Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume
ABSTRACT Spatial data became increasingly utilized in many scientific fields due to the accessibility of monitoring data from different sources. In the case of hydrological mapping, measurements of external environmental conditions, such as soil, climate, vegetation, are often available in addition...
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| Format: | Article |
| Language: | English |
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Associação Brasileira de Recursos Hídricos
2018-06-01
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| Series: | Revista Brasileira de Recursos Hídricos |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312018000100222&tlng=en |
| _version_ | 1819284189409705984 |
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| author | Lucas Vituri Santarosa Rodrigo Lilla Manzione |
| author_facet | Lucas Vituri Santarosa Rodrigo Lilla Manzione |
| author_sort | Lucas Vituri Santarosa |
| collection | DOAJ |
| description | ABSTRACT Spatial data became increasingly utilized in many scientific fields due to the accessibility of monitoring data from different sources. In the case of hydrological mapping, measurements of external environmental conditions, such as soil, climate, vegetation, are often available in addition to the measurements of water characteristics. An integrated modelling approach capable to incorporate multiple input data sets that may have heterogeneous geometries and other error characteristics can be achieved using geostatistical techniques. In this study, different physical hydric properties of soils extensively sampled and topography were used as auxiliary information for making optimal, point-level inferences of water table depths in forest areas. We used data from 48 wells in the Bauru Aquifer System in the Santa Bárbara Ecological Station (EEcSB), in the municipality of Aguas de Santa Bárbara in São Paulo State, Brazil. Using the resistance of soil to penetration and topography as auxiliary variables helped reduce prediction errors. With the generated maps, it was possible to estimate the volumes of water recovered from the water table in two periods during the monitoring period. These values showed that 30% of the recovered volume would be sufficient for a three-month supply of water for a population of 30,000 inhabitants. Therefore, this raises the possibility of using areas such as the EEcSB as strategic supplies in artificial recharging management. |
| first_indexed | 2024-12-24T01:43:25Z |
| format | Article |
| id | doaj.art-5ce29ffb43da46fbb46fda16d68a9276 |
| institution | Directory Open Access Journal |
| issn | 2318-0331 |
| language | English |
| last_indexed | 2024-12-24T01:43:25Z |
| publishDate | 2018-06-01 |
| publisher | Associação Brasileira de Recursos Hídricos |
| record_format | Article |
| series | Revista Brasileira de Recursos Hídricos |
| spelling | doaj.art-5ce29ffb43da46fbb46fda16d68a92762022-12-21T17:21:57ZengAssociação Brasileira de Recursos HídricosRevista Brasileira de Recursos Hídricos2318-03312018-06-012310.1590/2318-0331.231820170115Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volumeLucas Vituri SantarosaRodrigo Lilla ManzioneABSTRACT Spatial data became increasingly utilized in many scientific fields due to the accessibility of monitoring data from different sources. In the case of hydrological mapping, measurements of external environmental conditions, such as soil, climate, vegetation, are often available in addition to the measurements of water characteristics. An integrated modelling approach capable to incorporate multiple input data sets that may have heterogeneous geometries and other error characteristics can be achieved using geostatistical techniques. In this study, different physical hydric properties of soils extensively sampled and topography were used as auxiliary information for making optimal, point-level inferences of water table depths in forest areas. We used data from 48 wells in the Bauru Aquifer System in the Santa Bárbara Ecological Station (EEcSB), in the municipality of Aguas de Santa Bárbara in São Paulo State, Brazil. Using the resistance of soil to penetration and topography as auxiliary variables helped reduce prediction errors. With the generated maps, it was possible to estimate the volumes of water recovered from the water table in two periods during the monitoring period. These values showed that 30% of the recovered volume would be sufficient for a three-month supply of water for a population of 30,000 inhabitants. Therefore, this raises the possibility of using areas such as the EEcSB as strategic supplies in artificial recharging management.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312018000100222&tlng=enData fusionGroundwater managementGeostatisticsBauru Aquifer SystemGroundwater recharge |
| spellingShingle | Lucas Vituri Santarosa Rodrigo Lilla Manzione Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume Revista Brasileira de Recursos Hídricos Data fusion Groundwater management Geostatistics Bauru Aquifer System Groundwater recharge |
| title | Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume |
| title_full | Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume |
| title_fullStr | Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume |
| title_full_unstemmed | Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume |
| title_short | Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume |
| title_sort | soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume |
| topic | Data fusion Groundwater management Geostatistics Bauru Aquifer System Groundwater recharge |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312018000100222&tlng=en |
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