Effect of hyperspectral image-based initial conditions on improving short-term algal simulation of hydrodynamic and water quality models. (15th September 2021)

• Record Type: Journal Article
• Authors: Pyo, JongCheol; Kwon, Yong Sung; Min, Joong-Hyuk; Nam, Gibeom; Song, Yong-Sik; Ahn, Jung Min; Park, Sanghyun; Lee, Jeongwon; Cho, Kyung Hwa; Park, Yongeun
• Is Part Of: Journal of environmental management. Volume 294(2021)
• Publication Date: 2021-09-15
• Subjects: Hydrodynamic and water quality model -- Hyperspectral image -- Initial condition -- Chlorophyll-a; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2021.112988
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: Hydrodynamic and water quality modeling have provided valuable simulation results that have enhanced the understanding of the spatial and temporal distribution of algal blooms. Typical model simulations are performed with point-based observational data that are used to configure initial and boundary conditions, and for parameter calibration. However, the application of such conventional modeling approaches is limited due to cost, labor, and time constraints that preclude the retrieval of high-resolution spatial data. Thus, the present study applied fine-resolution algal data to configure the initial conditions of a hydrodynamic and water quality model and compared the accuracy of short-term algal simulations with the results simulated using conventional point-based initial conditions. The environmental fluid dynamics code (EFDC) model was calibrated to simulate Chlorophyll-a (Chl-a) concentrations. Hyperspectral images were used to generate Chl-a maps based on a two-band ratio algorithm for configuring the initial condition of the EFDC model. The model simulation with hyperspectral-based initial conditions returned relatively accurate results for Chl-a, compared to the simulation based on point-based initial conditions. The simulations exhibited percent bias values of 9.93 and 14.23, respectively. Therefore, the results of this study demonstrate how hyperspectral-based initial conditions could improve the reliability of short-term algal bloom simulations in a hydrodynamic model. Graphical abstract: Image 1 Highlights: A hydrodynamic and water quality model was constructed in weir pools. Hyperspectral map-based initial condition was applied to a 3D numerical modeling. Hyperspectral-applied modeling showed better performance than the conventional one. Hyperspectral application provided improvement of short-term algal bloom simulation.