**[Topic List:]{.underline}**

1.  Remote Sensing Lake Tahoe's Water Quality -- Simon Hook

2.  New CalTrans Oil and Grease Measurement Method -- Masoud Kayhanian

**[Topic Summaries:]{.underline}**

**Remote Sensing Lake Tahoe's Water Quality -- Simon Hook**

Since he came up from Pasadena, CA to make his presentation, Simon has
won our award for greatest distance traveled to speak to LTIMP. His
presentation was well attended and very interesting to many of us. He
began by describing NASA's reasons for choosing Lake Tahoe to validate
the remote measurements made by several satellites (ASTER,MODIS, and
several Landsats). These satellites measure the radiance reflected by or
emitted from the surface which can be used to determine the surface
reflectance, emissivity and temperature, which could be used to
determine several water quality parameters in the future. The remotely
measured quantities were calibrated to a series of buoy-mounted
instruments that have been making frequent in-situ measurements since
1999. The remote measurements are now capable of measuring within 0.5%
of the in-situ values. Another significant benefit of these validation
studies is that they now provide high-frequency in-situ data (2 min.
intervals) that can be used for a variety of other research.

The extraordinary sensitivity and scope of these satellite-instruments
makes them excellent for observing the big picture of some of Tahoe's
hydro-dynamics and water quality parameters. Simon showed impressive
temperature maps that depict the flow-patterns caused by Tahoe's
periodic upwellings. He also described a methodology for determining the
near shore clarity of the lake. This seems potentially very useful and
elicited many questions and comments from the group. He also discussed
the limitations of the method which include the need for clear weather,
bottom substrate differences, and more. Simon's next few slides
described a possible method to determine deep water clarity
measurements. This is being done in other areas, but has never been
tried here. In particular he showed a slide of lakes in Minnesota that
are currently being monitored for Secchi Depth many lakes at a time.
These techniques would demand empirical models to be effective and would
not be likely to replace TRG's in-situ Secchi Depth measurement program.
In fact, Simon's main theme throughout the presentation was that
remotely sensed information is excellent for large-scale views but is
best used in combination with in-situ instruments that provide detail
and calibration measurements. In his last few minutes Simon showed an
animation of drogues that are explaining Lake Tahoe's prevailing
currents and a crowd-pleasing map of "thermal scaring" from boat wakes
crossing the Lake. Take a look at
[[http://laketahoe.jpl.nasa.gov]{.underline}](http://laketahoe.jpl.nasa.gov/)
for the field data that is being collected in near real time, and
further information about the JPL's efforts at Lake Tahoe.

**A New Method to Measure Oil and Grease Concentration from Roadway
Runoff -- Masoud Kayhanian\
**Masoud took a break from his CalTrans funded work down at UC Davis to
explain a few of his team's latest findings to LTIMP.  The main research
focused on oil and grease (O&G) sampling.  Since it is difficult to gain
representative samples of O&G using an autosampler, Masoud's team had
been trying to determine:\
1.    if there is an optimum time to take a grab sample during an
event;\
2.    if O&G event mean concentrations (EMCs) can be estimated from
storm specific variables; and\
3.    if there is a relationship between O&G and COD or DOC.\
 \
The data for this study was collected (as part of the CalTrans' First
Flush Characterization Study) from three sites in southern California
over a three year period. \
          The first question was answered by analyzing the errors and
bias associated with a series of grab samples taken during the entire
event.  The analysis showed that the "best" time to take a sample was:\
 \
**Best sample time for O&G= 43.53 + 1.21(Total Rainfall (in.)) +
2.55(storm duration (hrs.))\
** \
This analysis provided an r-squared error of 0.78.  Typical rain events
were 8 hours in this study.  This analysis concluded that samples should
not be taken at the early or the late stage of an event. \
 \
            The second question regarding an estimate of O&G EMC from
storm variables includes a log transformation to minimize error.  The
equation determined was:\
 \
**Log (O&G~EMC~) = 0.37 + 0.64\*log(antecedent dry days) -
0.17\*log(total rainfall (in.))\
 \
**This analysis provided a r-squared error of 0.86.\
 \
            The third question was finding relationship between O&G to
other organic related constituents such as Chemical Oxygen Demand (COD)
or Dissolved Organic Carbon (DOC).  The most accurate relations Masoud
presented  include:\
 \
**O&G~EMC~= 3.705 + 0.037 COD~EMC\
~**and,\
**O&G~EMC~= 0.15 + 0.28 DOC~EMC\
~** \
Both of these relations were shown to have r-squared errors of 0.90. 
These relationships are particularly interesting because DOC and COD are
both measurable with standard autosampling techniques.  This method of
estimating O&G concentration could eliminate potentially misleading grab
sampling and reduce personnel costs.\
            Masoud concluded by recommending technique 3 as the best
estimate, technique 2 as the next best method, and technique 1 as the
least preferred method.  He cautioned that these relations should be
tested on a national (or Lake Tahoe regional) basis before these methods
should be fully accepted for universal application.  Masoud kindly
offered to come to LTIMP in the future and present other work including
information on the impacts of Annual Average Daily Traffic on highway
runoff and Dynamics of Highway Runoff Particle Size Distribution.

In Attendance:

Nancy Alvarez, USGS\*

Chris Anderson, Mactec

Larry Benoit, TRPA

Chris Bowles, PWA\*

Gerald Bowden, USGS

Nancy Carter, Entrix\*

Chris Conway, KJ Cons.

Mike Elam, TRPA

Robin Eppard, RCI

Vern Finney, NRCS

Michelle Gamble, AMEC

Mark Gookin, Wood Rodgers\*

Hamid Hakim, CalTrans\*

Michelle Kramer, WET Lab\*

Jack Landy, Lahontan

Chad Praul, NTCD\*

Bob Richards, TRG

Brent Richmond, TRPA

Mike Strobel, USGS

Rick Susfalk, DRI\*

Chris Twomey, c2me\*

David Vacarello, Placer Co.

Rita Witney, TRPA\*

Russ Wigart, CSLT

Matthew Setty, KJ Consultants

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