Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume
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https://scielo.figshare.com/articles/dataset/Soil_variables_as_auxiliary_information_in_spatial_prediction_of_shallow_water_table_levels_for_estimating_recovered_water_volume/7507055
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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.
摘要 随着多源监测数据的可获取性不断提升,空间数据在众多科学领域中的应用愈发广泛。在水文制图场景中,除水体特征的实测数据外,土壤、气候、植被等外部环境条件的观测数据通常也可获得。借助地质统计方法(geostatistical techniques),可构建集成建模方案,该方案能够整合几何结构与误差特征各异的多组输入数据集。本研究以经密集采样的土壤多项物理水文特性及地形数据作为辅助信息,对林区地下水位深度开展最优点位级推断。本次研究使用了巴西圣保罗州阿瓜斯-德圣巴巴拉市圣巴巴拉生态站(Santa Bárbara Ecological Station, EEcSB)内包鲁含水层系统(Bauru Aquifer System)中48口观测井的实测数据。以土壤贯入阻力与地形作为辅助变量,有效降低了预测误差。基于生成的地下水位空间分布图,研究人员可估算监测周期内两个时段从地下含水层中可回收的水体总量。测算结果显示,可回收水体总量的30%即可满足3万人口为期3个月的用水需求。综上,本研究表明可将圣巴巴拉生态站这类区域作为地下水人工补给管理中的战略供水储备区域。
提供机构:
SciELO journals
创建时间:
2018-12-26



