A Stochastic Simulation Method for Estimating Vegetation Interception Capacity Based on Mechanical-Geometric Analysis

Abstract

Vegetation interception is a vital ecohydrological process, and the interception capacity is a key parameter to many classical interception models. However, current canopy interception capacity estimation methods largely depend on measured interception data, which are high cost and insufficient portability. This study addresses vegetation interception capacity at both leaf and canopy scales. At the leaf scale, a stochastic simulation method that do not depend on measured interception data and can take into account wind loads is developed, incorporating geometric properties and mechanical analysis to estimate water storage per unit leaf area. At the canopy scale, leaf water storage is summed up by using canopy structure parameters including leaf area index, leaf inclination angle distribution, and stem area index obtained by high-precision LiDAR point cloud data. The water storage capacities of 27 different leaf types were measured using the water spray method, and canopy interception from 22 rainfall events were monitored using comprehensive equipment. The proposed approach was successfully validated at both the leaf and canopy scales. In addition, a reasonable parameterization scheme for the model is discussed in detail to facilitate further application.