A machine learning model for detecting and quantifying tropical cyclone related disturbance and recovery in estuaries.

ABSTRACT: Tropical cyclones have a significant impact on estuaries, resulting in deteriorating water quality, changes in phytoplankton productivity, as well as scouring and physical harm to mangroves and other vegetation. Furthermore, they have the potential to impede, pause, or even reverse ecosystem restoration and management efforts. As such, it is crucial to devise methods for detecting and measuring the severity of estuarine disturbances caused by tropical cyclones. Several statistical methods have been proposed in the past to detect and quantify disturbances, with varying levels of complexity and accuracy. Recent advancements in data collection and the quality of high-frequency data have opened up the opportunity to employ machine learning models for assessing the impact of tropical cyclones o

SUBMITTER: Ibrar MA 

PROVIDER: S-EPMC11821897 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature