Surface Water Quality

I have explored water quality in lakes and reservoirs through the phenomenon of algae blooms. One way I have explored this is by looking at how patterns in chlorophyll concentrations (as a measure for algae biomass) have changed over time through remote sensing. This has involved developing empirical algorithms for detecting lake-surface chlorophyll concentrations in several lake and reservoir systems in central Utah. A major part of my analysis in these lakes involves looking long-term historical patterns, so I have focused on imagery from Landsat satellites*.

Hansen, Carly H., Steven J. Burian, Philip E. Dennison, and Gustavious P. Williams. "Evaluating historical trends and influences of meteorological and seasonal climate conditions on lake chlorophyll a using remote sensing." Lake and Reservoir Management (2019): 1-19.

        • There are increasing trends in extremes and variability of chlorophyll concentrations
        • Timing of peak chlorophyll is shifting earlier over the past three decades
        • Sensitivity to short and long-term climate conditions is highly localized
        • This work was referenced in a Deseret News article

Hansen, Carly, and Gustavious Williams. "Evaluating Remote Sensing Model Specification Methods for Estimating Water Quality in Optically Diverse Lakes throughout the Growing Season." Hydrology 5.4 (2018): 62.

        • Common bands/band combinations used in literature did not produce accurate results when used in empirical models for lakes and reservoirs in Utah. This is likely due to the unique physical, optical, and biological characteristics of these lakes and their algae populations.

Hansen, Carly, Steven Burian, Philip Dennison, and Gustavious Williams. "Spatiotemporal variability of lake water quality in the context of remote sensing models." Remote Sensing 9, no. 5 (2017): 409.

        • There is very little spatial variation over the scales corresponding with MODIS and Landsat imagery resolution.
        • Temporal variability depends on the lake.
        • The rapid decline in temporal autocorrelation in observations collected via field sampling suggests that the time-window for near coincident data must be shorter than has been used in other water remote sensing studies.

Hansen, Carly Hyatt, Gustavious P. Williams, Zola Adjei, Analise Barlow, E. James Nelson, and A. Woodruff Miller. "Reservoir water quality monitoring using remote sensing with seasonal models: Case study of five central-Utah reservoirs." Lake and Reservoir Management 31, no. 3 (2015): 225-240.

        • Even among reservoirs of similar size and geographical location, there were variations in the long-term trends in water quality observed through Landsat-based records.

I have also had the opportunity to work with others who have studied statistical patterns that can serve as early warnings indicators of shifts to hypereutrophic states. This involves analysis of high-frequency water quality monitoring data to determine what patterns are occurring prior to a major shift (e.g. from a non-bloom state to an algae bloom). These indicators could help monitoring agencies better prepare for and respond to water quality events as they happen.

Hansen, C H., Wilkinson, G., Burian, S. "Developing and Implementing an Early Warning System for HABs in Utah Lake" Association for the Sciences of Limnology and Oceanography: Planet Water. February 2019. San Juan, Puerto Rico

        • We applied common statistical measures from literature, (autocorrelation, standard deviation, and skew) for chlorophyll and dissolved oxygen to high-frequency monitoring records of Utah Lake. None of the measures were perfect indicators of an imminent bloom, and there was substantial variability in the patterns depending on the site and bloom event.

*There are lots of newer, more optimal sensors that are better geared for water quality applications. I'm constantly working to keep up with and explore these other options!