NewsDrop-June-2024

AQUIFER MANAGEMENT SERVICES (AMS) DIVISION OF THE EAA

By: Alyssa Balzen , EAA Geoscientist II THEN & NOW ADVANCING AQUIFER MANAGEMENT SERVICES 28 YEARS OF SCIENTIFIC EXPLORATION OF THE EDWARDS AQUIFER

A plethora of hydrologic data is collected, including aquifer levels, streamflow, rainfall (starting in 1998), weather parameters (starting in 2014), and soil moisture (starting in 2022). 141 of 150 total sites are actively monitored with telemetry. Continuous data, including depth to water, water temperature, and specific conductivity, are collected for 61 groundwater wells; 63 rain gauges collect hourly and one-minute increment rainfall data; 18 weather stations monitor air pressure, air tempera ture, relative humidity, solar radiation, dewpoint, wind average speed, maximum wind speed, wind direc tion and soil moisture sensors where available; and 7 spring/stream sites measuring stream gage height, specific conductivity, dissolved oxygen, water temperature, pH and turbidity. The total amount of data collected has increased exponentially since the inception of the EAA (Figure 3).

Figure 3. Total number of measurements collected by Data Management over time (figure/data provided by Bryan Anderson).

The Aquifer Management Services Division (AMS) of the EAA is responsible for data management, aquifer research, modeling, and aquifer sustainability initiatives. Over the past 28 years, AMS programs and the staff members implementing those programs have achieved several significant milestones and have adapted to meet new challenges. This article chronicles the evolution of these program areas from “then”, the EAA’s formal inception in 1996, to “now” in 2024 as AMS works to support the Next Generation concept— the EAA’s strategy to manage, enhance, and protect the aquifer now and for future generations.

AQUIFER SCIENCE RESEARCH & MODELING

Then: Aquifer responses were estimated using GWSIM (a numeric groundwater flow model) and projections under likelihood climatic conditions were generated using statistical analyses. Water samples were collected from springs, wells, and surface waters on a limited scale (Figure 4). The EAA relied on the USGS and Texas Water Development Board (TWDB) to collect and provide data for many samples. A basic water quality analysis, including some organic compounds, was conducted for water samples, and detection limits ranged in parts per million.

DATA MANAGEMENT

Photo 4. Matt Schwarz samples the San Marcos Springs-Hotel with San Antonio Express News and Aquifer Science intern Jake in 2014.

Now: To enhance our understanding, the EAA worked with the United States Geological Survey (USGS) and others to develop the MODFLOW model in 2004, which is a common computer model to simulate groundwa ter flow through aquifers. MODFLOW was further revised in 2017 to produce the version we use today. The amount of data that informed the develop ment of the MODFLOW model was significantly greater than was available for GWSIM, in large part due to EAA data collection and funding of research to characterize the aquifer. Future groundwater levels and spring flow under projected climatic condi tions are predicted using an EAA-revised version of MODFLOW, machine learning models, and climate data from Global Climate Models. The EAA

is investigating multiple modeling approaches, including machine learn ing, to enhance our understanding of the system. Machine learning models are used to fill in, curate and analyze data. Enhanced modeling capabilities allow for increased accuracy and reliability on highly nonlinear and multivar iate hydroclimatic problems and enables us to analyze the intensity, dura tion, and frequency of future potential hydrological droughts, effectiveness of existing conservation measures, aquifer recharge dynamics, groundwater levels, and spring flow patterns under various climate scenarios projected up to the year 2100, which would have been exceedingly challenging, if not unattainable, using previous approaches. The EAA is investigating multiple modeling approaches, including machine learning, to enhance our understanding of the system.

Figure 1. J-17 Well Chart Recorder.

Figure 2. Data logger and telemetry transmission equipment at a continuously monitored EAA well.

Then: When the EAA was formed in the mid-1990s, continuous collection of well water levels was accomplished through chart recorder devices (Figure 1), which resemble seismographs for measuring earthquakes. Chart recorders consist of a floating weight placed into the well, attached to a pul ley system, and then hooked up to the chart recorder. As the weight moves up and down with water level changes, the needle on the chart recorder moves in tandem, recording water levels on paper, which then must be converted into a usable data format. These recorders require frequent site visits for maintenance.

Now: Pressure transducers installed at a fixed depth in a well measure pressure in the water column above the transducer (Figure 2). Fluid pres sure is converted into an electrical signal and sent to a data logger, then transmitted via cellular service to EAA servers. Continuous water level data is collected in fifteen-minute intervals. Pressure transducers reduce maintenance labor and potential transcription errors.

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