate indices, including the PDO, AMO and PNA, increased the Nash–Sutcliffe efficiency by 6% to 50%. Finally, although forecasting skill decreased with increasing forecast lead time, satisfactory forecasts (NSE>0.5) could be obtained two months in advance of the spring melt, at the end of February. Extensions of this study should address the tendency of different variable selection algorithms to pick irrelevant or redundant predictors after changes in training data.

Hydropower accounts for approximately 60% of electricity generation in Canada, with growth expected in the coming decades as part of renewable energy transitions; however, frequent cost overruns threaten the viability of this growth. Using the integrated assessment model GCAM, we develop an endogenous representation of hydropower for Canada that accounts for market dynamics, thus permitting analysis of hydropower competition with other electricity generation technologies, both with and without cost overruns. Results show that modelling hydropower resources endogenously increases Canadian hydropower deployment relative to an assumption of fixed hydropower production, from 417 to 495 TWh annually by 2050. In scenarios that apply cost overruns at historical levels, hydropower loses market share to more easily scalable technologies like wind power. When including high cost overrun assumptions, the model determines that hydropower falls from about 73% to 65% of Canadian electricity generation by 2050, while wind power increases from about 8% to 11%. Countries may be better able to achieve electrification and renewable energy targets at lower cost by avoiding large-scale, overrun-prone hydropower and nuclear generation projects. Model results support that cost overruns are important considerations for policy decisions related to electricity sector development in Canada and elsewhere.

Improved reservoir operation policies based on river basin management simulations have typically not been implemented in the field. This article investigates this disconnect between reservoir operations theory and practice. Interviews with water managers in southern Alberta (Canada) reveal that reservoir operations are based on basin-wide cooperation, a focus on the current state of the system without hedging rules, and early-season announcements of water rationing. Model development should focus on multiple time-step optimization approaches that can produce optimal release decisions for various levels of risk, provide better insight into effects of alternative releases and potentially reduce supply shortfalls.

Water is essential for the world’s food supply, for energy production, including bioenergy and hydroelectric power, and for power system cooling. Water is already scarce in many regions of the world and could present a critical constraint as society attempts simultaneously to mitigate climate forcing and adapt to climate change, and to provide for a larger and more prosperous human population. Numerous studies have pointed to growing pressures on the world’s scarce fresh water resources from population and economic growth, and climate change. This study goes further. We use the Global Change Assessment Model to analyze interactions between population, economic growth, energy, land, and water resources simultaneously in a dynamically evolving system where competing claims on water resources from all claimants—energy, land, and economy—are reconciled with water resource availability—from renewable water, non-renewable groundwater and desalinated water sources —across 14 geopolitical regions, 151 agriculture-ecological zones, and 235 major river basins. We find that previous estimates of global water withdrawal projections are overestimated. Model simulations show that it is more economical in some basins to alter agricultural and energy activities rather than utilize non-renewable groundwater or desalinated water. This study highlights the importance of accounting for water as a binding factor in agriculture, energy and land use decisions in integrated assessment models and implications for global responses to water scarcity, particularly in the trade of agricultural commodities and land-use decisions.

Despite significant effort to quantify the interdependence of the water and energy sectors, global requirements of energy for water (E4W) are still poorly understood, which may result in biases in projections and consequently in water and energy management and policy. This study estimates water-related energy consumption by water source, sector, and process for 14 global regions from 1973 to 2012. Globally, E4W amounted to 10.2 EJ of primary energy consumption in 2010, accounting for 1.7%-2.7% of total global primary energy consumption, of which 58% pertains to fresh surface water, 30% to fresh groundwater, and 12% to nonfresh water, assuming median energy intensity levels. The sectoral E4W allocation includes municipal (45%), industrial (30%), and agricultural (25%), and main process-level contributions are from source/conveyance (39%), water purification (27%), water distribution (12%), and wastewater treatment (18%). While the United States was the largest E4W consumer from the 1970s until the 2000s, the largest consumers at present are the Middle East, India, and China, driven by rapid growth in desalination, groundwater-based irrigation, and industrial and municipal water use, respectively. The improved understanding of global E4W will enable enhanced consistency of both water and energy representations in integrated assessment models.

Concerns about total residual chlorine effects on the aquatic environment have led to a lowering of allowable effluent discharge concentrations. Many municipalities use monochloramine as a water disinfectant, which makes its way into drainage systems through outdoor and industrial water uses, and ultimately into surface waters. Monochloramine is known to dissipate with variable temporal and spatial decay coefficients; however, no existing stormwater models simulate these aspects. Thus, this study describes a novel Variable Decay Coefficient Simulator (VDCS) that predicts levels of degradable pollutants in sewer systems. The importance of spatially- and temporally-varying monochloramine decay coefficients on pollutant concentrations was assessed through three scenarios using, (1) a constant decay coefficient, (2) spatially-varying decay coefficients per land-use, and (3) spatially- and temporally-varying decay coefficients. At the system outfall, the spatially- and temporally-varying decay coefficients generated 67% and 100% higher concentrations, respectively, than the constant decay coefficient. These differences have important implications for the modeling of degradable pollutants in stormwater systems, and for the application of environmental regulations.

