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Spatiotemporal monitoring of hydrilla [Hydrilla verticillata (L. f.) Royle] to aid management actions

Published online by Cambridge University Press:  16 May 2019

Abhishek Kumar Open the ORCID record for Abhishek Kumar [Opens in a new window] ,
Christopher Cooper ,
Caren M. Remillard ,
Shuvankar Ghosh ,
Austin Haney ,
Frank Braun ,
Zachary Conner ,
Benjamin Page ,
Kenneth Boyd  and
Susan Wilde
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Abhishek Kumar*
Affiliation:
Graduate Student, Department of Geography, and NASA DEVELOP National Program, University of Georgia, Athens, GA, USA
Christopher Cooper
Affiliation:
Graduate Student, Department of Geography, and NASA DEVELOP National Program, University of Georgia, Athens, GA, USA
Caren M. Remillard
Affiliation:
Graduate Student, Department of Geography, and NASA DEVELOP National Program, University of Georgia, Athens, GA, USA
Shuvankar Ghosh
Affiliation:
Graduate Student, Department of Geography, and NASA DEVELOP National Program, University of Georgia, Athens, GA, USA
Austin Haney
Affiliation:
Undergraduate Student, Warnell School of Forestry and Natural Resources, and NASA DEVELOP National Program, University of Georgia, Athens, GA, USA
Frank Braun
Affiliation:
Undergraduate Student, Warnell School of Forestry and Natural Resources, and NASA DEVELOP National Program, University of Georgia, Athens, GA, USA
Zachary Conner
Affiliation:
Undergraduate Student, Department of Environmental Studies and Sciences, Ithaca College, Ithaca, NY, USA, and NASA DEVELOP National Program, University of Georgia, Athens, GA, USA
Benjamin Page
Affiliation:
Graduate Student, Department of Geography, and NASA DEVELOP National Program, University of Georgia, Athens, GA, USA
Kenneth Boyd
Affiliation:
Natural Resources Specialist, US Army Corps of Engineers, Savannah District, Savannah, GA, USA
Susan Wilde
Affiliation:
Associate Professor, Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA, USA
Deepak R. Mishra
Affiliation:
Professor, Center for Geospatial Research, Department of Geography, University of Georgia, Athens, GA, USA.
*
*Author for Correspondence: Abhishek Kumar, Email: [email protected]
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Abstract

Hydrilla is an invasive aquatic plant that has rapidly spread through many inland water bodies across the globe by outcompeting native aquatic plants. The negative impacts of hydrilla invasion have become a concern for water resource management authorities, power companies, and environmental scientists. The early detection of hydrilla infestation is very important to reduce the costs associated with control and removal efforts of this invasive species. Therefore, in this study, we aimed to develop a tool for rapid, frequent, and large-scale monitoring and predicting spatial extent of hydrilla habitat. This was achieved by integrating in situ and Landsat 8 Operational Land Imager satellite data for Lake J. Strom Thurmond, the largest US Army Corps of Engineers lake east of the Mississippi River, located on the border of Georgia and South Carolina border. The predictive model for presence of hydrilla incorporated radiometric and physical measurements, including remote-sensing reflectance, Secchi disk depth (SDD), light-attenuation coefficient (Kd), maximum depth of colonization (Zc), and percentage of light available through the water column (PLW). The model-predicted ideal habitat for hydrilla featured high SDD, Zc, and PLW values, low values of Kd. Monthly analyses based on satellite images showed that hydrilla starts growing in April, reaches peak coverage around October, begins retreating in the following months, and disappears in February. Analysis of physical and meteorological factors (i.e., water temperature, surface runoff, net inflow, precipitation) revealed that these parameters are closely associated with hydrilla extent. Management agencies can use these results not only to plan removal efforts but also to evaluate and adapt their current mitigation efforts.

Keywords

Prashant Jha, Montana State UniversityHydrillaHydrilla verticillata (L. f.) RoyleLake J. Strom ThurmondLandsat 8 OLIpercentage of light available through the water column (PLW)prediction toolremote sensingSecchi disk depth (SDD)
Type
Research Article
Information
Weed Technology , Volume 33 , Issue 3 , June 2019 , pp. 518 - 529
Copyright
© Weed Science Society of America, 2019 

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