Geology topics

Bridget Seegers

Publications and source records attributed to Bridget Seegers.

4 recordsLinked to original sources

USGS2026

Cyanobacterial bloom occurrence and emergency department visits for asthma or wheeze, Wisconsin, 2017–2019

Background: Cyanobacterial harmful algal blooms (cyanoHABs) pose risks to human and animal health. Methods: We investigated the relationship between cyanoHABs and asthma or wheeze-related emergency department (ED) visits near three Wisconsin cities (Green Bay, Madison, and Oshkosh) during 2017–2019. CyanoHAB exposure was approximated using the Cyanobacterial Assessment Network remotely sensed satellite indicator of cyanobacterial biomass, a chlorophyl algorithm (Chl BS ) aggregated by water-adjacent ZIP Code Tabulation Areas (ZCTA), and distance weighted from the nearest waterbody. Weekly counts of ED visits for asthma or wheeze were aggregated by ZCTA. Poisson generalized linear models estimated the association between the weekly number of ED visits and weekly Chl BS, adjusting for maximum temperature, dewpoint, fine particulate matter (PM 2.5 ), month, and correlation within ZCTA. Results: During 2017–2019, 7,057 ED visits for asthma or wheeze occurred in the study area (42 ZCTAs). Peaks in Chl BS occurred between June and October, with higher values in Lake Winnebago and Lake Mendota compared to Green Bay. Chl BS was not associated with ED visits for asthma or wheeze (adjusted rate ratio = 1.00, 95% confidence interval = 0.99, 1.00), and the presence of onshore winds did not change this result. Monthly aggregations of ED visits and Chl BS showed a monotonic trend between increasing Chl BS and ED visits during July–September. Conclusion: This study demonstrates the utility of remote sensing data in environmental health research. Future studies could explore individual-level exposure and outcomes to refine health risks associated with cyanoHABs.

Wisconsin↗

USGS2022

A validation of satellite derived cyanobacteria detections with state reported events and recreation advisories across U.S. lakes

Cyanobacteria harmful algal blooms (cyanoHABs) negatively affect ecological, human, and animal health. Traditional methods of validating satellite algorithms with data from water samples are often inhibited by the expense of quantifying cyanobacteria indicators in the field and the lack of public data. However, state recreation advisories and other recorded events of cyanoHAB occurrence reported by local authorities can serve as an independent and publicly available dataset for validation. State recreation advisories were defined as a period delimited by a start and end date where a warning was issued due to detections of cyanoHABs over a state's risk threshold. State reported events were defined as any event that was documented with a single date related to cyanoHABs. This study examined the presence-absence agreement between 160 state reported cyanoHAB advisories and 1,343 events and cyanobacteria biomass estimated by a satellite algorithm called the Cyanobacteria Index (CI cyano ). The true positive rate of agreement with state recreation advisories was 69% and 60% with state reported events. CI cyano detected a reduction or absence in cyanobacteria after 76% of the recreation advisories ended. CI cyano was used to quantify the magnitude, spatial extent, and temporal frequency of cyanoHABs; each of these three metrics were greater ( r > 0.2) during state recreation advisories compared to non-advisory times with effect sizes ranging from small to large. This is the first study to quantitatively evaluate satellite algorithm performance for detecting cyanoHABs with state reported events and advisories and supports informed management decisions with satellite technologies that complement traditional field observations.

Harmful Algae↗

USGS2021

Satellites for long-term monitoring of inland U.S. lakes: The MERIS time series and application for chlorophyll-a

Lakes and other surface fresh waterbodies provide drinking water, recreational and economic opportunities, food, and other critical support for humans, aquatic life, and ecosystem health. Lakes are also productive ecosystems that provide habitats and influence global cycles. Chlorophyll concentration provides a common metric of water quality, and is frequently used as a proxy for lake trophic state. Here, we document the generation and distribution of the complete MEdium Resolution Imaging Spectrometer (MERIS; Appendix A provides a complete list of abbreviations) radiometric time series for over 2300 satellite resolvable inland bodies of water across the contiguous United States (CONUS) and more than 5,000 in Alaska. This contribution greatly increases the ease of use of satellite remote sensing data for inland water quality monitoring, as well as highlights new horizons in inland water remote sensing algorithm development. We evaluate the performance of satellite remote sensing Cyanobacteria Index (CI)-based chlorophyll algorithms, the retrievals for which provide surrogate estimates of phytoplankton concentrations in cyanobacteria dominated lakes. Our analysis quantifies the algorithms' abilities to assess lake trophic state across the CONUS. As a case study, we apply a bootstrapping approach to derive a new CI-to-chlorophyll relationship, ChlBS, which performs relatively well with a multiplicative bias of 1.11 (11%) and mean absolute error of 1.60 (60%). While the primary contribution of this work is the distribution of the MERIS radiometric timeseries, we provide this case study as a roadmap for future stakeholders' algorithm development activities, as well as a tool to assess the strengths and weaknesses of applying a single algorithm across CONUS.

Alaska, Minnesota↗

USGS2018

An initial validation of Landsat 5 and 7 derived surface water temperature for U.S. lakes, reservoirs, and estuaries

The United States Harmful Algal Bloom and Hypoxia Research Control Act of 2014 identified the need for forecasting and monitoring harmful algal blooms (HAB) in lakes, reservoirs, and estuaries across the nation. Temperature is a driver in HAB forecasting models that affects both HAB growth rates and toxin production. Therefore, temperature data derived from the U.S. Geological Survey Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus thermal band products were validated across 35 lakes and reservoirs, and 24 estuaries. In situ data from the Water Quality Portal (WQP) were used for validation. The WQP serves data collected by state, federal, and tribal groups. Discrete in situ temperature data included measurements at 11,910 U.S. lakes and reservoirs from 1980 through 2015. Landsat temperature measurements could include 170,240 lakes and reservoirs once an operational product is achieved. The Landsat-derived temperature mean absolute error was 1.34°C in lake pixels >180 m from land, 4.89°C at the land-water boundary, and 1.11°C in estuaries based on comparison against discrete surface in situ measurements. This is the first study to quantify Landsat resolvable U.S. lakes and reservoirs, and large-scale validation of an operational satellite provisional temperature climate data record algorithm. Due to the high performance of open water pixels, Landsat satellite data may supplement traditional in situ sampling by providing data for most U.S. lakes, reservoirs, and estuaries over consistent seasonal intervals (even with cloud cover) for an extended period of record of more than 35 years.

International Journal of Remote Sensing↗