In Maine, McCullough et al. [93] combined watershed characteristics with
Landsat data to assess the water clarity of ~1,500 lakes. This approach was also
used to investigate temporal trends in water clarity [94], which found that water
clarity declined in Maine’s lakes during the 1995–2010 period.
4.1.1 Remote Sensing of Great Lakes Water Clarity
The Great Lakes are a good example of water resources for which remote sensing
has been used to compensate for the paucity of in situ data. Binding et al. [95]
showed the advantage of remote sensing over ground-based monitoring with
substantial increase in spatial and temporal coverage. Results using CZCS for the
1979–1985 period and the SeaWiFS for the 1998–2006 period showed seasonal and
interannual variability in SD due to phytoplankton blooms, resuspension of bottom
sediments, and whiting events. The satellite observations document how long-term
impacts can be monitored. The findings indicate that the reduction of nutrient
loading and particulate removal by the introduction of zebra mussels through filter
feeding significantly changed water clarity for Lake Erie and Lake Ontario. For
Lake Erie, SD increased in the eastern basin but decreased in the western basin. SD
in Lake Ontario more than doubled to > 4 m after the introduction of zebra mussels.
The study also indicated a reduction in the frequency and intensity of whiting
events due to the effects of calcium uptake by increased mussel populations.
4.2 Geospatial and Temporal Analysis of Minnesota’s
10,000 Lakes
Landsat imagery provides a reliable method to obtain comprehensive spatial and
temporal coverage of an important water quality variable, water clarity. Traditional
ground-based monitoring programs generally target larger recreational lakes and
thus are not randomly selected. Using such data to extrapolate to the larger
population could lead to biased conclusions [89]. Fortunately, the use of such
data to calibrate Landsat imagery for regional assessments allows for the entire
population to be studied.
In Minnesota the water clarity database for more than 10,500 lakes for time
periods centered around 1985, 1990, 1995, 2000, and 2005 was analyzed statistically for spatial distributions, temporal trends, and relationships with morphometric
and watershed factors that potentially affect lake clarity [89]. The analysis found
that water clarity is lower in southern and southwestern Minnesota and clearer in
the northern and northeastern portions of the state. Temporal trends were detected
in ~11 % of the lakes with 4.6 % having improving clarity and 6.2 % decreasing
clarity. Small and shallow lakes appeared to be more susceptible to decreasing
clarity trends than large and deep lakes. Deep lakes generally had higher clarity
Remote Sensing for Regional Lake Water Quality Assessment: Capabilities and. . .
133
Landsat data to assess the water clarity of ~1,500 lakes. This approach was also
used to investigate temporal trends in water clarity [94], which found that water
clarity declined in Maine’s lakes during the 1995–2010 period.
4.1.1 Remote Sensing of Great Lakes Water Clarity
The Great Lakes are a good example of water resources for which remote sensing
has been used to compensate for the paucity of in situ data. Binding et al. [95]
showed the advantage of remote sensing over ground-based monitoring with
substantial increase in spatial and temporal coverage. Results using CZCS for the
1979–1985 period and the SeaWiFS for the 1998–2006 period showed seasonal and
interannual variability in SD due to phytoplankton blooms, resuspension of bottom
sediments, and whiting events. The satellite observations document how long-term
impacts can be monitored. The findings indicate that the reduction of nutrient
loading and particulate removal by the introduction of zebra mussels through filter
feeding significantly changed water clarity for Lake Erie and Lake Ontario. For
Lake Erie, SD increased in the eastern basin but decreased in the western basin. SD
in Lake Ontario more than doubled to > 4 m after the introduction of zebra mussels.
The study also indicated a reduction in the frequency and intensity of whiting
events due to the effects of calcium uptake by increased mussel populations.
4.2 Geospatial and Temporal Analysis of Minnesota’s
10,000 Lakes
Landsat imagery provides a reliable method to obtain comprehensive spatial and
temporal coverage of an important water quality variable, water clarity. Traditional
ground-based monitoring programs generally target larger recreational lakes and
thus are not randomly selected. Using such data to extrapolate to the larger
population could lead to biased conclusions [89]. Fortunately, the use of such
data to calibrate Landsat imagery for regional assessments allows for the entire
population to be studied.
In Minnesota the water clarity database for more than 10,500 lakes for time
periods centered around 1985, 1990, 1995, 2000, and 2005 was analyzed statistically for spatial distributions, temporal trends, and relationships with morphometric
and watershed factors that potentially affect lake clarity [89]. The analysis found
that water clarity is lower in southern and southwestern Minnesota and clearer in
the northern and northeastern portions of the state. Temporal trends were detected
in ~11 % of the lakes with 4.6 % having improving clarity and 6.2 % decreasing
clarity. Small and shallow lakes appeared to be more susceptible to decreasing
clarity trends than large and deep lakes. Deep lakes generally had higher clarity
Remote Sensing for Regional Lake Water Quality Assessment: Capabilities and. . .
133