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Brady Couvillion

Publications and source records attributed to Brady Couvillion.

22 records · Page 2Linked to original sources
USGS2013

Spectroscopic remote sensing of the distribution and persistence of oil from the Deepwater Horizon spill in Barataria Bay marshes

We applied a spectroscopic analysis to Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) data collected from low and medium altitudes during and after the Deepwater Horizon oil spill to delineate the distribution of oil-damaged canopies in the marshes of Barataria Bay, Louisiana. Spectral feature analysis compared the AVIRIS data to reference spectra of oiled marsh by using absorption features centered near 1.7 and 2.3 μm, which arise from CH bonds in oil. AVIRIS-derived maps of oiled shorelines from the individual dates of July 31, September 14, and October 4, 2010, were 89.3%, 89.8%, and 90.6% accurate, respectively. A composite map at 3.5 m grid spacing, accumulated from the three dates, was 93.4% accurate in detecting oiled shorelines. The composite map had 100% accuracy for detecting damaged plant canopy in oiled areas that extended more than 1.2 m into the marsh. Spatial resampling of the AVIRIS data to 30 m reduced the accuracy to 73.6% overall. However, detection accuracy remained high for oiled canopies that extended more than 4 m into the marsh (23 of 28 field reference points with oil were detected). Spectral resampling of the 3.5 m AVIRIS data to Landsat Enhanced Thematic Mapper (ETM) spectral response greatly reduced the detection of oil spectral signatures. With spatial resampling of simulated Landsat ETM data to 30 m, oil signatures were not detected. Overall, ~ 40 km of coastline, marsh comprised mainly of Spartina alterniflora and Juncus roemerianus, were found to be oiled in narrow zones at the shorelines. Zones of oiled canopies reached on average 11 m into the marsh, with a maximum reach of 21 m. The field and airborne data showed that, in many areas, weathered oil persisted in the marsh from the first field survey, July 10, to the latest airborne survey, October 4, 2010. The results demonstrate the applicability of high spatial resolution imaging spectrometer data to identifying contaminants in the environment for use in evaluating ecosystem disturbance and response.

Louisiana↗
USGS2008

Coastal Louisiana ecosystem assessment and restoration program: The role of ecosystem forecasting in evaluating restoration planning in the Mississippi River Deltaic Plain

The development of ecosystem management plans to restore and rehabilitate natural resources requires an understanding of how specific ecological mechanisms regulate the structure and function of ecosystems. To achieve restoration goals, comprehensive plans and engineering designs must effectively change environmental drivers at the regional level to reduce stress conditions at the local environment that are responsible for ecosystem degradation. This document focuses on the Coastal Louisiana Ecosystem Assessment and Restoration (CLEAR) ecosystem forecasting framework and how it can be used to support the analysis of Louisiana’s coastal restoration plans. Specifically, the framework is designed to (1) develop and incorporate conceptual ecological models that can be used to integrate ecological needs and opportunities with engineering designs, (2) utilize wetland loss rates to describe the most likely “future without” scenario for a variety of ecosystem attributes, (3) estimate broad ecosystem responses to restoration alternatives based on processes associated with succession of geomorphic and ecological systems, and (4) calculate ecological benefits for incorporation into decision support tools associated with large-scale geomorphic and hydrologic processes. This paper provides a brief overview of the spatial framework and modular design of the CLEAR ecosystem forecasting framework and describes in greater detail the evolution of the landscape change module, concepts for its refinement, and how it was utilized in evaluating a coastal restoration alternative proposed in the Coastal Protection and Restoration Authority Preliminary Draft Master Plan. Such projections by the CLEAR forecasting framework can evaluate processes and conditions that result in sustainable coastal ecosystems with habitat functions that support higher trophic levels.

Louisiana↗
USGS2006

Data collection network to support ecosystem forecasting for the Barataria Basin - Mississippi River domain

Ecosystem forecasting is limited by a number of uncertainties including inadequate initialization information, unknown boundary conditions, inaccurate model physics and atmospheric forcing functions, and inadequate algorithm development of geomorphic and ecological responses to hydrodynamic and geophysical processes. Monitoring can help reduce these uncertainties by providing numerical information on those variables that can improve simulation capabilities. A data collection network was designed for the Mississippi River, south of Tarbert Landing, Ms. to Venice, La., and for the inland and nearshore waters of Barataria Basin, La. The network considered existing monitoring efforts that effectively link oceanographic and water quality observations to system drivers to support ecosystem hindcasting, nowcasting, and forecasting capabilities. The design was driven by the diverse needs of the modeling community and utilized questionnaire surveys, workshops, and web- based applications to inventory past and present modeling applications, domains, and attributes. The use of existing monitoring stations, including variables measured and frequency of data collection, were also considered, as well as recommendations on where new monitoring stations should be located, what types of data should be collected, and at what temporal frequency. Compiled databases are presented as a series of GIS layers to represent overlap between existing and requested stations, and priorities are established for either maintaining or augmenting existing stations or deploying new stations. An optimization plan will be prepared from the results of this study that will provide a rationale for the ecosystem forecasting data collection network that includes a description of existing monitoring programs to support ecosystem forecasting and a set of justifiable locations for "megastations" that meet the needs of the modeling and assessment communities.

Louisiana↗