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    Probabilistic Potentiometric Surface Mapping

    Source: Journal of Geotechnical Engineering:;1989:;Volume ( 115 ):;issue: 011
    Author:
    Pinnaduwa H. S. W. Kulatilake
    DOI: 10.1061/(ASCE)0733-9410(1989)115:11(1569)
    Publisher: American Society of Civil Engineers
    Abstract: The paper provides a methodology to estimate the spatial variation of potentiometric surfaces, allowing for possible uncertainties such as instrument errors, human errors, and statistical errors. The spatial variation is expressed in terms of the mean estimation, the coefficient of variation of the estimation, and the variance of the data scatter. The methodology is illustrated by a case study. The paper provides the criteria to decide the best estimation model when a number of theoretically consistent models are available to estimate spatial variation. A procedure to detect anomalous data is discussed in the paper through an example. The paper also provides a procedure to estimate the confidence of the mean spatial variation estimation, and describes steps one should take to improve this confidence, if it is needed. A technique is also given to estimate the random‐error component of the measurements.
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      Probabilistic Potentiometric Surface Mapping

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    http://yetl.yabesh.ir/yetl1/handle/yetl/20381
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    contributor authorPinnaduwa H. S. W. Kulatilake
    date accessioned2017-05-08T20:35:12Z
    date available2017-05-08T20:35:12Z
    date copyrightNovember 1989
    date issued1989
    identifier other%28asce%290733-9410%281989%29115%3A11%281569%29.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/20381
    description abstractThe paper provides a methodology to estimate the spatial variation of potentiometric surfaces, allowing for possible uncertainties such as instrument errors, human errors, and statistical errors. The spatial variation is expressed in terms of the mean estimation, the coefficient of variation of the estimation, and the variance of the data scatter. The methodology is illustrated by a case study. The paper provides the criteria to decide the best estimation model when a number of theoretically consistent models are available to estimate spatial variation. A procedure to detect anomalous data is discussed in the paper through an example. The paper also provides a procedure to estimate the confidence of the mean spatial variation estimation, and describes steps one should take to improve this confidence, if it is needed. A technique is also given to estimate the random‐error component of the measurements.
    publisherAmerican Society of Civil Engineers
    titleProbabilistic Potentiometric Surface Mapping
    typeJournal Paper
    journal volume115
    journal issue11
    journal titleJournal of Geotechnical Engineering
    identifier doi10.1061/(ASCE)0733-9410(1989)115:11(1569)
    treeJournal of Geotechnical Engineering:;1989:;Volume ( 115 ):;issue: 011
    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