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...
Main Authors: | , , , |
---|---|
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 |
id |
doaj-e003d97cbd114369a35894b1c9ff5d57 |
---|---|
record_format |
Article |
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 |
_version_ |
1725824914933415936 |