Dynamic Roughness Modeling of Seasonal Vegetation Effect: Case Study of the Nanakita River

Abstract

Hydraulic models of rivers are essential for vulnerability assessment in disaster management. This study simulates the 2019 Typhoon Hagibis at the Nanakita River using a dynamic roughness model. The model estimates the roughness of the river on a pixel level from the relationship between the Manning roughness coefficient and the degree of submergence of vegetation. This degree is defined as the ratio of water depth to plant height. After validating the model, the effect of vegetation on the water level in different seasons from April 2020 to March 2021 was assessed. The vegetation area and height were obtained on a pixel level using unmanned aerial vehicle photogrammetry. The dynamic roughness model showed that the water level profile increased by 7.03% on average. The seasonal effect of vegetation was observed, revealing a strong correlation between variations in the vegetation conditions and water level profile. This approach may help mitigate flood damage by indicating the factors that can increase the risk of flooding.

Keywords

• flood vulnerability
• hydraulic resistance
• Manning roughness coefficient
• Typhoon Hagibis
• unmanned aerial vehicles
• structure from motion