Year Established: 2015 Start Date: 2015-03-01 End Date: 2016-02-29
Total Federal Funds: $22,429 Total Non-Federal Funds: Not available
Principal Investigators: John Jenson, Nathan Habana, Mark Lander
Abstract: The Northern Guam Lens Aquifer (NGLA) provides 80% of Guams drinking water. The anticipated addition of US Marine Corps activities will require additional production, while ongoing economic growth will increase demand as well. Policy-makers and water managers have begun asking what is the absolute maximum volume of water that could be sustainably withdrawn from the aquifer? Answering such a question requires identifying (1) the natural limits on aquifer recharge, storage, and water quality imposed by climatic and geologic conditions, (2) , but doing it for an ideal production system, i.e., one that is constructed and operated so as to achieve the maximum possible production for a given standard of quality. This study is therefore directed at estimating the maximum potential capacity of the NGLA, i.e., the capacity that ultimately could be achieved by an ideal production system, given what we currently know or must assume about the natural limiting conditions. Recent modeling has incorporated the current state of knowledge regarding natural conditions and constraints. Estimates of maximum potential capacity can now be made by exploring scenarios in which hypothetical well depths, locations, and pumping rates are distributed so as to maximize the capacity for given upper limits of chloride. This study will thus help provide some estimates of the absolute upper limits of production that could, in principle, be achieved by an optimum system. These will provide ultimate baselines against which to make economic evaluations of future options for holistic sustainable management of the aquifer. Methods: The principal investigators will lead a research team composed of themselves, a WERI research associate trained in modeling, and WERI-based graduate and undergraduate research assistants (UOG environmental science MS candidate), working in collaboration with colleagues at the USGS Pacific Islands Water Science Center (PIWSC) to assemble and prepare the data sets; identify climatic phenomena and geologic features that are most likely to exert significant control on rainfall amount and intensity, infiltration rates, aquifer storage, groundwater flow, and groundwater salinity on northern Guam; and apply statistical, geospatial, and other analytical tools to identify, characterize, and interpret past and present spatial patterns in rainfall, groundwater levels, specific conductivity, chloride concentrations, and production rates from existing wells within the NGLA. The team will develop scenarios to identify ideal configurations (i.e., configurations not limited by economic, social, legal, or other non-natural factors) of well distribution and spacing, depth, and pumping rates that could thus in principle maximize production from the aquifer for specified limits on saltwater content. Scenarios will also examine how the ideal configuration might also respond to different long term climatic conditions. Objectives: The objectives of the respective phases of this project are: 1) Data acquisition and literature review of published and emerging research on spatial and temporal distributions and trends of rainfall and salinity in the NGLA by WERI, USGS and others; 2) Study of meteorological and geological phenomena that might control or influence the observed rates and amounts of rainfall, infiltration, storage, flow, and salinity; 3) Analyses of spatial and time-series data on rainfall, groundwater levels, specific conductivity, chloride concentrations, and production rates from existing wells within the NGLA; 4) Application of a groundwater model to estimate the maximum production that could be attained from an optimum set of strategically spaced shallow-draft vertical wells producing at specified maximum acceptable values of salinity, under specified natural conditions (e.g., long-term average rainfall, vs. historic wet and drought conditions); and 5) Development of a production function that estimates the relationships between quantity and quality that might be produced by an ideal production system (i.e., one that would produce maximum quantity for a given quality or maximum quality for a given quantity.