A practical 4-stage-3-model framework is introduced that models and maps pollutant concentrations in, and potential hazards of, municipal stormwater point-source releases to surface water bodies. The framework consists of a stormwater model, a stormwater quality model, geographic information systems (GIS) mapping models, and a hazard assessment procedure based on event mean concentrations (EMC) and fuzzy logic. This framework was applied to project both outfall concentrations and environmental hazards of a degradable point-source pollutant, monochloramine, in stormwater effluents released to the North Saskatchewan River, Alberta, Canada, under different weather conditions. Monochloramine loads were over the permissible limits under dry weather flows throughout the basin, and only a design storm of a 10-year return period produced monochloramine concentrations below regulation discharge limits. An EMC-based hazard map was developed that revealed 25% of the study area to lie within the moderate to high-risk zones. EMC-based hazards were driven primarily by proximity to the system outlet, total pollutant mass and system layout. Next, a generalized, fuzzy-based monochloramine hazard map was developed, using monochloramine decay-inducing factors such as annual rainfall, land-use type, EMC values, ground slope, decay rates, property assessment values, drainage system proximity and density of impervious areas. This map showed 54% of the basin at moderate to high risk. The maps developed using the proposed 4-stage-3-model framework can help system operators to improve management of stormwater pollutants without time- and labor-intensive, case-by-case calculations and to focus mitigation measures on releases from specific “hot spot” locations in the system. The framework can be generalized to other chemical substances that impair stormwater quality through either point or non-point source pollution.

Future changes in climate and socioeconomic systems will drive both the availability and use of water resources, leading to evolutions in scarcity. The contributions of both systems can be quantified individually to understand the impacts around the world, but also combined to explore how the coevolution of energy-water-land systems affects not only the driver behind water scarcity changes, but how human and climate systems interact in tandem to alter water scarcity. Here we investigate the relative contributions of climate and socioeconomic systems on water scarcity under the Shared Socioeconomic Pathways-Representative Concentration Pathways framework. While human systems dominate changes in water scarcity independent of socioeconomic or climate future, the sign of these changes depend particularly on the socioeconomic scenario. Under specific socioeconomic futures, human-driven water scarcity reductions occur in up to 44% of the global land area by the end of the century.

Integrated models are crucial for evaluation of the complex interactions and trade-offs among policy choices and socioeconomic, technical, and environmental processes. The use of process-based crop models as components of integrated models offers the possibility of significantly improving such analyses; however, challenges exist in terms of simulation scales and degree of integration. Therefore, this study evaluates the applicability of coarser-than-daily simulation time steps to simulate long-term crop yields in integrated models, and the impacts of aggregated weather input data on yields for a water-driven crop-process model based on the FAO AquaCrop model. We ran simulations at daily, semi-weekly, and weekly time steps in conjunction with coarser temporal resolution (weekly) weather input data for three crops in four locations over ten years to represent a range of crops and growing environments. Simulation results were compared to a reference case from AquaCrop using daily time step with daily weather data. Model skill for simulating crop biomass and yield and water demands was assessed statistically for each of these four hypothetical farms. Visual representations were also used to compare simulated soil moisture, crop canopy, and actual evapotranspiration values. Weekly climate data led to overestimation of crop biomass and yield regardless of the time step used. High agreements and low bias errors were realized for crop production and water estimates at daily and semi-weekly time steps, whereas weekly simulations showed poorer performance. Longer time steps intensified the impacts of weather input data aggregation, and overestimation became more pronounced with increases in time step length. The findings have important implications for integrated assessments that couple crop models with other socioeconomic, environmental, or hydrologic models, and provide guidance for modelers involved in interdisciplinary agricultural and water resources applications, including policy assessments, evaluation of water and food security, and resource use and efficiency under climate change.

A system dynamics-based simulation gaming model, developed as a component of Agriculture and Agri-Food Canada's Invitational Drought Tournament (IDT; Hill et al., 2014), is introduced in this paper as a decision support tool for drought management at the river-basin scale. This IDT Model provides a comprehensive and integrated overview of drought conditions, and illustrates the broad effects of socio-economic drought and mitigation strategies. It is intended to provide a safe, user-friendly experimental environment with fast run-times for testing management options, and to promote collaborative decision-making and consensus building. Examples of model results from several recent IDT events demonstrate potential effects of drought and the short-to longer-term effectiveness of policies selected by IDT teams; such results have also improved teams' understanding of the complexity of water resources systems and their management trade-offs. The IDT Model structure and framework can also be reconfigured quickly for application to different river basins.

