Download Cheaper, Easier, and Better Tools for Characterizing Receiving

Cheaper, Easier, and Better
Tools for Characterizing
Receiving Water Environments
Julie Padilla
LimnoTech
MWEA 2016
Why Do We Care?—Climate Change
• Increasing water streamflow nation-wide.
Decreasing streamflows in the West,
Southeast, and Northwest.
• Increasing surface water temperatures.
…….thermal discharge challenges.
• Variable precipitation and temperature
influence hydrology and water temperature
over decadal and multi-decadal scales.
• Landscape changes alter surface flow
volume, timing, magnitude, and quality and
groundwater leading to decreasing
baseflows and/or increasing stream
temperatures.
Why Do We Care?—Current Permitting
NPDES Permit Writers’ Manual:
Inclusion of Climate Change
Considerations
“…climate change could alter historical
flow patterns …making these
historical flow records less accurate
in predicting current and future
critical flows. Where appropriate,
water quality modelers should
consider alternate approaches to
establishing critical low flow
conditions…”
https://www3.epa.gov/npdes/pubs/pwm_2010.pdf
Why Do We Care?—Future Compliance
These principles are demonstrated by tools
such as:
• public accountability through increased
transparency of compliance data,
• electronic reporting,
• advanced pollutant monitoring for point
source discharges,
• ambient monitoring in water bodies,
both upstream and downstream from
dischargers, and
• third-party verification of compliance
with environmental requirements.
http://www2.epa.gov/compliance/next-generation-compliance
Expectations are high and compliance
burdens are heavy and costly!
How are we incorporating new
technologies, existing data,
and new shared information?
So Many New Tools, Applications, and
Resources
• Remote sensing
• GPS
• GIS
• Data collection/storage
• Modeling physical
environment
• Data collection/storage
• Data management
Remote Sensing
The collection of information about an object
without being in direct physical contact with it
NOAA
NOAA
LimnoTech
Remote Sensing
The collection of information about an object
without being in direct physical contact with it
• Fine-scale spatial data
• Challenging to develop
algorithms to translate raw
data into useful units
NOAA
Remote Sensing
http://www.greatlakesremotesensing.org/
Remote Sensing—LiDAR
• Precise 3-D
information about
Earth’s surface
• Land surface or
bathymetry data
• Requires clear
water
LimnoTech
NOAA
Remote Sensing—Buoys
LimnoTech
http://www.ndbc.noaa.gov/
Open Access Water Quality Data
http://www.waterqualitydata.us/
Open Access Water Quality Data
http://glos.us/
Open Access Water Quality Data
http://waterdata.usgs.gov/
Open Access Water Quality Data
http://glos.us/
Case Studies
#1
316(a) Point Source
Thermal Discharge for a
Lake Erie Power Plant
#2
Monitoring Lake Erie
Harmful Algal Blooms
Example #1: Lake Erie Power Plant
Example #1: Lake Erie Power Plant
Field
Thermal Infrared Imaging
Buoy
Example #1: Lake Erie Power Plant
Example #2: Lake Erie Harmful Algal
Blooms (HABs)
http://habs.glos.us/map/
(Near Real-Time) Data  Decision
(Near Real-Time) Data  Decision
(Near Real-Time) Data  Decision
(Near Real-Time) Data  Decision
(Near Real-Time) Data  Decision
Thanks
Doug Bradley
Ed Verhamme
Hans Holmberg
Tad Slawecki
Questions?