Ⅰ. Background and aims of research
oIt is necessary to systematize new water management by developing an integrated prediction model for water quality and biodiversity using artificial intelligence techniques. The development of such a model would induce improvement of integrated water management policy. Furthermore, a framework is needed to link and analyze the databases on water environment measurement which are currently operated separately. In addition, it is necessary to apply the integrated model to the establishment of water environment policy plans and the scoping and screening of environmental impact assessments, and to prepare a new convergence water environment evaluation system that can predict water environmental health at the watershed unit.

oThe water environment measurement network consists of a total of eight detailed measurement networks, including the water quality monitoring network, flow measurement network, and bio monitoring network, and shows the current status and data of the water environment. As of January 2022, the Ministry of Environment is operating 1,952 water quality monitoring networks and 3,883 bio monitoring networks. However, each measurement point of the representative water quality measurement network and bio network differs even in the same water system, so efficient and integrated water management is not achieved.

oCurrently, the water quality monitoring network and the bio monitoring network are operated separately , and the watershed health evaluation of the unit basins, medium-sized basins, and large basins is managed by measurem