414 results found
Costa D, Pomeroy J, Wheater H, 2018, A numerical model for the simulation of snowpack solute dynamics to capture runoff ionic pulses during snowmelt: The PULSE model, Advances in Water Resources, Vol: 122, Pages: 37-48, ISSN: 0309-1708
© 2018 Elsevier Ltd Early ionic pulse during spring snowmelt can account for a significant portion of the total annual nutrient load in seasonally snow-covered areas. Ionic pulses are a consequence of snow grain core to surface ion segregation during metamorphism, a process commonly referred to as ion exclusion. While numerous studies have provided quantitative measurements of this phenomenon, very few process-based mathematical models have been proposed for diagnostic and prognostic investigations. A few early modelling attempts have been successful in capturing this process assuming transport through porous media with variable porosity. However, this process is represented in models in ways that misalign with the mechanistic view of the process described in the literature. In this research, a process-based model is proposed that can simulated ionic pulses in runoff by emulating solute leaching from snow grains during melt and the subsequent vertical solute transport by meltwater through the snowpack. To facilitate its use without the need for snow-physics’ models, simplified alternative methods are proposed to estimate some of the variables required by the model. The model was applied to two regions, and a total of 4 study sites, that are subject to significantly different winter climatic and hydrological conditions. Comparison between observations and simulation results suggest that the model can capture well the overall snow melt runoff concentration pattern, including both the timing and magnitude of the early melt ionic pulse. The model enables the prediction of concentration profiles of the dry (snow) and liquid (wet) fractions within the snow matrix for the first time. Although there is a computational cost associated with the proposed modelling framework, this study demonstrates that it can provide more detailed information about the reallocation and transport of ions through snowpacks, which can ultimately be used to improve nutrient transport p
Morales-Marín L, Wheater H, Lindenschmidt KE, 2018, Potential changes of annual-averaged nutrient export in the South Saskatchewan River Basin under climate and land-use change scenarios, Water (Switzerland), Vol: 10
© 2018 by the author. Climate and land-use changes modify the physical functioning of river basins and, in particular, influence the transport of nutrients from land to water. In large-scale basins, where a variety of climates, topographies, soil types and land uses co-exist to form a highly heterogeneous environment, a more complex nutrient dynamic is imposed by climate and land-use changes. This is the case of the South Saskatchewan River (SSR) that, along with the North Saskatchewan River, forms one of the largest river systems in western Canada. The SPAtially Referenced Regression On Watershed (SPARROW) model is therefore implemented to assess water quality in the basin, in order to describe spatial and temporal patterns and identify those factors and processes that affect water quality. Forty-five climate and land-use change scenarios comprehended by five General Circulation Models (GCMs) and three Representative Concentration Pathways (RCPs) were incorporated into the model to explain how total nitrogen (TN) and total phosphorus (TP) export could vary across the basin in 30, 60 and 90 years from now. According to model results, annual averages of TN and TP export in the SSR are going to increase in the range 0.9-1.28 kg km-2 year-1 and 0.12-0.17 kg km-2 year-1, respectively, by the end of the century, due to climate and land-use changes. Higher increases of TP compared to TN are expected since TP and TN are going to increase ~36% and ~21%, respectively, by the end of the century. This research will support management plans in order to mitigate nutrient export under future changes of climate and land use.