Water withdrawal for electricity generation in the United States accounts for approximately half the total freshwater withdrawal. With steadily growing electricity demands, a changing climate, and limited water supplies in many water-scarce states, meeting future energy and water demands poses a significant socioeconomic challenge. Employing an integrated modeling approach that captures the energy–water interactions at regional and national scales can improve our understanding of the key drivers that govern those interactions and the role of national policies. In this study, the Global Change Assessment Model (GCAM), a technologically-detailed integrated model of the economy, energy, agriculture and land use, water, and climate systems, was extended to model the electricity and water systems at the state level in the U.S. (GCAM-USA). GCAM-USA was employed to estimate future state-level electricity generation and consumption, and their associated water withdrawals and consumption under a set of seven scenarios with extensive detail on the generation fuel portfolio, cooling technology mix, and their associated water use intensities. These seven scenarios were explored to investigate the implications of socioeconomic development and growing electricity demands, cooling system transitions, adoption of water-saving technologies, climate mitigation policy and electricity trading options on future water demands of the U.S. electric-sector. Our findings include: 1) decreasing water withdrawals and increasing water consumption from the conversion from open-loop to closed-loop cooling systems; 2) different energy-sector water demand behaviors with alternative pathways to the mitigation goal; 3) open trading of electricity benefiting energy-scarce yet demand-intensive states; 4) across-state homogeneity under certain driving forces (e.g., climate mitigation and water-saving technologies) and mixed effects under other drivers (e.g.,, electricity trade); and 5) a clear trade-off between water consumption and withdrawal for the electricity sector in the U.S. The paper discusses this withdrawal–consumption trade-off in the context of current national policies and regulations that favor decreasing withdrawals (and increasing consumptive use), and the role of water-saving technologies. The study also clearly shows that climate mitigation strategies focusing on CCS and nuclear power will have less favorable water consumption effects than strategies that support renewable energy and water-saving technologies. The highly-resolved nature of this study, both geographically and technologically, provides a useful platform to address scientific and policy-relevant and emerging issues at the heart of the water–energy nexus in the U.S.

Urban stormwater lakes in cold regions are ice-covered for substantial parts of the winter. It has long been considered that the ice-covered period is the “dormant season,” during which ecological processes are inactive. However, little is known about this period due to the historical focus on the open-water season. Recent pioneering research on ice-covered natural lakes has suggested that some critical ecological processes play out on the ice. The objective of this study was to investigate the active processes in ice-covered stormwater lakes. Data collected during a two-year field measurement program at a stormwater lake located in Edmonton, Alberta, Canada were analyzed. The lake was covered by ice from November to mid-April of the following year. The mean value of chlorophyll-a during the ice-covered period was 22.09% of the mean value for the open-water season, suggesting that primary productivity under the ice can be important. Nitrogen and phosphorus were remarkably higher during the ice-covered period, while dissolved organic carbon showed little seasonal variation. Under ice-covered conditions, the total phosphorus was the major nutrient controlling the ratio of total nitrogen to total phosphorus, and a significant positive correlation existed between total phosphorus and chlorophyll-a when the ratio was smaller than 10. The results provide preliminary evidence of the critical nutrient processes in Stormwater Lake during the ice-covered period.

Monochloramine (NH2Cl) is widely used for secondary disinfection by water utilities. However, Edmonton field stormwater sampling results have shown that NH2Cl, because of its long-lasting property, can cause stormwater contamination through outdoor potable water uses during the summer season. To protect water sources, it is important to understand NH2Cl dissipation mechanisms in stormwater. Natural organic matter (NOM) is the dominant species that contributes to NH2Cl decay in stormwater. In this research, it is proposed that NOM reacted with both NH2Cl and free chlorine through rapid and long-term reactions during NH2Cl dissipation. Based on this assumption, a kinetic model was developed and applied to estimate the NH2Cl decay in real stormwater samples, and the modeling results matched experimental data well under all the conditions. Further, the stormwater dissolved organic matter (SWDOM) collected from different neighborhoods was analyzed by Fourier transform infrared (FTIR) and fluorescence excitation-emission matrix (EEM) techniques. Humic substances were found to be dominant in SWDOM, and the samples from different neighborhoods had similar organic constituents. After reaction with excess NH2Cl, 25%-41% SWDOM fluorophores converted to inorganic components, while most of DOM remained in organic form. Humic substances as the major components in SWDON, are the dominant precursors of disinfection by-products in chloramination. Therefore, the potential reaction products of stormwater humic substances with NH2Cl should also be of concern. This research provided a useful method to estimate the NH2Cl dissipation in stormwater, and the methodology can also be applied for stormwater NH2Cl decay studies in other cities. Further, it is believed the SWDOM analysis in this research will contribute to future studies of NH2Cl NOM reaction mechanisms in both storm sewers and drinking water distribution systems.

