Remotely sensed lake color measurements suggest strong seasonal yet limited multi-decadal trends in turbid and productive lakes in the Nebraska Sandhills
Daniel Gschwentner, Carly R. Olson, Jessica R. Corman
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引用次数: 0
Abstract
Long-term monitoring of lakes is necessary to detect and determine drivers of water quality impairment and ecological change. Yet extensive water quality records are limited to few lakes and are cost- and labor-intensive. In contrast, remotely sensed data such as the dominant wavelength, a measure of lake color, is an accessible water quality metric with high spatial and temporal coverage. We tracked changes in remotely sensed lake color across the understudied and data-poor Nebraska Sandhills, a turbid and eutrophic lake district, over three decades. We found that remotely sensed lake color exhibited strong seasonal variability and that changes in dominant wavelength related to climatic and groundwater controls in the Nebraska Sandhills although this relation weakened at local spatial scales. Surprisingly, long-term trends in remotely sensed lake color were rare, suggesting that intra-annual variation in lake color was more pronounced than inter-annual variation in Sandhill lakes. Our study suggests that the dominant wavelength (1) is a viable indicator of ecological change in lakes, (2) is capable of detecting seasonal variation in water quality even in turbid and eutrophic lakes, and (3) provides an opportunity to study mechanisms and rates of ecological change in lakes at multiple spatiotemporal scales and in understudied, data-poor regions.
期刊介绍:
Limnology and Oceanography (L&O; print ISSN 0024-3590, online ISSN 1939-5590) publishes original articles, including scholarly reviews, about all aspects of limnology and oceanography. The journal''s unifying theme is the understanding of aquatic systems. Submissions are judged on the originality of their data, interpretations, and ideas, and on the degree to which they can be generalized beyond the particular aquatic system examined. Laboratory and modeling studies must demonstrate relevance to field environments; typically this means that they are bolstered by substantial "real-world" data. Few purely theoretical or purely empirical papers are accepted for review.