Marsh CB, Spiteri RJ, Pomeroy JW, et al., 2018, Multi-objective unstructured triangular mesh generation for use in hydrological and land surface models, COMPUTERS & GEOSCIENCES, Vol: 119, Pages: 49-67, ISSN: 0098-3004
Xu L, Gober P, Wheater HS, et al., 2018, Reframing socio-hydrological research to include a social science perspective, JOURNAL OF HYDROLOGY, Vol: 563, Pages: 76-83, ISSN: 0022-1694
Sapriza-Azuri G, Gamazo P, Razavi S, et al., 2018, On the appropriate definition of soil profile configuration and initial conditions for land surface-hydrology models in cold regions, HYDROLOGY AND EARTH SYSTEM SCIENCES, Vol: 22, Pages: 3295-3309, ISSN: 1027-5606
Asong ZE, Wheater HS, Bonsal B, et al., 2018, Historical drought patterns over Canada and their teleconnections with large-scale climate signals, HYDROLOGY AND EARTH SYSTEM SCIENCES, Vol: 22, Pages: 3105-3124, ISSN: 1027-5606
Sadeghian A, Chapra SC, Hudson J, et al., 2018, Improving in-lake water quality modeling using variable chlorophyll a/algal biomass ratios, Environmental Modelling and Software, Vol: 101, Pages: 73-85, ISSN: 1364-8152
© 2017 Elsevier Ltd Algal simulations in many water quality models perform poorly because of oversimplifications in the process descriptions of the algae growth mechanisms. In this study, algae simulations were improved by implementing variable chlorophyll a/algal biomass ratios in the CE-QUAL-W2 model, a sophisticated two-dimensional laterally-averaged water quality model. Originally a constant in the model, the chlorophyll a/algal biomass ratio was reprogrammed to vary according to the nutrient and light limiting conditions in the water column. The modified model was tested on Lake Diefenbaker, a prairie reservoir in Saskatchewan, Canada, where, similar to many other lakes in the world, field observations confirm variable spatiotemporal ratios between chlorophyll a and algal biomass. The modified version yielded more accurate simulations compared to the standard version and provides a promising algorithm to improve results for many lakes and reservoirs globally.
Morales-Marin LA, Wheater HS, Lindenschmidt KE, 2018, Estimating Sediment Loadings in the South Saskatchewan River Catchment, WATER RESOURCES MANAGEMENT, Vol: 32, Pages: 769-783, ISSN: 0920-4741
Haghnegahdar A, Razavi S, Yassin F, et al., 2017, Multicriteria sensitivity analysis as a diagnostic tool for understanding model behaviour and characterizing model uncertainty, Hydrological Processes, Vol: 31, Pages: 4462-4476, ISSN: 0885-6087
Copyright © 2017 John Wiley & Sons, Ltd. Complex hydrological models are being increasingly used nowadays for many purposes such as studying the impact of climate and land-use change on water resources. However, building a high-fidelity model, particularly at large scales, remains a challenging task, due to complexities in model functioning and behaviour and uncertainties in model structure, parameterization, and data. Global sensitivity analysis (GSA), which characterizes how the variation in the model response is attributed to variations in its input factors (e.g., parameters and forcing data), provides an opportunity to enhance the development and application of these complex models. In this paper, we advocate using GSA as an integral part of the modelling process by discussing its capabilities as a tool for diagnosing model structure and detecting potential defects, identifying influential factors, characterizing uncertainty, and selecting calibration parameters. Accordingly, we conduct a comprehensive GSA of a complex land surface–hydrology model, Modélisation Environmentale–Surface et Hydrologie (MESH), which combines the Canadian land surface scheme with a hydrological routing component, WATROUTE. Various GSA experiments are carried out using a new technique, called Variogram Analysis of Response Surfaces, for alternative hydroclimatic conditions in Canada using multiple criteria, various model configurations, and a full set of model parameters. Results from this study reveal that, in addition to different hydroclimatic conditions and SA criteria, model configurations can also have a major impact on the assessment of sensitivity. GSA can identify aspects of the model internal functioning that are counter-intuitive and thus help the modeller to diagnose possible model deficiencies and make recommendations for improving development and application of the model. As a specific outcome of this work, a list of the most influential para
Guerrero J-L, Pernica P, Wheater H, et al., 2017, Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes, Hydrology and Earth System Sciences, Vol: 21, Pages: 6345-6362, ISSN: 1027-5606
