Dynamic Response of the Freshwater Lens to Natural Variations in Recharge, Northern Guam Lens Aquifer
Wednesday, December 5, 2018: 11:00 a.m.
Exhibit Hall- C4 & C5 (Las Vegas Convention Center)
The Northern Guam Lens Aquifer (NGLA), is a deep karst limestone aquifer that supplies more than 90% of the island’s 45 MGD of potable water. As Guam prepares for economic growth, the growing demand for water is a major concern. The quantity of groundwater available for extraction can be measured in terms of the freshwater lens thickness. Lens thickness can be measured directly from well salinity profiles and inferred indirectly from water levels. The amount of recharge that replenishes the aquifer depends primarily on seasonal and inter-annual changes in rainfall as well as on the porous media properties, recharge, and discharge. The Yigo-Tumon Aquifer Basin, the most productive (21 MGD) of 6 aquifer basins in the NGLA, has 3 deep observation and 3 observation water level wells used in this study. Time series CTD data was evaluated in order to determine lens response to recharge and drought. A multi-variable time-series analysis was made to align possible communicative data from ONI, rainfall, and sea level to the phreatic graphs. Lag and attenuation of lens response to rainfall-recharge was examined to determine lens stability. The goal of this project was to interpret the response of the lens to natural climate variations, given the ongoing well production, through observation of temporal lens and saltwater transition zone dynamics in response to excess recharge and extensive drought. The single most important question is how much of rainfall constitutes effective recharge, actual groundwater recharge that thickens the freshwater lens. This research provides an empirical basis for estimating the percent of rainfall actually goes into lens storage under certain conditions. It provides an observational baseline for which the accuracy of past, present, and future modeling studies can be evaluated and by which future modeling studies can be reliably parameterized.