An Investigation into Field and Remote Sensing Methods for the Estimation of Dynamic Hydraulic Roughness of Floodplains from Riparian Vegetation

Abstract:

The influence of riparian vegetation on floodplain hydrodynamic processes, an integral element of river/floodplain ecosystems, can be modeled via the hydraulic roughness. Riparian vegetation increases resistance and may decrease channel conveyance and capacity, thus enhancing local flood risk and the attenuation of flood waves. The conventional approach to assign hydraulic roughness is based on land use types, photographs, and professional judgment, which ignores the effects on roughness due to local flow characteristics such as water depth and velocity. The objectives of this study were to implement numerical routines for simulating dynamic roughness in a two dimensional (2D) hydrodynamic model and to evaluate the performance of two dynamic roughness approaches (Jarvela (2004) & Baptist et al. (2007)) as compared with field measurement and the standard static approach. Vegetation parameters including vegetation height, density, and leaf area index were measured in the field and also determined using LiDAR data. The method was implemented along the San Joaquin River near Fresno, California, USA using a 2D hydrodynamic model produced by the Bureau of Reclamation (SRH-2D). The model was modified with algorithms to solve two approaches to calculate dynamic roughness. The 2D model for the static roughness condition was calibrated with the field observation which was then compared with the dynamic roughness condition. The results demonstrated the spatial variability of roughness with respect to discharge and vegetation species in a floodplain. Overall, the dynamic roughness was higher compared to static roughness for both approaches. As a result, the velocity was lower with higher water depth when applying the dynamic roughness approaches. This study demonstrated a new approach for advancing the understanding of dynamic roughness and its influence on hydraulic parameters including water depth and velocity.