© 2017 Author(s). Lakes might be sentinels of climate change, but the uncertainty in their main feedback to the atmosphere-heat-exchange fluxes-is often not considered within climate models. Additionally, these fluxes are seldom measured, hindering critical evaluation of model output. Analysis of the Canadian Small Lake Model (CSLM), a one-dimensional integral lake model, was performed to assess its ability to reproduce diurnal and seasonal variations in heat fluxes and the sensitivity of simulated fluxes to changes in model parameters, i.e., turbulent transport parameters and the light extinction coefficient (Kd). A C++ open-source software package, Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), was used to perform sensitivity analysis (SA) and identify the parameters that dominate model behavior. The generalized likelihood uncertainty estimation (GLUE) was applied to quantify the fluxes' uncertainty, comparing daily-averaged eddy-covariance observations to the output of CSLM. Seven qualitative and two quantitative SA methods were tested, and the posterior likelihoods of the modeled parameters, obtained from the GLUE analysis, were used to determine the dominant parameters and the uncertainty in the modeled fluxes. Despite the ubiquity of the equifinality issue-different parameter-value combinations yielding equivalent results-the answer to the question was unequivocal: Kd, a measure of how much light penetrates the lake, dominates sensible and latent heat fluxes, and the uncertainty in their estimates is strongly related to the accuracy with which Kd is determined. This is important since accurate and continuous measurements of Kd could reduce modeling uncertainty.
Costa D, Roste J, Pomeroy J, et al., 2017, A modelling framework to simulate field-scale nitrate response and transport during snowmelt: The WINTRA model, Hydrological Processes, Vol: 31, Pages: 4250-4268, ISSN: 0885-6087
Copyright © 2017 John Wiley & Sons, Ltd. Modelling nutrient transport during snowmelt in cold regions remains a major scientific challenge. A key limitation of existing nutrient models for application in cold regions is the inadequate representation of snowmelt, including hydrological and biogeochemical processes. This brief period can account for more than 80% of the total annual surface runoff in the Canadian Prairies and Northern Canada and processes such as atmospheric deposition, overwinter redistribution of snow, ion exclusion from snow crystals, frozen soils, and snow-covered area depletion during melt influence the distribution and release of snow and soil nutrients, thus affecting the timing and magnitude of snowmelt runoff nutrient concentrations. Research in cold regions suggests that nitrate (NO3) runoff at the field-scale can be divided into 5 phases during snowmelt. In the first phase, water and ions originating from ion-rich snow layers travel and diffuse through the snowpack. This process causes ion concentrations in runoff to gradually increase. The second phase occurs when this snow ion meltwater front has reached the bottom of the snowpack and forms runoff to the edge-of-the-field. During the third and fourth phases, the main source of NO3transitions from the snowpack to the soil. Finally, the fifth and last phase occurs when the snow has completely melted, and the thawing soil becomes the main source of NO3to the stream. In this research, a process-based model was developed to simulate hourly export based on this 5-phase approach. Results from an application in the Red River Basin of southern Manitoba, Canada, shows that the model can adequately capture the dynamics and rapid changes of NO3concentrations during this period at relevant temporal resolutions. This is a significant achievement to advance the current nutrient modelling paradigm in cold climates, which is generally limited to satisfactory results at monthly or annual resolut
Pan X, Helgason W, Ireson A, et al., 2017, Field-scale water balance closure in seasonally frozen conditions, Hydrology and Earth System Sciences, Vol: 21, Pages: 5401-5413, ISSN: 1027-5606
Hydrological water balance closure is a simple concept, yet in practice it is uncommon to measure every significant term independently in the field. Here we demonstrate the degree to which the field-scale water balance can be closed using only routine field observations in a seasonally frozen prairie pasture field site in Saskatchewan, Canada. Arrays of snow and soil moisture measurements were combined with a precipitation gauge and flux tower evapotranspiration estimates. We consider three hydrologically distinct periods: the snow accumulation period over the winter, the snowmelt period in spring, and the summer growing season. In each period, we attempt to quantify the residual between net precipitation (precipitation minus evaporation) and the change in field-scale storage (snow and soil moisture), while accounting for measurement uncertainties. When the residual is negligible, a simple 1-D water balance with no net drainage is adequate. When the residual is non-negligible, we must find additional processes to explain the result. We identify the hydrological fluxes which confound the 1-D water balance assumptions during different periods of the year, notably blowing snow and frozen soil moisture redistribution during the snow accumulation period, and snowmelt runoff and soil drainage during the melt period. Challenges associated with quantifying these processes, as well as uncertainties in the measurable quantities, caution against the common use of water balance residuals to estimate fluxes and constrain models in such a complex environment.
