The complexity associated with water quality models (WQMs) has increased owing to the introduction of numerous physical and biological mechanisms in the models. Sensitivity analysis (SA) is conducted to identify influential parameters in these mechanisms. However, enormous computational power and time are required to obtain numerical solutions from thousands of model simulations. Therefore, a cloud-based toolbox is developed for performing SA of WQMs by implementing a cloud computing system using grab sampling data and hyperspectral images (HSI) of waterbodies. Cloud computing can provide high-performance computation by adjusting the scale of the computational power according to user preference. The developed toolbox with the cloud system can reduce the computation time for SA by approximately 20 times compared to that of a desktop computer.

由于在模型中引入了许多物理和生物学机制，与水质模型（WQM）相关的复杂性有所增加。进行敏感性分析（SA）以确定这些机制中的影响参数。但是，从数千个模型仿真中获得数值解需要大量的计算能力和时间。因此，通过使用抓取采样数据和水体的高光谱图像（HSI）实施云计算系统，开发了基于云的工具箱来执行WQM的SA。云计算可以根据用户的喜好调整计算能力的规模，从而提供高性能的计算。与台式计算机相比，带有云系统的开发工具箱可以将SA的计算时间减少大约20倍。