Floods are costly natural disasters that are projected to increase in severity and frequency into the future. Exceedances over a high threshold and analysis of their distributions, as determined through the Peak Over Threshold (POT) method and approximated by a Generalized Pareto Distribution (GPD), respectively, are widely used for flood frequency analysis. This study investigates the combined effects of threshold selection and GPD parameter estimation on the accuracy of flood quantile estimates, and develops a new, widely-applicable framework that significantly improves the accuracy of flood quantile estimations. First, the performance of several parameter estimators (i.e., Maximum Likelihood; Probability Weighted Moments; Maximum Goodness of Fit; Likelihood Moment; Modified Likelihood Moment; and Nonlinear Weighted Least Square Error) for the GPD was compared through Monte Carlo simulation. Then, a calibrated Soil and Water Assessment Tool (SWAT) model for the province of Alberta, Canada, was used to reproduce daily streamflow series for 47 watersheds distributed across the province, and the POT was applied to each. The Goodness of Fit for the resulting flood frequency models was measured by the upper tail Anderson-Darling (AD) test and the root-mean-square error (RMSE) and demonstrated improvements for more than one-third of stations by averages of 65% (AD) and 47% (RMSE), respectively.

Many municipalities in Canada and all over the world use chloramination for drinking water secondary disinfection to avoid DBPs formation from conventional chlorination. However, the long-lasting monochloramine (NH2Cl) disinfectant can pose a significant risk to aquatic life through its introduction into municipal storm sewer systems and thus fresh water sources by residential, commercial, and industrial water uses. To establish general total active chlorine (TAC) concentrations in discharges from storm sewers, the TAC concentration was measured in stormwater samples in Edmonton, Alberta, Canada, during the summers of 2015 and 2016 under both dry and wet weather conditions. The field-sampling results showed TAC concentration variations from 0.02 to 0.77 mg/L in summer 2015, which exceeds the discharge effluent limit of 0.02 mg/L. As compared to 2015, the TAC concentrations were significantly lower during the summer 2016 (0–0.24 mg/L), for which it is believed that the higher precipitation during summer 2016 reduced outdoor tap water uses. Since many other cities also use chloramines as disinfectants for drinking water disinfection, the TAC analysis from Edmonton may prove useful for other regions as well. Other physicochemical and biological characteristics of stormwater and storm sewer biofilm samples were also analyzed, and no significant difference was found during these two years. Higher density of AOB and NOB detected in the storm sewer biofilm of residential areas – as compared with other areas – generally correlated to high concentrations of ammonium and nitrite in this region in both of the two years, and they may have contributed to the TAC decay in the storm sewers. The NH2Cl decay laboratory experiments illustrate that dissolved organic carbon (DOC) concentration is the dominant factor in determining the NH2Cl decay rate in stormwater samples. The high DOC concentrations detected from a downstream industrial sampling location may contribute to a high stormwater NH2Cl decay rate in this area.

Water scarcity conditions over the 21st century both globally and regionally are assessed in the context of climate change and climate mitigation policies, by estimating both water availability and water demand within the Global Change Assessment Model (GCAM), a leading community-integrated assessment model of energy, agriculture, climate, and water. To quantify changes in future water availability, a new gridded water-balance global hydrologic model – namely, the Global Water Availability Model (GWAM) – is developed and evaluated. Global water demands for six major demand sectors (irrigation, livestock, domestic, electricity generation, primary energy production, and manufacturing) are modeled in GCAM at the regional scale (14 geopolitical regions, 151 sub-regions) and then spatially downscaled to 0.5° × 0.5° resolution to match the scale of GWAM. Using a baseline scenario (i.e., no climate change mitigation policy) with radiative forcing reaching 8.8 W m−2 (equivalent to the SRES A1Fi emission scenario) and three climate policy scenarios with increasing mitigation stringency of 7.7, 5.5, and 4.2 W m−2 (equivalent to the SRES A2, B2, and B1 emission scenarios, respectively), we investigate the effects of emission mitigation policies on water scarcity. Two carbon tax regimes (a universal carbon tax (UCT) which includes land use change emissions, and a fossil fuel and industrial emissions carbon tax (FFICT) which excludes land use change emissions) are analyzed. The baseline scenario results in more than half of the world population living under extreme water scarcity by the end of the 21st century. Additionally, in years 2050 and 2095, 36% (28%) and 44% (39%) of the global population, respectively, is projected to live in grid cells (in basins) that will experience greater water demands than the amount of available water in a year (i.e., the water scarcity index (WSI) > 1.0). When comparing the climate policy scenarios to the baseline scenario while maintaining the same baseline socioeconomic assumptions, water scarcity declines under a UCT mitigation policy but increases with a FFICT mitigation scenario by the year 2095, particularly with more stringent climate mitigation targets. Under the FFICT scenario, water scarcity is projected to increase, driven by higher water demands for bio-energy crops.