Yassin F, Razavi S, Wheater H, et al., 2017, Enhanced identification of a hydrologic model using streamflow and satellite water storage data: A multicriteria sensitivity analysis and optimization approach, Hydrological Processes, Vol: 31, Pages: 3320-3333, ISSN: 0885-6087
Copyright © 2017 John Wiley & Sons, Ltd. Hydrologic model development and calibration have continued in most cases to focus only on accurately reproducing streamflows. However, complex models, for example, the so-called physically based models, possess large degrees of freedom that, if not constrained properly, may lead to poor model performance when used for prediction. We argue that constraining a model to represent streamflow, which is an integrated resultant of many factors across the watershed, is necessary but by no means sufficient to develop a high-fidelity model. To address this problem, we develop a framework to utilize the Gravity Recovery and Climate Experiment's (GRACE) total water storage anomaly data as a supplement to streamflows for model calibration, in a multiobjective setting. The VARS method (Variogram Analysis of Response Surfaces) for global sensitivity analysis is used to understand the model behaviour with respect to streamflow and GRACE data, and the BORG multiobjective optimization method is applied for model calibration. Two subbasins of the Saskatchewan River Basin in Western Canada are used as a case study. Results show that the developed framework is superior to the conventional approach of calibration only to streamflows, even when multiple streamflow-based error functions are simultaneously minimized. It is shown that a range of (possibly false) system trajectories in state variable space can lead to similar (acceptable) model responses. This observation has significant implications for land-surface and hydrologic model development and, if not addressed properly, may undermine the credibility of the model in prediction. The framework effectively constrains the model behaviour (by constraining posterior parameter space) and results in more credible representation of hydrology across the watershed.
Masud MB, Khaliq MN, Wheater HS, 2017, Projected changes to short- and long-duration precipitation extremes over the Canadian Prairie Provinces, CLIMATE DYNAMICS, Vol: 49, Pages: 1597-1616, ISSN: 0930-7575
Wada Y, Bierkens MFP, De Roo A, et al., 2017, Human-water interface in hydrological modelling: Current status and future directions, Hydrology and Earth System Sciences, Vol: 21, Pages: 4169-4193, ISSN: 1027-5606
© Author(s) 2017. This work is distributed under. Over recent decades, the global population has been rapidly increasing and human activities have altered terrestrial water fluxes to an unprecedented extent. The phenomenal growth of the human footprint has significantly modified hydrological processes in various ways (e.g. irrigation, artificial dams, and water diversion) and at various scales (from a watershed to the globe). During the early 1990s, awareness of the potential for increased water scarcity led to the first detailed global water resource assessments. Shortly thereafter, in order to analyse the human perturbation on terrestrial water resources, the first generation of largescale hydrological models (LHMs) was produced. However, at this early stage few models considered the interaction between terrestrial water fluxes and human activities, including water use and reservoir regulation, and even fewer models distinguished water use from surface water and groundwater resources. Since the early 2000s, a growing number of LHMs have incorporated human impacts on the hydrological cycle, yet the representation of human activities in hydrological models remains challenging. In this paper we provide a synthesis of progress in the development and application of human impact modelling in LHMs. We highlight a number of key challenges and discuss possible improvements in order to better represent the human-water interface in hydrological models.
