mmlMRVAgen1, Source Code for Construction of Multiple Machine-Learning Models of Water Levels in the Mississippi River Valley Alluvial Aquifer

The mmlMRVAgen1 repository contains R, LaTeX, Mermaid, and Perl language source code that can be used for construction multiple methods of machine learning (MML) of water levels in the Mississippi River Valley alluvial aquifer (MRVA) within the Mississippi Alluvial Plain (MAP), south-central United States. The source code is written in R (primary and extensive), LaTeX (for structured narrative as additional software documentation), Mermaid (workflow diagrams), and Perl (minor utility for simple implementation of parallel processing on certain operating systems for two workflows within the repository). Extensive Markdown documentation is provided in many README and similar files. The mmlMRVAgen1 software requires input files stemming from the companion software titled covMRVAgen1 presenting observed monthly MRVA water levels (response variable) and associated covariates (predictor variables). These files are used for MML construction (generation), but a formal data release provides a particular version of the input data for MML construction. The MML generation workflow (the genMML/ subdirectory) creates, using R, large quantities of statistical output, intermediate diagnostics, extensive visualization of overall MML prediction performance and detailed visualization of MML results for selected groundwater wells within the MAP. The mmlMRVAgen1 also has extensive demonstration of workflow capacity (1) to predict MRVA water-level time-series for specific locations on the 1-kilometer National Hydrogeologic Grid (NHG) and (2) to predict gridded surfaces of MRVA water-levels in time on the NHG for the MAP. These two capacities represent two independent implementation phases of mmlMRVAgen1. The mmlMRVAgen1 software for the implementation phase again requires input files of covariates on the NHG that come from the covMRVAgen1 companion software. MML implementation workflow (the useMMLsu/ and useMMLts/ subdirectories) creates, using R, large quantities of statistical output, geospatial layers, and visualization of status and trends of MRVA water levels. Additional documentation in the form of LaTeX source-code application (subdirectories moredoc/ExampleMMLsurfaces/ and moredoc/ExampleMMLtimeseries/) is available to potentially serve as formal Supplemental Information designed as companion material to external interpretive publications. In total, the source code is expansive and technically demanding with advanced statistical methods involved along with novice-level geospatial operations. Sophisticated understanding of the R language itself and numerous external open-source libraries also are needed. The repository organization is such that the greater workflow is designed to nearly run-out-of-the box so that interested readers can readily evaluate and otherwise test the veracity of the algorithms herein.