In this paper, we assess future water demands for the agricultural (irrigation and livestock), energy (electricity generation, primary energy production and processing), industrial (manufacturing and mining), and municipal sectors, by incorporating water demands into a technologically-detailed global integrated assessment model of energy, agriculture, and climate change � the Global Change Assessment Model (GCAM). Base-year water demands � both gross withdrawals and net consumptive use � are assigned to specific modeled activities in a way that maximizes consistency between bottom-up estimates of water demand intensities of specific technologies and practices, and top-down regional and sectoral estimates of water use. The energy, industrial, and municipal sectors are represented in fourteen geopolitical regions, with the agricultural sector further disaggregated into as many as eighteen agro-ecological zones (AEZs) within each region. We assess future water demands representing six socioeconomic scenarios, with no constraints imposed by future water supplies. The scenarios observe increases in global water withdrawals from 3710 km3 year- 1 in 2005 to 6195�8690 km3 year- 1 in 2050, and to 4869�12,693 km3 year- 1 in 2095. Comparing the projected total regional water withdrawals to the historical supply of renewable freshwater, the Middle East exhibits the highest levels of water scarcity throughout the century, followed by India; water scarcity increases over time in both of these regions. In contrast, water scarcity improves in some regions with large base-year electric sector withdrawals, such as the USA and Canada, due to capital stock turnover and the almost complete phase-out of once-through flow cooling systems. The scenarios indicate that: 1) water is likely a limiting factor in meeting future water demands, 2) many regions can be expected to increase reliance on non-renewable groundwater, water reuse, and desalinated water, but they also highlight an important role for development and deployment of water conservation technologies and practices.

Electricity production has traditionally required extensive water use, so growing economies such as China are expected to increase their freshwater withdrawal and consumption to meet growing electricity demand. Research shows, however, that through restructuring the electricity sector and increasing efficiency, China may have broken this coupling.

This paper introduces a comprehensive modeling framework for Integrated Water Resources Management (IWRM). The model incorporates water demands, allocation, and uses under various climate, population, and economic scenarios as well as management strategies. Model outputs include crop yields, municipal water use, power generation, recreational reservoir uses, and environmental flows. Further, a novel indicator integrates many key model outputs for social, economic, and environmental assessment based on the basin-scale water balance, and provides a comprehensive and clear representation of basin conditions to improve the understanding of IWRM trade-offs. When applied to the Bow River Basin, Canada, as a practical example, this Bow River Integrated Model (BRIM) revealed through a set of modeling scenarios that (1) only the industrial demands exceeded the water license in the high-water demand and reference scenarios due to population growth and economic development; (2) increased cooling tower shares for thermal power plants was the most effective policy in managing industrial demand; and (3) the new indicator reflected both basin-scale conditions and sectoral water stresses. Finally, model results from three gaming scenarios showed socio-economic and environmental trade-offs clearly, providing users with guidance in developing a comprehensive view of basin-scale water security, and hands-on experience to support IWRM. Therefore, the modeling framework and novel indicator can improve an understanding of IWRM concepts and strategic trade-offs in efforts towards basin water sustainability.

Monochloramine (NH2Cl), with its long-lasting disinfection effect, has been widely used for drinking water secondary disinfection. However, NH2Cl can enter storm sewers and ultimately fresh water sources (e.g., rivers or lakes) through outdoor tap water uses, and total active chlorine levels as high as 0.77 mg/L have been detected in Edmonton stormwater. To evaluate the potential harmful impact of NH2Cl on aquatic environment, it is crucial to elucidate NH2Cl dissipation mechanisms in storm sewers. The objective of this research is to investigate the effect of biofilm colonized on storm sewers on NH2Cl decay. Storm sewer biofilm was cultured in annular reactors on PVC and cement materials under operational conditions that mimicked the storm sewer environment. Biofilm microbial community analysis detected a higher abundance of total bacteria, ammonia oxidizing bacteria (AOB) and nitrite oxidizing bacteria functional gene copies in biofilm formed on cement surfaces, as compared to that on PVC materials. Three NH2Cl dissipation mechanisms in the presence of stormwater biofilm were evaluated in batch experiments, including, (i) the direct NH2Cl reaction with biofilm, (ii) AOB cometabolism, and (iii) the NH2Cl reaction with AOB utilized associated products produced during AOB metabolism process. In this research, a kinetic model was developed to characterize these dissipation processes in storm sewer biofilm. The modeled results agreed well with the experimental data, which suggests that this model can be used to describe the NH2Cl dissipation under various stormwater conditions. It is believed that this is the first study to simulate the NH2Cl decay in the presence of storm sewer biofilm, thus contributing to the regulation of chloraminated water discharge in storm sewer systems.

This corrigendum addresses errors in the printing of three figures that made the original version difficult to interpret.

Measures to limit greenhouse gas concentrations will result in dramatic changes to energy and land systems and in turn alter the character of human requirements for water. We employ the global change assessment model (GCAM), an integrated assessment model, to explore the interactions of energy, land, and water systems under combinations of three alternative radiative forcing stabilization levels and two carbon tax regimes. The paper analyzes two important research questions: i) how large may global irrigation water demands become over the next century, and ii) what are the potential impacts of emissions mitigation policies on global irrigation-water withdrawals. We find that increasing population and economic growth could more than double the demand for water for agricultural systems in the absence of climate policy, and policies to mitigate climate change further increase agricultural demands for water. The largest increases in agricultural irrigation water demand occur in scenarios where only fossil fuel emissions are priced (but not land use change emissions) and are primarily driven by rapid expansion in bio-energy production. Regions such as China, India, and other countries in South and East Asia are likely to experience the greatest increases in water demands. Finally, we test the sensitivity of water withdrawal demands to the share of bio-energy crops under irrigation and conclude that many regions have insufficient space for heavy bio-energy crop irrigation in the future—a result that calls into question the physical possibility of producing the associated biomass energy, especially under climate policy scenarios.