Pechlivanidis IG, McIntyre N, Wheater HS, 2017, The significance of spatial variability of rainfall on simulated runoff: an evaluation based on the Upper Lee catchment, UK, HYDROLOGY RESEARCH, Vol: 48, Pages: 1118-1130, ISSN: 1998-9563
Hosseini N, Chun KP, Wheater H, et al., 2017, Parameter Sensitivity of a Surface Water Quality Model of the Lower South Saskatchewan River—Comparison Between Ice-On and Ice-Off Periods, Environmental Modeling and Assessment, Vol: 22, Pages: 291-307, ISSN: 1420-2026
© 2016, Springer International Publishing Switzerland. Little is known about seasonal differences (ice-on vs. ice-off periods) and the sensitivity of in-stream processes to surface water quality constituents in rivers that have a persistent ice cover in winter. The goal of this study is to investigate the sensitivity of nutrient transformation processes on surface water quality, especially rivers in cold regions where ice-covered conditions persist for a substantial part of the year. We established a sensitivity analysis framework for water quality modelling and monitoring of rivers in cold regions using the Water Quality Analysis Program WASP7. The lower South Saskatchewan River in the interior of western Canada, from the Gardiner Dam at Lake Diefenbaker to the confluence of the North and South Saskatchewan rivers, is used as a test case for this purpose. The study reveals that parameter sensitivities differ between ice-covered and ice-free periods and biological model parameters related to nutrient-phytoplankton dynamics can still be sensitive during the ice-covered season. For example, sediment oxygen demand is an important parameter during the ice-on period, whereas parameters related to nitrification are more sensitive in the ice-off period. These results provide insight into important water quality monitoring aspects in cold regions during different seasons.
Sadeghian A, Hudson J, Wheater H, et al., 2017, Sediment plume model-a comparison between use of measured turbidity data and satellite images for model calibration., Environ Sci Pollut Res Int, Vol: 24, Pages: 19583-19598
In this study, we built a two-dimensional sediment transport model of Lake Diefenbaker, Saskatchewan, Canada. It was calibrated by using measured turbidity data from stations along the reservoir and satellite images based on a flood event in 2013. In June 2013, there was heavy rainfall for two consecutive days on the frozen and snow-covered ground in the higher elevations of western Alberta, Canada. The runoff from the rainfall and the melted snow caused one of the largest recorded inflows to the headwaters of the South Saskatchewan River and Lake Diefenbaker downstream. An estimated discharge peak of over 5200 m3/s arrived at the reservoir inlet with a thick sediment front within a few days. The sediment plume moved quickly through the entire reservoir and remained visible from satellite images for over 2 weeks along most of the reservoir, leading to concerns regarding water quality. The aims of this study are to compare, quantitatively and qualitatively, the efficacy of using turbidity data and satellite images for sediment transport model calibration and to determine how accurately a sediment transport model can simulate sediment transport based on each of them. Both turbidity data and satellite images were very useful for calibrating the sediment transport model quantitatively and qualitatively. Model predictions and turbidity measurements show that the flood water and suspended sediments entered upstream fairly well mixed and moved downstream as overflow with a sharp gradient at the plume front. The model results suggest that the settling and resuspension rates of sediment are directly proportional to flow characteristics and that the use of constant coefficients leads to model underestimation or overestimation unless more data on sediment formation become available. Hence, this study reiterates the significance of the availability of data on sediment distribution and characteristics for building a robust and reliable sediment transport model.
