Remote Sensing of Lake Water Quality

Project Description

Project Summary: 

Flathead Lake, located in northwest Montana, is one of the 300 largest natural freshwater lakes in the world, covering an area of 480 km2 with a maximum depth of 113 m. The Lake is oligotrophic, yet experienced an increase in eutrophication from 1977 to 2001, and two lakewide blooms of macroalgae in 1984 and 1994 that represented anomalous declines in water quality likely due to increasing nutrient inputs from anthropogenic sources. Summer field surveys in 2004 and 2005 showed surface chlorophyll-a levels from 0.1 to 0.9 mg m-3, Secchi depths of 1.5 to 17.0 m, and surface temperatures from 8.3 to 22.6 C. Depth profiles from surface to lake bottom were also obtained using a flourometer and transmissometer. We examined the potential utility of MODIS medium resolution (250m and 500m) data (bands 1-4) and 1km ocean bands (8-14) to monitor spatial and temporal fluctuations in lake productivity indicators including chlorophyll content and turbidity. Several alternative approaches for retrieving water quality parameters from the MODIS data were evaluated, including atmospherically corrected reflectance products, and single scattering corrected radiance data. The zone of peak chlorophyll content and turbidity is found to occur immediately above the thermocline at water depths from 15-20m, but with statistically significant linkages to surface conditions. Initial results indicate that the single scattering corrected radiance data provide the best prediction of chlorophyll-a, Secchi depth, and turbidity of the first 5m depth (r2 = 0.46 - 0.75), but these parameters often co-vary at specific times throughout the season, creating difficulties in applying a consistent algorithm. Two complete daily time series from May 1 to Sept 30, 2004 were created from the 500m reflectance product and the single scattering corrected data to assess the sensor’s ability to track lake fluctuations in water quality indicators. Mean daily lake reflectance values from these time series are found to be sensitive to both atmospheric particulate deposition and river discharge inputs at weekly to monthly time scales. Our results show the potential of MODIS for water quality monitoring, but also highlight the need for improved algorithms and products specific to large inland water bodies.

Estimated Secchi Depth for Flathead Lake derived from MODIS 500m resolution multispectral image data for July 28, 2004; results are compared against field sampling data collected on July 31, 2004.

Estimated Secchi Depth for Flathead Lake derived from MODIS 500m resolution multispectral image data for July 28, 2004; results are compared against field sampling data collected on July 31, 2004.

Secchi depth vs MODIS 500m reflectance ratio data over Flathead Lake.

Secchi depth vs MODIS 500m reflectance ratio data over Flathead Lake.

Publications

Publications: 

Jones, M.O., 2006. Application of MODIS for monitoring water quality of a large oligotrophic lake. M.S. Thesis, University of Montana, 363.61, J782a, 62 pp.

Jones, M.O., J. Kimball, S.W. Running, B.K. Ellis, and A.E. Klene, 2005. Application of MODIS for monitoring water quality of a large oligotrophic lake. Eos Trans. AGU, 85(52), B41A-0160