Abstract. Roughness length of land surfaces is an essential variable for the parameterisation of momentum and heat exchanges. The growing interest about the estimation of the surface turbulent flux parameterisation from passive remote sensing lead to an increasing development of models, and the common use of simple semi-empirical formulations to estimate surface roughness. Over complex surface land cover, these approaches would benefit from the combined use of passive remote sensing and land surface structure measurements from Light Detection And Ranging (LIDAR) techniques. Following early studies based on LIDAR profile data, this paper explores the use of imaging LIDAR measurements for the estimation of the aerodynamic roughness length over a heterogeneous landscape of the Heihe river basin, a typical inland river basin in the northwest of China. LIDAR points were used to extract a Digital Surface Model (DSM) and a Digital Elevation Model (DEM) from a single flight pass over an irrigated area covered by field crops, small trees arrays and tree hedges, with a ground resolution of 1 m and a total surface of 7.2 km2. As a first step, the DSM is used to estimate the plan surface density and frontal surface density of obstacles to wind flow and compute a displacement height and roughness length following strictly geometrical approaches. In a second step, both the DSM and DEM are introduced in a Computational Fluid Dynamics model (CFD) to calculate wind fields from the surface to the top of the Planetary Boundary Layer (PBL), and invert wind profiles for each calculation grid and compute a roughness length. Examples of the use of these three approaches are presented for various wind direction together with a cross-comparison of results on heterogeneous land cover and complex roughness element structures.
Estimation of Aerodynamic Roughness Length over Oasis in the Heihe River Basin by Utilizing Remote Sensing and Ground Data
