Towards better environmental software for spatio-temporal ecological models: Lessons from developing an intelligent system supporting phytoplankton prediction in lakes

Implementing a case study using existing spatio-temporal ecological models could be time-consuming and error-prone. To alleviate this problem, several strategies, aiming to achieve a robust but easy-to-use environmental software, were used to develop an intelligent system supporting phytoplankton prediction in Lakes (iLake). This environmental software coupled three modules (a two-dimensional hydrodynamic module, a mass-transport module and a phytoplankton kinetics module) together to predict the time dynamics of phytoplankton distribution in a lake. A case study of phytoplankton prediction in Lake Taihu using iLake demonstrated its high potential, but low learning curve, for lake modeling.