Morales-Marin LA, Wheater HS, Lindenschmidt KE, 2017, Assessment of nutrient loadings of a large multipurpose prairie reservoir, JOURNAL OF HYDROLOGY, Vol: 550, Pages: 166-185, ISSN: 0022-1694
Hassanzadeh E, Elshorbagy A, Nazemi A, et al., 2017, The ecohydrological vulnerability of a large inland delta to changing regional streamflows and upstream irrigation expansion, Ecohydrology, Vol: 10, ISSN: 1936-0584
Copyright © 2016 John Wiley & Sons, Ltd. Future climate change and anthropogenic interventions can alter historical streamflow conditions and consequently degrade the health and biodiversity of freshwater ecosystems. Future ecohydrological threats, however, are difficult to quantify using the cascade of climate and hydrological models due to various uncertainties involved. This study instead uses a fully bottom-up approach to evaluate the ecohydrological vulnerability of the Saskatchewan River Delta (SRD), the largest inland delta in North America, to changing streamflow regime and irrigation expansion. An ensemble of perturbed streamflow sequences, along with scenarios of current and expanded irrigation, was generated and fed into a regional water resource system model. Results show that the streamflow regime in the delta is more sensitive to upstream changes in annual flow volume than peak flow timing and/or irrigation expansion. The sensitivity to changes in flow volume, however, may be intensified when combined with changes in peak timing. Shifts in the upstream peak flow timing can alter the magnitude and timing of peak flow to the delta, with prime importance to aquatic biota that are adapted to historical rhythmicity in peak flows and timing. Irrigation expansion decreases the magnitude and frequency of the peak flows, alters the frequency of average and low flows, and slightly shifts the timing of the mean annual peak flow in the SRD. This can lead to isolation of lakes and wetlands from the main stream. Our results highlight the ecohydrological vulnerability of the SRD under potential changing conditions and can assist in proposing adaptation policies to protect this ecosystem.
Chun KP, Mamet SD, Metsaranta J, et al., 2017, A novel stochastic method for reconstructing daily precipitation times-series using tree-ring data from the western Canadian Boreal Forest, Dendrochronologia, Vol: 44, Pages: 9-18, ISSN: 1125-7865
© 2017 Tree ring data provide proxy records of historical hydroclimatic conditions that are widely used for reconstructing precipitation time series. Most previous applications are limited to annual time scales, though information about daily precipitation would enable a range of additional analyses of environmental processes to be investigated and modelled. We used statistical downscaling to simulate stochastic daily precipitation ensembles using dendrochronological data from the western Canadian boreal forest. The simulated precipitation series were generally consistent with observed precipitation data, though reconstructions were poorly constrained during short periods of forest pest outbreaks. The proposed multiple temporal scale precipitation reconstruction can generate annual daily maxima and persistent monthly wet and dry episodes, so that the observed and simulated ensembles have similar precipitation characteristics (i.e. magnitude, peak, and duration)—an improvement on previous modelling studies. We discuss how ecological disturbances may limit reconstructions by inducing non-linear responses in tree growth, and conclude with suggestions of possible applications and further development of downscaling methods for dendrochronological data.
Wong JS, Razavi S, Bonsal BR, et al., 2017, Inter-comparison of daily precipitation products for large-scale hydro-climatic applications over Canada, Hydrology and Earth System Sciences, Vol: 21, Pages: 2163-2185, ISSN: 1027-5606
A number of global and regional gridded climate products based on multiple data sources are available that can potentially provide reliable estimates of precipitation for climate and hydrological studies. However, research into the consistency of these products for various regions has been limited and in many cases non-existent. This study inter-compares several gridded precipitation products over 15 terrestrial ecozones in Canada for different seasons. The spatial and temporal variability of the errors (relative to station observations) was quantified over the period of 1979 to 2012 at a 0.5° and daily spatio-temporal resolution. These datasets were assessed in their ability to represent the daily variability of precipitation amounts by four performance measures: percentage of bias, root mean square error, correlation coefficient, and standard deviation ratio. Results showed that most of the datasets were relatively skilful in central Canada. However, they tended to overestimate precipitation amounts in the west and underestimate in the north and east, with the underestimation being particularly dominant in northern Canada (above 60°N). The global product by WATCH Forcing Data ERA-Interim (WFDEI) augmented by Global Precipitation Climatology Centre (GPCC) data (WFDEI [GPCC]) performed best with respect to different metrics. The Canadian Precipitation Analysis (CaPA) product performed comparably with WFDEI [GPCC]; however, it only provides data starting in 2002. All the datasets performed best in summer, followed by autumn, spring, and winter in order of decreasing quality. Findings from this study can provide guidance to potential users regarding the performance of different precipitation products for a range of geographical regions and time periods.