Three future projections of global municipal water use are established: business-as usual (BAU), low technological improvement (Low Tech), and high technological improvement (High Tech). A global municipal water demand model is constructed using global water-use statistics at the country scale, calibrated to the base year of 2005, and simulated to the end of the 21st century. Since the constructed water demand model hinges on socio-economic variables (population, income), water price, and end-use technology and efficiency improvement rates, projections of those input variables are adopted to characterize the uncertainty in future water demand estimates. The water demand model is linked to the Global Change Assessment Model (GCAM), a global change integrated assessment model. Under the reference (BAU) scenario, the global total water withdrawal increases from 466 km3 year−1 in 2005 to 1098 km3 year−1 in 2100, while withdrawals in the High and Low Tech scenarios are 437 and 2000 km3 year−1, respect...

Globally, electricity generation accounts for a large and potentially growing water demand, and as such is an important component to assessments of global and regional water scarcity. However, the current suite—as well as potential future suite—of thermoelectric generation technologies has a very wide range of water demand intensities, spanning two orders of magnitude. As such, the evolution of the generation mix is important for the future water demands of the sector. This study uses GCAM, an integrated assessment model, to analyze the global electric sector's water demands in three futures of climate change mitigation policy and two technology strategies. We find that despite five- to seven-fold expansion of the electric sector as a whole from 2005 to 2095, global electric sector water withdrawals remain relatively stable, due to the retirement of existing power plants with water-intensive once-through flow cooling systems. In the scenarios examined here, climate policies lead to the large-scale deployment of advanced, low-emissions technologies such as carbon dioxide capture and storage (CCS), concentrating solar power, and engineered geothermal systems. In particular, we find that the large-scale deployment of CCS technologies does not increase long-term water consumption from hydrocarbon-fueled power generation as compared with a no-policy scenario without CCS. Moreover, in sensitivity scenarios where low-emissions electricity technologies are required to use dry cooling systems, we find that the consequent additional costs and efficiency reductions do not limit the utility of these technologies in achieving cost-effective whole-system emissions mitigation.

Electric power plants account for approximately half the global industrial water withdrawal. Although continued electric-sector expansion is probable, significant variations in water intensity by electricity technology and cooling system type make its effects on water demands uncertain. Using GCAM, an integrated assessment model of energy, agriculture, and climate change, we establish lower-, median-, and upper-bound estimates for current electric-sector water withdrawals and consumption in 14 geopolitical regions, and compare them with available estimates. We then explore water use for electricity to 2095, focusing on uncertainties in water withdrawal and consumption intensities, power plant cooling system changes, and adoption rates of water-saving technologies. Results reveal a probable decrease in the water withdrawal intensity with capital stock turnover, but a corresponding increase in consumptive use, for which technologies under development may compensate. At a regional scale, water use varies significantly based on the existing capital stock and its evolution over the century.

Over the course of this coming century, global electricity use is expected to grow at least five fold and if stringent greenhouse gas emissions controls are in place the growth could be more than seven fold from current levels. Given that the electric power sector represents the second largest industrial use of water and given growing concerns about the nature and extent of future water scarcity driven by population growth and a changing climate, significant concern has been expressed about the electricity sector's use of water going forward. In this paper, the authors demonstrate that an often overlooked but absolutely critical issue that needs to be taken into account in discussions about the sustainability of the electric sector's water use going forward is the tremendous turn over in electricity capital stock that will occur over the course of this century; i.e., in the scenarios examined here more than 80% of global electricity production in the year 2050 is from facilities that have not yet been built. The authors show that because of the large scale changes in the global electricity system, the water withdrawal intensity of electricity production is likely to drop precipitously with the result being relatively constant water withdrawals over the course of the century even in the face of the large growth in electricity usage. The ability to cost effectively reduce the water intensity of power plants with carbon dioxide capture and storage systems in particular is key to constraining overall global water use.

Awareness of increasing water scarcity has driven efforts to model global water resources for improved insight into water resources infrastructure and management strategies. Most water resources models focus explicitly on water systems and represent socio-economic and environmental change as external drivers. In contrast, the system dynamics-based integrated assessment model employed here, ANEMI, incorporates dynamic representations of these systems, so that their broader changes affect and are affected by water resources systems through feedbacks. Sectors in ANEMI therefore include the global climate system, carbon cycle, economy, population, land use and agriculture, and novel versions of the hydrological cycle, global water use and water quality. Since the model focus is on their interconnections through explicit nonlinear feedbacks, simulations with ANEMI provide insight into the nature and structure of connections between water resources and socio-economic and environmental change. Of particular interest to water resources researchers and modelers will be the simulated effects of a new water stress definition that incorporates both water quality and water quantity effects into the measurement of water scarcity. Five simulation runs demonstrate the value of wastewater treatment and reuse programs and the feedback-effects of irrigated agriculture and greater consumption of animal products.

