日本地球惑星科学連合2025年大会

講演情報

[E] ポスター発表

セッション記号 A (大気水圏科学) » A-HW 水文・陸水・地下水学・水環境

[A-HW24] Human- and Climate-induced variability in water cycle and (sub)surface water resources

2025年5月26日(月) 17:15 〜 19:15 ポスター会場 (幕張メッセ国際展示場 7・8ホール)

コンビーナ:Abhishek Abhishek(Indian Institute of Technology Roorkee)、ZHAO WENPENG(Yangzhou University)、Yadav Brijesh Kumar(Indian Institute of Technology Roorkee)、Kinouchi Tsuyoshi(東京科学大学)

17:15 〜 19:15

[AHW24-P03] The Evaluation of Global Micro-Hydropower Potential

*Cai-Rou Chen1、Hua-San Shih1、Yung-Yu Fang1、Hsin-Wen Pai1Yuan-Chien Lin1 (1.Department of Civil Engineering, National Central University)

キーワード:Micro-Hydropower, Renewable Energy, Python-Based Geographic Information System

Traditional hydropower requires the construction of large-scale infrastructure such as reservoirs and dams, which have significant environmental impacts. As a result, many countries have ceased building new dams, directly leading to stagnation in hydropower development over the past decade. However, micro-hydropower technology eliminates the drawbacks of traditional hydropower by utilizing existing irrigation channels or natural waterways and designing modular units like solar panels, thereby reducing the negative impact on the environment. At the same time, micro hydropower systems are convenient and can be widely installed to make more efficient use of surface water resources. They can also complement solar power, providing an alternative renewable energy option that can generate clean energy during both dry and wet seasons.
Therefore, understanding the potential of micro-hydropower in different regions will provide important references for the future installation of related systems. This study aims to operate on a global scale, combining terrain elevation, water level elevation data from remote sensing satellites, and global historical rainfall data. It also simulates various climate scenarios, such as typical conditions, climate change, and extreme climate change scenarios, to assess and predict global micro-hydropower potential. The study integrates spatial data mining methods with Python-based geographic information system (GIS) overlays, and the resulting global micro hydropower potential assessment maps will help increase the coverage of hydropower in the future. This approach will enable self-sufficiency similar to solar power, reduce the cost of installing electrical grids, and ultimately achieve the goal of affordable and clean energy.