Masud MB, Khaliq MN, Wheater HS, 2017, Future changes to drought characteristics over the Canadian Prairie Provinces based on NARCCAP multi-RCM ensemble, CLIMATE DYNAMICS, Vol: 48, Pages: 2685-2705, ISSN: 0930-7575
Asong ZE, Razavi S, Wheater HS, et al., 2017, Evaluation of Integrated Multisatellite Retrievals for GPM (IMERG) over Southern Canada against Ground Precipitation Observations: A Preliminary Assessment, JOURNAL OF HYDROMETEOROLOGY, Vol: 18, Pages: 1033-1050, ISSN: 1525-755X
Mahmood TH, Pomeroy JW, Wheater HS, et al., 2017, Hydrological responses to climatic variability in a cold agricultural region, HYDROLOGICAL PROCESSES, Vol: 31, Pages: 854-870, ISSN: 0885-6087
Nazemi A, Wheater HS, Chun KP, et al., 2017, Forms and drivers of annual streamflow variability in the headwaters of Canadian Prairies during the 20th century, HYDROLOGICAL PROCESSES, Vol: 31, Pages: 221-239, ISSN: 0885-6087
Morales-Marin LA, Chun KP, Wheater HS, et al., 2016, Trend analysis of nutrient loadings in a large prairie catchment, HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES, Vol: 62, Pages: 657-679, ISSN: 0262-6667
Mockler EM, Chun KP, Sapriza-Azuri G, et al., 2016, Assessing the relative importance of parameter and forcing uncertainty and their interactions in conceptual hydrological model simulations, ADVANCES IN WATER RESOURCES, Vol: 97, Pages: 299-313, ISSN: 0309-1708
Asong ZE, Khaliq MN, Wheater HS, 2016, Multisite multivariate modeling of daily precipitation and temperature in the Canadian Prairie Provinces using generalized linear models, CLIMATE DYNAMICS, Vol: 47, Pages: 2901-2921, ISSN: 0930-7575
Hassanzadeh E, Elshorbagy A, Wheater H, et al., 2016, A risk-based framework for water resource management under changing water availability, policy options, and irrigation expansion, Advances in Water Resources, Vol: 94, Pages: 291-306, ISSN: 0309-1708
© 2016 Elsevier Ltd Long-term water resource management requires the capacity to evaluate alternative management options in the face of various sources of uncertainty in the future conditions of water resource systems. This study proposes a generic framework for determining the relative change in probabilistic characteristics of system performance as a result of changing water availability, policy options and irrigation expansion. These probabilistic characteristics can be considered to represent the risk of failure in the system performance due to the uncertainty in future conditions. Quantifying the relative change in the performance risk can provide a basis for understanding the effects of multiple changing conditions on the system behavior. This framework was applied to the water resource system of the Saskatchewan River Basin (SaskRB) in Saskatchewan, Canada. A “bottom-up” flow reconstruction algorithm was used to generate multiple realizations for water availability within a feasible range of change in streamflow characteristics. Consistent with observed data and projected change in streamflow characteristics, the historical streamflow was perturbed to stochastically generate feasible future flow sequences, based on various combinations of changing annual flow volume and timing of the annual peak. In addition, five alternative policy options, with and without potential irrigation expansion, were considered. All configurations of water availability, policy decisions and irrigation expansion options were fed into a hydro-economic water resource system model to obtain empirical probability distributions for system performance – here overall and sectorial net benefits – under the considered changes. Results show that no one specific policy can provide the optimal option for water resource management under all flow conditions. In addition, it was found that the joint impacts of changing water availability, policy, and irrigation expansi
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