MaheuAnctilGaboritEtAl2018

Référence

Maheu, A., Anctil, F., Gaborit, É., Fortin, V., Nadeau, D.F., Therrien, R. (2018) A field evaluation of soil moisture modelling with the Soil, Vegetation, and Snow (SVS) land surface model using evapotranspiration observations as forcing data. Journal of Hydrology, 558:532-545. (Scopus )

Résumé

To address certain limitations with their current operational model, Environment and Climate Change Canada recently developed the Soil, Vegetation, and Snow (SVS) land surface model and the representation of subsurface hydrological processes was targeted as an area for improvement. The objective of this study is to evaluate the ability of HydroSVS, the component of SVS responsible for the vertical redistribution of water, to simulate soil moisture under snow-free conditions when using flux-tower observations of evapotranspiration as forcing data. We assessed (1) model fidelity by comparing soil moisture modelled with HydroSVS to point-scale measurements of volumetric soil water content and (2) model complexity by comparing the performance of HydroSVS to that of HydroGeoSphere, a state-of-the-art integrated surface and subsurface hydrologic model. To do this, we performed one-dimensional soil column simulations at four sites of the AmeriFlux network. Results indicate that under Mediterranean and temperate climates, HydroSVS satisfactorily simulated soil moisture (Nash-Sutcliffe efficiency between 0.26 and 0.70; R2 ≥ 0.80), with a performance comparable to HydroGeoSphere (Nash-Sutcliffe efficiency ≥0.60; R2 ≥ 0.80). However, HydroSVS performed weakly under a semiarid climate while HydroGeoSphere performed relatively well. By decoupling the magnitude and sourcing of evapotranspiration, this study proposes a powerful diagnostic tool to evaluate the representation of subsurface hydrological processes in land surface models. Overall, this study highlights the potential of SVS for hydrological applications. © 2018

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@ARTICLE { MaheuAnctilGaboritEtAl2018,
    AUTHOR = { Maheu, A. and Anctil, F. and Gaborit, É. and Fortin, V. and Nadeau, D.F. and Therrien, R. },
    TITLE = { A field evaluation of soil moisture modelling with the Soil, Vegetation, and Snow (SVS) land surface model using evapotranspiration observations as forcing data },
    JOURNAL = { Journal of Hydrology },
    YEAR = { 2018 },
    VOLUME = { 558 },
    PAGES = { 532-545 },
    NOTE = { cited By 0 },
    ABSTRACT = { To address certain limitations with their current operational model, Environment and Climate Change Canada recently developed the Soil, Vegetation, and Snow (SVS) land surface model and the representation of subsurface hydrological processes was targeted as an area for improvement. The objective of this study is to evaluate the ability of HydroSVS, the component of SVS responsible for the vertical redistribution of water, to simulate soil moisture under snow-free conditions when using flux-tower observations of evapotranspiration as forcing data. We assessed (1) model fidelity by comparing soil moisture modelled with HydroSVS to point-scale measurements of volumetric soil water content and (2) model complexity by comparing the performance of HydroSVS to that of HydroGeoSphere, a state-of-the-art integrated surface and subsurface hydrologic model. To do this, we performed one-dimensional soil column simulations at four sites of the AmeriFlux network. Results indicate that under Mediterranean and temperate climates, HydroSVS satisfactorily simulated soil moisture (Nash-Sutcliffe efficiency between 0.26 and 0.70; R2 ≥ 0.80), with a performance comparable to HydroGeoSphere (Nash-Sutcliffe efficiency ≥0.60; R2 ≥ 0.80). However, HydroSVS performed weakly under a semiarid climate while HydroGeoSphere performed relatively well. By decoupling the magnitude and sourcing of evapotranspiration, this study proposes a powerful diagnostic tool to evaluate the representation of subsurface hydrological processes in land surface models. Overall, this study highlights the potential of SVS for hydrological applications. © 2018 },
    AFFILIATION = { Département des sciences naturelles, Université du Québec en Outaouais, Canada; Département de génie civil et de génie des eaux, Université Laval, Canada; Environment and Climate Change Canada, Canada; Département de géologie et de génie géologique, Université Laval, Canada },
    AUTHOR_KEYWORDS = { HydroGeoSphere; Land surface model; Soil moisture; SVS },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1016/j.jhydrol.2018.01.065 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041531585&doi=10.1016%2fj.jhydrol.2018.01.065&partnerID=40&md5=1c937c4f85da419e24f2606ea38b4f7b },
}

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