In Lake Tana, Ethiopia, an overabundance of water hyacinth is causing a decline in biodiversity and degradation of the lake ecosystem. Using remote sensing technologies such as satellites and drones as well as local observation data, we will quantify the biomass of water hyacinth and create a growth prediction model. Based on the growth-prediction model, we aim to create a water hyacinth harvesting plan to protect the ecosystem of Lake Tana and develop an ICT-based water hyacinth management system in collaboration with the Amhara State government that manages the Lake Tana.

Lake Tana, the largest lake in Ethiopia, has an area of 3,000 km2, which is about 4.5 times the size of Lake Biwa. It is difficult to manage the entire lake by hand, so it is necessary to establish an ICT-based lake environment and water hyacinth management system. In order to correctly identify the amount of water hyacinth growing in the lake, satellite images and drones can be used to identify water hyacinth from other water plants, and streamflow meters can be used to study the extent to which water hyacinth is carried away by the wind. By estimating the amount of water hyacinth and creating a growth prediction model, we will be able to calculate annual harvesting targets. We will then develop a system that allows local people to check the environment of Lake Tana and the growth predictions of the mallow in order to manage the mallow resource sustainably.

Lake Biwa Environmental Research Institute： Kanako Ishikawa, Jiao Chunmeng, Youichiro Sakai, Cai Ji
Soka Universitys： Hiroki Imamura, Victor S. Kuwahara, Diego Alberto Herrera Ollachica

LTaOWPDA：Ayalew Wondie, Zelalem Liyew
Bahir Dar University：Solomon Addisu, Mulatie Mekonnen, Gatachew Bayable, Esubalew Tesfaye
Injibara University：Fentanesh Anemut, Yonas Derebe

Japanese Side：Mainly biomass estimation, construction of growth and harvesting model for water hyacinth
Ethiopian Side：Mainly field observation and harvesting plan development