Calibrating Environment Canada's MESH Modelling System over the Great Lakes Basin

Haghnegahdar, Amin; Tolson, Bryan A.; Davison, Bruce; Seglenieks, Frank; Klyszejko, Erika; Soulis, E. D.; Fortin, Vincent; Matott, L. Shawn

doi:10.1080/07055900.2014.939131

Cited by 34 publications

(24 citation statements)

References 50 publications

(64 reference statements)

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“…MESH is a semi‐distributed coupled land surface–hydrology modelling system developed by ECCC for large‐scale watershed modelling with consideration of cold region processes in Canada (Pietroniro et al, ). It has been widely used in different parts of Canada (e.g., Davison et al, ; Haghnegahdar et al, ; Mekonnen et al, ; Mengistu & Spence, ; Pietroniro et al, ; Pohl & Marsh, ) and has been under continuous development at the National Hydrology Research Centre in Saskatoon, Canada, via collaboration between researchers from the GIWS and ECCC.…”

Section: Mesh Modelling Systemmentioning

confidence: 99%

Multicriteria sensitivity analysis as a diagnostic tool for understanding model behaviour and characterizing model uncertainty

Haghnegahdar

Razavi

Yassin

et al. 2017

Hydrological Processes

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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 parameters for the MESH model is developed. This list, along with some specific recommendations, is expected to assist the wide community of MESH and Canadian land surface scheme users, to enhance their modelling applications.

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Section: Mesh Modelling Systemmentioning

confidence: 99%

Multicriteria sensitivity analysis as a diagnostic tool for understanding model behaviour and characterizing model uncertainty

Haghnegahdar

Razavi

Yassin

et al. 2017

Hydrological Processes

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“…Validation of the previous version of CLASS has been performed as part of Project for Inter-comparison of Land Surface Parameterization (PILPS) [52][53][54]. Langlois et al [55] and Haghnegahdar et al [56], have evaluated the performance of the recent version 3.5 of CLASS, but when coupled with RCMs, focusing on snow simulations and hydrological modelling.…”

Section: Methodsmentioning

confidence: 99%

Biophysical Impacts of Land Use Change over North America as Simulated by the Canadian Regional Climate Model

2016

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This study investigates the biophysical impacts of human-induced land use change (LUC) on the regional climate of North America, using the fifth generation Canadian Regional Climate Model (CRCM5). To this end, two simulations are performed with CRCM5 using different land cover datasets, one corresponding to the potential vegetation and the other corresponding to current land use, spanning the 1988-2012 period, driven by European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA)-Interim at the lateral boundaries. Comparison of the two suggests higher albedo values, and therefore cooler temperatures, over the LUC regions, in the simulation with LUC, in winter. This is due to the absence of crops in winter, and also possibly due to a snow-mediated positive feedback. Some cooling is observed in summer for the simulation with LUC, mostly due to the higher latent heat fluxes and lower sensible heat fluxes over eastern US. Precipitation changes for these regions are not statistically significant. Analysis of the annual cycles for two LUC regions suggests that the impact of LUC on two meter temperature, evapotranspiration, soil moisture and precipitation are present year round. However, the impact on runoff is mostly restricted to the snowmelt season. This study thus highlights regions and variables most affected by LUC over North America.

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“…DDS has been successfully applied to a number of case studies before and has shown to be efficient for finding good solutions in complex models with limited calibrated budget (e.g. Dornes et al ., ; Haghnegahdar et al ., ; Tolson and Shoemaker, ). Razavi et al .…”

Section: Case Study: Mesh Model Applied To the Nottawasaga River Basinmentioning

confidence: 97%

“…Modélisation Environmentale–Surface et Hydrologie (MESH) is a land surface‐hydrological model developed by Environment Canada (Pietroniro et al ., ) for various water resources management applications mostly at large scales (e.g. Deacu et al ., ; Dupont et al ., ; Haghnegahdar et al ., ). MESH evolved from WATCLASS (Soulis et al ., ), which was a combination of the routing module of WATFLOOD (Kouwen et al ., ) and the land surface scheme CLASS (Verseghy, ; Verseghy et al ., ).…”

Section: Case Study: Mesh Model Applied To the Nottawasaga River Basinmentioning

confidence: 98%

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Assessing the performance of a semi‐distributed hydrological model under various watershed discretization schemes

Haghnegahdar

Tolson

Craig

et al. 2015

Hydrological Processes

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Physically based distributed and semi‐distributed hydrological models have become some of the primary tools for water resources studies and management over the past decades owing to increased computational capabilities and advances in data measurements. Representation of the existing heterogeneity in nature still remains one of the main challenges in these models and is accomplished primarily via watershed discretization, subdividing watersheds into hydrologically similar land parcels. Discretization decisions in distributed modelling studies are often ad hoc and determined with little or no quantitative analysis to support these decisions. In this work, we present a quantitative methodology for assessing alternative watershed discretization schemes in terms of their corresponding model performance in ungauged basins. The effect of the computational time spent for calibrating each scheme (calibration budget) is considered as part of the assessment. Here, these schemes differ in how they represent landscape attributes and range from a simple lumped scheme to more complex ones by adding spatial land cover and then soil information. The methodology is demonstrated using the Modélisation Environmentale–Surface et Hydrologie (MESH) model as applied to the Nottawasaga River basin in Ontario, Canada. Results reveal that model performance in ungauged basins depends upon the location of the validation sub‐basin (i.e. upstream or downstream) with respect to the calibration sub‐basins. Also, using a more complex scheme did not necessarily lead to improved performance in validation, when constrained by calibration budget. Therefore, the calibration budget also should be considered as a factor in the assessment process. This methodology was also implemented using a shorter sub‐period for calibration, which leads to substantial computational saving. Results of the sub‐period test were promising and consistent particularly when sufficient budget is spent to calibrate the model. Other strategies utilized for reducing the computational burden of the proposed analyses are also discussed in this study. Copyright © 2015 John Wiley & Sons, Ltd.

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Calibrating Environment Canada's MESH Modelling System over the Great Lakes Basin

Cited by 34 publications

References 50 publications

Multicriteria sensitivity analysis as a diagnostic tool for understanding model behaviour and characterizing model uncertainty

Multicriteria sensitivity analysis as a diagnostic tool for understanding model behaviour and characterizing model uncertainty

Biophysical Impacts of Land Use Change over North America as Simulated by the Canadian Regional Climate Model

Assessing the performance of a semi‐distributed hydrological model under various watershed discretization schemes

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