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Sequential Data Assimilation for Estimating Bed Roughness of Vegetated Flooded Rivers

Author(s): Keisuke Yoshida; Shiro Maeno

Linked Author(s): Keisuke Yoshida

Keywords: Sequential importance sampling; Distributed manning’s coefficients; Vegetated rivers

Abstract: Forestation in rivers has been increasingly reported in Japan. Thick vegetation often decreases the river flow capacity during flooding. For river management tasks for flood control, it is necessary to estimate the distributed bed roughness values because of vegetation establishment in actual flooded rivers. We developed a sequential data assimilation method for estimating distributed Manning’s roughness coefficients in natural vegetated flooded rivers. For that purpose, we used a simplified particle filter, coupling a sequential importance sampling (SIS) technique with a horizontal twodimensional hydraulic model (shallow water model). The data assimilation method was applied for inverse estimation of the distributed roughness coefficients in the lower reaches of the Asahi River in Japan during flooding in 2011. For practical use, the assimilated data comprised water levels measured along the river at regular time intervals. Results show that the estimated Manning’s roughness coefficients are consistent with vegetation conditions observed onsite. Results also show that the coefficient value distribution exhibits a similar trend to that of previous investigation results obtained using four-dimensional variational method, thereby demonstrating the effectiveness of the present method.


Year: 2016

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