Spatial characterization of raingauge networks: case study for the basin of Peñitas dam.

A methodology to determine the relative importance of the location of a raingauge station within a meteorological or climatological network is presented based upon the induced error due to insufficient coverage. This analysis is carried out based on the mean error through the explained variance in t...

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Main Authors: René Lobato Sánchez, Francisco Javier Aparicio Mijares, Marco Antonio Sosa Chiñas, Indalecio Mendoza Uribe
Format: Article
Language:Spanish
Published: Instituto Mexicano de Tecnología del Agua 2012-02-01
Series:Tecnología y ciencias del agua
Subjects:
Online Access:http://www.revistatyca.org.mx/ojs/index.php/tyca/article/view/11
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spelling doaj-e003d97cbd114369a35894b1c9ff5d572020-11-24T22:05:44ZspaInstituto Mexicano de Tecnología del AguaTecnología y ciencias del agua0187-83362007-24222012-02-01311031217Spatial characterization of raingauge networks: case study for the basin of Peñitas dam.René Lobato Sánchez0Francisco Javier Aparicio Mijares1Marco Antonio Sosa Chiñas2Indalecio Mendoza Uribe3Servicio Meteorológico NacionalInstituto Mexicano de Tecnología del AguaInstituto Mexicano de Tecnología del AguaInstituto Mexicano de Tecnología del AguaA methodology to determine the relative importance of the location of a raingauge station within a meteorological or climatological network is presented based upon the induced error due to insufficient coverage. This analysis is carried out based on the mean error through the explained variance in the spatial domain, in which every raingauge station is considered. The whole raingauge network is taken as a reference base and then every station is randomly removed, along with its corresponding associated error. A regular-spaced grid obtained using the standard regression-kriging is used in the analysis since it proved to be the best methodology for including two variables at the same time for highly irregular terrains, as is the case for the Peñitas Basin. The greater the difference with respect to the reference grid, the greater the importance of the station, demonstrated by the value of the root mean square error. The analysis shows that the importance of each raingauge station varies for the two seasons studied (winter and summer). For example, the raingauge station in Ocotepec showed that its observations are important for the two periods, whereas other stations do not show the same agreement. This methodology is useful when the number of stations needs to be increased, since it helps to determine the optimum location of sites where the best spatial and local representation can be expected.http://www.revistatyca.org.mx/ojs/index.php/tyca/article/view/11redes meteorológicas, interpolación espacial con Kriging con regresión, lluvia por cuencas, análisis de error, bases de datos climatológicos
collection DOAJ
language Spanish
format Article
sources DOAJ
author René Lobato Sánchez
Francisco Javier Aparicio Mijares
Marco Antonio Sosa Chiñas
Indalecio Mendoza Uribe
spellingShingle René Lobato Sánchez
Francisco Javier Aparicio Mijares
Marco Antonio Sosa Chiñas
Indalecio Mendoza Uribe
Spatial characterization of raingauge networks: case study for the basin of Peñitas dam.
Tecnología y ciencias del agua
redes meteorológicas, interpolación espacial con Kriging con regresión, lluvia por cuencas, análisis de error, bases de datos climatológicos
author_facet René Lobato Sánchez
Francisco Javier Aparicio Mijares
Marco Antonio Sosa Chiñas
Indalecio Mendoza Uribe
author_sort René Lobato Sánchez
title Spatial characterization of raingauge networks: case study for the basin of Peñitas dam.
title_short Spatial characterization of raingauge networks: case study for the basin of Peñitas dam.
title_full Spatial characterization of raingauge networks: case study for the basin of Peñitas dam.
title_fullStr Spatial characterization of raingauge networks: case study for the basin of Peñitas dam.
title_full_unstemmed Spatial characterization of raingauge networks: case study for the basin of Peñitas dam.
title_sort spatial characterization of raingauge networks: case study for the basin of peñitas dam.
publisher Instituto Mexicano de Tecnología del Agua
series Tecnología y ciencias del agua
issn 0187-8336
2007-2422
publishDate 2012-02-01
description A methodology to determine the relative importance of the location of a raingauge station within a meteorological or climatological network is presented based upon the induced error due to insufficient coverage. This analysis is carried out based on the mean error through the explained variance in the spatial domain, in which every raingauge station is considered. The whole raingauge network is taken as a reference base and then every station is randomly removed, along with its corresponding associated error. A regular-spaced grid obtained using the standard regression-kriging is used in the analysis since it proved to be the best methodology for including two variables at the same time for highly irregular terrains, as is the case for the Peñitas Basin. The greater the difference with respect to the reference grid, the greater the importance of the station, demonstrated by the value of the root mean square error. The analysis shows that the importance of each raingauge station varies for the two seasons studied (winter and summer). For example, the raingauge station in Ocotepec showed that its observations are important for the two periods, whereas other stations do not show the same agreement. This methodology is useful when the number of stations needs to be increased, since it helps to determine the optimum location of sites where the best spatial and local representation can be expected.
topic redes meteorológicas, interpolación espacial con Kriging con regresión, lluvia por cuencas, análisis de error, bases de datos climatológicos
url http://www.revistatyca.org.mx/ojs/index.php/tyca/article/view/11
work_keys_str_mv AT renelobatosanchez spatialcharacterizationofraingaugenetworkscasestudyforthebasinofpenitasdam
AT franciscojavierapariciomijares spatialcharacterizationofraingaugenetworkscasestudyforthebasinofpenitasdam
AT marcoantoniososachinas spatialcharacterizationofraingaugenetworkscasestudyforthebasinofpenitasdam
AT indaleciomendozauribe spatialcharacterizationofraingaugenetworkscasestudyforthebasinofpenitasdam
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