Large-scale computational investigations of groundwater levels are proposed to accelerate science delivery through a workflow spanning database assembly, statistics, and information synthesis and packaging. A water-availability study of the Mississippi River alluvial plain, and particularly the Mississippi River Valley alluvial aquifer (MRVA), is ongoing. Software (visGWDBmrva) has been released as part of the study that demonstrates groundwater informatics for the aquifer. Considerable water-level data collected by multiple agencies over a seven-state area exist (18,903 wells; 287,272 measurements [April 22, 2019]). Data and metadata quality assurance methods, basic statistics, hydrograph visualization, outlier identification, hypothesis testing, and time-series modeling are described. Two approaches (generalized additive models [GAMs] and support vector machines [SVMs]) are used for data interpolation and extension to monthly water-level estimates. Numerical congruence between GAM and SVM estimates will be useful to limit inclusion of monthly estimates from subsequent science activities.

提出了对地下水水位的大规模计算研究，以通过跨数据库组装，统计以及信息合成和打包的工作流来加速科学交付。密西西比河冲积平原，特别是密西西比河谷冲积含水层（MRVA）的水利用度研究正在进行中。作为研究的一部分，已经发布了软件（visGWDBmrva），该软件演示了含水层的地下水信息学。存在由多个机构在一个七州地区收集的大量水位数据（18,903口井； 287,272口测量值[2019年4月22日]）。描述了数据和元数据质量保证方法，基本统计数据，水文图形可视化，离群值识别，假设检验和时间序列建模。两种方法（通用添加剂模型[GAM]和支持向量机[SVM]）用于数据插值和扩展到每月水位估计。GAM和SVM估算之间的数值一致性将有助于限制后续科学活动中每月估算的包含。