Spatial interpolation of point velocities in stream cross-section

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F15%3A66990" target="_blank" >RIV/60460709:41330/15:66990 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1515/johh-2015-0006" target="_blank" >http://dx.doi.org/10.1515/johh-2015-0006</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1515/johh-2015-0006" target="_blank" >10.1515/johh-2015-0006</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Spatial interpolation of point velocities in stream cross-section

Popis výsledku v původním jazyce

The most frequently used instrument for measuring velocity distribution in the cross-section of small rivers is the propeller?type current meter. Output of measuring using this instrument is point data of a tiny bulk. Spatial interpolation of measured data should produce a dense velocity profile, which is not available from the measuring itself. This paper describes the preparation of interpolation models. Measuring campaign was realized to obtain operational data. It took place on real streams with different velocity distributions. Seven data sets were obtained from four cross-sections varying in the number of measuring points, 24?82. Following methods of interpolation of the data were used in the same context: methods of geometric interpolation arithmetic mean and inverse distance weighted, the method of fitting the trend to the data thin-plate spline and the geostatistical method of ordinary kriging. Calibration of interpolation models carried out in the computational program Scilab

Název v anglickém jazyce

Spatial interpolation of point velocities in stream cross-section

Popis výsledku anglicky

The most frequently used instrument for measuring velocity distribution in the cross-section of small rivers is the propeller?type current meter. Output of measuring using this instrument is point data of a tiny bulk. Spatial interpolation of measured data should produce a dense velocity profile, which is not available from the measuring itself. This paper describes the preparation of interpolation models. Measuring campaign was realized to obtain operational data. It took place on real streams with different velocity distributions. Seven data sets were obtained from four cross-sections varying in the number of measuring points, 24?82. Following methods of interpolation of the data were used in the same context: methods of geometric interpolation arithmetic mean and inverse distance weighted, the method of fitting the trend to the data thin-plate spline and the geostatistical method of ordinary kriging. Calibration of interpolation models carried out in the computational program Scilab

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

DA - Hydrologie a limnologie

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Hydrology and Hydromechanics

ISSN

0042-790X

e-ISSN

—

Svazek periodika

63

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

8

Strana od-do

21-28

Kód UT WoS článku

000356811500003

EID výsledku v databázi Scopus

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