Introduction

This document includes a collection of web maps that present information related to the optimization of water-quality monitoring in the eastern Snake River Plain aquifer beneath the Idaho National Laboratory and vicinity. A web map is an interactive display of geographic information that is powered by the web. Interactive panning and zooming allows for an explorative view of the study area. Clicking on a marker icon at a well site location will bring up a window with details about the site and (or) sampling data. The dynamic base maps are provided by The National Map and displayed in a WGS 84 / Pseudo-Mercator (EPSG:3857) coordinate reference system.


Location of Monitoring Wells

Figure 1.1. Location of sampling sites in the U.S. Geological Survey aquifer water-quality monitoring network, Idaho National Laboratory and vicinity, Idaho, 1989–2018.


Optimal Sampling Sites

Figure 1.3. U.S. Geological Survey aquifer water-quality monitoring network after removing 10, 20, 30, 40, and 50 optimally selected wells, Idaho National Laboratory and vicinity, Idaho. A island parallel genetic algorithm was used to preserve spatial accuracy and long-term temporal trends in the reduced monitoring network.


Historical Sampling Frequencies

Figure 1.4. Sampling sites were partitioned into three categories based on their median sampling interval during the time period from 1989–2018. A continuous-record site is a sampling site where data were collected on a regularly scheduled basis—sampling frequency may be one or more times monthly, quarterly, semiannually, or annually. A partial-record site is a sampling site where limited water-quality data were collected over a period of years. And a no-record site is a sampling site where groundwater samples were collected and the substance was never analyzed for.


Optimal Sampling Intervals

Figure 1.5. Increase in the sampling interval for selected constituents at wells in the U.S. Geological Survey aquifer water-quality monitoring network, Idaho National Laboratory and vicinity, 1989–2018. An increase in the sampling interval is expressed as the percent change between historic and optimized sampling intervals. An iterative thinning approach was used to identify the optimal sampling interval that may be used for future long-term monitoring, one that reduces temporal redundancy.