YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • AMS
    • Journal of Hydrometeorology
    • View Item
    •   YE&T Library
    • AMS
    • Journal of Hydrometeorology
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    Modeling Rainfall Interception Loss for an Epiphyte-Laden Quercus virginiana Forest Using Reformulated Static- and Variable-Storage Gash Analytical Models

    Source: Journal of Hydrometeorology:;2016:;Volume( 017 ):;issue: 007::page 1985
    Author:
    Van Stan, John T.
    ,
    Gutmann, Ethan D.
    ,
    Lewis, Elliott S.
    ,
    Gay, Trent E.
    DOI: 10.1175/JHM-D-16-0046.1
    Publisher: American Meteorological Society
    Abstract: arrier island forests are sensitive to changing precipitation characteristics as they typically rely on a precipitation-fed freshwater lens. Understanding and predicting significant rainfall losses is, therefore, critical to the prediction and management of hydrometeorological processes in the barrier island forest ecosystem. This study measures and models one such loss, canopy rainfall interception, for a barrier island forest common across subtropical and tropical coastlines: epiphyte-laden Quercus virginiana on St. Catherine?s Island (Georgia, United States). Reformulated Gash analytical models (RGAMs) relying on static- and variable-canopy-storage formulations were parameterized using common maximum water storage (minimum, mean, maximum, and laboratory submersion) and evaporation (Penman?Monteith, saturated rain?throughfall regression, and rain?interception regression) estimation methods. Cumulative interception loss was 37% of rainfall, and the epiphyte community contribution to interception loss was 11%. Variable-storage RGAMs using inferred evaporation and maximum water storage estimates performed best: mean absolute error of 1?2 mm, normalized mean percent error of 15%?25%, and model efficiency of 0.88?0.97, resulting in a 2%?5% overestimate of cumulative interception. Static- and variable-storage RGAMs using physically derived evaporation (Penman?Monteith) underestimated observed interception loss (40%?60%), yet the error was significantly lowered for submersion estimates of maximum water storage. Greater apparent error when using Penman?Monteith rates may result from unknown drying times, evaporation sources, and/or in situ epiphyte storage dynamics. As such, it is suggested that future research apply existing technologies to quantify evaporative processes during rainfall (e.g., eddy covariance) and to develop new methods to directly monitor in situ epiphyte water storage.
    • Download: (1.232Mb)
    • Show Full MetaData Hide Full MetaData
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      Modeling Rainfall Interception Loss for an Epiphyte-Laden Quercus virginiana Forest Using Reformulated Static- and Variable-Storage Gash Analytical Models

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4225498
    Collections
    • Journal of Hydrometeorology

    Show full item record

    contributor authorVan Stan, John T.
    contributor authorGutmann, Ethan D.
    contributor authorLewis, Elliott S.
    contributor authorGay, Trent E.
    date accessioned2017-06-09T17:17:06Z
    date available2017-06-09T17:17:06Z
    date copyright2016/07/01
    date issued2016
    identifier issn1525-755X
    identifier otherams-82390.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4225498
    description abstractarrier island forests are sensitive to changing precipitation characteristics as they typically rely on a precipitation-fed freshwater lens. Understanding and predicting significant rainfall losses is, therefore, critical to the prediction and management of hydrometeorological processes in the barrier island forest ecosystem. This study measures and models one such loss, canopy rainfall interception, for a barrier island forest common across subtropical and tropical coastlines: epiphyte-laden Quercus virginiana on St. Catherine?s Island (Georgia, United States). Reformulated Gash analytical models (RGAMs) relying on static- and variable-canopy-storage formulations were parameterized using common maximum water storage (minimum, mean, maximum, and laboratory submersion) and evaporation (Penman?Monteith, saturated rain?throughfall regression, and rain?interception regression) estimation methods. Cumulative interception loss was 37% of rainfall, and the epiphyte community contribution to interception loss was 11%. Variable-storage RGAMs using inferred evaporation and maximum water storage estimates performed best: mean absolute error of 1?2 mm, normalized mean percent error of 15%?25%, and model efficiency of 0.88?0.97, resulting in a 2%?5% overestimate of cumulative interception. Static- and variable-storage RGAMs using physically derived evaporation (Penman?Monteith) underestimated observed interception loss (40%?60%), yet the error was significantly lowered for submersion estimates of maximum water storage. Greater apparent error when using Penman?Monteith rates may result from unknown drying times, evaporation sources, and/or in situ epiphyte storage dynamics. As such, it is suggested that future research apply existing technologies to quantify evaporative processes during rainfall (e.g., eddy covariance) and to develop new methods to directly monitor in situ epiphyte water storage.
    publisherAmerican Meteorological Society
    titleModeling Rainfall Interception Loss for an Epiphyte-Laden Quercus virginiana Forest Using Reformulated Static- and Variable-Storage Gash Analytical Models
    typeJournal Paper
    journal volume17
    journal issue7
    journal titleJournal of Hydrometeorology
    identifier doi10.1175/JHM-D-16-0046.1
    journal fristpage1985
    journal lastpage1997
    treeJournal of Hydrometeorology:;2016:;Volume( 017 ):;issue: 007
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian