Improving catchment scale stream habitat models based on a runoff analysis: focusing on flow regime and spatial resolution

2021 Fiscal Year Final Research Report

• Project/Area Number: 19K15101
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 22040:Hydroengineering-related
• Research Institution: University of Miyazaki
• Principal Investigator: Nukazawa Kei 宮崎大学, 工学部, 准教授 (20725642)
• Project Period (FY): 2019-04-01 – 2022-03-31
• Keywords: 分布型流出モデル / 底生動物 / 気候変動 / 機械学習 / 流況改変

Outline of Final Research Achievements

We have developed a distributed runoff model that can accurately reproduce the flow rate in the Omaru River basin in southwest Japan. We then quantified fluctuations in river flow rate (flow regime alteration) due to dams and climate change on a basin scale. Furthermore, we are calibrating parameters to calculate the flow velocity and water depth on a fine spatial scale for the upper reaches of the Omaru River.
We collected data on benthic invertebrate communities at 82 sites in the Omaru River basin for 3 years, and constructed species distribution models by machine learning algorithms, random forest and gradient boosting. These models suggest that the distribution of benthic animals can be reproduced more accurately by using hydraulic variables and proxy indicators of flow regime alteration.

Free Research Field

河川生態学

Academic Significance and Societal Importance of the Research Achievements

開発された分布型流出モデルは高精度で流域全体の流量予測が可能である．これにより得られた，気候変動や河川整備に伴う広域での流量改変程度に関する知見は学界のみならず社会的に価値が高いと言える．さらに，詳細な水理変数を広域的に再現する試みは，世界的にもほとんど存在せず，新たな広域河川環境評価手法として学術的に意義深いと言える．
流域網羅的な底生動物群集データは流域管理の基礎データとして有益である．水理学的・水文学的変動を踏まえて河川生物の広域分布を予測する試みは存在せず，研究成果は学界においてインパクトが大きいと言える．