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

Abhishek Kumar, Christopher Cooper, Caren M. Remillard, Shuvankar Ghosh, Austin Haney, Frank Braun, Zachary Conner, Benjamin Page, Kenneth Boyd, Susan Wilde, Deepak R. Mishra

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)518-529
Number of pages12
JournalWeed Technology
Issue number3
StatePublished - Jun 1 2019
Externally publishedYes


  • Lake J. Strom Thurmond
  • Landsat 8 OLI
  • Secchi disk depth (SDD)
  • percentage of light available through the water column (PLW)
  • prediction tool
  • remote sensing

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