User Profile: John Lehrter
Who Uses NASA Earth Science Data? John Lehrter, to study the water quality of estuarine and coastal environments
Research interests: Estuarine and coastal nutrient biogeochemistry and ecosystem responses to nutrient loading.
Current research focus: NASA’s Applied Sciences Program funded a recently completed five-year research effort in which Lehrter and his colleagues developed new methods to retrieve water quality information in estuarine and coastal environments from satellite observations. The objective of this research was to integrate remote sensing technologies into water quality assessment and standards development decisions by water-quality management organizations, including the U.S. EPA and the State of Florida. Building upon this work, new efforts include developing and applying satellite data products for managing water quality across the nation.
Current research by Lehrter also includes observing and modeling coastal ecosystem response and recovery to nutrient loading. These models are used to predict the impacts to water quality and aquatic life from land-based nutrients and other local and global factors that can create stress on aquatic environments.
Data products and analysis tools used:
- Moderate Resolution Imaging Spectroradiometer (MODIS) (1km) ocean color products available through the Ocean Biology Distributed Active Archive Center (OB.DAAC) (doi: 10.5067/TERRA/MODIS_OC.2014.0 [Terra] and doi: 10.5067/AQUA/MODIS_OC.2014.0 [Aqua])
- Processing tools provided in the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) Data Analysis System (SeaDAS) through the OB.DAAC (http://seadas.gsfc.nasa.gov/)
- Tropical Rainfall Measuring Mission (TRMM) data products available through the Goddard Earth Sciences Data and Information Services Center (GES DISC)
- Visualized TRMM data products available through the GES DISC TRMM Online Visualization and Analysis System (TOVAS)
- Sea surface temperature and sea surface topography (altimetry) data from multiple NASA and NOAA satellites available through the Physical Oceanography DAAC (PO.DAAC)
- MODIS hi-resolution band data (250m [MOD02QKM] and 500m [MOD02HKM]) available through the Level 1 and Atmosphere Archive and Distribution System DAAC (LAADS DAAC)
- European Space Agency Medium Resolution Imaging Spectrometer (MERIS) data (300m)
- Landsat imagery (30m)
Research findings: Areas with higher nutrients can lead to blooms of phytoplankton and other small organisms that, in turn, consume oxygen in these areas, leading to the death of other organisms. These areas are described as being eutrophic or hypoxic. Lehrter and his colleagues used remote sensing time-series to better understand the contributions of Mississippi River nutrient loading to eutrophication and hypoxia, and were the first to observationally relate nutrient loads to remotely-sensed phytoplankton biomass and the contributions of this to hypoxic areas. This is a key metric used by the Mississippi River/Gulf of Mexico Hypoxia Task Force to manage Mississippi River nutrient loads. Research by Lehrter and his colleagues also demonstrated the usefulness of remote sensing data for developing numeric water quality standards for nutrients and for assessing water quality in estuarine and coastal settings.
Read about the research:
Le C., Lehrter J.C., Hu C., Murrell M.C. & Qi L. 2014. “Spatiotemporal chlorophyll-a dynamics on the Louisiana continental shelf derived from a dual satellite imagery algorithm.” Journal of Geophysical Research: Oceans 119(11): 7449-7462 [doi: 10.1002/2014JC010084].
Lehrter J.C., Ko D.S., Murrell M.C., Hagy J.D., Schaeffer B.A., Greene R.M., Gould R.W. & Penta B. 2013. “Nutrient distributions, transports, and budgets on the inner margin of a river-dominated continental shelf.” Journal of Geophysical Research: Oceans 118(10): 4822-4838 [doi: 10.1002/jgrc.20362].
Schaeffer, B.A., Hagy, J.D., Conmy, R.N., Lehrter, J.C. & Stumpf, R.P. 2012. “An approach to developing numeric water quality criteria for coastal waters using the SeaWiFS satellite data record.” Environ. Sci. Technol., 46(2): 916–922 [doi: 10.1021/es2014105].
Published December 31, 2015
Last Updated: Oct 18, 2019 at 12:36 PM EDT