Development of 3D temperature monitoring and predicting system in reservoirs using UAV

2022 Fiscal Year Final Research Report

• Project/Area Number: 20K04709
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 22040:Hydroengineering-related
• Research Institution: Tokyo Metropolitan University
• Principal Investigator: SHINTANI Tetsuya 東京都立大学, 都市環境科学研究科, 准教授 (80281244)
• Co-Investigator(Kenkyū-buntansha): 赤松 良久 山口大学, 大学院創成科学研究科, 教授 (30448584) ; 宮本 仁志 芝浦工業大学, 工学部, 教授 (50283867) ; 中山 恵介 神戸大学, 工学研究科, 教授 (60271649)
• Project Period (FY): 2020-04-01 – 2023-03-31
• Keywords: 閉鎖性水域 / 水温管理 / 風の非一様性 / 機械学習 / 数値シミュレーション

Outline of Final Research Achievements

This study was carried out to understand the spatial variation of surface water temperature, which is important for water quality management in reservoirs. First, an infrared UAV was used to capture infrared images of the lake surface to measure the distribution of water temperature on the surface, and then the images were combined using an image merging algorithm based on GPS and azimuth information of the UAV. Second, in order to estimate the non-uniform spatial distribution of wind that strongly affects the distribution of surface water temperature, we developed a wind estimation model based on deep learning system and improved the hydrodynamic model to enable the application of non-uniform wind. As a result, it was shown that non-uniform wind can be roughly estimated from wind speed data of a fixed point, and that the non-uniformity of wind affects mass transport.

Free Research Field

水工水理学

Academic Significance and Societal Importance of the Research Achievements

本研究で試みられた赤外線ドローンによる水面水温の空間的な計測は，鉛直水温分布計測と組み合わせることによって貯水池の水資源の良好な維持のための水温モニタリング手法の簡易化・高精度化に貢献するものと考えられる．また，同時に行った数値シミュレーションモデルの開発・改良によって，将来予想される気候変動に伴う水温変化を含め，水温予測の高精化を可能とし，今後の貯水地における水質管理に応用できるものであると考えられる．