Improvement of real-time flood prediction with satellite images and high resolution climate data

2015 Fiscal Year Final Research Report

• Project/Area Number: 25420519
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Hydraulic engineering
• Research Institution: Gifu University
• Principal Investigator: Kojima Toshihaur 岐阜大学, 流域圏科学研究センター, 准教授 (90346057)
• Project Period (FY): 2013-04-01 – 2016-03-31
• Keywords: 林内水収支 / 樹冠疎密度 / 季節変動 / 降雨遮断モデル / 高解像度植生分布

Outline of Final Research Achievements

It is investigated to improve the estimation method of rainfall interception in order to improve a real-time flood prediction model with phenology by satellite images. The rainfall interception model with phenology information by MODIS NDIV images is developed. However the interception model with phenology information does not indicate better performance than another model with annual averaged crown densities distribution. It is suggested that canopy interception is not much affected by seasonal changes of canopy structures rather than other factors and the model is not suitable for real-time simulation. On the other hands, the produced interception model indicates better performance to estimate the interception loss with annual averaged crown densities information. It is suggested that the model is suitable to evaluate a typical interception loss for a specific basin.

Free Research Field

水文学