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<br />00843
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<br />of the water. the aqualic food base. and Ihe presence of warm backwater areas Ihal serve as fish
<br />habitats.
<br />
<br />3.1.1 Waler Parameters
<br />
<br />Waler Resources Division of the USGS collects and analyzes data from waler-gage
<br />stations and waler samples al various locations wilhin Lake Powell. the main channel. and within
<br />major !ribularies. From the tailwaters to Lees Ferry. remote moniloring stalions measure and
<br />transmit every four hours the sediment load, lurbidily. and waler temperature in the main channel.
<br />Monthly water samples are collected at river miles O. -3, -6, ,9, -II, and -16 and the samples arc
<br />analyzed for chlorophyll, phytoplankton, and zooplanklOn. Remole water monitoring stations
<br />also measure the above parameters at the same frequency wilhin several tribularies (Paria River.
<br />Shinumo Creek, Tapeats Creek, Spenser Creek, Havasu Creek, Kanab Creek. Bright Angel
<br />Creek, Little Colorado River, and Diamond Creek) and within Ihe main channel above the Glen
<br />Canyon dam, at Lee's Ferry, above Ihe Little Colorado River eon/luence, near Ihe Grand Canyon,
<br />above National Canyon, and aoove Diamond Creek. At Lake Powell, surveys are conducted
<br />quarterly (March, June, September, and December) 10 obtain profiles of water temperature and
<br />lurbidity at approximately twenty slations north of Glen Canyon Dam between river mile 2 to
<br />263. Water samples are also collected at some of these sites and are analyzed for chlorophyll,
<br />phytoplankton, and zooplankton.
<br />
<br />Numerous remote.sensing studies conducted within the last decade have developed
<br />algorithms to measure sediment load (as total suspended sediment), turbidity, chlorophyll a and b.
<br />total chlorophyll, and total dissolved solids (specific conductance), bul the depth of measurement
<br />is limited to the depth of light penetration and such measurements cannot determine variations
<br />with depth (e.g., Goodin el aI., 1993; McFeeters, 1996; George, 1997; Sathyendranath el aI.,
<br />1997; Fraser, 1998a. b; Tassan, 1998), Most studies determined that multiple wavelength bands
<br />within Ihe 0.420 I'm and 0.710 11m wavelength region are necessary to obtain accurate eSlimates
<br />and that the algorithms to estimate the water parameters require periodic verification of their
<br />calibration. This latter requirement might suggest that remote sensing cannot benefil aqualic
<br />monitoring because it cannot replace i1l situ measurements that are necessary for remote,sensing
<br />calibration. However, the real strength of remote sensing is not the elimination of field
<br />verification, but rather the extrapolalion of site- speci tic information to wide areas at a significant
<br />savings of time and cost. For example, the areal perspective provided by remote-sensing data can
<br />assist in determining the most representative sites for i1l situ measurement systems, which may
<br />not have been done for the existing water monitoring nelwork. Chavez et al. (1997) used
<br />temporal remote-sensing data acquired under different environmental conditions within Sa"-
<br />Francisco Bay to help water resource personnel determine the most appropriate sites for their i1l
<br />situ monitoring systems. In addition, remote-sensing data can be used to produce maps that show
<br />the distribution of particular parameters over large areas for a particular time period. I1I situ
<br />measurement syslems provide only point-source information. which might miss or misrepresent
<br />an event that has spatial variation. Remote-sensing algorithms that have been developed for lakes
<br />can map chlorophyll concentralions with a sensitivity of31'glI (George, 1997). Algorithms have
<br />been developed specitically for the Colorado River thai relate spectral radiance of Ihe water to the
<br />water's chlorophyll content, lurbidity. and suspended load. using waler-gage data for calibration
<br />(Chavez et ai, 2002a.b). The algorilhms can now be used 10 produce water-parameter maps for
<br />parts or all of the CRE using the multispectral camera thai Pal Chavez has purchased. whose
<br />bandwidlhs are optimized for mapping the aqualic environment; one component oflhis approach
<br />was recommended by the rcmote,sensing PEP (Berlin et aI., 1998).
<br />
<br />3.1.2 Aquatic Foodbase
<br />
<br />II
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