On the island of Hainan, China, the provincial government has recently committed itself to sustainable development, which requires the integration of social, environmental, and economic factors in decision making. However, while Hainan’s recent Eco-province designation establishes environmental and economic factors as the basis of policy development, it overlooks the equally important social component of sustainability, in which social needs and values are key considerations. This paper presents the results of a study on Hainan in 2002, with government officials, forestry workers, and the Li, an indigenous minority group, and places the province’s situation within the context of both the larger changes underway in China, and the theory and practice of sustainable forestry. The research results show that the government of Hainan has not yet been able to manage both social welfare and environmental and economic issues, demonstrating the difficulty of implementing sustainable forestry and of balancing short- with long-term goals. The inclusion of Li communities in forestry-related decision making could reduce tensions between local communities and forestry management and also improve the sustainability of the government’s forestry practices.

Climatic change affects virtually every natural system on Earth,from the water cycle, sea levels, and ocean circulation to the pro-ductivity of natural and agricultural systems, and the abundanceand survival of plant and animal species. Therefore, it is influenc-ing human welfare, through changes in supply of and demand forwater, food and energy, and leads to a loss of life and property.These effects on natural and human systems mean that the climaticchange debate is directly related to the sustainability of the cur-rent socio-economic and environmental systems. The argument asto the connection is simple: because human welfare and ecologicalwell-being are interdependent, and the concerns of both present andfuture generations are equally important, failing to address climaticchange adequately may be disastrous for our current way of life,and will almost certainly be disastrous for our children’s (Gibson,2002).Climate modelling using general circulation models or globalclimate models (GCMs) offers the best approach to understand-ing the physical climate system, and indeed the entire naturalEarth system (McGuffie and Henderson-Sellers, 1997). Earth-systemmodels of intermediate complexity (EMICs) make clear that feed-backs exist both within particular system components (atmosphere,oceans, cryosphere, land surface, and biosphere) and between them(Claussen

We investigate the effects of emission mitigation policies on water scarcity both globally and regionally using the Global Change Assessment Model (GCAM), a leading community integrated assessment model of energy, agriculture, climate, and water. Three climate policy scenarios with increasing mitigation stringency of 7.7, 5.5, and 4.2 W m−2 in year 2095 (equivalent to the SRES A2, B2, and B1 emission scenarios, respectively), under two carbon tax regimes (a universal carbon tax (UCT) which includes land use change emissions, and a fossil fuel and industrial emissions carbon tax (FFICT) which excludes land use change emissions) are analyzed. The results are compared to a baseline scenario (i.e. no climate change mitigation policy) with radiative forcing reaching 8.8 W m−2 (equivalent to the SRES A1Fi emission scenario) by 2095. When compared to the baseline scenario and maintaining the same baseline socioeconomic assumptions, water scarcity declines under a UCT mitigation policy but increases with a FFICT mitigation scenario by the year 2095 particularly with more stringent climate mitigation targets. The decreasing trend with UCT policy stringency is due to substitution from more water-intensive to less water-intensive choices in food and energy production, and in land use. Under the FFICT scenario, water scarcity is projected to increase driven by higher water demands for bio-energy crops. This study implies an increasingly prominent role for water availability in future human decisions, and highlights the importance of including water in integrated assessment of global change. Future research will be directed at incorporating water shortage feedbacks in GCAM to better understand how such stresses will propagate across the various human and natural systems in GCAM.

Water scarcity conditions over the 21st century both globally and regionally are assessed in the context of climate change, by estimating both water availability and water demand within the Global Change Assessment Model (GCAM), a leading community integrated assessment model of energy, agriculture, climate, and water. To quantify changes in future water availability, a new gridded water-balance global hydrologic model – namely, the Global Water Availability Model (GWAM) – is developed and evaluated. Global water demands for six major demand sectors (irrigation, livestock, domestic, electricity generation, primary energy production, and manufacturing) are modeled in GCAM at the regional scale (14 geopolitical regions, 151 sub-regions) and then spatially downscaled to 0.5° × 0.5° resolution to match the scale of GWAM. Using a baseline scenario (i.e., no climate change mitigation policy) with radiative forcing reaching 8.8 W m−2 (equivalent to the SRES A1Fi emission scenario) and a global population of 14 billion by 2095, global annual water demand grows from about 9–10% of total annual renewable freshwater in 2005 to about 32–37% by 2095. This results in more than half of the world population living under extreme water scarcity by the end of the 21st century. Regionally, the demand for water exceeds the amount of water availability in two GCAM regions, the Middle East and India. Additionally, in years 2050 and 2095 36% (28%) and 44% (39%) of the global population, respectively is projected to live in grid cells (in basins) that will experience greater water demands than the amount of available water in a year (i.e., the water scarcity index (WSI) > 1.0). This study implies an increasingly prominent role for water in future human decisions, and highlights the importance of including water in integrated assessment of global change.

