Prototyping a numerical model coupled with remote sensing for tracking harmful algal blooms in shallow lakes

In this paper, we present the design, development and test cases of LakeM, a software package for modeling the transport pathways of harmful algal blooms in shallow lakes. LakeM integrates implementation of numerical methods and data visualization for the purpose of facilitating the communication between modelers and decision makers. By making use of Finite Difference Method, LakeM is able to numerically solve the Shallow Water Equations on a staggered grid. The core of LakeM consists of two modules, the hydrodynamic and tracer module, which are run separately. The hydrodynamic module simulates the surface level and water movement, and the tracer module simulates the movement of harmful algal blooms subject to advection and dispersion processes. Most of the LakeM programs are developed based on the Python language in an object-oriented fashion, which can be readily adapted to changing requirements. Computationally intensive programs are written in Fortran routines for interoperating with Python. Model validation is performed by comparing model predictions to analytical solutions. Additionally, the capability and effectiveness of LakeM are illustrated by a case study of modeling algal bloom transport in Taihu Lake. The results have shown good agreements with analytical solutions and available remote sensing images. The model is efficient, robust, and can be used to aid environmental managers in developing emergency response actions for HABs. Besides that, the development of LakeM offers a design pattern for future model development efforts in tracking HABs. (C) 2020 Published by Elsevier B.V.