Geostatistical Temporal-Spatial (GTS) Optimization Software

GTS was developed with technical oversight and funding by the Air Force Civil Engineer Center (AFCEC), formerly Air Force Center for Environmental Excellence. MacStat Consulting Ltd. and SAIC were tasked with software development, and designed the functionality, formulated algorithms for the decision framework and testing, and compiled the programming code as an open-domain resource. The software was developed to optimize long-term monitoring programs for both individual sites and entire installations having over 500 wells and sampling events spanning over 30 years of record.

Non-linear Trend Plots

Baseline (All Wells) vs Optimal Well Network Comparison

The software is designed to reduce monitoring redundancy by determining optimal sampling frequencies and identifying the optimal number and placement of wells. In addition, new sampling locations are proposed in areas of high spatial uncertainty to address gaps in network coverage. State-of-the-art statistical and geostatistical analytical routines are built-in to perform non-linear trend analysis (locally-weighted quadratic regression) and to generate concentration-based plume maps (quantile local regression) over multiple sampling events. A quasi-genetic algorithm identifies redundancy in the monitoring network and determines essential well locations.

Water Table Configuration Map
The software includes basic GIS capability and imports shape files of infrastructure, installation boundaries, or potentiometric data. Formal tests for trend (using Mann Kendall or Thiel-Sen nonparametric methods) are performed on all wells spanning: 1) the entire historical sampling record, 2) the last 4 years, and 3) the last 4 sampling events. Trend maps consolidate these trend tests to give a bird’s-eye view of where concentrations are increasing or decreasing at the site. One of the unique features of the software is the ability to generate and analyze concentration maps over distinct time periods (time slices) and vertical space (depth horizons). This capability analysis is helpful for developing conceptual site models and analyzing concentration patterns with respect to changing site conditions.

GTS also offers helpful exploratory tools for visualizing and summarizing important characteristics of groundwater data, including a relative ranking of chemicals and a comparison of distinct depth horizons. GTS allows import and tracking of new data to determine whether those values are consistent with previous trends and estimates of concentration maps.

GTS was designed to run in Windows XP but also runs in the Windows 7 PC environment. Operation in the Windows 8 platform has not been fully tested at this time but some success has been realized. The installation of GTS includes other open-source programs that perform or support statistical computing, data visualization, module navigation, and database management. These programs include: R, MatLab, SQLite, and QT (no additional installation is needed). Data are imported into GTS using a tab-delimited ASCII format. Visualization and tabular output is mostly HTML format but some reports are output as ASCII files.

Cost: Free
Software Requirements: Windows XP, Windows 7, pending testing on Windows 8
Level of Difficulty: Moderate to High

To ensure that the R statistical routines upon which GTS is built will work, a specific version of R (included in the GTS installation) must be used with the current version of GTS. GTS will not run if paired with a newer version of R than 2.10.1. However, multiple versions of R can co-exist and be run on a given computer, so that a newer or more current R version can be used for non-GTS purposes.

Download files here:

If you have trouble downloading the GTS files, please contact

The files are available as a compressed file. The compressed file includes:

  1. GTS setup and installation code
  2. User's Guide
  3. ASCII example data set
  4. ESTCP (Environmental Security Technology Certification Program) Report ER-0714, 2011

For more information about groundwater statistics, see the Groundwater Statistics and Monitoring Compliance (GSMC-1) document.