Energy, water and land are scarce resources, critical to humans. Developments in each affect the availability and cost of the others, and consequently human prosperity. Measures to limit greenhouse gas concentrations will inevitably exact dramatic changes on energy and land systems and in turn alter the character, magnitude and geographic distribution of human claims on water resources. We employ the Global Change Assessment Model (GCAM), an integrated assessment model to explore the interactions of energy, land and water systems in the context of alternative policies to limit climate change to three alternative levels: 2.5 Wm-2 (445 ppm CO2-e), 3.5 Wm-2 (535 ppm CO2-e) and 4.5 Wm-2 (645 ppm CO2-e). We explore the effects of two alternative land-use emissions mitigation policy options—one which taxes terrestrial carbon emissions equally with fossil fuel and industrial emissions, and an alternative which only taxes fossil fuel and industrial emissions but places no penalty on land-use change emissions. We find that increasing populations and economic growth could be anticipated to almost triple demand for water for agricultural systems across the century even in the absence of climate policy. In general policies to mitigate climate change increase agricultural demands for water still further, though the largest changes occur in the second half of the century, under both policy regimes. The two policies examined profoundly affected both the sources and magnitudes of the increase in irrigation water demands. The largest increases in agricultural irrigation water demand occurred in scenarios where only fossil fuel emissions were priced (but not land-use change emission) and were primarily driven by rapid expansion in bioenergy production. In these scenarios water demands were large relative to present-day total available water, calling into question whether it would be physically possible to produce the associated biomass energy. We explored the potential of improved water delivery and irrigation system efficiencies. These could potentially reduce demands substantially. However, overall demands remained high under our fossil-fuel-only tax policy. In contrast, when all carbon was priced, increases in agricultural water demands were smaller than under the fossil-fuel-only policy and were driven primarily by increased demands for water by non-biomass crops such as rice. Finally we estimate the geospatial pattern of water demands and find that regions such as China, India and other countries in south and east Asia might be expected to experience greatest increases in water demands.

Simple models of the social-economic-climatic system offer an alternative to the standard GCM-driving scenario modelling approach, which focuses on the climate system and neglects important feedback-effects from socio-economic systems. This failure to represent the whole system is clearly problematic, because natural and socio-economic systems exhibit complex, nonlinear behaviour, and each certainly affects the other. We therefore offer an alternative approach, based on explicit modelling of the feedbacks within and between components of the system. The system dynamics simulation methodology used here facilitates representation of feedback processes, time delays, and nonlinearities, and encourages an understanding of the interconnections within a system that fundamentally determine its behaviour. As a working example of the system dynamics approach, our paper describes a simple climate-carbon cycle-water cycle-population closed-loop model. A set of three experiments compare a "business-as-usual" case with model modifications, including exogenous technology change, and endogenous equation and parameter changes. Analysis of the experimental results demonstrates model sensitivities and shortcomings: exponential growth patterns may indicate the necessity for additional model sectors and feedbacks, and sensitive relationships suggest the need for further study. Future work will improve the representation of socio-economic sectors of the model.

This paper describes a new model, ANEMI, for the integrated assessment of climate and global change. ANEMI reproduces the main characteristics of eight sectors of the society-biosphere-climate system – climate, carbon cycle, land use, population, surface water flow, water use, water quality, and the economy – and explores the manner in which interactions, or feedbacks, between these components determine the behaviour of the whole. The model's reference behaviour forms the basis of comparison for the set of experiments undertaken to date with the model; these experiments and their goals are summarised. A sample Monte Carlo simulation illustrates typical model behaviour, and shows how change in one model variable affects the others. Conclusions reiterate the value of integrated assessment modelling and describe future additions to the model.

Proactive drought preparedness is a challenge for a variety of physical, institutional, and social reasons. Significant progress has been made in monitoring and forecasting water deficits, both temporally and spatially. However, less progress has been made in translating this information into proactive decision-making frameworks to support drought preparedness. The Invitational Drought Tournament (IDT), a simulation adaptation framework developed by Agriculture and Agri-Food Canada, is a recent innovation that supports drought preparedness efforts. The IDT provides a mechanism for presenting physical science information to decision makers across a variety of educational levels and professional backgrounds, in a way that allows for peer-to-peer education and synthesis. Second, the game simulation environment allows players to integrate this information into economic, policy and institutional frameworks in a non-threatening manner. Third, it maintains realism by constraining players׳ risk management options via a budget, the physical realities of the drought presented, and the technical expertise of the ‘referees’. Post-game follow-up allows players to explore lessons learned and to identify topics that warrant further in-depth exploration of policy options and subsequent implementation. The game provides an interim step between recognition of the risk posed by drought hazards and the actual implementation of vulnerability-reduction actions. This allows for a broad discussion within a sports-themed process that provides room for reflection and a richer understanding of the issues that must be addressed to ensure drought preparedness actions are effective.